Comparison of MRI Sequences to Predict ATRX Status Using Radiomics-Based Machine Learning

Abstract

ATRX is an important molecular marker according to the 2021 WHO classification of adult-type diffuse glioma. We aim to predict the ATRX mutation status non-invasively using radiomics-based machine learning models on MRI and to determine which MRI sequence is best suited for this purpose. In this retrospective study, we used MRI images of patients with histologically confirmed glioma, including the sequences T1w without and with the administration of contrast agent, T2w, and the FLAIR. Radiomics features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects. Feature preselection and subsequent model development were performed using Lasso regression. The T2w sequence was found to be the most suitable and the FLAIR sequence the least suitable for predicting ATRX mutations using radiomics-based machine learning models. For the T2w sequence, our seven-feature model developed with Lasso regression achieved a mean AUC of 0.831, a mean accuracy of 0.746, a mean sensitivity of 0.772, and a mean specificity of 0.697. In conclusion, for the prediction of ATRX mutation using radiomics-based machine learning models, the T2w sequence is the most suitable among the commonly used MRI sequences.

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

“…Overall, 41/62 of the reviewed studies (66%) focused on predicting IDH mutation and 1p/19q codeletion status only, while 33 studies (53%) analyzed other molecular subgroups. These were TERT [9,37,[40][41][42][43][44][45][46], ATRX [8,[47][48][49][50][51], H3K27 [4,[15][16][17][18], MGMT [50,[52][53][54][55], P53 [8,16,51,53], CDKN2A/B [12,30,35,56], EGFR [36], chr7/10 [57] and BRAF alterations [3,[5][6][7]. The reported AUC values range from 0.6 to 0.98 for these predictions with an average of 0.82 to 0.9.…”

Meta‐analysis of the impact of laser interstitial hyperthermia on wound healing complications in brain tumors

“…LITT has increasingly prioritized the treatment of high‐grade gliomas (HGGs), specifically Grade IV gliomas as classified by the World Health Organization (WHO) 3 . These malignant tumours exhibit a grim prognosis, with an overall survival rate of approximately 12 to 16 months.…”

“…LITT has increasingly prioritized the treatment of high‐grade gliomas (HGGs), specifically Grade IV gliomas as classified by the World Health Organization (WHO). 3 These malignant tumours exhibit a grim prognosis, with an overall survival rate of approximately 12 to 16 months. Recurrent high‐grade gliomas (HGGs) present additional difficulties, leading to the investigation of alternative therapies beyond conventional approaches.…”