Language：Japanese   Publisher：Tomography  

Objectives: Few studies have reported in vivo measurements of electron density (ED) and effective atomic number (Z<inf>eff</inf>) in normal brain tissue. To address this gap, dual-energy computed tomography (DECT)-derived ED and Z<inf>eff</inf> maps were used to characterize normal-appearing adult brain tissues, evaluate age-related changes, and investigate correlations with myelin partial volume (V<inf>my</inf>) from synthetic magnetic resonance imaging (MRI). Materials and Methods: Thirty patients were retrospectively analyzed. The conventional computed tomography (CT) value (CT<inf>conv</inf>), ED, Z<inf>eff</inf>, and V<inf>my</inf> were measured in the normal-appearing gray matter (GM) and white matter (WM) regions of interest. V<inf>my</inf> and DECT-derived parameters were compared between WM and GM. Correlations between V<inf>my</inf> and DECT parameters and between age and DECT parameters were analyzed. Results: V<inf>my</inf> was significantly greater in WM than in GM, whereas CT<inf>conv</inf>, ED, and Z<inf>eff</inf> were significantly lower in WM than in GM (all p < 0.001). Z<inf>eff</inf> exhibited a stronger negative correlation with V<inf>my</inf> (ρ = −0.756) than CT<inf>conv</inf> (ρ = −0.705) or ED (ρ = −0.491). ED exhibited weak to moderate negative correlations with age in nine of the 14 regions. In contrast, Z<inf>eff</inf> exhibited weak to moderate positive correlations with age in nine of the 14 regions. CT<inf>conv</inf> exhibited negligible to insignificant correlations with age: Conclusions: This study revealed distinct GM–WM differences in ED and Z<inf>eff</inf> along with opposing age-related changes in these quantities. Therefore, myelin may have substantially contributed to the lower Z<inf>eff</inf> observed in WM, which underlies the GM–WM contrast observed on non-contrast-enhanced CT.

DOI： 10.3390/tomography11090095

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Language：Japanese   Publisher：Japanese Journal of Radiology  

Purpose: To clarify the usefulness of electron density (ED) using dual-energy CT (DECT) parameters for predicting treatment response in patients with pulmonary embolism (PE). Materials and methods: The study population comprised 30 patients with PE (49 thrombi) who underwent pretreatment DECT. The study coordinator diagnosed PE using contrast-enhanced CT (CECT) as the gold standard and annotated the location of thrombi on CECT prior to the DECT image analyses. CT attenuation values on conventional 120 kVp, 40 keV, and 70 keV virtual monochromatic (VM) images; effective atomic number; and ED of pretreatment pulmonary thrombi were measured on unenhanced CT. Thrombi were classified into dissolved and residual groups according to the findings of posttreatment follow-up CT. DECT parameters were compared between the two groups using the Mann–Whitney U test. For statistically significant parameters, receiver-operating characteristic (ROC) analysis was used to evaluate their performance for differentiating two groups. Diagnostic accuracy for predicting treatment response in patients with PE was determined by calculating the area under the ROC curve (AUC). Results: ED values, CT values on conventional 120 kVp imaging, and those on 70 keV VM imaging were significantly higher in thrombi in the dissolved group than the residual group (p < 0.001, p = 0.012, p = 0.009, respectively). AUC values for predicting dissolution response by ED, conventional 120 kVp imaging, and 70 keV VM imaging (cut-off value, 3.49 × 10²³/cm³, 53.4 HU, and 50.7 HU, respectively) were 0.856, 0.744, and 0.755, respectively. AUC was significantly higher for ED than for conventional 120 kVp imaging and 70 keV VM imaging (p = 0.032, p = 0.016). Conclusions: ED derived from unenhanced DECT may help predict therapeutic efficacy in patients with PE.

DOI： 10.1007/s11604-025-01747-z

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PubMed

Language：English   Publisher：(公社)日本医学放射線学会  

当院で治療前にデュアルエナジーCT(DECT)検査を受けた肺血栓塞栓症(PE)患者30例が有する血栓49個に対し、造影CT(CECT)で診断したPEを参照標準として、DECT画像分析前にCECT上で血栓位置のアノテーションを行った。治療前肺血栓を撮像した120kVp画像、40keVおよび70keV画像により、仮想単色X線(VM)画像からCT減衰値と実効原子番号および電子密度(ED)を単純CT画像から測定した。また、治療後の経過観察CT画像により血栓を溶解群と残存群に分け、群間でDECTパラメータを比較した。その結果、溶解群血栓のED値、120kVp画像上および70keV VM画像上のCT減衰値は残存群に比べ有意に高く、ED、120kVp画像および70keV VM画像による治療効果予測に対するAUCは0.856、0.744および0.755で、EDのAUCは他2つに比べ有意に高かったことからも、単純DECTによるEDは、PE患者の治療効果予測に役立つと考えられた。

Language：Japanese   Publisher：Japanese Journal of Radiology  

Objectives: This study evaluates the effectiveness of machine learning (ML) models that incorporate clinical and 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]-FDG)-positron emission tomography (PET)-radiomic features for predicting outcomes in gallbladder cancer patients. Materials and methods: The study analyzed 52 gallbladder cancer patients who underwent pre-treatment [¹⁸F]-FDG-PET/CT scans between January 2011 and December 2021. Twenty-seven patients were assigned to the training cohort between January 2011 and January 2018, and the data randomly split into training (70%) and validation (30%) sets. The independent test cohort consisted of 25 patients between February 2018 and December 2021. Eight clinical features (T stage, N stage, M stage, Union for International Cancer Control [UICC] stage, histology, tumor size, carcinoembryonic antigen level, and carbohydrate antigen 19-9 level) and 49 radiomic features were used to forecast progression-free survival (PFS). Three feature selection methods were applied including the univariate statistical feature selection test method, least absolute shrinkage and selection operator Cox regression method and recursive feature elimination method, and two ML algorithms (Cox proportional hazard and random survival forest [RSF]) were employed. Predictive performance was assessed using the concordance index (C-index). Results: Two clinical variables (UICC stage, N stage) and three radiomic features (total lesion glycolysis, grey-level size-zone matrix_grey level non-uniformity and grey-level run-length matrix_run-length non-uniformity) were identified by the statistical feature selection method as significant for PFS prediction. The RSF model incorporating these features demonstrated strong predictive performance, with C-indices above 0.80 in both training and testing sets (training 0.81, testing 0.89). This model almost closely matched the actual and predicted progression timelines with a low mean absolute error of 1.435, a median absolute error of 0.082, and a root mean square error of 2.359. Conclusion: This study highlights the potential of using ML approaches with clinical and pre-treatment [¹⁸F]-FDG-PET radiomic data for predicting the prognosis of gallbladder cancer.

DOI： 10.1007/s11604-024-01722-0

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PubMed

Language：English   Publisher：(公社)日本医学放射線学会  

胆嚢癌の予後予測に、臨床データと[18F]-FDG-PETのラジオミクスデータを取り入れた機械学習(ML)モデルが有用か検討した。治療前[18F]-FDG-PET/CT検査を受けた胆嚢癌患者52例をトレーニング群27例とテスト群25例に分けて評価した結果、統計的特徴抽出法により、無増悪生存率予測に重要な2種類の臨床的変数と3種類のラジオミクス特徴量が同定された。また、これらの特徴量を取り入れたランダムサバイバルフォレストモデルでは高い予後予測能が示され、両群ともC-indexは0.80超であった。さらに、本モデルでは実際の増悪タイムラインと予測がほぼ一致しており、low mean absolute errorが1.435、中央絶対誤差は0.082、二乗平均平方根誤差では2.359得られた。本報により、胆嚢癌の予後予測において、臨床データと治療前[18F]-FDG-PETによるラジオミクスデータを用いたML法の有用性が示された。

Language：Japanese   Publisher：Laryngoscope Investigative Otolaryngology  

Objectives: The purpose of this study is to investigate the genetic mutational status of anaplastic thyroid carcinoma (ATC) and its prognostic implications. Methods: Data were analyzed for 129 consecutive patients with ATC registered at the Japan National Cancer Center, Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 2019 and June 2024. Genetic alterations were determined by FoundationOne CDx or Liquid CDx next-generation sequencing. The survival of patients was determined by the log-rank test and a Cox proportional hazards model. Results: The top 30 mutations in ATC were TERT (98/129), TP53 (88/129), BRAF (72/129), CDKN2A (39/129), CDKN2B (29/129), LTK (26/129), NRAS (25/129), KMT2D (24/129), PIK3CA (26/129), NOTCH3 (27/129), NF2 (19/129), MTAP (17/129), TET2 (16/129), STK11 (15/129), ATM (14/129), FANCA (14/129), NF1 (13/129), DNMT3A (13/129), KIT (13/129), NOTCH1 (13/129), EP300 (12/129), BRCA2 (11/129), CARD11 (11/129), KEL (11/129), MSH3 (11/129), PTEN (11/129), RICTOR (11/129), TSC1 (11/129), ROS1 (10/129), and KMT2A (10/129) with 13.7 ± 0.5 (mean ± SEM) mutations/individual. Mutations in BRAF (p = 0.003), PIK3CA (p = 0.014), and BRCA2 (p = 0.036) were associated with a significantly better prognosis, whereas mutations in STK11 (p = 0.024) was associated with a significantly worse prognosis, as determined by log-rank tests. The hazard ratios for cases with these mutations were 0.248 (95% CI, 0.0973–0.633, p = 3.5 × 10⁻³) for PIK3CA, 2.410 (1.054–5.515, p = 0.037) for STK11, and 0.157 (0.0376–0.659, p = 0.011) for BRCA2. Conclusions: In ATC, PIK3CA, and BRCA2 mutations were associated with a better prognosis, and STK11 mutation was associated with a poorer prognosis in this study. Level of Evidence: 3.

DOI： 10.1002/lio2.70110

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Language：Japanese   Publisher：European Journal of Radiology  

Purpose: To assess the postoperative prognostic utility of extracellular volume (ECV) fraction measurement using equilibrium contrast-enhanced CT (CECT) in patients with thymomas. Methods: Enrolled in the study were patients with thymomas who were assessed by pretreatment CECT. ECV fraction was determined from measurements within the lesion and aorta on unenhanced and equilibrium phase CECT. Masaoka–Koga stage, WHO histological classification, and morphological features on CT including tumor size and boundary clarity were also evaluated. Univariate and bivariate analyses using Cox proportional hazards regression model were performed to evaluate the factors affecting recurrence-free survival (RFS). RFS rates were analyzed using the Kaplan–Meier method. Results: A total of 100 consecutive patients (52 low-risk and 48 high-risk thymomas) were enrolled in this study. Bivariate analyses identified boundary, Masaoka–Koga stage, and ECV fraction as independent significant variables for predicting RFS across all parameters. Mean RFS was significantly shorter in the group with ill-defined boundary (ill-defined, 102.5 months; well-defined, 167.4 months; p < 0.001), high Masaoka–Koga stage (stage 3 or 4, 54.9 months; stage 1 or 2, 164.2 months; p < 0.001), and high ECV fraction (ECV fraction ≥ 27.5 %, 110.3 months; ECV fraction < 27.5 %, 170.1 months; p < 0.001). Conclusions: ECV fraction derived from equilibrium CECT was an independent risk factor for RFS in patients with thymoma.

