Predicting prognosis of light-chain cardiac amyloidosis by magnetic resonance imaging and deep learning
This fully automated DL model can predict individualized prognosis of AL-CA through LGE images, which complements the presently used Mayo staging method.
Authors
- Chengcai Liu (ORCID: https://orcid.org/0009-0009-5816-1679)
- Xiao Li (ORCID: https://orcid.org/0000-0003-3776-5026)
- Lu Lin (ORCID: https://orcid.org/0000-0002-3261-6569)
- Long Jiang Zhang (ORCID: https://orcid.org/0000-0002-6664-7224)
- H. S. Sang
- Yubo Guo (ORCID: https://orcid.org/0009-0009-7632-2667)
- Shuo Wang (ORCID: https://orcid.org/0009-0004-4569-5392)
- Jian Li (ORCID: https://orcid.org/0000-0002-4549-0694)
- Yining Wang (ORCID: https://orcid.org/0000-0001-6441-2002)
- Jie Tian
- Xinwei Li (ORCID: https://orcid.org/0000-0003-0713-9366)
- Xiaohu Li (ORCID: https://orcid.org/0000-0002-7551-5282)
Institutions
- Anhui Medical University (CN)
- Chinese Academy of Sciences (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Nanjing General Hospital of Nanjing Military Command (CN)
- Peking Union Medical College Hospital (CN)
- Shandong Institute of Automation (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Beijing Advanced Sciences and Innovation Center (CN)
- Beihang University (CN)
- Nanjing Medical University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- European Heart Journal - Cardiovascular Imaging
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1093/ehjci/jeaf248
- Citations
- 4
- Primary Topic
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- National Natural Science Foundation of China
- Peking Union Medical College Hospital
- Fundamental Research Funds for the Central Universities