Affiliation:
1. Huaxi MR Research Center (HMRRC), Department of Radiology West China Hospital of Sichuan University Chengdu China
2. Department of Pathology West China Hospital of Sichuan University Chengdu China
3. Department of Neurosurgery West China Hospital of Sichuan University Chengdu China
Abstract
As an important genomic marker for oligodendrogliomas, early determination of 1p/19q co‐deletion status is critical for guiding therapy and predicting prognosis in patients with glioma. The purpose of this study is to systematically review the literature concerning the magnetic resonance imaging (MRI) with artificial intelligence (AI) methods for predicting 1p/19q co‐deletion status in glioma. PubMed, Scopus, Embase, and IEEE Xplore were searched in accordance with the Preferred Reporting Items for systematic reviews and meta‐analyses guidelines. Methodological quality of studies was assessed according to the Quality Assessment of Diagnostic Accuracy Studies‐2. Finally, 28 studies were included in the quantitative analysis. Diagnostic test accuracy reached an area under the ROC curve of 0.71–0.98 were reported in 24 studies. The remaining four studies with no available AUC provided an accuracy of 0.75–0. 89. The included studies varied widely in terms of imaging sequences, input features, and modeling methods. The current review highlighted that integrating MRI with AI technology is a potential tool for determination 1p/19q status pre‐operatively and noninvasively, which can possibly help clinical decision‐making. However, the reliability and feasibility of this approach still need to be further validated and improved in a real clinical setting.Evidence Level2.Technical Efficacy2.
Funder
National Natural Science Foundation of China
Subject
Radiology, Nuclear Medicine and imaging
Cited by
2 articles.
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