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

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. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) 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), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and Ktrans (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 ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

DOI： 10.3390/cancers13153914

DOI： 10.3390/cancers13153914

PubMed

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

DOI： 10.1007/s11604-020-00942-4

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

DOI： 10.1007/s00330-019-06443-x

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

DOI： 10.1007/s00330-018-5832-1.

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Jpn J Radiol.  

DOI： 10.1007/s11604-018-0787-3.

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)  

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

Authorship：Lead author   Language：Japanese   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)  

Objectives: The potential use of electron density (ED) and effective atomic number (Zeff) derived from dual-energy computed tomography (DECT) as novel quantitative imaging biomarkers for differentiating malignant brain tumors was investigated. Methods: Data pertaining to 136 patients with a pathological diagnosis of brain metastasis (BM), glioblastoma, and primary central nervous system lymphoma (PCNSL) were retrospectively reviewed. The 10th percentile, mean and 90th percentile values of conventional 120-kVp CT value (CTconv), ED, Zeff, and relative apparent diffusion coefficient derived from diffusion-weighted magnetic resonance imaging (rADC: ADC of lesion divided by ADC of normal-appearing white matter) within the contrast-enhanced tumor region were compared across the three groups. Furthermore, machine learning (ML)-based diagnostic models were developed to maximize diagnostic performance for each tumor classification using the indices of DECT parameters and rADC. Machine learning models were developed using the AutoGluon-Tabular framework with rigorous patient-level data splitting into training (60%), validation (20%), and independent test sets (20%). Results: The 10th percentile of Zeff was significantly higher in glioblastomas than in BMs (p = 0.02), and it was the only index with a significant difference between BMs and glioblastomas. In the comparisons including PCNSLs, all indices of CTconv, Zeff, and rADC exhibited significant differences (p < 0.001-0.02). DECT-based ML models exhibited high area under the receiver operating characteristic curves (AUC) for all pairwise differentiations (BMs vs. Glioblastomas: AUC = 0.83; BMs vs. PCNSLs: AUC = 0.91; Glioblastomas vs. PCNSLs: AUC = 0.82). Combined models of DECT and rADC demonstrated excellent diagnostic performance between BMs and PCNSLs (AUC = 1) and between Glioblastomas and PCNSLs (AUC = 0.93). Conclusion: This study suggested the potential of DECT-derived ED and Zeff as novel quantitative imaging biomarkers for differentiating malignant brain tumors.

DOI： 10.3390/tomography11110120

PubMed

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

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

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

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

PubMed

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

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

PubMed

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

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

PubMed

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

The purpose of this study is to evaluate left atrial function using cine-magnetic resonance imaging (cine-MRI) in patients with pulmonary vein stump thrombus (PVST) after left upper lobectomy (LUL). The study population comprised 91 patients (30 with PVST and 61 without PVST) who underwent LUL for pulmonary lesions and evaluation by cine-MRI. Left atrial functional parameters were evaluated and compared between patients with and without the development of PVST after LUL using the Mann-Whitney U test. The diagnostic capabilities of these parameters for predicting PVST development were assessed using receiver-operating characteristic (ROC) curve analysis. Clinical and left atrial functional parameters were analyzed by multivariate logistic regression models to determine predictors of PVST. Left atrial end-systolic volume (LAESV), left atrial end-diastolic volume (LAEDV), LAESV index (LAESVI), and LAEDV index (LAEDVI) were significantly greater in patients who developed PVST than in those without PVST (p = 0.009, < 0.001, 0.004, and < 0.001, respectively). Left atrial ejection fraction (LAEF) was significantly lower in patients who developed PVST than in those without PVST (p < 0.001). The area under the ROC curve for predicting PVST was 0.668, 0.769, 0.688, 0.792, and 0.803 for LAESV, LAEDV, LAESVI, LAEDVI, and LAEF, respectively. In the multivariate logistic regression analysis, only LAEF was identified as an independent predictor of PVST (OR 0.896; 95% CI 0.846-0.950). In conclusion, left atrial enlargement and left atrial dysfunction were associated with the development of PVST after LUL.

