Abstract
Pre-treatment T2-weighted magnetic resonance radiomics for prediction of loco-regional recurrence after image-guided adaptive brachytherapy for locally advanced cervical cancer
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Molecular and Cellular Biology, University of California Davis, Davis, USA
Purpose:
The aim of this study was to investigate the predictive value of radiomic features of pre-treatment T2-weighted magnetic resonance images (MRI) for clinical outcomes of radiotherapy in cervical cancer patients.
Material and methods:
Ninety cervical cancer patients with stage IB-IVA were retrospectively analyzed. All patients received definitive radiotherapy with or without concurrent chemotherapy. Radiomic features were extracted from gross tumor volume (GTV) on pre-treatment T2-weighted MRI. The association between radiomic features and loco-regional recurrence (LRR) was analyzed with Student’s t test, and false discovery rate was controlled using Storey method. Multivariate analysis with significant radiomic features with p-value < 0.01 and known clinical prognostic factors was performed using Cox proportional hazard model.
Results:
The majority of patients were stage IIIB (47.8%) and stage IIB (36.7%), and the most common histology was squamous cell carcinoma (74.5%). The median GTV volume was 37.5 ml (IQR, 16.3-93.1). The median dose of D90 received by high-risk clinical target volume (HR-CTV) was 86.2 Gy (IQR, 67.2-94.2). In a median follow-up time of 29.2 months, 12 of the 90 patients (13.3%) developed LRR. Eighty radiomic features were collected. There were four radiomic features, which showed significant correlation with LRR: Maximum intensity (p = 0.0002), Correlation135 GLCM (p = 0.0014), Correlation90 (p = 0.0015), and Correlation45 (p = 0.0034). Cox regression analysis yielded a significant hazard ratio for the maximum intensity (p = 0.038) and Correlation135 GLCM (p = 0.013) features. There was no statistically significant association for overall survival with any radiomic features.
Conclusions:
The maximum intensity and Correlation135 GLCM radiomic features of the pre-treatment T2-weighted MR images are predictive of loco-regional recurrence in cervical cancer patients after definitive radiotherapy with 3D-IGABT.
Keywords
radiomics, cervical cancer, loco-regional recurrence, prognostic factors, magnetic resonance imaging, features selection
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