Integrated imaging, body composition, and systemic immune-inflammatory profiling for non-invasive prediction of HER2 status in endometrial cancer

Objectives Preoperative evaluation of human epidermal growth factor receptor 2 (HER2) status in endometrial cancer (EC) is clinically important for molecular stratification and treatment planning. This study aimed to develop a non-invasive predictive model integrating functional MRI-derived tumor characteristics, CT-derived body composition, and systemic immune-inflammatory markers for identifying HER2-positive EC. Methods In this single-center retrospective study, 75 patients with pathologically confirmed EC (41 HER2-positive, 34 HER2-negative) who underwent preoperative 3.0 T magnetic resonance imaging (MRI), including amide proton transfer–weighted (APTw) imaging and intravoxel incoherent motion (IVIM) diffusion-weighted imaging, and chest CT between August 2019 and June 2026 were evaluated. Quantitative MRI parameters, including APT values, the slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and perfusion fraction (f), and CT-derived body composition, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), skeletal muscle (SM) and intramuscular adipose tissue (IMAT), were extracted. Systemic immune-inflammatory parameters including neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), platelet to lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) were calculated. Multivariable logistic regression was performed to identify independent risk factors and build predictive models, with diagnostic efficacy assessed using receiver operating characteristic (ROC) curve analysis and internal validation using 1000-resample bootstrap. Results The HER2 (+) group demonstrated significantly higher APT values (2.76% vs. 2.44%), D* values (3.23 × 10– 3 mm 2 /s vs. 1.88 × 10– 3 mm 2 /s), f values (0.22 vs. 0.19), SAT area (138.38 cm 2 vs. 112.73 cm 2 ), and MLR values (0.19 vs. 0.14) compared with the HER2 (-) group, whereas lower D values (0.59 × 10– 3 mm 2 /s vs. 0.67 × 10– 3 mm 2 /s) were observed in the HER2 (+) group. Multivariable logistic regression analysis identified APT (OR = 9.368, P = 0.011), f (OR = 8.303, P = 0.002), SAT (OR = 1.017, P = 0.033), and MLR (OR = 8.336, P = 0.006) as independent predictors of HER2 positivity. The integrated model incorporating APT value, f, SAT, and MLR achieved an AUC of 0.879, sensitivity of 87.8%, and specificity of 79.4%. Conclusion An integrated model combining tumor imaging characteristics, body composition parameters, and systemic immune-inflammatory markers may provide a non-invasive approach for preoperative prediction of HER2-positive EC.