Purpose: Patients with locally advanced rectal cancer (LARC) achieving pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) have significantly improved long term survival. Preoperative detection o...Purpose: Patients with locally advanced rectal cancer (LARC) achieving pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) have significantly improved long term survival. Preoperative detection of pCR may enable a conservative therapeutic approach in some patients. The purpose of the current prospective pilot study was to assess multiparametric qualitative and quantitative MR, PET, PET-MR and tumor texture features in predicting pCR to CRT in patients with LARC. Material and Methods: Eighteen LARC patients underwent staging with FDG-PET and MR-rectum and 15 had post-CRT restaging. Response was assessed qualitatively and quantitatively. SUV (tumor/background), SUV/ADC, and tumor texture parameters derived via machine learning algorithms (MLA) from PET and multiple MR sequences and were correlated with histopathology. Results: A third of patients had pCR. Sensitivity, specificity & accuracy of PET, MR and combined PET-MR were 90, 60, & 80;90, 20 & 66.7;90, 80 & 86.7, respectively. Differences did not reach statistical significance. Quantitatively, only tumor-muscle (SUV/ADC) ratio improved prediction of pCR. Of all texture features assessed using MLA, only the classifier trained on pre-treatment PET was significant (p = 0.034;accuracy, 92.8%). Combined PET and MR texture features did not improve performance. Conclusion: Combined PET-MR may improve specificity compared with PET or MR alone, although this needs to be validated in a larger cohort. Tumor to muscle SUV/ADC ratios post-therapy and texture features on baseline PET show promise in improving prediction of pCR post-CRT in LARC.展开更多
文摘Purpose: Patients with locally advanced rectal cancer (LARC) achieving pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) have significantly improved long term survival. Preoperative detection of pCR may enable a conservative therapeutic approach in some patients. The purpose of the current prospective pilot study was to assess multiparametric qualitative and quantitative MR, PET, PET-MR and tumor texture features in predicting pCR to CRT in patients with LARC. Material and Methods: Eighteen LARC patients underwent staging with FDG-PET and MR-rectum and 15 had post-CRT restaging. Response was assessed qualitatively and quantitatively. SUV (tumor/background), SUV/ADC, and tumor texture parameters derived via machine learning algorithms (MLA) from PET and multiple MR sequences and were correlated with histopathology. Results: A third of patients had pCR. Sensitivity, specificity & accuracy of PET, MR and combined PET-MR were 90, 60, & 80;90, 20 & 66.7;90, 80 & 86.7, respectively. Differences did not reach statistical significance. Quantitatively, only tumor-muscle (SUV/ADC) ratio improved prediction of pCR. Of all texture features assessed using MLA, only the classifier trained on pre-treatment PET was significant (p = 0.034;accuracy, 92.8%). Combined PET and MR texture features did not improve performance. Conclusion: Combined PET-MR may improve specificity compared with PET or MR alone, although this needs to be validated in a larger cohort. Tumor to muscle SUV/ADC ratios post-therapy and texture features on baseline PET show promise in improving prediction of pCR post-CRT in LARC.
基金Supported by National Key Research and Development Plan Digital Diagnosis and Treatment Equipment Research and Development Project Research and Practice of PET-CT Comprehensive Evaluation System and Training System (No.2017YFC0113300)