DOI： 10.1016/j.ejrad.2025.111978

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PubMed

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：English   Publisher：(公社)日本医学放射線学会  

耳下腺疾患(PGD)患者62例63病変の[18F]-FDG-PET CT画像を用い、良悪性の鑑別に深層学習(DL)によるアンサンブル機械学習(ML)モデルが有用か後向きに検討した。対象患者はトレーニング群44病変とテスト群19病変に分け、トレーニング群には従来型MLアルゴリズムモデルとDLによるアンサンブルMLモデルを最も重要なラジオミクス特徴量5つを用いて構築し、PGD病変を鑑別した。その結果、良性病変が24病変、悪性病変が39病変が同定され、ROC曲線下面積と正確度により性能を比較したところ、DLによるアンサンブルMLモデルで両群ともに最も高性能が示された。以上より、[18F]-FDG-PETラジオミクス特徴量を用いたDLによるアンサンブルMLモデルは、PGDの良悪性鑑別に有用と判断された。

Language：Japanese   Publisher：Journal of Neuroimaging  

Background and Purpose: Differentiation between functioning and nonfunctioning pituitary adenomas/pituitary neuroendocrine tumors (PAs) is clinically relevant. The goal of this study was to determine the feasibility of using time-dependent diffusion MRI (dMRI) for microstructural characterization of PAs. Methods: The study included 54 participants, 24 with functioning PA and 30 with nonfunctioning PA. Time-dependent dMRI of the pituitary gland was performed using an inner field-of-view echo-planar imaging based on 2-dimensional-selective radiofrequency excitations with oscillating gradient and pulsed gradient preparation (effective diffusion time: 7.1 and 36.3 ms) at b-values of 0 and 1000 seconds/mm². Each tumor had its apparent diffusion coefficients (ADCs) measured at two diffusion times (ADC<inf>7.1 ms</inf> and ADC<inf>36.3 ms</inf>), its ADC change (cADC), and relative ADC change. The mean values of diffusion parameters were compared between functioning and nonfunctioning PAs. We compared the diffusion parameters of nonfunctioning PAs with those of each type of hormone-producing PAs. The diagnostic performances of the diffusion parameters were assessed. Results: The cADC was significantly higher in functioning PAs than nonfunctioning PAs (p =.0124). The receiver operating characteristic (ROC) curve analysis revealed that cADC (area under the ROC curve [AUC] =.677, p =.017) is effective in distinguishing between functioning and nonfunctioning PAs. The cADC was significantly higher in growth hormone (GH)-producing PAs compared to nonfunctioning PAs (p =.006). The ROC curve analysis indicated that cADC (AUC =.771, p <.001) effectively distinguishes between GH-producing and nonfunctioning PAs. Conclusions: The cADC derived from time-dependent dMRI could distinguish between functioning and nonfunctioning PAs, particularly those producing GH.

DOI： 10.1111/jon.13254

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Language：Japanese   Publisher：Japanese Journal of Radiology  

Objectives: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs). Materials and methods: This retrospective study included 62 patients with 63 PGDs who underwent pretreatment [¹⁸F]-FDG-PET/computed tomography (CT). The lesions were assigned to the training (n = 44) and testing (n = 19) cohorts. In total, 49 [¹⁸F]-FDG-PET-based radiomic features were utilized to differentiate benign from malignant PGDs using five different conventional ML algorithmic models (random forest, neural network, k-nearest neighbors, logistic regression, and support vector machine) and the deep learning (DL)-based ensemble ML model. In the training cohort, each conventional ML model was constructed using the five most important features selected by the recursive feature elimination method with the tenfold cross-validation and synthetic minority oversampling technique. The DL-based ensemble ML model was constructed using the five most important features of the bagging and multilayer stacking methods. The area under the receiver operating characteristic curves (AUCs) and accuracies were used to compare predictive performances. Results: In total, 24 benign and 39 malignant PGDs were identified. Metabolic tumor volume and four GLSZM features (GLSZM_ZSE, GLSZM_SZE, GLSZM_GLNU, and GLSZM_ZSNU) were the five most important radiomic features. All five features except GLSZM_SZE were significantly higher in malignant PGDs than in benign ones (each p < 0.05). The DL-based ensemble ML model had the best performing classifier in the training and testing cohorts (AUC = 1.000, accuracy = 1.000 vs AUC = 0.976, accuracy = 0.947). Conclusions: The DL-based ensemble ML model using [¹⁸F]-FDG-PET-based radiomic features can be useful for differentiating benign from malignant PGDs. Second abstract: The DL-based ensemble ML model using [¹⁸F]-FDG-PET-based radiomic features can overcome the previously reported limitation of [¹⁸F]-FDG-PET/CT scan for differentiating benign from malignant PGDs. The DL-based ensemble ML approach using [¹⁸F]-FDG-PET-based radiomic features can provide useful information for managing PGD.

DOI： 10.1007/s11604-024-01649-6

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Language：Japanese   Publisher：Otolaryngologia Polska  

Introduction: Although genetic mutations have been reported in nasopharyngeal carcinoma (NPC), there are currently no scientifically validated treatments targeting these mutations. Furthermore, cancer genomic profiling tests are underutilized in clinical practice. This highlights an urgent need to explore the genomic landscape of NPC and its potential therapeutic implications. Aim: The aim of this study is to investigate the genetic mutational landscape of recurrent and/or metastatic nasopharyngeal carcinoma (NPC). Materials and methods: Data were analyzed for 67 consecutive patients with NPC registered at the Japan National Cancer Center, Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 2019 and May 2024. Genetic mutations were determined by FoundationOne CDx or Liquid CDx next-generation sequencing. Survival of patients was determined by the log-rank test and a Cox proportional hazards model. Results: The top 10 mutations in NPC were CDKN2A (41.8%), CDKN2B (31.3%), TP53 (20.9%), KMT2D(20.9%), DNMT3A(19.4%), NOTCH1(17.9%), STK11(17.9%), MTAP(17.9%), EP300 (17.9%), TSC1 (13.4%), with 11.1 ±6.1 (mean ±SEM) mutations/individual. Mutations in KMT2D (p = 0.0127), DNMT3A (p = 1.41×10^-7), GNAS (p = 3.64×10^-11), SPEN (p = 0.0167), BRCA1 (p = 0.0379), and KMT2A (p = 2.06×10^-5) were associated with a significantly worse prognosis, as determined by the log-rank test. The hazard ratios for cases with these mutations were 0.0122 (95% CI, 1.58×10^-4-0.936, p = 0.046) for TP53, 1847.0 (95% CI, 4.619-7.386×10⁵, p = 0.014) for DNMT3A, 126.7 (95% CI, 1.262-12720, p = 0.039) for BRCA2, 197.9 (95% CI, 2.844-13770, p = 0.015) for ALK, 34.22 (95% CI, 1.256-932.7, p = 0.036) for SPEN, and 6.445×10^-4 (95% CI, 2.913×10^-6-0.143, p = 7.6×10^-3) for MYCL. Conclusions: This study identified genetic mutations in recurrent and/or metastatic NPC.Even in advanced cases,prognosis-related mutations were identified,underscoring the importance of cancer genomic profiling tests.

DOI： 10.5604/01.3001.0055.1903

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Language：Japanese   Publisher：Molecular Imaging and Biology  

Purpose: To examine the usefulness of semi-quantitative analysis using the standardized uptake value (SUV) of iodine-123 metaiodobenzylguanidine ([¹²³I]-MIBG) for predicting metastatic potential in patients with pheochromocytoma (PHEO) and paraganglioma (PGL). Procedures: This study included 18 PHEO and 2 PGL patients. [¹²³I]-MIBG visibility and SUV-related parameters (SUVmax, SUVmean, tumor volume of [¹²³I]-MIBG uptake [TV_MIBG], and total lesion [¹²³I]-MIBG uptake) were compared with the pathological grading obtained using the Pheochromocytoma of the Adrenal Gland Scaled Score (PASS) and the Grading System for Adrenal Pheochromocytoma and Paraganglioma (GAPP), which are used to predict metastatic potential. The PASS scores were categorized as < 4 and ≥ 4. Based on the GAPP scores, PHEOs/PGLs were categorized as follows: well, moderately, and poorly differentiated tumors. The Mann–Whitney U test or Spearman’s rank correlation was used to assess differences or associations between two quantitative variables. Results: All PHEOs/PGLs were visualized on [¹²³I]-MIBG scintigraphy. There were 16 PASS < 4 and 4 PASS ≥ 4 tumors. Moreover, 11 and 9 tumors were well and moderately differentiated, respectively. The uptake scores and SUV-related parameters significantly differed between tumors with a PASS score of < 4 and those with a PASS score of ≥ 4 (each, p > 0.05). Moderately differentiated tumors had significantly higher uptake scores and SUV-related parameters except TV_MIBG than well-differentiated tumors (each, p < 0.05). The GAPP score was positively correlated with the uptake scores and SUV-related parameters (each, p < 0.05) except TV_MIBG. Conclusions: The primary tumor [¹²³I]-MIBG uptake assessed using SUV-related parameters can be an imaging tool for predicting metastatic potential in patients with PHEO/PGL.

DOI： 10.1007/s11307-024-01952-8

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PubMed

Language：English   Publisher：(公社)日本医学放射線学会  

Synthetic MRIにより、唾液腺の良性病変と悪性病変の鑑別能を後向きに検討した。2021年3月～2023年9月までの期間内に、唾液腺の術前MRI検査を受けた患者のうち、選択基準を満たした44例(男性26例、女性18例、年齢22～88歳)を調査した。その結果、多形腺腫(PA)のT1、T2、プロトン密度(PD)および見かけの拡散係数(ADC)はWarthin腫瘍(WT)に比べ有意に高く、T1、T2およびADCは悪性腫瘍(MT)に比べ有意に高かった。また、WTのT1、T2およびPDではMTに比べ有意に低く、T2とADCではMTとPAの鑑別に最も有効で、T1とPDではMTとWTの鑑別に最も有効であった。さらに、T1とT2やADCの併用により、良性/悪性病変が86.4%の正確度で鑑別され、PDとT2やADCの併用により、良性/悪性病変が86.4%の正確度で識別された。以上より、Synthetic MRIによる画像パラメータの併用は、唾液腺の良性病変と悪性病変の鑑別に役立つと結論付けられた。

Language：Japanese   Publisher：Japanese Journal of Radiology  

Purpose: To determine whether synthetic MR imaging can distinguish between benign and malignant salivary gland lesions. Methods: The study population included 44 patients with 33 benign and 11 malignant salivary gland lesions. All MR imaging was obtained using a 3 Tesla system. The QRAPMASTER pulse sequence was used to acquire images with four TI values and two TE values, from which quantitative images of T1 and T2 relaxation times and proton density (PD) were generated. The Mann–Whitney U test was used to compare T1, T2, PD, and ADC values among the subtypes of salivary gland lesions. ROC analysis was used to evaluate diagnostic capability between malignant tumors (MTs) and either pleomorphic adenomas (PAs) or Warthin tumors (WTs). We further calculated diagnostic accuracy for distinguishing malignant from benign lesions when combining these parameters. Results: PAs demonstrated significantly higher T1, T2, PD, and ADC values than WTs (all p < 0.001). Compared to MTs, PAs had significantly higher T1, T2, and ADC values (all p < 0.001), whereas WTs had significantly lower T1, T2, and PD values (p < 0.001, p = 0.008, and p = 0.003, respectively). T2 and ADC were most effective in differentiating between MTs and PAs (AUC = 0.928 and 0.939, respectively), and T1 and PD values for differentiating between MTs and WTs (AUC = 0.915 and 0.833, respectively). Combining T1 with T2 or ADC achieved accuracy of 86.4% in distinguishing between malignant and benign tumors. Similarly, combining PD with T2 or ADC reached accuracy of 86.4% for differentiating between malignant and benign tumors. Conclusions: Utilizing a combination of synthetic MRI parameters may assist in differentiating malignant from benign salivary gland lesions.

