Abdominal radiology (New York) · 2026
Integrated dual-energy CT spectral kinetics and subregional habitat phenotyping for preoperative prediction of perineural invasion in gastric adenocarcinoma.
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Wang Chong, Wang Zhen, Liu Xiaohan, Wu Chen, Wang Xiaolong, Jin Shang, Zhang He, Xu Yixin, Sun Aiyun, Ding Tao, Xu Kai, Meng Yankai
Аннотация
BACKGROUND: Perineural invasion (PNI) is a key prognostic determinant in gastric adenocarcinoma but remains radiologically occult on conventional CT.
PURPOSE: To develop and validate an integrated model combining dual-energy CT (DECT)-derived functional spectral slopes and subregional habitat signatures for the preoperative prediction of PNI.
MATERIALS AND METHODS: In this retrospective study, 175 patients (median age, 66 years; interquartile range, 58-73 years; 131 men) with gastric adenocarcinoma who underwent preoperative DECT between 2023 and 2025 were evaluated. Patients were randomized into a training cohort (n = 122) and an internal test cohort (n = 53). Tumor subregions were parcellated into three biologically distinct habitats using voxel-wise clustering. Stable habitat features (ICC ≥ 0.75), three-phase spectral slopes, and a Habitat-Graph Neural Network (H-GNN)-derived Topological Interaction Score (TIS)-capturing spatial adjacency relationships between habitat subregions-were collectively submitted as candidate predictors to LASSO regression for construction of the final Spectral-Habitat Signature. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Clinical utility was assessed via decision curve analysis.
RESULTS: PNI was pathologically confirmed in 46.9% (82 of 175) of patients. The integrated Spectral-Habitat model achieved an AUC of 0.832 (95% CI: 0.760, 0.898) in the training cohort and 0.758 (95% CI: 0.666, 0.845) in the internal test cohort. A stratified 5-fold cross-validation demonstrated the stability of the framework, yielding a mean AUC of 0.765 (SD, 0.084). The combined model significantly outperformed the extracellular volume (ECV) model (AUC, 0.758 vs. 0.544; P < .001). Equilibrium-phase spectral slope emerged as a decisive functional biomarker. Model calibration was excellent in the test cohort (P = .560, Hosmer-Lemeshow test). Decision curve analysis demonstrated a substantial net clinical benefit across threshold probabilities of 10%-80%.
CONCLUSION: In this retrospective single-center study, an integrated model leveraging functional spectral kinetics and subregional spatial heterogeneity showed potential for the preoperative stratification of occult perineural invasion. However, these preliminary findings derived from a limited sample size require further validation in larger, multi-institutional prospective cohorts before clinical implementation in surgical planning.
PURPOSE: To develop and validate an integrated model combining dual-energy CT (DECT)-derived functional spectral slopes and subregional habitat signatures for the preoperative prediction of PNI.
MATERIALS AND METHODS: In this retrospective study, 175 patients (median age, 66 years; interquartile range, 58-73 years; 131 men) with gastric adenocarcinoma who underwent preoperative DECT between 2023 and 2025 were evaluated. Patients were randomized into a training cohort (n = 122) and an internal test cohort (n = 53). Tumor subregions were parcellated into three biologically distinct habitats using voxel-wise clustering. Stable habitat features (ICC ≥ 0.75), three-phase spectral slopes, and a Habitat-Graph Neural Network (H-GNN)-derived Topological Interaction Score (TIS)-capturing spatial adjacency relationships between habitat subregions-were collectively submitted as candidate predictors to LASSO regression for construction of the final Spectral-Habitat Signature. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Clinical utility was assessed via decision curve analysis.
RESULTS: PNI was pathologically confirmed in 46.9% (82 of 175) of patients. The integrated Spectral-Habitat model achieved an AUC of 0.832 (95% CI: 0.760, 0.898) in the training cohort and 0.758 (95% CI: 0.666, 0.845) in the internal test cohort. A stratified 5-fold cross-validation demonstrated the stability of the framework, yielding a mean AUC of 0.765 (SD, 0.084). The combined model significantly outperformed the extracellular volume (ECV) model (AUC, 0.758 vs. 0.544; P < .001). Equilibrium-phase spectral slope emerged as a decisive functional biomarker. Model calibration was excellent in the test cohort (P = .560, Hosmer-Lemeshow test). Decision curve analysis demonstrated a substantial net clinical benefit across threshold probabilities of 10%-80%.
CONCLUSION: In this retrospective single-center study, an integrated model leveraging functional spectral kinetics and subregional spatial heterogeneity showed potential for the preoperative stratification of occult perineural invasion. However, these preliminary findings derived from a limited sample size require further validation in larger, multi-institutional prospective cohorts before clinical implementation in surgical planning.