NI-12 The ratio of T1-Weighted to T2-Weighted Signal Intensity and IDH mutation in glioma

Introduction: Prediction of IDH mutation status for Lower-grade glioma (LrGG) is clinically significant. The purpose of this study is to test the hypothesis that the T1-weighted image/T2-weighted image ratio (rT1/T2), an imaging surrogate developed for myelin integrity, is a useful MRI biomarker for predicting the IDH mutation status of LrGG. Methods: Twenty-five LrGG patients (IDHwt: 8, IDHmt: 17) at Asahikawa Medical University Hospital (AMUH) were used as an exploratory cohort. Twenty-nine LrGG patients (IDHwt: 13, IDHmt: 16) from Osaka International Cancer Institute (OICI) and 103 patients from the Cancer Imaging Archive (TCIA) / Cancer Genome Atlas (TCGA) dataset (IDHwt: 19, IDHmt: 84) were used as validation cohorts. rT1/T2 images were calculated from T1- and T2-weighted images using a recommended signal correction. The region-of-interest was defined on T2-weighted images, and the relationship between the mean rT1/T2 (mrT1/T2) and the IDH mutation status was investigated. Results: The mrT1/T2 was able to significantly predict the IDH mutation status for the AMUH exploratory cohort (AUC = 0.75, p = 0.048). The ideal cut-off for detecting mutant IDH was mrT1/T2 < 0.666 ~ 0.677, with a sensitivity of 58.8% and a specificity of 87.5%. This result was further validated by the OICI validation cohort (AUC = 0.75, p = 0.023) with a sensitivity of 56.3% and a specificity of 69.2%. On the other hand, the sensitivity was 42.9% and the specificity was 68.4 % for the TCIA validation cohort (AUC = 0.63, p = 0.068). Conclusion: Our results supported the hypothesis that mrT1/T2 could be a useful image surrogate to predict the IDH mutation status of LrGG using two domestic cohorts. The decline of the accuracy for the TCIA cohort should be further investigated.

Fatty disc: An unusual pattern of disc degeneration

The intervertebral disc is the fibrocartilaginous structure between the endplates of adjacent vertebral bodies, providing support and mobility to the spine. Normally, the disc is isointense on the T1 weighted image (T1WI) and hyperintense on the T2 weighted image (T2WI). Degenerating disc shows loss of hyperintensity on T2WI due to disc dehydration. The development of hyperintensity on T1WI in degenerating disc is unusual. Causes of discal hyperintensity on T1WI include calcification, hemorrhage, melanin, mucin, or fat within the disc. Fat contents in the disc may be rarely seen in degeneration and appear as hyperintense signal on T1WI and T2WI. We, hereby report a case of discal hyperintensity on T1WI and T2WI due to fatty degeneration of the disc.

Mildly Elevated Bilirubin Levels are Associated with Increased Magnetic Resonance Imaging Signal Intensity in the Basal Ganglia of Preterm Neonates

Objective This study aimed to test whether mildly elevated bilirubin levels in preterm infants are associated with increased signal intensity (SI) on magnetic resonance imaging (MRI) of the basal ganglia (BG). Study Design MRI was performed at term equivalent age in 55 postpreterm infants using a neonatal MRI 1-T scanner. SI of the BG was correlated with mild hyperbilirubinemia. Results BG MRI SI was significantly increased in infants with mild hyperbilirubinemia on T1-weighted image (T1; p = 0.0393) and T2-weighted image (T2; p = 0.0309). We found no effect of gestational age or sepsis on BG MRI intensity; however, there was a significant effect of acidosis on T1 (p = 0.0223) but not on T2 (p = 0.2316). Infants with combined hyperbilirubinemia and acidosis had the most significant increase in SI on both T1 and T2 respectively (p = 0.0072 and 0.0195, respectively). Conclusion We found a positive association between increased BG MRI SI and mildly elevated bilirubin levels. The effect was greatly strengthened when hyperbilirubinemia was associated with acidosis. Key Points

MRI Finding of Prostatic Ductal Adenocarcinoma

Ductal adenocarcinoma is a variant of prostatic adenocarcinoma, originating from the epithelial lining of the primary and secondary ducts of the prostate. We report a 63-year-old male with prostatic ductal adenocarcinoma, presenting as urinary retention and a prostate-specific antigen (PSA) level of 11.71 ng/mL and biopsy-proven prostate cancer (Gleason score 3 + 3). MRI showed 2 hemorrhagic, multilocular cysts projecting into the bladder side from the prostatic inner gland and between the prostate and the right seminal vesicle. The prostate inner gland showed high signal intensity on the T2-weighted image and included tiny hyperintense spots on the fat-suppression T1-weighted image. In the part of the border of the hemorrhagic, multilocular cyst, a solid portion showing slight low intensity on T1-weigthed imaging and markedly restricted diffusion was observed, suggesting prostate cancer. He underwent total prostatectomy, and ductal adenocarcinoma (Gleason score 4 + 4) in the prostate inner gland and multilocular cysts was pathologically diagnosed. After the operation, his PSA level gradually increased, and MRI 8 months after the operation showed a vesical multilocular cyst, suggesting local recurrence. After he underwent radiation therapy and hormonal therapy, PSA level decreased, and no re-recurrence was observed during 8 years. We suggest its inclusion in the differential diagnosis of cases of prostatic ductal adenocarcinoma’s multiloculated cystic formation around the prostate and the bladder.

A Radiomics Model for Predicting Early Recurrence in Grade II Gliomas Based on Preoperative Multiparametric Magnetic Resonance Imaging

ObjectiveThis study aimed to develop a radiomics model to predict early recurrence (<1 year) in grade II glioma after the first resection.MethodsThe pathological, clinical, and magnetic resonance imaging (MRI) data of patients diagnosed with grade II glioma who underwent surgery and had a recurrence between 2017 and 2020 in our hospital were retrospectively analyzed. After a rigorous selection, 64 patients were eligible and enrolled in the study. Twenty-two cases had a pathologically confirmed recurrent glioma. The cases were randomly assigned using a ratio of 7:3 to either the training set or validation set. T1-weighted image (T1WI), T2-weighted image (T2WI), and contrast-enhanced T1-weighted image (T1CE) were acquired. The minimum-redundancy-maximum-relevancy (mRMR) method alone or in combination with univariate logistic analysis were used to identify the most optimal predictive feature from the three image sequences. Multivariate logistic regression analysis was then used to develop a predictive model using the screened features. The performance of each model in both training and validation datasets was assessed using a receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).ResultsA total of 396 radiomics features were initially extracted from each image sequence. After running the mRMR and univariate logistic analysis, nine predictive features were identified and used to build the multiparametric radiomics model. The model had a higher AUC when compared with the univariate models in both training and validation data sets with an AUC of 0.966 (95% confidence interval: 0.949–0.99) and 0.930 (95% confidence interval: 0.905–0.973), respectively. The calibration curves indicated a good agreement between the predictable and the actual probability of developing recurrence. The DCA demonstrated that the predictive value of the model improved when combining the three MRI sequences.ConclusionOur multiparametric radiomics model could be used as an efficient and accurate tool for predicting the recurrence of grade II glioma.