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Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
Published on: March 29, 2019
MRI-based multiregional radiomics for desmoplastic reaction classification and prognosis stratification in stage II
Shuxuan Fan1, Jing Wang2, Yan Hou3
1Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Purpose:
To develop an MRI-based multiregional radiomics model for the noninvasive desmoplastic reaction (DR) classification and prognosis stratification in stage II rectal cancer (RC) patients.
Materials And Methods:
This study retrospectively involved 336 patients with RC from two centers, with 239 from Center 1 divided into training (n = 191) and internal validation (n = 48) datasets at an 8:2 ratio, and 97 from Center 2 serving as external validation dataset. Radiomics features were extracted, and a multiregional radiomics DR (M-RDR) signature was established using multi-level feature selection procedure. The cut-off value for M-RDR was determined using Youden's index. We further evaluated the predictive values of M-RDR on prognosis and adjuvant chemotherapy stratification. The primary outcome was 3-year disease-free survival (DFS), and cox model performance was assessed using AUCs and 95 % confidence intervals.
Results:
M-RDR demonstrated a high accuracy in DR classification with AUCs of 0.778 and 0.798 in the training and internal validation datasets. Multivariable analysis confirmed M-RDR as an independent prognostic factor after adjusting for clinicopathological factors.The combined model incorporating M-RDR and clinicopathological factors showed good performance in predicting 3-year DFS, with AUCs of 0.923, 0.908, and 0.891 in the training, internal validation and external validation datasets, respectively. Additionally, patients in the M-RDR-high group who received adjuvant chemotherapy had significantly better DFS compared with those who did not (P < 0.05).
Conclusion:
The MRI-based multiregional radiomics model could effectively improve non-invasive DR classification, and was able to enhance postoperative risk stratification and treatment decision-making in stage II RC patients.
