Prognostic Impact of Tumor Cell Nuclear Size Assessed by Artificial Intelligence in Esophageal Squamous Cell Carcinoma.

• Tác giả: Takahiro Einama, Hiroyuki Horiguchi, Yoji Kishi, Keita Kouzu, Ines P Nearchou, Hitoshi Tsuda, Hironori Tsujimoto, Hideki Ueno, Takanori Watanabe
• Ngôn ngữ: eng
• Ký hiệu phân loại: 598.634 *Tetrao
• Thông tin xuất bản: United States : Laboratory investigation; a journal of technical methods and pathology , 2025
• Bộ sưu tập: NCBI
• ID: 720572

Tóm tắt

 Tumor cell nuclear size (NS) indicates malignant potential in breast cancer
  however, its clinical significance in esophageal squamous cell carcinoma (ESCC) is unknown. Artificial intelligence (AI) can quantitatively evaluate histopathological findings. The aim was to measure NS in ESCC using AI and elucidate its clinical significance. We investigated the relationship between NS assessed by AI and prognosis in 138 patients with ESCC who underwent curative esophagectomy. Hematoxylin and eosin-stained slides from the deepest tumor sections were digitized. Using HALO-AI DenseNet v2, we created a deep-learning classifier that identified tumor cells with an NS area >
 20 μm