Naoumov, Nikolai V;
Chng, Elaine;
(2024)
Second harmonic generation digital pathology with artificial intelligence: breakthroughs in studying fibrosis dynamics and treatment response.
Future Medicine AI
, 2
(2)
pp. 1-19.
10.2217/001c.121609.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | Second harmonic generation digital pathology with artificial intelligence: breakthroughs in studying fibrosis dynamics and treatment response |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.2217/001c.121609 |
| Publisher version: | https://doi.org/10.2217/001c.121609 |
| Language: | English |
| Additional information: | © The Authors 2025. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10202907 |
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