DOI： 10.1007/s11604-024-01578-4

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Language：English   Publisher：(公社)日本医学放射線学会  

心サルコイドーシス(CS)患者の臨床有害事象(ACE)の予測に、治療前18F-FDG-PET画像を用いた機械学習(ML)モデルが有用か検討した。MLモデルは7種類のMLアルゴリズムとジニ不純度の低下により最上位となった4つの特徴量を用いて構築した。治療前に18F-FDG-PET/CTが撮像されたCS患者47例(男性9例、女性38例、年齢39～81歳)を対象に、トレーニングコホート38例とテストコホート9例に分けて比較した。その結果、ACE発症患者では非発症患者に比べ、表面積とgray level run length matrix run length non-uniformityでは有意に大きかった一方、neighborhood gray-tone difference matrix_coarsenessおよび球形度は有意に小さかった。また、トレーニングコホートでは全てのMLアルゴリズムが良好な分類性能を示し、テストコホートではrandom forestアルゴリズムで、最も大きなROC曲線下面積と最も高い正確度が得られた。以上より、18F-FDG-PET画像をベースとしたラジオミクス特徴量によるML解析は、CS患者においてACEの予測に有用と判断された。

Language：Japanese   Publisher：Journal of Magnetic Resonance Imaging  

Background: Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer. Purpose: To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI. Study Type: Retrospective. Subjects: Sixty-three women (mean age: 58 [range: 32–85] years) with endometrial cancer. Field Strength/Sequence: 3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences. Assessment: Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADC<inf>OGSE</inf>) and PGSE (ADC<inf>PGSE</inf>) as well as the ADC ratio (ADC<inf>OGSE</inf>/ADC<inf>PGSE</inf>) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated. Statistical Tests: Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADC<inf>OGSE</inf>, ADC<inf>PGSE</inf>, and ADC<inf>OGSE</inf>/ADC<inf>PGSE</inf> with prognostic factors were examined using the Kendall rank correlation coefficient, Mann–Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant. Results: Compared with ADC<inf>OGSE</inf> and ADC<inf>PGSE</inf>, ADC<inf>OGSE</inf>/ADC<inf>PGSE</inf> was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADC<inf>OGSE</inf>/ADC<inf>PGSE</inf> for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83–0.98; observer 2, 0.84, 95% CI: 0.73–0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68–0.89; observer 2, 0.76, 95% CI: 0.63–0.86) were significantly higher than that of ADC<inf>OGSE</inf> and ADC<inf>PGSE</inf>. Data Conclusion: The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer. Level of Evidence: 3. Technical Efficacy: Stage 2.

DOI： 10.1002/jmri.29106

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PubMed

Language：Japanese   Publisher：Japanese Journal of Radiology  

Objectives: To investigate the usefulness of machine learning (ML) models using pretreatment ¹⁸F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS). Materials and methods: This retrospective study included 47 patients with CS who underwent ¹⁸F-FDG-PET/CT scan before treatment. The lesions were assigned to the training (n = 38) and testing (n = 9) cohorts. In total, 49 ¹⁸F-FDG-PET-based radiomic features and the visibility of right ventricle ¹⁸F-FDG uptake were used to predict ACEs using seven different ML algorithms (namely, decision tree, random forest [RF], neural network, k-nearest neighbors, Naïve Bayes, logistic regression, and support vector machine [SVM]) with tenfold cross-validation and the synthetic minority over-sampling technique. The ML models were constructed using the top four features ranked by the decrease in Gini impurity. The AUCs and accuracies were used to compare predictive performances. Results: Patients who developed ACEs presented with a significantly higher surface area and gray level run length matrix run length non-uniformity (GLRLM_RLNU), and lower neighborhood gray-tone difference matrix_coarseness and sphericity than those without ACEs (each, p < 0.05). In the training cohort, all seven ML algorithms had a good classification performance with AUC values of > 0.80 (range: 0.841–0.944). In the testing cohort, the RF algorithm had the highest AUC and accuracy (88.9% [8/9]) with a similar classification performance between training and testing cohorts (AUC: 0.945 vs 0.889). GLRLM_RLNU was the most important feature of the modeling process of this RF algorithm. Conclusion: ML analyses using ¹⁸F-FDG-PET-based radiomic features may be useful for predicting ACEs in patients with CS.

DOI： 10.1007/s11604-024-01546-y

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PubMed

Language：English  

DOI： 10.7759/cureus.65783

PubMed

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000005449

CiNii Research

Language：English   Publisher：(一社)日本核医学会  

2022年に日本アイソトープ協会(JRIA)専門委員会が実施した核医学診療実態に関する第9回全国調査結果について報告した。2022年6月に日本国内核医学診療施設1208施設に向けアンケート調査を行った結果、PETセンターを含む1095施設から回答が得られた。調査結果から、ガンマカメラ保有台数は1299台と5年間で2.5%減少しており、シングルフォトントレーサー検査件数は1110000件で2.7%増加が認められた。また、PET検査は1992年～2017年までは増加傾向であったが、この5年間では1.5%減少し、核医学検査全体の増加率は1.0%にとどまった。なお、褐色細胞腫やパラガングリオーマに対しては131-MIBGによる治療が、神経内分泌腫瘍に対しては177Lu-DOTA-TATEによる治療が新たに開始されたが、131IRaおよび223Raを用いた標的治療の件数の減少や一部の放射性同位体の供給中断により、標的アイソトープ治療総数は17.7%の減少となった。本調査結果から、5年前の調査と比べ、核医学検査の総数に大きな変化はみられなかったが、新たなアイソトープ治療の開発は今後も継続するものと推測された。

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：Annals of Nuclear Medicine  

Subcommittee on Survey of Nuclear Medicine Practice in Japan has performed a nationwide survey of nuclear medicine practice every 5 years since 1982 to survey contemporary nuclear medicine practice and its changes over the years. The subcommittee sent questionnaires, including the number and category of examinations as well as the kind of the radiopharmaceuticals during the 30 days of June 2022 to all nuclear medicine institutes in Japan. The total numbers of them for the year 2022 were estimated depends on the 1-month data. A total of 1095 institutes responded to the survey, including 364 positron emission tomography (PET) centers. The recovery rate was 90.6%. The number of gamma cameras installed was 1299 in total, with 2.5% decrease in 5 years. Dual-head cameras and hybrid SPECT/CT scanners accounted for 83.8% and 35.5%, respectively. The number of single-photon tracer studies in 2022 was 1.11 million which means increase in 2.7% in 5 years. Bone scintigraphy was a leading examination (31.0%), followed by myocardial scintigraphy (27.1%) and cerebral perfusion study (23.8%) in order. The percentage of SPECT studies showed an increase from 63.5% in previous survey to 66.8% in this survey. PET centers have also increased from 389 to 412, as compared with the previous one. One hundred and twenty-two PET centers have installed one or two in-house cyclotrons. Increasing trends of the PET studies were observed from 1992 to 2017, the trend changed and PET studies showed 1.5% decrease in 5 years. ¹⁸F-FDG accounted for 98.6% (610,497 examinations). PET examinations using ¹¹C-methionine, ¹³N-NH<inf>3</inf> and ¹¹C-PIB have decreased, with 1624, 2146 and 525 examinations, respectively in 2022. The total number of nuclear medicine examination was eventually increased by 1.0%. Therapies for pheochromocytoma or paraganglioma (PPGL) with ¹³¹I-MIBG and for neuroendocrine tumor with ¹⁷⁷Lu-DOTA-TATE were newly started, however, a total number of targeted radionuclide therapy was decreased by 17.7% because ¹³¹I-radioiodine and ²²³Ra targeted therapies were decreased and supply of some radioisotopes was discontinued. ¹³¹I-radioiodine targeted therapy showed a decrease in 5 years (− 15.9%), including 4099 patients for thyroid cancer. The number of out-patient thyroid bed ablation therapy with 1110 MBq of ¹³¹I was also decreased to 1015 per year. The number of admission rooms specialized for radionuclide targeted therapy increased from 157 to 160. The number of ²²³Ra targeted therapies for castration-resistant metastatic prostate cancer (mCRPC) was 1041 patients. This survey was performed during COVID-19 pandemic, however, total number of nuclear medicine examinations was almost same as previous survey (+ 1.0%). Radionuclide therapies with ¹³¹I-MIBG and ¹⁷⁷Lu-DOTA-TATE were newly started, and new radionuclide therapy will be available in future, therefore, the development of radionuclide therapy will be continued. We are convinced that this survey report is useful in understanding the current status of the nuclear medicine practice in Japan, and in devising the new strategy to strengthen a role of nuclear medicine.

DOI： 10.1007/s12149-024-01905-9

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PubMed

Language：Japanese   Publisher：Indian Journal of Otolaryngology and Head and Neck Surgery  

Adult T-cell leukemia/lymphoma (ATL) is a form of leukemia caused by the human T-cell leukemia virus type I (HTLV-1). Otolaryngologists often diagnose ATL based on cervical lymphadenopathy or Waldeyer ring lesions. However, there are few reports of ATL occurring in the nasal and paranasal cavity. Here, we report four such cases of ATL. Case 1: An 82-year-old man diagnosed with acute-type ATL with a tumor in the nasal cavity underwent 5 courses of THP-COP, but died after 36 months due to ATL. Case 2: A 62-year-old woman diagnosed with lymphoma-type ATL with a tumor in the frontal sinus was treated with 5 courses of VCAP-AMP-VECP, and has survived for more than 10 years. Case 3: A 64-year-old man diagnosed with lymphoma-type ATL with a tumor in the maxillary sinus underwent 8 courses of VCAP-AMP-VECP and 2 courses of mogamulizumab, but died after 34 months due to ATL. Case 4: A 52-year-old woman diagnosed with lymphoma-type ATL with tumors in both ethmoid sinuses received 2 courses of CHOP, 2 courses of DeVIC, radiotherapy (32 Gy) and 2 courses of mogamulizumab, but died after 9 months due to ATL.

DOI： 10.1007/s12070-023-04258-3

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PubMed

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：Japanese   Publisher：Japanese Journal of Radiology  

Machine learning (ML) analyses using ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics features have been applied in the field of oncology. The current review aimed to summarize the current clinical articles about ¹⁸F-FDG PET/CT radiomics-based ML analyses to solve issues in classifying or constructing prediction models for several types of tumors. In these studies, lung and mediastinal tumors were the most commonly evaluated lesions, followed by lymphatic, abdominal, head and neck, breast, gynecological, and other types of tumors. Previous studies have commonly shown that ¹⁸F-FDG PET radiomics-based ML analysis has good performance in differentiating benign from malignant tumors, predicting tumor characteristics and stage, therapeutic response, and prognosis by examining significant differences in the area under the receiver operating characteristic curves, accuracies, or concordance indices (> 0.70). However, these studies have reported several ML algorithms. Moreover, different ML models have been applied for the same purpose. Thus, various procedures were used in ¹⁸F-FDG PET/CT radiomics-based ML analysis in oncology, and ¹⁸F-FDG PET/CT radiomics-based ML models, which are easy and universally applied in clinical practice, would be expected to be established.