DOI： 10.1038/s41598-025-91030-y

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：(公社)日本医学放射線学会  

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

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. 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

PubMed

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

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

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

PubMed

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

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

PubMed

Language：Japanese   Publisher：(株)インナービジョン  

頭頸部には眼窩・視神経,鼻副鼻腔,口腔,側頭骨,唾液腺,咽頭,喉頭,甲状腺,リンパ節など,多数の評価対象となる構造が存在するため,病変の指摘や質的診断には,十分な空間分解能とともに高いコントラスト分解能を有する画像の取得が求められる。そのため,頭頸部領域における局所評価にはMRIが推奨され,特に腫瘍性病変の局所評価を行う目的でMRI検査が施行されることが多い。しかし,病変の組織生検が行いやすい部位であるため,臨床上は質的診断よりも解剖学的な位置や広がりについての評価が求められる場合が多い。一方で,頭頸部領域におけるMRI検査は,主に脳神経領域で開発,検討されているさまざまな定量的画像評価法を応用しやすい領域の一つである。拡散強調画像をはじめとした多くの定量的画像が,病変の質的診断のみならず,治療効果判定や予後予測にも有用であることが報告されており,解剖学的情報に加えて,定量的画像から得られる情報も臨床医に適切に提供することが望ましい。本稿では,定量的画像評価法のうち,今後の発展が期待される化学交換飽和移動(chemical exchange saturation transfer:CEST)イメージングについて,頭頸部領域での臨床応用の現状や今後の展望を,筆者の個人的な期待を含めて述べる。(著者抄録)

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

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 (ADCOGSE) and PGSE (ADCPGSE) as well as the ADC ratio (ADCOGSE/ADCPGSE) 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 ADCOGSE, ADCPGSE, and ADCOGSE/ADCPGSE 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 ADCOGSE and ADCPGSE, ADCOGSE/ADCPGSE 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 ADCOGSE/ADCPGSE 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 ADCOGSE and ADCPGSE. 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

PubMed

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

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

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：(株)日本臨床社  

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000005003

CiNii Research

Language：Japanese   Publisher：(株)Gakken  

＜文献概要＞Point　●感染性心内膜炎による心原性脳梗塞は,菌血症による疣贅の形成,疣贅の塞栓により,脳塞栓症・仮性動脈瘤形成・くも膜下出血・髄膜炎・脳膿瘍が生じる.●空気塞栓症(動脈性)は,外傷・心臓手術・CTガイド下肺生検などが原因となり,その病態は,空気による機械的閉塞,気泡に対する炎症反応による脳浮腫・虚血・血管内皮損傷・微小出血である.●脂肪塞栓症は,骨折により発症,脂肪による微小動脈塞栓,遊離脂肪酸による脳組織損傷が生じる.●腫瘍塞栓症の原因の多くは心臓粘液腫であり,心臓粘液腫では,腫瘍塞栓による梗塞・脳転移だけでなく,敗血症性脳塞栓症・動脈瘤形成を認めることがある.

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

DOI： 10.1002/jmri.29106.

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

BACKGROUND: Glioblastoma (GBM) is a malignant brain tumor, with radiological and genetic heterogeneity. We examined the association between radiological characteristics and driver gene alterations. METHODS: We analyzed the driver genes of 124 patients with IDH wild-type GBM with contrast enhancement using magnetic resonance imaging. We used a next-generation sequencing panel to identify mutations in driver genes and matched them with radiological information. Contrast-enhancing lesion localization of GBMs was classified into 4 groups based on their relationship with the subventricular zone (SVZ) and cortex (Ctx). RESULTS: The cohort included 69 men (55.6%) and 55 women (44.4%) with a mean age of 66.4 ± 13.3 years. EGFR and PDGFRA alterations were detected in 28.2% and 22.6% of the patients, respectively. Contrast-enhancing lesion touching both the SVZ and Ctx was excluded because it was difficult to determine whether it originated from the SVZ or Ctx. Contrast-enhancing lesions touching the SVZ but not the Ctx had significantly worse overall survival than non-SVZ lesions (441 days vs. 897 days, P = .002). GBM touching only the Ctx had a better prognosis (901 days vs. 473 days, P < .001) than non-Ctx lesions and was associated with EGFR alteration (39.4% vs. 13.2%, P = .015). Multiple contrast lesions were predominant in PDGFRA alteration and RB1-wild type (P = .036 and P = .031, respectively). CONCLUSIONS: EGFR alteration was associated with cortical lesions. And PDGFRA alteration correlated with multiple lesions. Our results suggest that clarifying the association between driver genes and tumor localization may be useful in clinical practice, including prognosis prediction.

