Comprehensive multicentre retrospective analysis for predicting isocitrate dehydrogenase-mutant lower-grade gliomas.

in Annals of clinical and translational neurology by Dongxu Zhao, Lin Duan, Tareq A Juratli, Fazheng Shen, Liyun Zhou, Shulin Cui, Hang Zhang, Hang Ren, Luyao Cheng, Hailan Wang, Wenhan Shi, Tianxiao Li, Ming Li

TLDR

  • This study aims to help doctors diagnose and treat brain tumors called gliomas. Gliomas can be divided into different grades, and some of them have a specific genetic mutation that can help doctors predict how the tumor will behave. The study used a combination of imaging tests and genetic testing to determine the grade of the glioma and whether it had the specific genetic mutation. The study found that a specific imaging test called the T2-FLAIR mismatch sign was better at predicting the grade of the glioma and whether it had the genetic mutation than another imaging test called the Hyper FLAIR rim sign. The study also found that a specific genetic test called the Cho/Cr ratio was better at predicting the grade of the glioma and whether it had the genetic mutation than other genetic tests. The study developed a tool that combines these tests to help doctors diagnose and treat gliomas more accurately.

Abstract

To differentiate glioma grading and determine isocitrate dehydrogenase (IDH) mutation status, which are crucial for prognosis assessment and treatment planning in glioma patients. This retrospective study included patients diagnosed with adult diffuse glioma from 1 January, 2018 to 31 July, 2023 in two independent institutions. It documented and analysed clinical and radiographic features. A nomogram model was constructed using stepwise regression to predict lower-grade gliomas and IDH mutation status. A total of 383 adult patients with diffuse glioma were included in the study, with Cohort A (297 patients) serving as the training set and Cohort B (86 patients) serving as the validation cohort. Consistent with previous reports, the Hyper fluid-attenuated inversion recovery (FLAIR) rim sign exhibited higher sensitivity in lower-grade gliomas for IDH mutant gliomas compared with the T2-FLAIR mismatch sign. However, the Hyper FLAIR rim sign was also present in Grade 4 gliomas, and thus, the T2-FLAIR mismatch sign exhibited better clinical efficacy in predicting glioma grade and IDH mutation compared with the Hyper FLAIR rim sign in clinical applications. Meanwhile, preoperative magnetic resonance spectroscopy (MRS) indicators, particularly the Cho/Cr ratio, have shown excellent performance in predicting glioma grade and IDH mutation status. The nomogram developed through stepwise regression demonstrated excellent predictive capabilities in distinguishing glioma grade and IDH mutation status. Combining imaging and molecular features, the predictive model established in this study offers a reliable non-invasive tool for predicting glioma grading and IDH mutation status, aiding the clinical decision-making process and improving patient management.

Overview

  • The study aims to differentiate glioma grading and determine isocitrate dehydrogenase (IDH) mutation status in adult diffuse glioma patients using clinical and radiographic features. A nomogram model was constructed using stepwise regression to predict lower-grade gliomas and IDH mutation status. The study included 383 adult patients with diffuse glioma, with Cohort A (297 patients) serving as the training set and Cohort B (86 patients) serving as the validation cohort. The study found that the Hyper fluid-attenuated inversion recovery (FLAIR) rim sign exhibited higher sensitivity in lower-grade gliomas for IDH mutant gliomas compared with the T2-FLAIR mismatch sign. However, the Hyper FLAIR rim sign was also present in Grade 4 gliomas, and thus, the T2-FLAIR mismatch sign exhibited better clinical efficacy in predicting glioma grade and IDH mutation compared with the Hyper FLAIR rim sign in clinical applications. Preoperative magnetic resonance spectroscopy (MRS) indicators, particularly the Cho/Cr ratio, have shown excellent performance in predicting glioma grade and IDH mutation status. The nomogram developed through stepwise regression demonstrated excellent predictive capabilities in distinguishing glioma grade and IDH mutation status. The study aims to provide a reliable non-invasive tool for predicting glioma grading and IDH mutation status, aiding the clinical decision-making process and improving patient management.

Comparative Analysis & Findings

  • The study compared the outcomes observed under different experimental conditions or interventions detailed in the study. The Hyper fluid-attenuated inversion recovery (FLAIR) rim sign exhibited higher sensitivity in lower-grade gliomas for IDH mutant gliomas compared with the T2-FLAIR mismatch sign. However, the Hyper FLAIR rim sign was also present in Grade 4 gliomas, and thus, the T2-FLAIR mismatch sign exhibited better clinical efficacy in predicting glioma grade and IDH mutation compared with the Hyper FLAIR rim sign in clinical applications. Preoperative magnetic resonance spectroscopy (MRS) indicators, particularly the Cho/Cr ratio, have shown excellent performance in predicting glioma grade and IDH mutation status. The nomogram developed through stepwise regression demonstrated excellent predictive capabilities in distinguishing glioma grade and IDH mutation status.

Implications and Future Directions

  • The study's findings suggest that combining imaging and molecular features can provide a reliable non-invasive tool for predicting glioma grading and IDH mutation status, aiding the clinical decision-making process and improving patient management. The study highlights the importance of preoperative MRS indicators, particularly the Cho/Cr ratio, in predicting glioma grade and IDH mutation status. Future research should focus on validating the nomogram model in larger cohorts and incorporating other imaging and molecular features to improve its predictive capabilities. Additionally, the study's findings can be used to develop personalized treatment plans for glioma patients based on their IDH mutation status and glioma grade.