MRI-based Radiomics Model for Preoperative Prediction of Lateral Pelvic Lymph Node Metastasis in Locally Advanced Rectal Cancer

Wei Zhao; Hui Xu; Rui Zhao; Sicheng Zhou; Shiwen Mei; Zhijie Wang; Fuqiang Zhao; Tixian Xiao; Fei Huang; Wenlong Qiu; Jianqiang Tang; Qian Liu

doi:10.1016/j.acra.2023.07.016

MRI-based Radiomics Model for Preoperative Prediction of Lateral Pelvic Lymph Node Metastasis in Locally Advanced Rectal Cancer

Acad Radiol. 2023 Aug 27:S1076-6332(23)00385-9. doi: 10.1016/j.acra.2023.07.016. Online ahead of print.

Authors

Wei Zhao¹, Hui Xu², Rui Zhao³, Sicheng Zhou¹, Shiwen Mei¹, Zhijie Wang¹, Fuqiang Zhao¹, Tixian Xiao¹, Fei Huang¹, Wenlong Qiu¹, Jianqiang Tang¹, Qian Liu⁴

Affiliations

¹ Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (W.Z., S.Z., S.M., Z.W., F.Z., T.X., F.H., W.Q., J.T., Q.L.).
² School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China (H.X.).
³ Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (R.Z.).
⁴ Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (W.Z., S.Z., S.M., Z.W., F.Z., T.X., F.H., W.Q., J.T., Q.L.). Electronic address: liuqncc@foxmail.com.

PMID: 37643928
DOI: 10.1016/j.acra.2023.07.016

Abstract

Rationale and objectives: To develop a magnetic resonance imaging (MRI)-based radiomics model for preoperative prediction of lateral pelvic lymph node (LPLN) metastasis (LPLNM) in patients with locally advanced rectal cancer MATERIALS AND METHODS: We retrospectively enrolled 263 patients with rectal cancer who underwent total mesorectal excision and LPLN dissection. Radiomics features from the primary lesion and LPLNs on baseline MRI images were utilized to construct a radiomics model, and their radiomics scores were combined to develop a radiomics scoring system. A clinical prediction model was developed using logistic regression. A hybrid predicting model was created through multivariable logistic regression analysis, integrating the radiomics score with significant clinical risk factors (baseline Carcinoembryonic Antigen (CEA), clinical circumferential resection margin status, and the short axis diameter of LPLN). This hybrid model was presented with a hybrid clinical-radiomics nomogram, and its calibration, discrimination, and clinical usefulness were assessed.

Results: A total of 148 patients were included in the analysis and randomly divided into a training cohort (n = 104) and an independent internal testing cohort (n = 44). The hybrid clinical-radiomics model exhibited the highest discrimination, with an area under the receiver operating characteristic (AUC) of 0.843 [95% confidence interval (CI), 0.706-0.968] in the testing cohort compared to the clinical model [AUC (95% CI) = 0.772 (0.589-0.856)] and radiomics model [AUC (95% CI) = 0.731 (0.613-0.849)]. The hybrid prediction model also demonstrated good calibration, and decision curve analysis confirmed its clinical usefulness.

Conclusion: This study developed a hybrid MRI-based radiomics model that incorporates a combination of radiomics score and significant clinical risk factors. The proposed model holds promise for individualized preoperative prediction of LPLNM in patients with locally advanced rectal cancer.

Data availability statement: The data presented in this study are available on request from the corresponding author.

Keywords: Lateral pelvic lymph nodes; Magnetic resonance imaging; Prediction model; Radiomics; Rectal neoplasms.