Utility of multimodal deep learning model to diagnose lymph node metastasis in esophageal cancer using computed tomography and positron emission tomography images
The multimodal deep learning model using computed tomography and positron emission tomography demonstrated performance comparable to that of experts in diagnosing the presence of lymph node metastasis, a key prognostic factor in esophageal cancer, suggesting its potential clinical utility.
Authors
- Hiroshi Okamoto (ORCID: https://orcid.org/0000-0003-2807-5277)
- Yohei Ozawa (ORCID: https://orcid.org/0000-0002-5136-8281)
- Tomoya Kobayashi (ORCID: https://orcid.org/0000-0001-8179-1702)
- Yasuharu Shinozaki
- Tomofumi Kaneno
- Hirotaka Ishida (ORCID: https://orcid.org/0000-0002-6814-3564)
- Takuya Ueda (ORCID: https://orcid.org/0000-0002-0913-5791)
- Eichi Takaya (ORCID: https://orcid.org/0000-0003-2541-1685)
- Takashi Kamei
- Chiaki Sato (ORCID: https://orcid.org/0000-0002-3728-8154)
- Yusuke Taniyama
Institutions
- Tohoku University (JP)
- Tohoku University Hospital (JP)
Publication Details
- Journal
- Surgery Today
- Published
- 2025-10-18
- DOI
- https://doi.org/10.1007/s00595-025-03152-5
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Core Research for Evolutional Science and Technology