An MRI-based pelvimetry nomogram for predicting surgical difficulty of transabdominal resection in patients with middle and low rectal cancer

Abstract

ObjectiveThe current work aimed to develop a nomogram comprised of MRI-based pelvimetry and clinical factors for predicting the difficulty of rectal surgery for middle and low rectal cancer (RC).MethodsConsecutive mid to low RC cases who underwent transabdominal resection between June 2020 and August 2021 were retrospectively enrolled. Univariable and multivariable logistic regression analyses were carried out for identifying factors (clinical factors and MRI-based pelvimetry parameters) independently associated with the difficulty level of rectal surgery. A nomogram model was established with the selected parameters for predicting the probability of high surgical difficulty. The predictive ability of the nomogram model was assessed by the receiver operating characteristic (ROC) curve and decision curve analysis (DCA).ResultsA total of 122 cases were included. BMI (OR = 1.269, p = 0.006), pelvic inlet (OR = 1.057, p = 0.024) and intertuberous distance (OR = 0.938, p = 0.001) independently predicted surgical difficulty level in multivariate logistic regression analysis. The nomogram model combining these predictors had an area under the ROC curve (AUC) of 0.801 (95% CI: 0.719–0.868) for the prediction of a high level of surgical difficulty. The DCA suggested that using the nomogram to predict surgical difficulty provided a clinical benefit.ConclusionsThe nomogram model is feasible for predicting the difficulty level of rectal surgery, utilizing MRI-based pelvimetry parameters and clinical factors in mid to low RC cases.

Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer

“…Appropriate pelvic debridement and total mesorectal excision (TME) are essential to prevent local recurrence [ 20 ]. Previous studies have focused on the consequence of pelvic factors and rectal mesenteric fat area on the surgical outcome of lower and middle rectal cancer [ 21 , 22 ], the consequence of a large vertical pelvic depth, a small pelvis, a short transverse meridian, a large sacrococcygeal curvature and a high rectal mesenteric fat area on the difficulty of the procedure was also determined [ 17 , 23 , 24 ], and these factors are particularly significant for men [ 25 ]. However, the relationship between quantitative pelvic measurements and surgical difficulty is uncertain, and some studies have even found no association between pelvic measurements and surgical difficulty [ 26 ].…”

Nomogram for predicting the surgical difficulty of laparoscopic total mesorectal excision and exploring the technical advantages of robotic surgery

“…Yuan et al. ( 25 ) developed a nomogram to predict the difficulty of rectal surgery. However, it’s worth noting that this nomogram model did not include MFA, which has been reported to be an important factor in the difficulty of rectal surgery ( 26 ).…”

Advances in pelvic imaging parameters predicting surgical difficulty in rectal cancer

“…Using multivariate analysis, they found the factors significantly associated with surgical difficulty were BMI, pelvic inlet and intertuberous distance, and a nomogram model was established with the selected parameters for predicting the probability of high surgical difficulty. This objective method would provide a visualization tool to effectively predict the probability of surgical difficulty in RC [ 21 ]. Similarly, the study of T. Yamamoto et al also used multiple criteria to comprehensively define the difficulty of surgery [ 47 ].…”