Automated extracellular volume fraction measurement for diagnosis and prognostication in patients with light-chain cardiac amyloidosis
T1 mapping on CMR imaging, derived from AI-automated segmentation, not only allows for improved diagnosis of CA from other etiologies of LVH, but also provides significant prognostic value in patients with AL-CA.
Authors
- Goo‐Yeong Cho (ORCID: https://orcid.org/0000-0002-7067-5535)
- Byoung Wook Choi (ORCID: https://orcid.org/0000-0002-8873-5444)
- Eun Ju Chun (ORCID: https://orcid.org/0000-0002-1041-8035)
- Hong‐Mi Choi (ORCID: https://orcid.org/0000-0002-6856-2486)
- In‐Chang Hwang (ORCID: https://orcid.org/0000-0003-4966-3924)
- Pan Ki Kim (ORCID: https://orcid.org/0000-0001-6006-0732)
- Yeonyee Elizabeth Yoon (ORCID: https://orcid.org/0000-0002-8479-9889)
- Jiesuck Park (ORCID: https://orcid.org/0000-0001-6924-7106)
- Myeongju Kim (ORCID: https://orcid.org/0000-0003-0543-3019)
Institutions
- Seoul National University (KR)
- Yonsei University (KR)
- Seoul National University Bundang Hospital (KR)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1371/journal.pone.0317741
- Citations
- 3
- Primary Topic
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- Seoul National University Bundang Hospital
- Seoul National University
- National IT Industry Promotion Agency
- Ministry of Science and ICT, South Korea