Frontiers in Oncology
Preoperative CT-derived liver fat fraction and visceral adipose tissue index enhance postoperative recurrence risk stratification in colorectal cancer
By Ke Yin, Mei Wei, Wenjuan Ba and 2 others.
Abstract
Background Postoperative recurrence remains a major cause of treatment failure in colorectal cancer (CRC). We evaluated whether preoperative computed tomography (CT)-derived liver fat fraction (LFF) and visceral adipose tissue index (VATI) improve postoperative recurrence-risk prediction. Methods This multi-cohort study included 525 patients after curative-intent surgery: a training cohort (n=260), external validation cohort (n=208), and exploratory prospective cohort (n=57). Candidate clinicopathologic and CT-derived variables were evaluated using Cox regression. Performance was assessed with Harrell C-index, time-dependent area under the receiver operating characteristic curve (AUC) at 12 and 24 months, calibration, decision curve analysis, and Kaplan–Meier analysis. Results RFS events were observed in 129 patients. The final model included five predictors. N1–2 stage (hazard ratio [HR], 3.332; 95% confidence interval [CI], 1.807-6.145), elevated carbohydrate antigen 19-9 (CA19-9; HR, 2.414; 95% CI, 1.459-3.994), lymphovascular invasion (HR, 2.166; 95% CI, 1.250-3.752), VATI per 1-standard-deviation increase (HR, 1.519; 95% CI, 1.217-1.896), and LFF per 1-standard-deviation increase (HR, 2.228; 95% CI, 1.728-2.871) were independently associated with recurrence-free survival. C-indices were 0.851, 0.809, and 0.828 in the training, external, and prospective cohorts, respectively. Prospective 12- and 24-month AUCs were 0.759 (95% CI, 0.242-1.000) and 0.890 (95% CI, 0.709-1.000), with the latter based on only 20 evaluable patients. The combined validation cohort yielded a C-index of 0.813 and 12- and 24-month AUCs of 0.807 and 0.860. Conclusion CT-derived VATI and LFF improved risk stratification beyond routine clinicopathologic variables. The prospective findings remain exploratory and require confirmation in larger cohorts before clinical implementation.








