mlsanityData to 14 Oct 2026

Feature-interactive Siamese graph encoder-based image analysis to predict STAS from histopathology images in lung cancer

arXiv 2411.15274 ↗First posted 22 Nov 2024eess.IV cs.AI cs.CVcited by 4

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Abstract (arXiv)

Spread through air spaces (STAS) is a distinct invasion pattern in lung cancer, crucial for prognosis assessment and guiding surgical decisions. Histopathology is the gold standard for STAS detection, yet traditional methods are subjective, time-consuming, and prone to misdiagnosis, limiting large-scale applications. We present VERN, an image analysis model utilizing a feature-interactive Siamese graph encoder to predict STAS from lung cancer histopathological images. VERN captures spatial topological features with feature sharing and skip connections to enhance model training. Using 1,546 histopathology slides, we built a large single-cohort STAS lung cancer dataset. VERN achieved an AUC of 0.9215 in internal validation and AUCs of 0.8275 and 0.8829 in frozen and paraffin-embedded test sections, respectively, demonstrating clinical-grade performance. Validated on a single-cohort and three external datasets, VERN showed robust predictive performance and generalizability, providing an open platform (http://plr.20210706.xyz:5000/) to enhance STAS diagnosis efficiency and accuracy.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 14 of its 72 references that are in the map. First posted on arXiv 22 Nov 2024.

Builds on

14 of 72 references.

References · 14

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2 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2025SMILE: a Scale-aware Multiple Instance Learning Method for Multicenter STAS Lung Cancer Histopathology Diagnosiscited by 1
  2. 2025DLiPath: A Benchmark for the Comprehensive Assessment of Donor Liver Based on Histopathological Image Datasetcited by 0
  3. 2025STAMP: Multi-pattern Attention-aware Multiple Instance Learning for STAS Diagnosis in Multi-center Histopathology Imagescited by 0
  4. 2026Diffusion Attention Expert Model for Predicting and Semi-automatic Localizing STAS in Lung Cancer Histopathological Imagescited by 0