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A Novel CT Habitat Radiomics Approach for HER2 Status Prediction in Gastric Cancer.

Xiuzhen Yao1, Jun Lin2, Can Hu3

  • 1Department of Ultrasound, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China (X.Y.).

Academic Radiology
|March 18, 2026
PubMed
Summary

This study developed CT-based radiomics habitat models to predict human epidermal growth factor receptor 2 (HER2) expression in gastric cancer (GC). The combined model, integrating Habitat3 radiomics and clinical data, demonstrated superior accuracy for noninvasive preoperative HER2 assessment.

Keywords:
Computed tomographyGastric cancerHER2Habitat imagingRadiomics

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Accurate preoperative human epidermal growth factor receptor 2 (HER2) status evaluation is critical for personalized gastric cancer (GC) treatment.
  • Noninvasive methods for predicting HER2 expression are needed to improve treatment selection.

Purpose of the Study:

  • To evaluate the clinical value of CT-based multi-subregion habitat radiomics for noninvasive preoperative prediction of HER2 expression in GC.
  • To develop and validate radiomics models for predicting HER2 status.

Main Methods:

  • Retrospective study of 857 GC patients from two centers.
  • Radiomics features extracted from contrast-enhanced CT images; radiomics score (Radscore) generated.
  • Unsupervised clustering defined habitat subregions; models (2, 3, 4 subregions) developed. Combined model integrated optimal habitat model with clinical features.

Main Results:

  • Six models evaluated: clinical, Radscore, Habitat2, Habitat3, Habitat4, and combined.
  • The combined model (Habitat3 + clinical variables) showed the highest predictive performance (Area Under the Curve [AUC] 0.94 in training cohort).
  • Habitat3 model also demonstrated robust predictive accuracy, followed by the combined model in test and external validation cohorts.

Conclusions:

  • CT-based radiomics habitat models, particularly Habitat3, can robustly predict HER2 expression in GC.
  • The combined model integrating Habitat3 radiomics and clinical variables offers superior efficacy and clinical applicability for preoperative HER2 assessment.
  • This approach provides a valuable non-invasive tool for guiding personalized gastric cancer treatment.