Construction of recurrence prediction model after radical resection of middle and low rectal cancer based on magnetic resonance imaging measurement of perirectal fat content and its application value
10.3760/cma.j.cn115610-20230608-00269
- VernacularTitle:基于磁共振成像检查测量直肠周围脂肪含量构建中低位直肠癌根治术后复发预测模型及其应用价值
- Author:
JiaMing QIN
1
;
Yumeng ZHAO
;
Rui ZHANG
;
Yifei YU
;
Ziting YU
;
Shiqi ZHENG
;
Hongqi ZHANG
;
Shuxian LI
;
Wenhong WANG
Author Information
1. 南开大学医学院，天津 300071
- Keywords:
Rectal neoplasms;
Middle and low;
High resolution magnetic resonance imaging;
Rectal posterior mesangial thickness;
Prediction model;
Nomogram
- From:
Chinese Journal of Digestive Surgery
2023;22(7):924-932
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the influencing factors of recurrence after radical resection of middle and low rectal cancer, and to establish a prediction model based on magnetic resonance imaging (MRI) measurement of perirectal fat content and investigate its application value.Methods:The retrospective cohort study was constructed. The clinicopathological data of 254 patients with middle and low rectal cancer who were admitted to Tianjin Union Medical Center from December 2016 to December 2021 were collected. There were 188 males and 66 females, aged (61±9)years. All patients underwent radical resection of rectal cancer and routine pelvic MRI examina-tion. Observation indicators: (1) follow-up and quantitative measurement of perirectal fat content; (2) factors influencing tumor recurrence after radical resection of middle and low rectal cancer; (3) construction and evaluation of the nomogram prediction model of tumor recurrence after radical resection of middle and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(rang) and M( Q1, Q2). Count data were described as absolute numbers. Univariate and multivariate analyses were conducted using the COX regression model. The rms software package (4.1.3 version) was used to construct the nomogram and calibration curve. The survival software package (4.1.3 version) was used to calculate the C-index. The ggDCA software package (4.1.3 version) was used for decision curve analysis. Results:(1) Follow-up and quantitative measurement of perirectal fat content. All 254 patients were followed up for 41.0(range, 1.0?59.0)months after surgery. During the follow-up period, there were 81 patients undergoing tumor recurrence with the time to tumor recurrence as 15.0(range, 1.0?43.0)months, and there were 173 patients without tumor recurrence. The preoperative rectal mesangial fascia envelope volume, preoperative rectal mesangial fat area, preoperative rectal posterior mesangial thickness were 159.1(68.6,266.5)cm3, 17.0(5.1,34.4)cm2, 1.2(0.4,3.2)cm in the 81 patients with tumor recurrence, and 178.5(100.1,310.1)cm3, 19.8(5.3,40.2)cm2 and 1.6(0.3,3.7)cm in the 173 patients without tumor recurrence. (2) Factors influencing tumor recurrence after radical resection of middle and low rectal cancer. Results of multivariate analysis showed that poorly differentiated tumor, tumor pathological N staging as N1?N2 stage, rectal posterior mesangial thickness ≤1.43 cm, magnetic resonance extra mural vascular invasion, tumor invasion surrounding structures were independent risk factors of tumor recurrence after radical resection of middle and low rectal cancer ( hazard ratio=1.64, 2.20, 3.19, 1.69, 4.20, 95% confidence interval as 1.03?2.61, 1.29?3.74, 1.78?5.71, 1.02?2.81, 2.05?8.63, P<0.05). (3) Construction and evaluation of the nomogram prediction model of tumor recurrence after radical resection of middle and low rectal cancer. Based on the results of multivariate analysis, the tumor differentiation, tumor pathological N staging, rectal posterior mesangial thickness, magnetic resonance extra mural vascular invasion, tumor invasion surrounding structures were included to construct the nomogram predic-tion model of tumor recurrence after radical resection of middle and low rectal cancer. The total score of these index in the nomogram prediction model corresponded to the probability of post-operative tumor recurrence. The C-index of the nomogram was 0.80, indicating that the prediction model with good prediction accuracy. Results of calibration curve showed that the nomogram prediction model with good prediction ability. Results of decision curve showed that the prediction probability threshold range was wide when the nomogram prediction model had obvious net benefit rate, and the model had good clinical practicability. Conclusions:Poorly differentiated tumor, tumor pathological N staging as N1?N2 stage, rectal posterior mesangial thickness ≤1.43 cm, magnetic resonance extra mural vascular invasion, tumor invasion surrounding structures are independent risk factors of tumor recurrence after radical resection of middle and low rectal cancer. Nomogram prediction model based on MRI measurement of perirectal fat content can effectively predict the probability of postoperative tumor recurrence.