DOI： 10.1007/s11604-023-01476-1

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PubMed

Language：Japanese   Publisher：Cancer Imaging  

Background: This study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases. Methods: A retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC<inf>50Hz</inf> and ADC<inf>0Hz</inf>), we generated maps of the ADC change (cADC): ADC<inf>50Hz</inf> − ADC<inf>0Hz</inf> and the relative ADC change (rcADC): (ADC<inf>50Hz</inf> − ADC<inf>0Hz</inf>)/ ADC<inf>0Hz</inf> × 100 (%). Results: The mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC<inf>0Hz</inf> and ADC<inf>50Hz</inf> showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10⁻³mm²/s vs. 0.14 ± 0.03 × 10⁻³mm²/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC<inf>0Hz</inf>^5th (0.595; all p < 0.001). Conclusions: The time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

DOI： 10.1186/s40644-023-00595-2

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PubMed

Language：Japanese   Publisher：Cancer Imaging  

Background: This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters. Methods: A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δ<inf>eff</inf> = 7.1 ms) and conventional pulsed gradient (Δ<inf>eff</inf> = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC<inf>7.1 ms</inf> and ADC<inf>44.5 ms</inf>), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95^th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices. Results: In enhancing regions, the mean and fifth and 95^th percentile values of ADC<inf>44.5 ms</inf> and ADC<inf>7.1 ms</inf> in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95^th percentile of ADC<inf>44.5 ms</inf>, p = 0.04 for ADC<inf>7.1 ms</inf>, and p < 0.01 for others). Furthermore, the mean and fifth and 95^th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC<inf>7.1 ms</inf> was significantly lower than that for ADC<inf>44.5 ms</inf> (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC<inf>44.5 ms</inf>, ADC<inf>7.1 ms</inf>, cADC, and rcADC was observed between PCNSLs and GBMs. Conclusions: Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

DOI： 10.1186/s40644-023-00639-7

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PubMed

Language：Japanese   Publisher：In Vivo  

Background: Low-grade fibromyxoid sarcoma (LGFMS) is a rare type of sarcoma which is observed in the soft tissue of proximal extremities, typically in young and middle-aged adults. It consists of a solid proliferation of bland spindle cells within collagenous and myxoid stroma. Case Report: Herein, we report a case of LGFMS with massive degeneration and hyalinization. A 30-year-old man presented with a well-circumscribed mass measuring 15 cm in diameter in his left biceps femoris muscle. Marginal tumor resection was performed under the clinical diagnosis of an ancient schwannoma or chronic expanding hematoma (CEH). The resected tissue revealed a well-demarcated tumor mass with massive degeneration and hyalinization with focal calcification. Proliferation of spindle tumor cells with abundant collagenous stroma, which resembled the fibrous capsule of CEH, was observed exclusively in a small area of the periphery of the tumor. No nuclear palisading, myxoid stroma, or collagen rosettes were identified. Immunohistochemical analysis demonstrated that the spindle tumor cells expressed mucin 4 and epithelial membrane antigen. Reverse transcriptase-polymerase chain reaction analysis detected mRNA expression of fused in sarcoma::CAMP-responsive element binding protein 3-like protein 2 (FUS::CREB3L2) fusion gene. Thus, a final diagnosis of LGFMS with massive degeneration and FUS::CREB3L2 fusion was made. Conclusion: The recognition of massive degeneration and hyalinization as unusual features of LGFMS might be helpful to differentiate it from CEH and other benign spindle-cell tumors.

DOI： 10.21873/invivo.13404

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PubMed

Language：English   Publisher：European Journal of Radiology  

Purpose: To assess the usefulness of extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT (CECT) for diagnosing anterior mediastinal tumors. Method: This study included 161 histologically confirmed anterior mediastinal tumors (55 low-risk thymomas, 57 high-risk thymomas, 32 thymic carcinomas, and 17 malignant lymphomas) that were assessed by pretreatment CECT. ECV fraction was calculated using measurements obtained within the lesion and the aorta on unenhanced and equilibrium phase CECT. ECV fraction was compared among anterior mediastinal tumors using one-way ANOVA or t-test. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the ability of ECV fraction to differentiate thymic carcinomas/lymphomas from thymomas. Results: ECV fraction differed significantly among the anterior mediastinal tumors (p < 0.001). ECV fraction of thymic carcinomas was significantly higher than those of low-risk thymomas, high-risk thymomas, and lymphomas (p < 0.001, p < 0.001, and p = 0.006, respectively). ECV fraction of lymphomas was significantly higher than that of low-risk thymomas (p < 0.001). ECV fraction was significantly higher in thymic carcinomas/lymphomas than in thymomas (40.1 % vs. 27.7 %, p < 0.001). The optimal cutoff value to differentiate thymic carcinomas/lymphomas from thymomas was 38.5 % (AUC, 0.805; 95 %CI, 0.736–0.863). Conclusions: ECV fraction derived from equilibrium CECT is helpful in diagnosing anterior mediastinal tumors. High ECV fraction is indicative of thymic carcinomas/lymphomas, particularly thymic carcinomas.

DOI： 10.1016/j.ejrad.2023.110891

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PubMed

Language：English   Publisher：(公社)日本医学放射線学会  

2018年4月～2021年8月までの期間内に、術前に[123I]-メタヨードベンジルグアニジン(MIBG)投与によるプラナー画像撮像とSPECT/CT検査を受け、心エコー検査も施行された褐色細胞腫患者18例(男性11例、女性7例、年齢28～76歳)を調査対象とした。後向きに検討した結果、肉眼的には6例は心筋の[123I]-MIBG集積が正常であったが、12例には心筋への[123I]-MIBG集積低下が認められた。また、心筋の[123I]-MIBG集積が正常な患者と集積が低下した患者では拡張機能不全の発症率に有意差が認められ、集積が低下した患者12例中9例には左室拡張機能不全が認められた。さらに、左室拡張機能不全が認められた9例の心筋のSUVmaxは心機能が正常な9例に比べ有意に低く、心筋のSUVmaxは中隔のe'と正相関を示し、中隔のE/e'とは負の相関性が示された。以上より、心筋[123I]-MIBG SUVmaxは、褐色細胞腫患者の心機能特性の評価に有用と考えられた。

Language：Japanese   Publisher：(公社)日本アイソトープ協会  

日本アイソトープ協会では1982年から5年ごとに専門委員会を設けて全国核医学診療実態調査を行っており,第9回調査を2022年6月に行った。回答回収率は90%超であった。年間推定検査件数は単光子放出核種を用いた核医学検査が前回より2.7%増加した一方で,PET検査は約1.5%減少した。この結果,核医学検査総数は1.0%増加した。非密封RIを用いた核医学治療は131I-MIBGによる褐色細胞腫・パラガングリオーマや177Lu-ルテチウムオキソドトレオチドによる神経内分泌腫瘍の治療が新規に開始されたが,223Raと131Iを用いた治療件数の減少や一部薬剤の供給停止もあり,全体で17.7%減少した。核医学検査の総数はあまり変わらないが,核医学治療が大きく変化していることが示された。(著者抄録)

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：Japanese   Publisher：Molecular Imaging and Biology  

Purpose: To develop and identify machine learning (ML) models using pretreatment clinical and 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography ([18F]-FDG-PET)-based radiomic characteristics to predict disease recurrences in patients with breast cancers who underwent surgery. Procedures: This retrospective study included 112 patients with 118 breast cancer lesions who underwent [18F]-FDG-PET/ X-ray computed tomography (CT) preoperatively, and these lesions were assigned to training (n=95) and testing (n=23) cohorts. A total of 12 clinical and 40 [18F]-FDG-PET-based radiomic characteristics were used to predict recurrences using 7 different ML algorithms, namely, decision tree, random forest (RF), neural network, k-nearest neighbors, naive Bayes, logistic regression, and support vector machine (SVM) with a 10-fold cross-validation and synthetic minority over-sampling technique. Three different ML models were created using clinical characteristics (clinical ML models), radiomic characteristics (radiomic ML models), and both clinical and radiomic characteristics (combined ML models). Each ML model was constructed using the top ten characteristics ranked by the decrease in Gini impurity. The areas under ROC curves (AUCs) and accuracies were used to compare predictive performances. Results: In training cohorts, all 7 ML algorithms except for logistic regression algorithm in the radiomics ML model (AUC = 0.760) achieved AUC values of >0.80 for predicting recurrences with clinical (range, 0.892–0.999), radiomic (range, 0.809–0.984), and combined (range, 0.897–0.999) ML models. In testing cohorts, the RF algorithm of combined ML model achieved the highest AUC and accuracy (95.7% (22/23)) with similar classification performance between training and testing cohorts (AUC: training cohort, 0.999; testing cohort, 0.992). The important characteristics for modeling process of this RF algorithm were radiomic GLZLM_ZLNU and AJCC stage. Conclusions: ML analyses using both clinical and [18F]-FDG-PET-based radiomic characteristics may be useful for predicting recurrence in patients with breast cancers who underwent surgery.

DOI： 10.1007/s11307-023-01823-8

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PubMed

Language：Japanese   Publisher：British Journal of Radiology  

Objective: To examine whether machine learning (ML) analyses involving clinical and¹⁸F-FDG-PET-based radiomic features are helpful in predicting prognosis in patients with laryngeal cancer. Methods: This retrospective study included 49 patients with laryngeal cancer who underwent¹⁸F-FDG-PET/CT before treatment, and these patients were divided into the training (n = 34) and testing (n = 15) cohorts.Seven clinical (age, sex, tumor size, T stage, N stage, Union for International Cancer Control stage, and treatment) and 40¹⁸F-FDG-PET–based radiomic features were used to predict disease progression and survival. Six ML algorithms (random forest, neural network, k-nearest neighbors, naïve Bayes, logistic regression, and support vector machine) were used for predicting disease progression. Two ML algorithms (cox proportional hazard and random survival forest [RSF] model) considering for time-to-event outcomes were used to assess progression-free survival (PFS), and prediction performance was assessed by the concordance index (C-index). Results: Tumor size, T stage, N stage, GLZLM_ZLNU, and GLCM_Entropy were the five most important features for predicting disease progression.In both cohorts, the naïve Bayes model constructed by these five features was the best performing classifier (training: AUC = 0.805; testing: AUC = 0.842). The RSF model using the five features (tumor size, GLZLM_ZLNU, GLCM_Entropy, GLRLM_LRHGE and GLRLM_SRHGE) exhibited the highest performance in predicting PFS (training: C-index = 0.840; testing: C-index = 0.808). Conclusion: ML analyses involving clinical and¹⁸F-F-DG-PET–based radiomic features may help predict disease progression and survival in patients with laryngeal cancer. Advances in knowledge: ML approach using clinical and¹⁸F-FDG-PET–based radiomic features has the potential to predict prognosis of laryngeal cancer.

DOI： 10.1259/bjr.20220772

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PubMed

Language：English   Publisher：Annals of Nuclear Medicine  

Since the inline positron emission tomography (PET)/magnetic resonance imaging (MRI) system appeared in clinical, more than a decade has passed. In this article, we have reviewed recently-published articles about PET/MRI. There have been articles about staging in rectal and breast cancers by PET/MRI using fluorodeoxyglucose (FDG) with higher diagnostic performance in oncology. Assessing possible metastatic bone lesions is considered a proper target by FDG PET/MRI. Other than FDG, PET/MRI with prostate specific membrane antigen (PSMA)-targeted tracers or fibroblast activation protein inhibitor have been reported. Especially, PSMA PET/MRI has been reported to be a promising tool for determining appropriate sites in biopsy. Independent of tracers, the clinical application of artificial intelligence (AI) for images obtained by PET/MRI is one of the current topics in this field, suggesting clinical usefulness for differentiating breast lesions or grading prostate cancer. In addition, AI has been reported to be helpful for noise reduction for reconstructing images, which would be promising for reducing radiation exposure. Furthermore, PET/MRI has a clinical role in neuroscience, including localization of the epileptogenic zone. PET/MRI with new PET tracers could be useful for differentiation among neurological disorders. Clinical applications of integrated PET/MRI in various fields are expected to be reported in the future.

DOI： 10.1007/s12149-022-01780-2

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PubMed

Language：Japanese   Publisher：Journal of Neuroimaging  

Background and Purpose: Differentiation between hemangioblastoma and brain metastasis remains a challenge in neuroradiology using conventional MRI. Amide proton transfer (APT) imaging can provide unique molecular information. This study aimed to evaluate the usefulness of APT imaging in differentiating hemangioblastomas from brain metastases and compare APT imaging with diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging. Methods: This retrospective study included 11 patients with hemangioblastoma and 20 patients with brain metastases. Region-of-interest analyses were employed to obtain the mean, minimum, and maximum values of APT signal intensity, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV), and these indices were compared between hemangioblastomas and brain metastases using the unpaired t-test and Mann-Whitney U test. Their diagnostic performances were evaluated using receiver operating characteristic (ROC) analysis and area under the ROC curve (AUC). AUCs were compared using DeLong's method. Results: All MRI-derived indices were significantly higher in hemangioblastoma than in brain metastasis. ROC analysis revealed the best performance with APT-related indices (AUC = 1.000), although pairwise comparisons showed no significant difference between the mean ADC and mean rCBV. Conclusions: APT imaging is a useful and robust imaging tool for differentiating hemangioblastoma from metastasis.

