Artificial Intelligence-Advanced Imaging for Solid-Type Lung Adenocarcinoma: Towards Greater Clinical Relevance
An AI-based volumetric analysis using a cV/tV threshold of ≥0.72 showed potential for predicting lymph node metastasis in this single-centre retrospective study of lung adenocarcinoma ≤30 mm. External validation in diverse, multicentre cohorts is essential before clinical implementation.
Authors
- Yoshikane Yamauchi (ORCID: https://orcid.org/0000-0002-3374-2399)
- Shoji Kido (ORCID: https://orcid.org/0000-0001-5293-4110)
- Yukinori Sakao (ORCID: https://orcid.org/0000-0002-6826-2280)
- Daiki Nishigaki (ORCID: https://orcid.org/0000-0002-7006-3408)
- Yuichi Saito (ORCID: https://orcid.org/0000-0002-2025-9226)
- Tomoki Nishida (ORCID: https://orcid.org/0000-0003-1186-1693)
- Noriyuki Tomiyama (ORCID: https://orcid.org/0000-0001-9918-7327)
- Junya Sato (ORCID: https://orcid.org/0000-0002-1206-2036)
- Yasushi Yatabe (ORCID: https://orcid.org/0000-0003-1788-559X)
- Yasushi Shintani (ORCID: https://orcid.org/0000-0002-2540-5288)
- Akinori Hata (ORCID: https://orcid.org/0000-0003-1149-7094)
- Masahiro Yanagawa (ORCID: https://orcid.org/0000-0002-0911-6769)
- Noriaki Sakakura (ORCID: https://orcid.org/0000-0002-9598-9629)
Institutions
- Osaka City University (JP)
- National Cancer Center (US)
- Aichi Cancer Center (JP)
- Shonan Kamakura General Hospital (JP)
- Tokyo National Hospital (JP)
- Teikyo University (JP)
- The University of Osaka (JP)
Publication Details
- Journal
- European Journal of Cardio-Thoracic Surgery
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1093/ejcts/ezaf385
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00