In AJR. American journal of roentgenology
OBJECTIVE. The response of desmoid tumors (DTs) to chemotherapy is evaluated with Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) in daily practice and clinical trials. MRI shows early change in heterogeneity in responding tumors due to a decrease in cellular area and an increase in fibronecrotic content before dimensional response. Heterogeneity can be quantified with radiomics. Our aim was to develop radiomics-based response criteria and to compare their performances with clinical and radiologic response criteria. MATERIALS AND METHODS. Forty-two patients (median age, 38.2 years) were included in this retrospective multicenter study because they presented with progressive DT and had an MRI examination at baseline, which we refer to as "MRI-0," and an early MRI evaluation performed after the first chemotherapy cycle (mean time after first chemotherapy cycle, 3 months [SD, 28 days]), which we refer to as "MRI-1." After signal intensity normalization, voxel size standardization, discretization, and segmentation of DT volume on fat-suppressed contrast-enhanced T1-weighted imaging, 90 baseline and delta 3D radiomics features were extracted. Using cross-validation and least absolute shrinkage and selection operator-penalized Cox regression, a radiomics score was generated. The performances of models based on the radiomics score, modified Response Evaluation Criteria in Solid Tumors, European Association for the Study of the Liver criteria, Cheson criteria, Choi criteria, and revised Choi criteria from MRI-0 to MRI-1 to predict progression-free survival (PFS, as defined by RECIST 1.1) were assessed with the concordance index. The results were adjusted for performance status, tumor volume, prior chemotherapy, current chemotherapy, and β-catenin mutation. RESULTS. There were 10 cases of progression. The radiomics score included four variables. A high score indicated a poor prognosis. The radiomics score independently correlated with PFS (adjusted hazard ratio = 5.60, p = 0.003), and none of the usual response criteria independently correlated with PFS. The prognostic model based on the radiomics score had the highest concordance index (0.84; 95% CI, 0.71-0.96). CONCLUSION. Quantifying early changes in heterogeneity through a dedicated radiomics score could improve response evaluation for patients with DT undergoing chemotherapy.
Crombé Amandine, Kind Michèle, Ray-Coquard Isabelle, Isambert Nicolas, Chevreau Christine, André Thierry, Lebbe Celeste, Cesne Axel Le, Bompas Emmanuelle, Piperno-Neumann Sophie, Saada Esma, Bouhamama Amine, Blay Jean-Yves, Italiano Antoine
MRI, Response Evaluation Criteria in Solid Tumors (RECIST), aggressive, antineoplastic agents, fibromatosis, supervised machine learning