DOI： 10.1111/jon.13019

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PubMed

Language：English   Publisher：Medicine (United States)  

Rationale: I-131 radioiodine false-positive findings in postoperative patients with differentiated thyroid cancer (DTC) should be recognized to avoid unnecessary therapies. Patient concerns and diagnoses: A 50-year-old man underwent I-131 therapy 3 times, including the initial ablative therapy after total thyroidectomy for papillary thyroid cancer. The initial I-131 posttherapeutic whole-body scintigraphy showed 2 cervical and one superior mediastinal focal I-131 positive uptake lesions. The serum thyroglobulin level was negative every time when the radioiodine therapy was performed. Although the 2 cervical positive uptake lesions disappeared after the second therapy, the superior mediastinal I-131 positive uptake persisted even after the third therapy, and this lesion was suspicion of I-131 therapy-resistant node metastasis. Interventions and outcomes: The lesion was resected, and the pathological diagnosis with immune-histochemical analysis was a thymic cyst with thymic epithelial cells having a weak expression of the sodium-iodide symporter (NIS). Lessons: The false-positive result may be attributed to the NIS expression in the thymic cyst epithelial cells. It is necessary to include a thymic cyst in the differential diagnosis, when I-131 uptake is noted in the superior mediastinal region on I-131 posttherapeutic scans of patients with postoperative DTC. Although the I-131 positive uptake in a thymic cyst may be influenced by the I-131 administered dose and scan timing after I-131 administration, the NIS expression may be essential to the false-positive uptake in a thymic cyst.

DOI： 10.1097/MD.0000000000029282

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PubMed

Language：English   Publisher：British Journal of Radiology  

Objective: To examine whether the machine-learning approach using 18-fludeoxyglucose positron emission tomography (18F-FDG-PET)-based radiomic and deep-learning features is useful for predicting the pathological risk subtypes of thymic epithelial tumors (TETs). Methods: This retrospective study included 79 TET [27 low-risk thymomas (types A, AB and B1), 31 high-risk thymomas (types B2 and B3) and 21 thymic carcinomas] patients who underwent pre-therapeutic18F-FDG-PET/ CT. High-risk TETs (high-risk thymomas and thymic carcinomas) were 52 patients. The 107 PET-based radiomic features, including SUV-related parameters [maximum SUV (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG)] and 1024 deep-learning features extracted from the convolutional neural network were used to predict the pathological risk subtypes of TETs using six different machine-learning algorithms. The area under the curves (AUCs) were calculated to compare the predictive performances. Results: SUV-related parameters yielded the following AUCs for predicting thymic carcinomas: SUVmax 0.713, MTV 0.442, and TLG 0.479 or high-risk TETs: SUVmax 0.673, MTV 0.533, and TLG 0.539. The bestperforming algorithm was the logistic regression model for predicting thymic carcinomas (AUC 0.900, accuracy 81.0%), and the random forest (RF) model for high-risk TETs (AUC 0.744, accuracy 72.2%). The AUC was significantly higher in the logistic regression model than three SUV-related parameters for predicting thymic carcinomas, and in the RF model than MTV and TLG for predicting high-risk TETs (each; p < 0.05). Conclusion:18F-FDG-PET-based radiomic analysis using a machine-learning approach may be useful for predicting the pathological risk subtypes of TETs. Advances in knowledge: Machine-learning approach using18F-FDG-PET-based radiomic features has the potential to predict the pathological risk subtypes of TETs.

DOI： 10.1259/bjr.20211050

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PubMed

Language：Japanese   Publisher：(公社)日本医学放射線学会  

Language：English   Publisher：(公社)日本医学放射線学会  

免疫チェックポイント阻害剤(ICI)療法が施行された悪性黒色腫患者に対し、3種類の18F-FDG PET/CTによる治療効果判定法(EORTC法、PERCIST法、imPERCIST法)を用いて、腫瘍縮小効果判定能と予後予測能を比較した。調査対象者は2014年8月～2019年10月までの期間内に、後向き多施設共同研究に参加した国内医療施設5施設で、PD-1阻害剤もしくはPD-L1阻害剤療法が施行された悪性黒色腫患者27例(男性18例、女性9例、年齢39～86歳)とした。FDG PET/CT検査は治療前、治療(ニボルマブ投与は21例、ペムブロリズマブ投与は6例)開始後3～9ヵ月行い、治療効果判定はEORTC法、PERCIST法、imPERCIST法で評価した。その結果、harmonized EORTC、PERCIST、imPERCISTによる完全代謝奏効(CMR)/部分代謝奏効(PMR)/安定代謝(SMD)/進行代謝(PMD)は、それぞれ3例/5例/4例/15例、4例/5例/3例/15例、4例/5例/5例/13例で、各治療効果判定法で概ね完全な一致が得られた。しかし、うち20例では悪性黒色腫が進行し、14例は中央値19.2ヵ月後に死亡が確認され、治療奏効患者(CMR/PMR)では非治療奏効患者(SMD/PMD)に比べ、有意にPFSとOSが長かった。以上より、今回評価した3種のharmonized FDG-PET治療効果判定法(EORTC法、PERCIST法、imPERCIST法)により、CMR/PMR/SMD/PMDで高い一致度が得られ、ICI療法の治療効果(腫瘍縮小効果)判定、悪性黒色腫患者の予後予測能が高精度であることが確認された。

Language：Japanese   Publisher：The Japanese Society of Nuclear Medicine  

DOI： 10.18893/kakuigaku.wgr.2234

PubMed

CiNii Research

Language：English   Publisher：Molecular Imaging and Biology  

Purpose: To examine whether the machine learning (ML) analyses using clinical and pretreatment 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography ([18F]-FDG-PET)–based radiomic features were useful for predicting prognosis in patients with hypopharyngeal cancer. Procedures: This retrospective study included 100 patients with hypopharyngeal cancer who underwent [18F]-FDG-PET/X-ray computed tomography (CT) before treatment, and these patients were allocated to the training (n=80) and validation (n=20) cohorts. Eight clinical (age, sex, histology, T stage, N stage, M stage, UICC stage, and treatment) and 40 [18F]-FDG-PET–based radiomic features were used to predict disease progression. A feature reduction procedure based on the decrease of the Gini impurity was applied. Six ML algorithms (random forest, neural network, k-nearest neighbors, naïve Bayes, logistic regression, and support vector machine) were compared using the area under the receiver operating characteristic curve (AUC). Progression-free survival (PFS) was assessed using Cox regression analysis. Results: The five most important features for predicting disease progression were UICC stage, N stage, gray level co-occurrence matrix entropy (GLCM_Entropy), gray level run length matrix run length non-uniformity (GLRLM_RLNU), and T stage. Patients who experienced disease progression displayed significantly higher UICC stage, N stage, GLCM_Entropy, GLRLM_RLNU, and T stage than those without progression (each, p<0.001). In both cohorts, the logistic regression model constructed by these 5 features was the best performing classifier (training: AUC=0.860, accuracy=0.800; validation: AUC=0.803, accuracy=0.700). In the logistic regression model, 5-year PFS was significantly higher in patients with predicted non-progression than those with predicted progression (75.8% vs. 8.3%, p<0.001), and this model was only the independent factor for PFS in multivariate analysis (hazard ratio = 3.22; 95% confidence interval = 1.03–10.11; p=0.045). Conclusions: The logistic regression model constructed by UICC, T and N stages and pretreatment [18F]-FDG-PET–based radiomic features, GLCM_Entropy, and GLRLM_RLNU may be the most important predictor of prognosis in patients with hypopharyngeal cancer.

DOI： 10.1007/s11307-022-01757-7

Scopus

PubMed

Language：English   Publisher：EJNMMI Research  

Background: To explore the feasibility of short-time-window Ki imaging using a population-based arterial input function (IF) and optimized Bayesian penalized likelihood (BPL) reconstruction as a practical alternative to long-time-window Ki imaging with an individual patient-based IF. Myocardial Ki images were generated from 73 dynamic 18F-FDG-PET/CT scans of 30 patients with cardiac sarcoidosis. For each dynamic scan, the Ki images were obtained using the IF from each individual patient and a long time window (10–60 min). In addition, Ki images were obtained using the normalized averaged population-based IF and BPL algorithms with different beta values (350, 700, and 1000) with a short time window (40–60 min). The visual quality of each image was visually rated using a 4-point scale (0, not visible; 1, poor; 2, moderate; and 3, good), and the Ki parameters (Ki-max, Ki-mean, Ki-volume) of positive myocardial lesions were measured independently by two readers. Wilcoxon’s rank sum test, McNemar’s test, or linear regression analysis were performed to assess the differences or relationships between two quantitative variables. Results: Both readers similarly rated 51 scans as positive (scores = 1–3) and 22 scans as negative (score = 0) for all four Ki images. Among the three types of population-based IF Ki images, the proportion of images with scores of 3 was highest with a beta of 1000 (78.4 and 72.5%, respectively) and lowest with a beta of 350 (33.3 and 23.5%) for both readers (all p < 0.001). The coefficients of determination between the Ki parameters obtained with the individual patient-based IF and those obtained with the population-based IF were highest with a beta of 1000 for both readers (Ki-max, 0.91 and 0.92, respectively; Ki-mean, 0.91 and 0.92, respectively; Ki-volume, 0.75 and 0.60, respectively; and all p < 0.001). Conclusions: Short-time-window Ki images with a population-based IF reconstructed using the BPL algorithm and a high beta value were closely correlated with long-time-window Ki images generated with an individual patient-based IF. Short-time-window Ki images using a population-based IF and BPL reconstruction might represent practical alternatives to long-time-window Ki images generated using an individual patient-based IF.

DOI： 10.1186/s13550-022-00933-8

Scopus

PubMed

Language：English   Publisher：Japanese Journal of Radiology  

Purpose: This study examined the usefulness of the maximum standardized uptake value (SUVmax) of myocardial [123I]-metaiodobenzylguanidine ([123I]-MIBG) to characterize myocardial function by comparing it with echocardiographic parameters in patients with pheochromocytoma. Materials and methods: This study included 18 patients with pheochromocytoma who underwent both planar and [123I]-MIBG single-photon emission computed tomography/computed tomography scans and echocardiography before surgery. Myocardial [123I]-MIBG visibility and SUVmax were compared with echocardiographic parameters related to systolic and diastolic functions. The Mann–Whitney U test, Fisher exact test, or Spearman rank correlation assessed differences or relationships between two quantitative variables. Results: On visual analysis, 6 patients showed normal myocardial [123I]-MIBG uptake, whereas 12 patients showed decreased myocardial [123I]-MIBG uptake. No patients showed systolic dysfunction. A significant difference was observed in the incidence of diastolic dysfunction between the groups with normal and decreased uptake (p = 0.009), and left ventricular (LV) diastolic dysfunction was observed in 9 (75%) of 12 patients with decreased myocardial uptake. The myocardial SUVmax was significantly lower in 9 patients with LV diastolic dysfunction than in 9 patients with normal cardiac function (1.67 ± 0.37 vs. 3.03 ± 1.38, p = 0.047). Myocardial SUVmax was positively correlated with septal e′ (early diastolic velocity of septal mitral annulus) (ρ = 0.51, p = 0.031) and negatively correlated with the septal E/e′ ratio (early mitral E-velocity to early diastolic velocity of septal mitral annulus; ρ = − 0.64, p = 0.004), respectively. Conclusions: LV diastolic dysfunction was inversely related to myocardial [123I]-MIBG uptake. Myocardial [123I]-MIBG SUVmax may be useful for characterizing cardiac function in patients with pheochromocytoma. Second abstract. The semiquantitative analysis using the myocardial SUVmax in 123I-MIBG SPECT/CT was found to be potentially useful for characterizing cardiac function in patients with pheochromocytoma.

