Measurement of pelvic parameters by magnetic resonance imaging to predict surgical difficulty of robot-assisted total mesorectal excision for mid and low rectal cancer
10.3760/cma.j.cn441530-20231108-00166
- VernacularTitle:基于MRI骨盆测量参数预测机器人辅助全直肠系膜切除术治疗中低位直肠癌的手术难度
- Author:
Mingyu HAN
1
;
Xiaofei DUAN
;
Quanbo ZHOU
;
Weitang YUAN
;
Yugui LIAN
Author Information
1. 郑州大学第一附属医院结直肠肛门外科，郑州 450052
- Keywords:
Rectal neoplasms;
Robotic surgery;
Pelvimetric parameters;
Total mesorectal excision;
Difficulty of surgery
- From:
Chinese Journal of Gastrointestinal Surgery
2024;27(8):824-832
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the relationship between pelvimetric parameters and surgical difficulty in robot-assisted total mesorectal excision (TME) performed by experienced colorectal surgeons, and to build a nomogram model.Methods:This was a retrospective observational study. The inclusion criteria were as follows: (1) tumor within 10 cm of the anal verge; (2) cancer confirmed by pathological examination of the postoperative specimen; (3) preoperative complete magnetic resonance imaging (MRI) data available; (4) depth of tumor invasion T1-3; (5) circumferential resection margin assessed as negative by MRI; and (6) R0 resection achieved. The exclusion criteria comprised (1) history of pelvic fractures; (2) history of pelvic surgery; and (3) emergency required because of tumor-related intestinal obstruction and/or perforation. Application of above criteria yielded 82 patients who had undergone robot-assisted total mesorectal excision of mid and low rectal cancer in the Department of Colorectal Surgery of the First Affiliated Hospital of Zhengzhou University from January 2021 to December 2022 (modeling group). Additionally, data of 35 patients with mid and low rectal cancer who had undergone robotic-assisted TME at the same center in 2023 January–August were collected for validation of the model (validation group). The following 13 pelvic parameters were studied: pelvic inlet diameter, pelvic outlet diameter, pubic tubercle height, sacral height, sacral depth, interspinous distance, inter-tuberosity distance, lateral mesorectal span, anterior-posterior mesorectal span, anterior mesorectal thickness, posterior mesorectal thickness, rectal area, and mesorectal area. Operating time was used as an indicator of the degree of surgical difficulty, this being defined as the time from the start of skin incision to the end of abdominal closure. Variables related to the duration of surgery were subjected to univariate and multivariate logistic regression analyses to identify factors associated with the difficulty of TME, after which a nomogram for predicting the difficulty of the procedure was established. We constructed receiver operating characteristic and calibration curves to validate the predictive power of nomogram. Furthermore, data from the validation group were used for external validation of the model.Results:The model group comprised 82 patients, including 54 men and 28 women of median age 61.0 years. The median body mass index (BMI) was 23.7 kg/m 2, median distance between the tumor and anal verge 6.1 cm, and median tumor diameter 4.5 cm. Fourteen of these patients had received preoperative adjuvant therapy and 12 had a history of abdominal surgery. There were 35 patients (24 men and 11 women) of median age 64.0 years in the validation group. Their median BMI was 23.7 kg/m 2 and median distance between the tumor and anal verge 6.3 cm. Multivariable analyses of the model group showed that BMI (OR=1.227, 95%CI: 1.240–1.469, P=0.026), distance between the tumor and anal verge (OR=0.733, 95%CI: 0.562–0.955, P=0.022), and interspinous distance (OR=0.468, 95%CI: 0.270–0.812, P=0.007) were independent predictors of surgical difficulty. We then built and validated a predictive nomogram based on the above three variables (AUC=0.804, 95%CI: 0.707–0.900). Calibration curves showed that the S:P in this model was 0.987 and the C-index 0.804. Area under the receiver operating characteristic curve of the predictive model in the validation dataset was 0.767 (95%CI: 0.606–0.928). Conclusion:MRI-based measurements of pelvic parameters are associated with difficulty of performing robot-assisted TME for mid and low rectal cancer. Our nomogram model constructed based on measurements of pelvic parameters has a good predictive ability.