DOI： 10.1093/noajnl/vdad110

DOI： 10.1093/noajnl/vdad110

PubMed

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

Amplification of the epidermal growth factor receptor gene (EGFR) and its variants are the most commonly detected pathogenic gene alterations in glioblastoma. Herein, we report a case of molecularly defined glioblastoma harboring an EGFR variant III (EGFRvIII) without EGFR amplification. The initial histological diagnosis was isocitrate dehydrogenase (IDH)-wildtype low-grade glioma, due to an absence of anaplasia, necrosis, and microvascular proliferation, and a low Ki-67 labeling index. DNA-based next-generation sequencing (NGS) panel analysis revealed a TERTp promoter mutation but no EGFR mutation or amplification, supporting the diagnosis of "molecular glioblastoma." However, RNA-based NGS panel analysis revealed mRNA expression of EGFRvIII. Therefore, the final integrative diagnosis was glioblastoma with non-amplified EGFRvIII. Our report suggests that non-amplified EGFRvIII might be an early molecular event in glioblastoma tumorigenesis. In addition to the usual DNA-based analysis, RNA-based analysis is required to identify exon-skipping EGFR variants without EGFR amplification.

DOI： 10.1016/j.prp.2023.154712

PubMed

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

DOI： 10.1259/bjr.20220772.

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

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

PubMed

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002853

CiNii Research

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002850

CiNii Research

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002851

CiNii Research

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002852

CiNii Research

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002849

CiNii Research

Publisher：学研メディカル秀潤社  

DOI： 10.15105/gz.0000002848

CiNii Research

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)Gakken  

Language：Japanese   Publisher：(株)日本臨床社  

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

Language：Japanese   Publisher：大道学館出版部  

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

OBJECTIVE: To evaluate the visualization of incidentally imaged normal pituitary gland on three-dimensional (3D) pseudo continuous arterial spin labeling (PCASL) perfusion imaging of the brain. METHODS: Ninety-three patients with a normal pituitary gland who underwent 3D PCASL for suspected brain diseases were retrospectively included. Visualization of the pituitary gland on PCASL cerebral blood flow (CBF) maps was assessed independently by two observers using a three-point grading system: Grade 1, pituitary CBF ≤ CBF of the cerebral white matter (WM); Grade 2, CBF of WM < pituitary CBF ≤ CBF of the cortical gray matter (GM); and Grade 3, CBF of GM < pituitary CBF. The interobserver agreement of visual grading was determined using weighted κ statistic. The associations of visual grades with age, sex, and pituitary volume were assessed using multivariate logistic regression. Pituitary glands were divided equally into three groups (small, medium, and large) according to their volume for categorization. RESULTS: The interobserver agreement for visual rating was excellent (weighted κ = 0.823). Of the 93 cases, Grades 1, 2, and 3 included 17 (18.3%), 41 (44.1%), and 35 cases (37.6%), respectively. Medium and large pituitary volume were significantly associated with Grade 3 visualization (p = 0.0153, OR = 4.8323; 95% CI: 1.3525, 17.2649 and p = 0.0009; OR = 9.0299; 95% CI: 2.4663, 33.0614, respectively), whereas there was no significant association for age or sex. CONCLUSION: The normal pituitary gland is often visualized with higher CBF than cortical GM on 3D PCASL, especially in individuals with larger pituitary volume. ADVANCES IN KNOWLEDGE: Appearance of the normal pituitary gland on 3D PCASL has been documented for the first time.