DOI： 10.1007/s11604-022-01365-z

Scopus

PubMed

Language：English   Publisher：Scientific Reports  

This study assessed the possibility of semi-automatic harmonization of standardized uptake values (SUVs) in multicenter studies. Phantom data were acquired using 16 PET/CT scanners (including 3 PET/CT scanners with a silicon photomultiplier detector). PET images obtained using 30-min/bed scans for optimum harmonization filter calculations and using 90–180-s/bed scans for SUV validation under clinical conditions were obtained. Time of flight and a reconstruction method with point-spread function correction were allowed. The optimal full width at half maximum of the 3D-Gaussian filter that minimizes the root mean square error with the median value of the JSNM harmonization range was calculated semi-automatically. The SUVmax and the SUVpeak of the hot spheres were measured, and the inter-scanner coefficient of variation (COV) was calculated before and after harmonization. The harmonization filter was applied to 11 of the 15 PET/CT scanners in which the SUV calibration accuracy had been verified, but not in the remaining 4 scanners. Under noiseless conditions before harmonization, the inter-scanner COVs of the SUVmax and the SUVpeak were as high as 21.57% and 12.20%, respectively, decreasing to 8.79% and 5.73% after harmonization, respectively. Harmonization brought the SUVmax of all the hot spheres to within the harmonization range. Even under clinical conditions affected by image noise, the inter-scanner COVs for the SUVmax and SUVpeak were as high as 8.83% and 5.18% after harmonization, respectively. By applying an optimal harmonization filter that is calculated semi-automatically, the harmonization of SUVs according to the JSNM strategy is possible in multicenter studies, thereby reducing inter-scanner COVs.

DOI： 10.1038/s41598-021-87942-0

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PubMed

Language：English   Publisher：Scientific Reports  

The association between 18F-fluorodeoxyglucose (18F-FDG) myocardial uptake and clinical presentations in cardiac sarcoidosis (CS) has not yet been clarified. The Patlak slope, Ki, which represents the rate of 18F-FDG uptake is a quantitative index of 18F-FDG metabolism. This study aims to investigate the usefulness of standardized uptake value (SUV) and Patlak Ki images (Ki images) extracted from dynamic 18F-FDG-PET/CT for evaluating the risk of clinical events (CEs) in CS. The SUV and Ki myocardial images were generated from 30 dynamic 18F-FDG-PET/CT scans of 21 CS patients. The SUV and Ki images both were rated as positive in 19 scans and negative in 11 scans with the same incidence of CEs which were significantly higher in positive than negative scans [cardiac dysfunction: 78.9% (15/19) vs. 27.2% (3/11); arrhythmic events: 65.5% (10/19) vs. 0% (0/11)]. In 19 positive scans, the three Ki parameters (Ki max, Ki mean and Ki volume) were significantly higher in scans for patients with arrhythmic events than in those without. Logistic regression analysis showed that the Ki volume alone was significantly associated with the risk of arrhythmic events. Our study suggests that Ki images may add value to SUV images for evaluating the risk of CEs in CS patients.

DOI： 10.1038/s41598-021-82217-0

Scopus

PubMed

Language：English   Publisher：Abdominal Radiology  

Purpose: To examine the usefulness of machine learning to predict prognosis in cervical cancer using clinical and radiomic features of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (CT) (18F-FDG-PET/CT). Methods: This retrospective study included 50 cervical cancer patients who underwent 18F-FDG-PET/CT before treatment. Four clinical (age, histology, stage, and treatment) and 41 18F-FDG-PET-based radiomic features were ranked and a subset of useful features for association with disease progression was selected based on decrease of the Gini impurity. Six machine learning algorithms (random forest, neural network, k-nearest neighbors, naive Bayes, logistic regression, and support vector machine) were compared using the areas under the receiver operating characteristic curve (AUC). Progression-free survival (PFS) was assessed using Cox regression analysis. Results: The five top predictors of disease progression were: stage, surface area, metabolic tumor volume, gray-level run length non-uniformity (GLRLM_RLNU), and gray-level non-uniformity for run (GLRLM_GLNU). The naive Bayes model was the best-performing classifier for predicting disease progression (AUC = 0.872, accuracy = 0.780, F1 score = 0.781, precision = 0.788, and recall = 0.780). In the naive Bayes model, 5-year PFS was significantly higher in predicted non-progression than predicted progression (80.1% vs. 9.1%, p < 0.001) and was only the independent factor for PFS in multivariate analysis (HR, 6.89; 95% CI, 1.92–24.69; p = 0.003). Conclusion: A machine learning approach based on clinical and pretreatment 18F-FDG PET-based radiomic features may be useful for predicting tumor progression in cervical cancer patients.

DOI： 10.1007/s00261-021-03350-y

Scopus

PubMed

Language：English   Publisher：American Journal of Roentgenology  

BACKGROUND. Accurate nodal staging is essential to guide treatment selection in patients with non-small cell lung cancer (NSCLC). To our knowledge, measurement of electron density (ED) using dual-energy CT (DECT) is unexplored for this purpose. OBJECTIVE. The purpose of our study was to assess the utility of ED from DECT in diagnosing metastatic mediastinal lymph nodes in patients with NSCLC in comparison with conventional CT and FDG PET/CT. METHODS. This retrospective study included 57 patients (36 men, 21 women; mean age, 68.4 } 8.9 [SD] years) with NSCLC and surgically resected mediastinal lymph nodes who underwent preoperative DECT and FDG PET/CT. The patients had a total of 117 resected mediastinal lymph nodes (33 metastatic, 84 nonmetastatic). Two radiologists independently reviewed the morphologic features of nodes on the 120-kVp images and also measured the iodine concentration (IC) and ED of nodes using maps generated from DECT data; consensus was reached for discrepancies. Two different radiologists assessed FDG PET/CT examinations in consensus for positive node uptake. Diagnostic performance was evaluated for individual and pairwise combinations of features. RESULTS. The sensitivity, specificity, and accuracy for nodal metastasis were 15.2%, 98.8%, and 75.2% for the presence of necrosis, respectively; 54.5%, 85.7%, and 76.9% for short-axis diameter greater than 8.5 mm; 63.6%, 73.8%, and 70.9% for long-axis diameter greater than 13.0 mm; 51.5%, 79.8%, and 71.8% for attenuation on 120-kVp images of 95.8 HU or less; 87.9%, 58.3%, and 66.7% for ED of 3.48 × 1023/cm3 or less; and 66.7%, 75.0%, and 72.6% for positive FDG uptake. Among pairwise combinations of features, accuracy was highest for the combination of ED and short-axis diameter (accuracy, 82.9%; sensitivity, 54.5%; specificity, 94.0%) and the combination of ED and positive FDG uptake (accuracy, 82.1%; sensitivity, 60.6%; specificity, 90.5%); these accuracies were greater than those for the individual features (p < .05). The remaining combinations exhibited accuracies ranging from 74.4% to 77.8%. Interobserver agreement analysis showed an intraclass correlation coefficient of 0.90 for ED. IC was not significantly different between metastatic and nonmetastatic nodes (p = .18) and was excluded from the diagnostic performance analysis. CONCLUSION. ED derived from DECT may help diagnose metastatic lymph nodes in NSCLC given decreased ED in metastatic nodes.

DOI： 10.2214/AJR.21.26208

Scopus

PubMed

Language：English   Publisher：Annals of Nuclear Medicine  

Objective: The prognostic value of treatment response in patients with non-small cell lung cancer (NSCLC) treated with immune-checkpoint inhibitors (ICIs) shown by 18F-fludeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) results obtained with multiple types of PET scanners using standardized uptake value (SUV) harmonization was evaluated. Methods: Fifty-eight patients treated with ICIs who underwent 18F-FDG PET/CT examinations with nine types of PET scanners at six hospitals were enrolled. SUV harmonization of multiple PET scanner results was performed using the dedicated software packages “RAVAT” and “RC Tool for Harmonization”. Tumor response was assessed by change in sum of harmonized SUVmax, according to the European Organization for Research and Treatment of Cancer (EORTC5) or the SUV of up to five lesions normalized to lean body mass, according to the PET Response Criteria in Solid Tumors (PERCIST5) and immunotherapy-modified PERCIST (imPERCIST5) criteria. The correlation between tumor response according to those three definitions and overall survival (OS) was evaluated and compared to known prognostic factors. Results: One-year OS in responders and non-responders for harmonized EROTC5 was 86 and 32%, for harmonized PERCIST5 was 86 and 32%, and for harmonized imPERCIST5 was 80 and 30%, respectively (each p = 0.001). Univariate analysis showed that all response criteria remained as prognostic factors. However, there was an overlap for the categories stable metabolic disease (SMD) and progression metabolic disease (PMD) in survival curves using the PET treatment response criteria. Conclusion: In patients with NSCLC treated with ICIs, tumor response based on the harmonized response criteria was associated with OS. PET response criteria using harmonized metabolic parameters may be difficult to routinely employ in daily practice due to overlapping SMD and PMD, although may have a supporting role for determining prognosis.

DOI： 10.1007/s12149-021-01667-8

Scopus

PubMed

Language：English   Publisher：(一社)日本核医学会  

免疫チェックポイント阻害薬(ICI)が投与された非小細胞肺癌(NSCLC)患者において、18F-FDG PET/CT検査よる治療効果判定で、PET装置の違いによるSUV値の変動を低減させるためSUV値を調和させることで、18F-FDG PET/CT検査で治療応答性予測が可能か検討した。2014年8月～2019年10月までの期間内に、国内医療施設6施設で免疫チェックポイント阻害薬(ICI)による治療前後に、9種類のPET装置で18F-FDG PET/CT検査が施行されたNSCLC患者のうち、選定基準を満たした患者58例(男性48例、女性10例、年齢54～88歳)を調査対象とした。SUVの調和には専用のソフトウェアを用いて行い、腫瘍応答性はSUV値を調和させたEuropean Organization for Research and Treatment of Cancer(EORTC5)、PET Response Criteria in Solid Tumors(PERCIST5)およびimmunotherapy-modified PERCIST(imPERCIST5)で評価した。その結果、SUV値を調和させたEROTC5、PERCIST5およびimPERCIST5によるレスポンダーおよびノンレスポンダーの1年全生存率(OS)は、それぞれ86%および32%、86%および32%、80%および30%であった。また、単変量解析により、これら全ての治療効果判定基準において予後予測能が認められたが、PET装置による治療効果判定基準を用いた生存曲線で、安定代謝(stable metabolic disease:SMD)と進行代謝(progression metabolic disease:PMD)のカテゴリーで重複が生じた。今回の後向き多施設共同研究により、SMDとPMDで重複が生じたため、本法を日常診療に導入することは難解と考えられたが、PET装置間のSUVを調和させることで施設間差が低減され、ICI治療を受けたNSCLC患者の治療応答性が予測され、OSと有意に関連することが明らかにされた。

Language：English   Publisher：Cancers  

The diagnostic value of18F-fluorodeoxyglucose (FDG) uptake in the management of intraductal papillary mucinous neoplasms (IPMNs) of the pancreas remains unclear. This study aimed to assess the role of FDG uptake in the diagnosis of different degrees of dysplasia of IPMNs. We retrospectively analyzed the following three points in 84 patients with IPMNs: (1) risk factors to predict high-grade dysplasia (HGD) and invasive carcinoma (INV); (2) the relationship between FDG uptake and glucose transporter 1 (GLUT-1) expression; and (3) the relationship between FDG uptake and the presence of mural nodules. The histopathological diagnosis was low-grade dysplasia (LGD) in 43 patients, HGD in 16, and INV in 25. The maximum standardized uptake value (SUV-max) was significantly higher in INV than in LGD/HGD (p < 0.0001, p = 0.0136). The sensitivity and specificity to discriminate INV from LGD/HGD were 80.0% and 86.2%, respectively, using the receiver operator characteristic curve, when the optimal cutoff score of SUV-max was set at 4.03. Those values were not different between HGD and LGD. More than half of HGD patients had low GLUT-1 expression. Taken together, FDG-PET/CT is useful in distinguishing between non-invasive and invasive IPMN. Our results offer critical information that may determine surgical treatment strategies.

