Value of MRI radiomics based on intratumoral and peritumoral heterogeneity in predicting spatial patterns of locally recurrent high-grade gliomas

To establish and validate a multimodal MRI radiomics model based on intratumoral and peritumoral heterogeneity for prediction of spatial pattern of locally recurrent high-grade gliomas (HGGs).

A retrospective analysis was conducted on the clinical and imaging data of all HGGs patients who underwent maximum safe resection followed by postoperative radiotherapy combined with temozolomide treatment and experienced in local recurrence in Army Medical Center of PLA from 2012 to 2021. Two radiologists independently assessed the spatial patterns of locally recurrence HGGs through continuous follow-up MRI data, and primarily categorized the pattern into intra-resection cavity recurrence and extra-resection cavity recurrence. The subjected patients were randomly divided into a training set and a validation set in a 7∶3 ratio. In the training set, Pearson or Spearman correlation analysis and least absolute shrinkage and selection operator (LASSO) analysis were employed to screen radiomic features within the intratumoral and peritumoral regions, as well as to calculate radiomic scores. A radiomics model was established using logistic regression analysis. The performance of the model was assessed using calibration curves, Hosmer-Lemeshow goodness-of-fit test, and the area under the receiver operating characteristic curve (AUC). Validation of the model was performed in the validation set.

A total of 121 patients with locally recurrent HGGs were enrolled in this study, including 54 in intra-resection cavity recurrence group and 67 in extra-resection cavity recurrence group. Among them, 84 were assigned into the training set and 37 into the validation set. In the training set, the radiomics score for the extra-resection cavity recurrence group was 0.424 (0.278, 0.573), which was higher than that for the intra-resection cavity recurrence group [-0.030 (-0.226,0.248), P<0.001]. In the validation set, the radiomics score for the extra-resection cavity recurrence group was 0.369 (0.258, 0.487), which was higher than that for the intra-resection cavity recurrence group [0.277 (0.103, 0.322), P=0.033]. The established radiomics model exhibited good calibration and performed well in predicting spatial recurrence patterns, with an AUC value of 0.844 (95%CI: 0 749~0.914) in the training set and 0.706 (95%CI: 0.534~0.844) in the validation set.

Our multimodal radiomics model combined with intratumoral and peritumoral heterogeneity can predict the spatial pattern of locally recurrent HGGs, providing a basis for individualized treatment of HGGs.