DOI： 10.1259/bjr.20201311

PubMed

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

Amide proton transfer (APT) imaging is a magnetic resonance (MR) molecular imaging technique that is sensitive to mobile proteins and peptides in living tissue. Studies have shown that APT-related signal intensity (APTSI) parallels with the malignancy grade of gliomas, allowing the preoperative assessment of tumor grades. An increased APTSI in malignant gliomas has been attributed to cytosolic proteins and peptides in proliferating tumor cells; however, the exact underlying mechanism is poorly understood. To get an insight into the mechanism of high APTSI in malignant gliomas, we investigated the correlations between APTSI and several MR imaging parameters including apparent diffusion coefficient (ADC), relative cerebral blood volume and pharmacokinetic parameters obtained in the same regions-of-interest in 22 high-grade gliomas. We found a significant positive correlation between APTSI and ADC (ρ = 0.625 and 0.490 for observers 1 and 2, respectively; p < 0.001 for both), which is known to be inversely correlated with cell density. Multiple regression analysis revealed that ADC was significantly associated with APTSI (p < 0.001 for both observers). Our results suggest possible roles of extracellular proteins and peptides in high APTSI in malignant gliomas.

DOI： 10.1038/s41598-021-90841-z

PubMed

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)  

DOI： 10.1016/j.acra.2019.04.012

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

DOI： 10.25259/SNI_5_2020

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

DOI： 10.1016/j.wneu.2019.07.179.

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

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

DOI： 10.1177/1971400918821085

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Eur Radiol.  

DOI： 10.1007/s00330-018-5570-4.

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

DOI： 10.2463/mrms.ci.2017-0160.

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

DOI： 10.1002/jmri.25987.

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

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

DOI： 10.1177/1971400917718843.

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Wolters Kluwer Health, Inc  

DOI： 10.1097/MD.0000000000002574.

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

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)  

Authorship：Lead author,　Corresponding 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：Japanese   Publishing type：Research paper (other academic)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (other academic)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (other academic)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (other academic)  

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

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

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

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

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

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

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

Language：Japanese

Responsible for pages：19-28   Language：Japanese

Total pages：527   Responsible for pages：8, 13, 55, 204, 245   Language：Japanese

Total pages：745-750   Language：Japanese Book type：General book, introductory book for general audience

Total pages：93-103   Language：Japanese Book type：General book, introductory book for general audience

Total pages：294   Responsible for pages：206-210   Language：Japanese Book type：Scholarly book

Total pages：60-65   Language：Japanese Book type：Scholarly book

Responsible for pages：1060-1066   Language：Japanese Book type：Scholarly book

Language：Japanese Book type：Scholarly book

Total pages：62-63   Language：Japanese Book type：Scholarly book

Total pages：4-12   Language：Japanese Book type：Scholarly book

Language：Japanese Book type：Scholarly book

Language：English Book type：Scholarly book

Event date： 2025.8

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2025.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2025.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：京都   Country：Japan  

Event date： 2024.9

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2024.5

Language：English   Presentation type：Poster presentation  

Venue：Singapore   Country：Singapore  

Event date： 2024.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2024.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：埼玉   Country：Japan  

Event date： 2024.2

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：埼玉   Country：Japan  

Event date： 2023.11

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2023.9

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2023.9

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：軽井沢   Country：Japan  

Event date： 2023.6

Language：English   Presentation type：Poster presentation  

Venue：virtual  

Event date： 2023.5

Language：English   Presentation type：Poster presentation  

Venue：VIRTUAL  

Event date： 2023.5 - 2023.12

Language：English   Presentation type：Oral presentation (general)  

Venue：virtual  

Event date： 2023.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2023.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京   Country：Japan  

Event date： 2023.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：福岡  

Event date： 2022.11 - 2022.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2022.11 - 2022.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2022.9 - 2022.10

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京   Country：Japan  

Event date： 2022.9

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.9

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.7

Language：Japanese  

Venue：小樽   Country：Japan  

Event date： 2022.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：福岡  

Event date： 2022.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：福岡  

Event date： 2022.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.4

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2022.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京   Country：Japan  

Event date： 2022.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京   Country：Japan  

Event date： 2022.1

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：博多   Country：Japan  

Event date： 2021.11 - 2021.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago   Country：United States  

