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Abstract
Background & Aims
Fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) is a prognostic indicator and clinical trial efficacy endpoint. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy images unstained tissue sections and, when integrated with artificial intelligence models, generates a continuous fibrosis value (qFibrosis) and ordinal qFibrosis stage. The impact of biopsy size and location on the accuracy of these approaches has not been assessed in MASLD, leaving quality assurance procedures undefined.
Methods
One unstained section each from 100 hepatectomy/explant MASLD cases, 20 of each pathologist-assigned NASH-CRN fibrosis stage (F0-F4), were used to create virtual core biopsies by cropping regions from within the whole parent section. Regions varied in length (5-30 mm) with a fixed width of 0.9 mm, width (0.5-1.3 mm) with a fixed length of 15 mm, or position within the whole parent section. SHG/TPEF was used and qFibrosis continuous value and stage of the virtual core biopsies determined for comparison with those of the whole parent section.
Results
qFibrosis continuous value and stage correlated strongly with pathologist-assigned NASH-CRN stage (rs = 0.92). Increasing length and width of virtual biopsies increased correlation with the qFibrosis continuous value and agreement with qFibrosis stage of the whole parent section, stabilising between 20-26 mm in length and 0.9 mm in width. Position within tissue did not influence qFibrosis metrics.
Conclusions
Longer (more than 20 mm) and wider (more than 0.9 mm) biopsies provide more accurate fibrosis assessment using SHG/TPEF. Biopsy position and orientation do not influence accuracy.
Fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) is a prognostic indicator and clinical trial efficacy endpoint. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy images unstained tissue sections and, when integrated with artificial intelligence models, generates a continuous fibrosis value (qFibrosis) and ordinal qFibrosis stage. The impact of biopsy size and location on the accuracy of these approaches has not been assessed in MASLD, leaving quality assurance procedures undefined.
Methods
One unstained section each from 100 hepatectomy/explant MASLD cases, 20 of each pathologist-assigned NASH-CRN fibrosis stage (F0-F4), were used to create virtual core biopsies by cropping regions from within the whole parent section. Regions varied in length (5-30 mm) with a fixed width of 0.9 mm, width (0.5-1.3 mm) with a fixed length of 15 mm, or position within the whole parent section. SHG/TPEF was used and qFibrosis continuous value and stage of the virtual core biopsies determined for comparison with those of the whole parent section.
Results
qFibrosis continuous value and stage correlated strongly with pathologist-assigned NASH-CRN stage (rs = 0.92). Increasing length and width of virtual biopsies increased correlation with the qFibrosis continuous value and agreement with qFibrosis stage of the whole parent section, stabilising between 20-26 mm in length and 0.9 mm in width. Position within tissue did not influence qFibrosis metrics.
Conclusions
Longer (more than 20 mm) and wider (more than 0.9 mm) biopsies provide more accurate fibrosis assessment using SHG/TPEF. Biopsy position and orientation do not influence accuracy.
Original language | English |
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Journal | JHEP Reports |
Early online date | 8 May 2025 |
Publication status | E-pub ahead of print - 8 May 2025 |
Keywords / Materials (for Non-textual outputs)
- Humans
- Metabolic Dysfunction-Associated Steatotic Liver Disease
- Non-alcoholic Fatty Liver Disease
- Liver Cirrhosis
- Biopsy
- Artificial Intelligence
- Deep Learning
- Second Harmonic Generation Microscopy
- Quality Control
- Collagen
Fingerprint
Dive into the research topics of 'Effect of liver biopsy size on MASLD fibrosis assessment by second harmonic generation/two-photon excitation fluorescence microscopy'. Together they form a unique fingerprint.Projects
- 1 Finished
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Development of an integrated precision AI tool for the stratification of non-alcoholic fatty liver disease (INTErPRET-NAFLD)
Kendall, T. (Principal Investigator) & Fallowfield, J. (Co-investigator)
1/10/20 → 30/09/22
Project: Research