Prediction of Overall Survival in Patients With Oesophageal Cancer Using AI-Based 3D CT Body Composition Analysis

Oesophageal cancer remains the sixth most lethal malignancy, with 5-year survival rates around 22%. CT-derived 2D body composition analysis has emerged as a promising prognostic tool, but conventional, often manually created single-slice L3 measurements are unsuited for future clinical implementation. We evaluated fully automated AI-derived volumetric body composition indices as prognostic parameters using conventional L3 and BMI measurements as reference.

This retrospective cohort study included patients with histologically confirmed oesophageal cancer treated between 2011 and 2024. Automated deep learning segmentation using the nnU-Net-based body and organ analysis pipeline quantified abdominal tissue volumes from staging CTs. Three normalized indices were calculated: sarcopenia index (SI, muscle/bone volume ratio), myosteatotic fat index (MFI, intramuscular/total adipose tissue volume ratio) and abdominal fat index (AFI, visceral/subcutaneous adipose tissue volume ratio). Cox proportional hazards models assessed prognostic value after sequential adjustment for age, sex, metastatic status, ECOG performance status, BMI and L3-derived indices. Kaplan-Meier analysis evaluated survival differences stratified by sex-specific median values.

The cohort comprised 563 patients (19.7% female), median age 65.4 years (IQR: 58.8-71.3); 10.1% (n = 57) had metastatic disease and 68.7% (n = 387) underwent surgery. Males had higher sarcopenia index (2.54 ± 0.41 vs. 2.24 ± 0.45, p < 0.001) and abdominal fat index (median 0.72 vs. 0.36, p < 0.001), whereas MFI showed no difference (p = 0.89). During median follow-up of 22 months, 367 deaths (65.9%) occurred. Median overall survival was 28.6 months (95% CI: 23.7-33.3); 1-year survival 70.7% (95% CI: 67.2%-74.8%) and 5-year survival 32.8% (95% CI: 29.6%-38.3%), with marked differences by metastatic status (M0 vs. M1 1-year survival: 73.4% vs. 46.4%). In the fully adjusted model incorporating all three volumetric indices alongside clinical covariates, BMI and L3-derived parameters (n = 532), only sarcopenia index retained independent significance (HR = 0.56, 95% CI: 0.37-0.82, p = 0.003); all others showed p ≥ 0.26. Metastatic status (HR = 2.23, p < 0.001) and ECOG (HR = 1.29, p < 0.001) remained significant. All L3 indices lost significance alongside volumetric parameters (p > 0.14). Male patients with high sarcopenia index showed longer survival compared with patients with low sarcopenia index (33.3 vs. 21.8 months, p < 0.001); female patients showed larger descriptive contrasts (68.8 vs. 16.8 months, p < 0.001) that were formally confirmed by a significant sex-SI Cox interaction (LRT p = 0.026).

Automatic AI-derived volumetric body composition parameters calculated from routine staging CTs predict overall survival in patients with oesophageal cancer and are associated with sex-related differences of prognostic impact, supporting further evaluation toward future clinical use.