Event date： 2021.11 - 2021.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago   Country：United States  

Event date： 2021.9

Language：Japanese   Presentation type：Oral presentation (general)  

Country：Japan  

Event date： 2021.9

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Event date： 2021.7

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：山形+web   Country：Japan  

Event date： 2021.7

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：web開催   Country：Japan  

Event date： 2021.7

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：web開催   Country：Japan  

Event date： 2021.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：福岡  

Event date： 2021.5 - 2021.2

Language：English   Presentation type：Oral presentation (general)  

Venue：VIRTUAL  

Event date： 2021.5

Language：English   Presentation type：Oral presentation (general)  

Venue：virtual  

Event date： 2021.4

Language：English   Presentation type：Oral presentation (general)  

Venue：Yokohama   Country：Japan  

Event date： 2021.4

Language：English   Presentation type：Oral presentation (general)  

Venue：Yokohama   Country：Japan  

Event date： 2021.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：大阪  

Event date： 2021.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：大分  

Event date： 2020.11 - 2020.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2020.11 - 2020.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2020.11 - 2020.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2020.11

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2020.10

Language：English   Presentation type：Oral presentation (general)  

Venue：virtual  

Event date： 2020.9 - 2020.10

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2020.8

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：三重  

Event date： 2020.8

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Event date： 2020.8

Language：English   Presentation type：Oral presentation (general)  

Venue：virtual  

Event date： 2020.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：島根  

Event date： 2020.6

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：島根  

Event date： 2020.6

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2020.5 - 2020.6

Language：English   Presentation type：Poster presentation  

Venue：VIRTUAL  

Event date： 2020.5 - 2020.6

Language：English   Presentation type：Poster presentation  

Venue：VIRTUAL  

Event date： 2020.5 - 2020.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Yokohama  

Event date： 2020.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：博多  

Event date： 2020.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：佐賀  

Event date： 2020.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：佐賀  

Event date： 2020.1

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago  

Event date： 2019.11

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2019.11

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.10

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Event date： 2019.9

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.9

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.8

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：福岡  

Event date： 2019.7

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：北九州  

Event date： 2019.7

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：北九州  

Event date： 2019.6

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：久留米  

Event date： 2019.6

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.5

Language：English   Presentation type：Poster presentation  

Event date： 2019.5

Language：English   Presentation type：Poster presentation  

Venue：Montoreal  

Event date： 2019.5

Language：English   Presentation type：Poster presentation  

Event date： 2019.4

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：沖縄  

Event date： 2019.4

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：沖縄  

Event date： 2019.4

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2019.2

Language：English   Presentation type：Oral presentation (general)  

Venue：博多  

Event date： 2019.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：久留米  

Event date： 2019.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2019.1

Language：Japanese  

Event date： 2018.11

Language：English   Presentation type：Poster presentation  

Venue：Chicago, USA  

Event date： 2018.9

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2018.9

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2018.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：熊本  

Event date： 2018.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：熊本  

Event date： 2018.6

Language：English   Presentation type：Poster presentation  

Venue：Paris  

Event date： 2018.4

Language：English   Presentation type：Oral presentation (general)  

Event date： 2018.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2018.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2018.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：茨城  

Event date： 2018.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：長崎  

Event date： 2017.11 - 2017.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago, USA  

Event date： 2017.11 - 2017.12

Language：English   Presentation type：Poster presentation  

Venue：Chicago, USA  

Event date： 2017.10

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2017.9

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2017.6 - 2017.7

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：岐阜  

Event date： 2017.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：久留米  

Event date： 2017.4

Language：English   Presentation type：Poster presentation  

Venue：Hawaii, USA  

Event date： 2017.4

Language：English   Presentation type：Poster presentation  

Venue：Hawaii  

Event date： 2017.4

Language：English   Presentation type：Oral presentation (general)  

Venue：横浜  

Event date： 2017.3

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：鹿児島  

Event date： 2017.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京  

Event date： 2017.2

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：沖縄  

Event date： 2016.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Saitama  

Event date： 2016.9

Language：English   Presentation type：Oral presentation (general)  

