Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease
The application of SHG/artificial intelligence algorithms in pediatric-onset AILD provides improved insight into liver histopathology through fibrosis mapping. SHG allows objective identification of patients with biliary tract involvement, which may be associated with a higher risk for refractory disease.
Authors
- Alexander Gerhard Miethke (ORCID: https://orcid.org/0000-0003-1395-9475)
- Rebekah Karns (ORCID: https://orcid.org/0000-0002-9720-4039)
- Jennifer Kasten (ORCID: https://orcid.org/0000-0001-6439-9872)
- Constance Nelson
- Leticia Khendek (ORCID: https://orcid.org/0000-0001-7903-5561)
- Amy Taylor (ORCID: https://orcid.org/0000-0001-5010-8157)
- Xiao Teng
- Cyd Castro-Rojas
- Mosab Alquraish
Institutions
- Cincinnati Children's Hospital Medical Center (US)
- Histoindex (Singapore) (SG)
- University of Cincinnati Medical Center (US)
Publication Details
- Journal
- Hepatology Communications
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1097/hc9.0000000000000594
- Citations
- 2
- Primary Topic
- Liver Diseases and Immunity
- Type
- article
- Field-Weighted Citation Impact
- 0.74