Abdominal radiology (New York) · 2025
MRI-based multiregional radiomics for pretreatment prediction of pathologic complete response to neoadjuvant chemoradiation therapy in locally advanced rectal cancer: a bicenter study.
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Lu Fulin, Li Xin, Chen Xiaoli, Liu Yisha, Liu Hao, Luo Bin, Zhang Xin, Li Hang
Аннотация
PURPOSE: This study aims to compare, select, and investigate MRI-based multiregional radiomics model to predict pathologic complete response (pCR) in Locally advanced rectal cancer (LARC) patients after neoadjuvant chemoradiotherapy (nCRT).
METHODS: This retrospective study included 245 patients who underwent rectal MRI examination before nCRT were recruited and split into training (hospital 1, n = 177) and external validation cohort (hospital 2, n = 68). Pretreatment T2WI and ADC images were used to manually delineate volumetric region of interest. Intratumoral, peritumoral-2 mm, peritumoral-3 mm, peritumoral-5 mm, and peritumoral-mesorectal fat (MRF) radiomics features were extracted. Clinical model was built based on clinical and MRI features. Diagnosis performance was compared among models. 3-year recurrence-free survival (RFS) was evaluated by Kaplan-Meier curve.
RESULTS: cN stage (odds ratio = 2.62, 95%CI,1.13-6.11) was a risk factor to construct clinical model. Peritumoral-3 mm radiomics model showed slightly higher performance than peritumoral-2 mm, peritumoral-5 mm, and peritumoral-MRF radiomics model, but there were no significant differences (all P > 0.05). Combining T2WI and ADC based intratumoral and peritumoral-3 mm radiomics model showed good performance with AUC of 0.793 and 0.759 in training and external validation cohort, respectively. The clinical-radiomics combined model showed better performance than clinical model (AUC, 0.829 vs. 0.599; P < 0.001) and better performance to the intratumoral and peritumoral-3 mm radiomics model (AUC, 0.829 vs. 0.793; P = 0.04) in training cohort. And the clinical-radiomics combined model showed better performance than clinical model (AUC, 0.793 vs. 0.599; P < 0.001) and better performance to the intratumoral and peritumoral-3 mm radiomics model (AUC, 0.795 vs. 0.759; P = 0.21) in external validation cohort. Kaplan-Meier survival curves showed high-risk patients defined by nomogram based non-pCR had a worse 3-year RFS than that of low-risk patients.
CONCLUSION: The nomogram integrating T2WI and ADC based intratumoral and peritumoral radiomics signatures and cN stage could preoperative predict pCR. The nomogram based pCR was associated with 3-year RFS.
METHODS: This retrospective study included 245 patients who underwent rectal MRI examination before nCRT were recruited and split into training (hospital 1, n = 177) and external validation cohort (hospital 2, n = 68). Pretreatment T2WI and ADC images were used to manually delineate volumetric region of interest. Intratumoral, peritumoral-2 mm, peritumoral-3 mm, peritumoral-5 mm, and peritumoral-mesorectal fat (MRF) radiomics features were extracted. Clinical model was built based on clinical and MRI features. Diagnosis performance was compared among models. 3-year recurrence-free survival (RFS) was evaluated by Kaplan-Meier curve.
RESULTS: cN stage (odds ratio = 2.62, 95%CI,1.13-6.11) was a risk factor to construct clinical model. Peritumoral-3 mm radiomics model showed slightly higher performance than peritumoral-2 mm, peritumoral-5 mm, and peritumoral-MRF radiomics model, but there were no significant differences (all P > 0.05). Combining T2WI and ADC based intratumoral and peritumoral-3 mm radiomics model showed good performance with AUC of 0.793 and 0.759 in training and external validation cohort, respectively. The clinical-radiomics combined model showed better performance than clinical model (AUC, 0.829 vs. 0.599; P < 0.001) and better performance to the intratumoral and peritumoral-3 mm radiomics model (AUC, 0.829 vs. 0.793; P = 0.04) in training cohort. And the clinical-radiomics combined model showed better performance than clinical model (AUC, 0.793 vs. 0.599; P < 0.001) and better performance to the intratumoral and peritumoral-3 mm radiomics model (AUC, 0.795 vs. 0.759; P = 0.21) in external validation cohort. Kaplan-Meier survival curves showed high-risk patients defined by nomogram based non-pCR had a worse 3-year RFS than that of low-risk patients.
CONCLUSION: The nomogram integrating T2WI and ADC based intratumoral and peritumoral radiomics signatures and cN stage could preoperative predict pCR. The nomogram based pCR was associated with 3-year RFS.