Second harmonic generation digital pathology with artificial intelligence: breakthroughs in studying fibrosis dynamics and treatment response
Fibrosis represents a highly conserved response to tissue injury. Assessing fibrosis is central in diagnostic pathology, evaluating treatment response and prognosis. Second harmonic generation digital pathology with artificial intelligence analyses provides unparalleled precision and granularity in quantifying tissue collagen in its natural, unstained environment.. This technology reveals new insights into the balance between fibrogenesis and fibrolysis, crucial in tracking disease evolution and treatment outcomes. This review describes applications of second harmonic generation digital pathology with artificial intelligence for detailed characterization of liver fibrosis, assessing treatment response in clinical trials, analyzing collagen features in other chronic diseases and cancers. Additionally, it offers a perspective on future developments in integrating various technologies into a comprehensive diagnostic workflow for more effective evaluation of therapy and disease prognosis.
Authors
- Elaine Chng (ORCID: https://orcid.org/0009-0007-8535-2281)
- Nikolai V. Naoumov (ORCID: https://orcid.org/0009-0009-3091-4990)
Institutions
- Histoindex (Singapore) (SG)
- University College London (GB)
Publication Details
- Journal
- Future Medicine AI
- Published
- 2024-08-05
- DOI
- https://doi.org/10.2217/001c.121609
- Citations
- 1
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.39