Using radiomics based on multicenter magnetic resonance images to predict isocitrate dehydrogenase mutation status of gliomas

Abstract

Background: Isocitrate dehydrogenase (IDH) mutation status is an important biomarker for the treatment strategy selection and prognosis evaluation of glioma. The purpose of this study is to predict the IDH mutation status of gliomas based on multicenter magnetic resonance (MR) images using radiomic models, which were composed from the selected radiomics features and logistic regression (LR), support vector machine (SVM), and LR least absolute shrinkage and selection operator (LASSO) classifiers. Methods:We retrospectively reviewed the medical records of 205 patients with gliomas. We enrolled 78 patients from Shandong Provincial Hospital from January 2018 to December 2019 as testing sets and 127 patients from The Cancer Genome Atlas (TCGA) as training sets. Preoperative MR images were stratified according to their IDH status, and the participants formed a consecutive and random series. Four MR modalities, including T1C, T2, T1 fluid-attenuated inversion recovery (FLAIR), and T2 FLAIR, were used for analysis. Five-fold cross-validation was adopted to train the models, and the models' performances were verified through the testing set. Tumor volumes of interest (VOI) were delineated on the 4 MR modalities. A total of 428 radiomics features were extracted. Two feature selection algorithms, Pearson correlation coefficient (PCC) and recursive feature elimination (RFE), were used to select radiomics features.These features were fed into 3 machine learning classifiers, which were LR, SVM, and LR LASSO, to construct prediction models. The accuracy (ACC), sensitivity (SEN), specificity (SPEC), and area under the curve (AUC) were applied to measure the predictive performance of the radiomics models. Results:The LR (SVM and LR LASSO) classifier predicted IDH mutation status with an average testing set ACC of 80.77% (80.64% and 80.41%), a SEN of 73.68% (84.21% and 89.47%), a SPEC of 87.50% (67.50% and 62.50%), and an AUC of 0.8572 (0.8217 and 0.8164). Conclusions:The radiomics models based on MR modalities demonstrated the potential to be used as tools across different data sets for the noninvasive prediction of the IDH mutation status in glioma.

Preoperative prediction of microvascular invasion classification in hepatocellular carcinoma based on clinical features and MRI parameters

“…Xu et al (25) reported no notable disparity in early recurrence after curative resection between patients with M0 HCC and patients with M1 HCC; however, the M2 grade was potentially associated with a poorer prognosis in patients with HCC. Although numerous studies (6,7,19,21,22,(26)(27)(28) have focused on predicting MVI status in patients with HCC, few have explored the preoperative grading of M2. To the best of our knowledge, no previous attempts have been made to use clinical and MRI features for preoperative prediction of the M2 classification in patients with HCC.…”

Novel Imaging Approaches for Glioma Classification in the Era of the World Health Organization 2021 Update: A Scoping Review

“…The analyzed images were mainly institution-based (imaged locally or in a multicentric setting), with only ten studies using a public cohort for external validation [7,11,[19][20][21][22][23][24][25][26] and four studies using public datasets (such as the BraTs 2021 [27][28][29][30]) without including local data. The studies utilizing public datasets could include significantly more patients than those with local imaging data.…”

Combination treatment of transcatheter arterial chemoembolization, intensity-modulated radiotherapy, and sorafenib for hepatocellular carcinoma with macrovascular invasion

“…This includes remarkable remission rates, durable local control, and extended survival times, whether applied alone or in combination with systemic treatments. [8][9][10][11][12][13] Specifically, unresectable HCC patients with MVI, possessing good liver function and well-developed periportal collateral circulation, may achieve substantial clinical benefits from TACE or combined TACE plus RT treatment. Moreover, the administration of sorafenib in conjunction with TACE and/or RT has demonstrated encouraging clinical outcomes for patients with locally advanced HCC.…”