Deep learning model to diagnose cardiac amyloidosis from haematoxylin/eosin-stained myocardial tissue
A deep learning model was developed to diagnose cardiac amyloidosis from HE-stained myocardial tissue accurately. Although further prospective validation of this model using HE-stained myocardial tissues from multiple centres is needed, it may help minimize the risk of missing cardiac amyloidosis and maximize the utility of histological diagnosis in clinical practice.
Authors
- Takeshi Iwasaki (ORCID: https://orcid.org/0000-0001-5277-2932)
- Koji Todaka (ORCID: https://orcid.org/0000-0003-0805-9974)
- Junji Kishimoto (ORCID: https://orcid.org/0000-0002-3833-4052)
- Shouji Matsushima
- Kayo Misumi (ORCID: https://orcid.org/0000-0003-3441-1628)
- Tomomi Ide
- Keisuke Shinohara (ORCID: https://orcid.org/0000-0002-9489-3836)
- Takeshi Tohyama (ORCID: https://orcid.org/0000-0002-7300-8180)
- Tatsuya Watanabe (ORCID: https://orcid.org/0000-0001-6841-2587)
- Kohtaro Abe
- Masataka Ikeda (ORCID: https://orcid.org/0000-0003-1893-8171)
- Takeo Fujino (ORCID: https://orcid.org/0000-0002-2886-3479)
- Masato Katsuki (ORCID: https://orcid.org/0000-0001-7806-4459)
- Toru Hashimoto (ORCID: https://orcid.org/0000-0001-9607-0852)
- Yoshinao Oda
Institutions
- Kyushu University (JP)
- Kyushu University Hospital (JP)
- Kyushu University Beppu Hospital (JP)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- European Heart Journal - Imaging Methods and Practice
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1093/ehjimp/qyae141
- Primary Topic
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Pfizer
- Japan Foundation for Applied Enzymology
- Uehara Memorial Foundation
- Pfizer Japan
- Japan Society for the Promotion of Science