DOI： 10.3390/cancers13184633

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PubMed

Language：Japanese   Publisher：Cancers  

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Phar-macokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (v<inf>e</inf> ), blood plasma volume per unit volume of tissue (v<inf>p</inf>), volume transfer constant between blood plasma and EES (K^trans ), and rate constant between EES and blood plasma (k<inf>ep</inf>) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), v<inf>e</inf> (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and K^trans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between v<inf>e</inf> and PCC (r = 0.601, p < 0.01). The v<inf>e</inf> derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

DOI： 10.3390/cancers13153914

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PubMed

Language：English   Publisher：Clinical nuclear medicine  

ABSTRACT: Granulocyte colony-stimulating factor (G-CSF)-producing tumors are malignant tumors associated with a poor prognosis, and G-CSF-producing liposarcoma is particularly rare. We report a case of G-CSF-producing dedifferentiated liposarcoma. 18F-FDG PET/CT showed abnormal 18F-FDG uptake throughout the bone marrow and in the primary site. When a diffuse bone marrow 18F-FDG uptake was observed on 18F-FDG PET/CT, G-CSF-producing dedifferentiated liposarcoma should be included in the differential diagnosis.

DOI： 10.1097/RLU.0000000000003783

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PubMed

Language：English   Publisher：European Journal of Nuclear Medicine and Molecular Imaging  

Purpose: To investigate the usefulness of the positron emission tomography response criteria in solid tumors 1.0 (PERCIST1.0) for predicting tumor response to neoadjuvant chemotherapy and prognosis and determine whether PERCIST improvements are necessary for esophageal squamous cell carcinoma (ESCC) patients. Patients and methods: We analyzed the cases of 177 ESCC patients and examined the association between PERCIST and their pathological responses. Associations of whole-PERCIST with progression-free survival (PFS) and overall survival (OS) were evaluated by a Kaplan-Meier analysis and Cox proportional hazards model. To investigate potential PERCIST improvements, we used the survival tree technique to understand patients’ prognoses. Results: There were significant correlations between the pathologic response and PERCIST of primary tumor (p < 0.001). The optimal cutoff value of the primary tumors’ SULpeak response to classify pathologic responses was −50.0%. The diagnostic accuracy of SULpeak response was 87.3% sensitivity, 54.1% specificity, 68.9% accuracy, positive predictive value 60.5%, and negative predictive value 84.1%. Whole-PERCIST was significantly associated with PFS and OS. The survival tree results indicated that a high reduction of the whole SULpeak response was significantly correlated with the patients’ prognoses. The cutoff values for the separation of prognoses were − 52.5 for PFS and − 47.1% for OS. Conclusion: PERCIST1.0 can help predict tumor responses and prognoses. However, 18F-FDG-PET/CT tends to underestimate residual tumors in histopathological response evaluations. Modified PERCIST, in which the partial metabolic response is further classified by the SULpeak response (−50%), might be more appropriate than PERCIST1.0 for evaluating tumor responses and stratifying high-risk patients for recurrence and poor prognosis.

DOI： 10.1007/s00259-021-05365-5

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PubMed

Language：English   Publisher：Medicine  

ABSTRACT: Recent breakthrough results from immune checkpoint inhibitors (ICIs) have paved the way to a new era of cancer immunotherapy, and have thus led to a paradigm shift of cancer treatment. In particular, inhibition of the antiprogrammed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) axis with ICI, including nivolumab and pembrolizumab, has been emerging as a novel treatment strategy for advanced gastric cancers. An accurate noninvasive assessment of the response to ICI is important for the management of patients with advanced or metastatic gastric cancer.To examine whether the European Organization for Research and Treatment of Cancer (EORTC) and PET Response Criteria in Solid Tumors (PERCIST) are valuable for predicting progression-free survival (PFS) in patients with advanced or metastatic gastric cancers treated with nivolumab.Six patients with advanced or metastatic gastric cancers who underwent 18F-FDG-PET/computed tomography (CT) scans before, and from 2 to 6 months after initiation of nivolumab therapy between September 2017 and August 2019, were evaluated retrospectively. The correlation between tumor progression and EORTC or PERCIST was assessed with the Fisher's exact test. The PFS was assessed with the Kaplan-Meier method.Two patients were alive without progression, and the remaining 4 patients exhibited tumor progression. Two patients without progression were classified as partial metabolic response (PMR) patients based on EORTC or PERCIST, while the other 4 patients with progression were classified as progressive metabolic disease (PMD) patients based on EORTC (P = .067), or stable metabolic disease (SMD) patients, or PMD patients based on PERCIST (P = .067).The mean and median PFS of all patients was 12.7 months (95% confidence interval [CI], 4.9-20.4 months) and 5 months (95%CI, 4.0-11.0 months). Two EORTC or PERCIST PMR patients showed significantly longer median PFS compared with 4 non-PMR patients (not reached vs 4.0 months, P = .044). Three PERCIST PMR or SMD patients also showed significantly longer median PFS compared with 3 PMD patients (not reached vs 4.0 months, P = .022). These results suggest that EORTC or PERCIST has the potential to predict PFS of patients with advanced or metastatic gastric cancers treated by nivolumab and further studies are needed to determine its value in larger study populations.

DOI： 10.1097/MD.0000000000025494

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PubMed

Publisher：メジカルビュー社  

DOI： 10.18885/ci.0000000553

CiNii Research

Language：Japanese   Publisher：(株)メジカルビュー社  

＜文献概要＞・正常副腎は,CT・MRIで腎頭側に逆Y字型としてみられる。・副腎偶発腫の大半を皮質腺腫が占める。皮質腺腫の診断手順を熟知することは重要である。皮質腺腫の診断は主に,腫瘤の脂質の有無と造影パターンによる2つのアプローチによりなされる。・褐色細胞腫が疑われる場合,副腎髄質シンチグラフィ(123I-MIBG)を積極的に行う。

Language：English   Publisher：Abdominal Radiology  

Purpose: To assess the utility of a machine-learning approach for predicting liver function based on technetium-99 m-galactosyl serum albumin (99mTc-GSA) single photon emission computed tomography (SPECT)/CT. Methods: One hundred twenty-eight patients underwent a 99mTc-GSA SPECT/CT-based liver function evaluation. All were classified into the low liver-damage or high liver-damage group. Four clinical (age, sex, background liver disease and histological type) and 8 quantitative 99mTc-GSA SPECT/CT features (receptor index [LHL15], clearance index [HH15], liver-SUVmax, liver-SUVmean, heart-SUVmax, metabolic volume of liver [MVL], total lesion GSA [TL-GSA, liver-SUVmean × MVL] and SUVmax ratio [liver-SUVmax/heart-SUVmax]) were obtained. To predict high liver damage, a machine learning classification with features selection based on Gini impurity and principal component analysis (PCA) were performed using a support vector machine and a random forest (RF) with a five-fold cross-validation scheme. To overcome imbalanced data, stratified sampling was used. The ability to predict high liver damage was evaluated using a receiver operating characteristic (ROC) curve analysis. Results: Four indices (LHL15, HH15, heart SUVmax and SUVmax ratio) yielded high areas under the ROC curves (AUCs) for predicting high liver damage (range: 0.89–0.93). In a machine learning classification, the RF with selected features (heart SUVmax, SUVmax ratio, LHL15, HH15, and background liver disease) and PCA model yielded the best performance for predicting high liver damage (AUC = 0.956, sensitivity = 96.3%, specificity = 90.0%, accuracy = 91.4%). Conclusion: A machine-learning approach based on clinical and quantitative 99mTc-GSA SPECT/CT parameters might be useful for predicting liver function.

DOI： 10.1007/s00261-021-02985-1

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Language：English   Publisher：Molecular Imaging and Biology  

Purpose: To examine the prognostic significance of pretreatment 2-deoxy-2-[18F]fluoro-d-glucose ([18F]-FDG) positron emission tomography (PET)-based radiomic features using a machine learning approach in patients with endometrial cancers. Procedures: Included in this retrospective study were 53 patients with endometrial cancers who underwent [18F]-FDG PET/X-ray computed tomography (CT) before treatment. Since two different PET scanners were used, post-reconstruction harmonization was performed for all PET parameters using the ComBat harmonization method. Four clinical (age, histological type, stage, and treatment method) and 40 [18F]-FDG PET-based radiomic features were ranked, and a subset of useful features was selected based on the decrease in the Gini impurity in terms of associations with disease progression. The machine learning algorithms (random forest, neural network, k-nearest neighbors (kNN), naive Bayes, logistic regression, and support vector machine) were compared using the areas under the receiver operating characteristic curve (AUC) and validated by the random sampling method. Progression-free survival (PFS) and overall survival (OS) were assessed by the Cox regression analysis. Results: The five best predictors of disease progression were coarseness, gray-level run length nonuniformity, stage, treatment method, and gray-level zone length nonuniformity. The kNN model obtained the best performance classifier for predicting the disease progression (AUC =0.890, accuracy =0.849, F1 score =0.848, precision =0.857, and recall =0.849). Coarseness which was the first ranked radiomic feature was selected for survival analyses, and only coarseness remained as a significant and independent factor for both PFS (hazard ratios (HR), 0.65; 95 % confidence interval [CI], 0.49–0.86; p=0.003) and OS (HR, 0.52; 95 % CI, 0.36–0.76; p<0.001) at multivariate Cox regression analysis. Conclusions: [18F]-FDG PET-based radiomic analysis using a machine learning approach may be useful for predicting tumor progression and prognosis in patients with endometrial cancers.

DOI： 10.1007/s11307-021-01599-9

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Language：English   Publisher：Japanese Journal of Radiology  

Objective: In malignant melanoma patients treated with immune checkpoint inhibitor (ICI) therapy, three different FDG-PET criteria, European Organization for Research and Treatment of Cancer (EORTC), PET Response Criteria in Solid Tumors (PERCIST), immunotherapy-modified PERCIST (imPERCIST), were compared regarding response evaluation and prognosis prediction using standardized uptake value (SUV) harmonization of results obtained with various PET/CT scanners installed at different centers. Materials and methods: Malignant melanoma patients (n = 27) underwent FDG-PET/CT examinations before and again 3 to 9 months after therapy initiation (nivolumab, n = 21; pembrolizumab, n = 6) with different PET scanners at five hospitals. EORTC, PERCIST, and imPERCIST criteria were used to evaluate therapeutic response, then concordance of the results was assessed using Cohen’s κ coefficient. Log-rank and Cox methods were employed to determine progression-free (PFS) and overall (OS) survival. Results: Complete metabolic response (CMR)/partial metabolic response (PMR)/stable metabolic disease (SMD)/progressive metabolic disease (PMD) with harmonized EORTC, PERCIST, and imPERCIST was seen in 3/5/4/15, 4/5/3/15, and 4/5/5/13 patients, respectively. Nearly perfect concordance between each pair of criteria was noted (κ = 0.939–0.972). Twenty patients showed progression and 14 died from malignant melanoma after a median 19.2 months. Responders (CMR/PMR) showed significantly longer PFS and OS than non-responders (SMD/PMD) (harmonized EORTC: p < 0.0001 and p = 0.011; harmonized PERCIST: p < 0.0001 and p = 0.0012; harmonized imPERCIST: p < 0.0001 and p = 0.0012, respectively). Conclusions: All harmonized FDG-PET criteria (EORTC, PERCIST, imPERCIST) showed accuracy for response evaluation of ICI therapy and prediction of malignant melanoma patient prognosis. Additional studies to determine their value in larger study populations will be necessary.