Venue：Saitama  

Event date： 2016.6 - 2016.7

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：金沢  

Event date： 2016.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：宮崎  

Event date： 2016.5

Language：English   Presentation type：Oral presentation (general)  

Event date： 2016.5

Language：English   Presentation type：Poster presentation  

Event date： 2016.4

Language：Japanese   Presentation type：Oral presentation (general)  

Event date： 2015.11

Language：English   Presentation type：Oral presentation (general)  

Event date： 2015.11

Language：English   Presentation type：Oral presentation (general)  

Event date： 2015.11

Language：English   Presentation type：Poster presentation  

Event date： 2015.6

Language：English   Presentation type：Oral presentation (general)  

Event date： 2015.6

Language：English   Presentation type：Oral presentation (general)  

Event date： 2015.3

Language：Japanese  

Venue：博多  

研究会

Event date： 2015.3

Language：Japanese  

Venue：名古屋  

国内学会

Event date： 2015.2

Language：Japanese  

Venue：福岡  

研究会

Event date： 2014.9

Language：Japanese  

Venue：第252回 九州神経放射線研究会  

研究会

Event date： 2013.3

Language：English   Presentation type：Oral presentation (general)  

Event date： 2013.3

Language：English  

Venue：Vienna/Austria.  

国際学会

Event date： 2013.3

Language：English  

Venue：Vienna/Austria.  

国際学会

Event date： 2013.2

Language：English  

Venue：Kagoshima, Japan.  

国際学会

Event date： 2013.2

Language：English  

Venue：Kagoshima, Japan.  

国際学会

Event date： 2012.12

Language：English  

Venue：Chicago, USA.  

国際学会

Event date： 2012.10

Language：English  

Venue：Lisbon, Portugal  

国際学会

Event date： 2012.10

Language：English  

Venue：Lisbon, Portugal  

国際学会

Event date： 2012.10

Language：English  

Venue： LISBON/Portugal  

国際学会

Event date： 2012.9

Language：Japanese  

Venue：京都  

国内学会

Event date： 2012.9

Language：Japanese  

Venue：博多  

研究会

Event date： 2012.9

Language：Japanese  

Venue：博多  

研究会

Event date： 2012.8

Language：English  

Venue：Sydney, Australia  

国際学会

Event date： 2012.3

Language：English  

Venue：Vienna/Austria  

国際学会

Event date： 2012.2

Language：English  

Venue：久留米市  

国際学会

Event date： 2012.2

Language：Japanese  

Venue：鹿児島  

研究会

Event date： 2011.12

Language：Japanese  

Venue：鹿児島  

研究会

Event date： 2011.9

Language：Japanese  

Venue：博多  

研究会

Event date： 2011.9

Language：Japanese  

Venue：鹿児島  

研究会

Event date： 2011.7

Language：Japanese  

Venue：鹿児島  

研究会

Event date： 2011.6

Language：Japanese  

Venue：鹿児島  

研究会

Event date： 2011.1

Language：Japanese  

Venue：大阪市  

研究会

Event date： 2011.1

Language：Japanese  

Venue：博多  

研究会

Event date： 2010.10

Language：Japanese  

Venue：博多  

研究会

Event date： 2010.9

Language：English  

Venue：South Africa  

国際学会

Event date： 2010.6

Language：Japanese  

Venue：宮崎  

国内学会

Event date： 2010.1

Language：Japanese  

Venue：博多  

研究会

Language：Japanese  

Language：Japanese  

Language：Japanese  

Language：Japanese  

Language：English  

Language：Japanese  

Language：Japanese  

Language：Japanese  

Award type：Award from international society, conference, symposium, etc.  Country：United States

Award type：Award from Japanese society, conference, symposium, etc.  Country：Japan

Award type：Award from Japanese society, conference, symposium, etc.  Country：Japan

Award type：Award from international society, conference, symposium, etc.  Country：United States

Award type：Award from Japanese society, conference, symposium, etc.  Country：Japan

Award type：Award from Japanese society, conference, symposium, etc.  Country：Japan

Award type：Award from Japanese society, conference, symposium, etc.  Country：Japan