DOI： 10.1007/s11604-021-01174-w

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Language：English   Publisher：EJNMMI Research  

Background: The aim of this study was to assess the reader variability in quantitatively assessing pre- and post-treatment 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) scans in a defined set of images of cancer patients using the same semi-automated analytical software (Auto-PERCIST™), which identifies tumor peak standard uptake value corrected for lean body mass (SULpeak) to determine [18F]FDG PET quantitative parameters. Methods: Paired pre- and post-treatment [18F]FDG PET/CT images from 30 oncologic patients and Auto-PERCIST™ semi-automated software were distributed to 13 readers across US and international sites. One reader was aware of the relevant medical history of the patients (readreference), whereas the 12 other readers were blinded to history but had access to the correlative images. Auto-PERCIST™ was set up to first automatically identify the liver and compute the threshold for tumor measurability (1.5 × liver mean) + (2 × liver standard deviation [SD]) and then detect all sites with SULpeak greater than the threshold. Next, the readers selected sites they believed to represent tumor lesions. The main performance metric assessed was the percent change in the SULpeak (%ΔSULpeak) of the hottest tumor identified on the baseline and follow-up images. Results: The intra-class correlation coefficient (ICC) for the %ΔSULpeak of the hottest tumor was 0.87 (95%CI: [0.78, 0.92]) when all reads were included (n = 297). Including only the measurements that selected the same target tumor as the readreference (n = 224), the ICC for %ΔSULpeak was 1.00 (95%CI: [1.00, 1.00]). The Krippendorff alpha coefficient for response (complete or partial metabolic response, versus stable or progressive metabolic disease on PET Response Criteria in Solid Tumors 1.0) was 0.91 for all reads (n = 380) and 1.00 including for reads with the same target tumor selection (n = 270). Conclusion: Quantitative tumor [18F]FDG SULpeak changes measured across multiple global sites and readers utilizing Auto-PERCIST™ show very high correlation. Harmonization of methods to single software, Auto-PERCIST™, resulted in virtually identical extraction of quantitative tumor response data from [18F]FDG PET images when the readers select the same target tumor.

DOI： 10.1186/s13550-021-00754-1

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Language：English   Publisher：Molecular Imaging and Biology  

DOI： 10.1007/s11307-020-01516-6

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Language：English   Publisher：European Journal of Radiology  

DOI： 10.1016/j.ejrad.2020.109397

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Language：English   Publishing type：Research paper (scientific journal)  

Publisher：European Radiology  

DOI： 10.1007/s00330-019-06463-7

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Publisher：European Radiology  

DOI： 10.1007/s00330-019-06517-w

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Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Publisher：Clinical Radiology  

DOI： 10.1016/j.crad.2019.09.132

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Publisher：Nuclear Medicine Communications  

DOI： 10.1097/MNM.0000000000001168

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Publisher：Pancreas  

DOI： 10.1097/MPA.0000000000001427

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Language：English   Publishing type：Research paper (scientific journal)  

Publisher：Molecular Imaging and Biology  

DOI： 10.1007/s11307-018-1290-z

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Publisher：Abdominal Radiology  

DOI： 10.1007/s00261-019-01958-9

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Language：English   Publishing type：Research paper (scientific journal)  

Publisher：一般社団法人 日本核医学会  

DOI： 10.18893/kakuigaku.rp.1971

CiNii Research

Publisher：一般社団法人 日本核医学会  

DOI： 10.18893/kakuigaku.wgr.1977

CiNii Research

Publisher：British Journal of Radiology  

DOI： 10.1259/bjr.20180620

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Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Publisher：European Journal of Nuclear Medicine and Molecular Imaging  

DOI： 10.1007/s00259-018-4008-1

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Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Publisher：(一社)インターナショナルハートジャーナル刊行会  

肺高血圧症(PH)患者では肺の123-メタヨードベンジルグアニジン(123I-MIBG)取り込みが低下しているとの仮説を立て、PH患者の肺123I-MIBG取り込みを評価し、心エコー検査や右心カテーテル法で得られた各指標と比較検討した。2003年12月〜2014年12月に123I-MIBGシンチを施行されたPH患者21例と、性別・年齢を一致させた対照8例を対象とした。心エコー、6分間歩行試験、B型ナトリウム利尿ペプチド測定、肺機能検査、右心カテーテル法を施行した。PH患者を慢性血栓塞栓性肺高血圧症(CTEPH)9例(男性2例、女性7例、平均69.1±7.5歳)と肺動脈高血圧症(PAH)12例(男性3例、女性9例、平均54.1±13.4歳)に分けた。平均肺動脈圧はCTEPH群が37.7±6.8mmHg、PAH群が32.3±5.3mmHgで有意差はなかった。両群間でその他の血行動態パラメーターに有意差はなかった。123I-MIBGの肺取り込みはPAH群ではearly image(EI)1.54±0.18、delayed image(DI) 1.41±0.16で、CTEPH群のEI 2.17±0.25、DI 1.99±0.20、対照群のEI2.32±0.27、DI 1.92±0.19よりも有意に低かった。PAH患者では肺血管内皮機能が低下している可能性が示唆された。

Publisher：一般社団法人 インターナショナル・ハート・ジャーナル刊行会  

<p>According to recent studies, lung uptake of iodine-123-metaiodobenzylguanidine (¹²³I-MIBG) is impaired in many lung diseases and low lung uptake of ¹²³I-MIBG suggests endothelial dysfunction of the pulmonary artery. ¹²³I-MIBG scintigraphy in patients with pulmonary hypertension (PH) has not yet been clinically evaluated. We hypothesized that the lung uptake of ¹²³I-MIBG is reduced in patients with PH and differs among PH subtypes. The purpose of the present study was to analyze the lung uptake of ¹²³I-MIBG in patients with PH and compare it with the data obtained by echocardiography or right heart catheterization. ¹²³I-MIBG scintigraphy was performed in 286 consecutive patients from 2003 to 2014. We enrolled 21 patients with PH and 8 control patients. The 21 patients with PH were categorized into those with pulmonary artery hypertension (PAH, <i>n</i> = 12) and those with chronic thromboembolic pulmonary hypertension (CTEPH, <i>n</i> = 9). The mean pulmonary artery pressure was not significantly different between patients with CTEPH and PAH (37.7 ± 6.8 versus 32.3 ± 5.3 mmHg respectively; <i>P</i> = 0.054). There were no significant differences in any other hemodynamic parameters between the two groups. The lung uptake of ¹²³I-MIBG in PAH patients (early image: 1.54 ± 0.18, delayed image: 1.41 ± 0.16) was significantly lower than that of CTEPH patients (early image: 2.17 ± 0.25, <i>P</i> < 0.0001; delayed image: 1.99 ± 0.20, <i>P</i> = 0.0001, adjusted for age and World Health Organization classification) and controls (early image: 2.32 ± 0.27, <i>P</i> = 0.0007; delayed image: 1.92 ± 0.19, <i>P</i> = 0.0007). In conclusion, we found for the first time that the lung uptake of ¹²³I-MIBG in patients with PAH is lower than that in patients with CTEPH and controls.</p>

DOI： 10.1536/ihj.16-629

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CiNii Research

Publisher：British Journal of Radiology  

DOI： 10.1259/bjr.20170546

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Publisher：Abdominal Radiology  

DOI： 10.1007/s00261-017-1207-3

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Publisher：European Journal of Nuclear Medicine and Molecular Imaging  

DOI： 10.1007/s00259-017-3787-0

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Publisher：Nagoya Journal of Medical Science  

DOI： 10.18999/nagjms.79.4.527

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Language：English   Publishing type：Research paper (scientific journal)  

Publisher：金原出版(株)  

PET検診6256件を対象に、癌発見率と年代や性別、受診回数との関連を検討した。実受診者数は4898人で、うち複数回受検者が710人、内訳は男3562人・女2694人・平均年齢58.0歳であった。162件(167の癌病変、重複癌3人、3重複癌1人を含む)の癌が発見され、癌発見率は延べで3.3%、初回で3.0%、癌病変発見率は延べで2.7%、初回で3.1%、2回目で1.4%であった。男女あわせた年代別発見率の推移では、加齢により有意に癌の発見率が上昇していた。男女別で50歳を境とした2群で年齢と発見率を比較したところ、男性では50歳以上で50歳未満に比べて発見率が高く、女性では有意差はなかった。初回受診者のみの病変発見率をみると、全体と同様に男性で発見率が高く、加齢によりその傾向が顕著であったが、各年代での発見率がより高かった。以上、PET癌検診発見率は受検者の年齢や性別、特に年齢に大きく影響されると考えられた。

Publisher：Journal of the Endocrine Society  

DOI： 10.1210/js.2017-00182

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Language：English   Publishing type：Research paper (scientific journal)  

Publisher：Abdominal Radiology  

DOI： 10.1007/s00261-016-0987-1

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Publisher：Journal of Magnetic Resonance Imaging  

DOI： 10.1002/jmri.25452

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Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Publisher：Abdominal Radiology  

DOI： 10.1007/s00261-016-0947-9

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Publisher：European Journal of Nuclear Medicine and Molecular Imaging  

DOI： 10.1007/s00259-016-3506-2

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Publisher：金原出版(株)  

Publisher：(株)メディカルアイ  

18F-FDG-PET/CTにおけるtexture解析は、腫瘍内の不均一性を評価する方法であり、腫瘍の悪性度評価や治療効果判定などに有用と考えられる。Texture解析方法の標準化などを含めて、日常臨床においてtexture解析を活用するには、様々な課題があるが、今後、人工知能(AI)を用いた研究の発展に期待される。(著者抄録)

Publisher：(一社)日本核医学会  

Publisher：(株)メジカルビュー社  

副腎の画像診断においては、代謝機能を反映する核医学画像は古くから非常に重要な役割を果たしてきた。最近ではSPECTやPETの核医学画像と形態画像のCTやMRIとの融合も容易となり、よりわかりやすい画像が得られるようになってきた。(著者抄録)

Publisher：名古屋大学医学部  

Event date： 2015.10

Language：English   Presentation type：Oral presentation (general)  

Venue：Hamburg, Germany  

Event date： 2015.6

Language：English   Presentation type：Oral presentation (general)  

Venue：Baltimore, USA.  

Event date： 2014.11

Language：Japanese  

Venue：大阪  

国内学会

Event date： 2014.6

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Venue：セントルイス  

国際学会

Event date： 2014.4

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Venue：神奈川  

国内学会

Event date： 2013.12

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Venue：シカゴ  

国際学会

Event date： 2013.11

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Venue：韓国  

国際学会

Event date： 2013.11

Language：Japanese  

Venue：福岡  

国内学会

Event date： 2013.6

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Venue：カナダ  

国際学会

Event date： 2013.4

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Venue：神奈川  

国内学会

Event date： 2012.11

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Venue：シカゴ  

国際学会

Event date： 2012.10

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Venue：札幌  

国内学会

Event date： 2012.6

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Venue：マイアミ  

国際学会

Event date： 2012.4

Language：Japanese  

Venue：神奈川  

国内学会

Event date： 2011.11

Language：Japanese  

Venue：茨城  

国内学会

Event date： 2011.10

Language：English  

Venue：イギリス  

国際学会

Event date： 2011.4

Language：Japanese  

Venue：神奈川  

国内学会

Language：Japanese  

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Language：Japanese  

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