Abstract

Nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH) is a major cause of liver fibrosis/cirrhosis and liver-related mortality. Despite emergence of noninvasive tests, liver biopsy remains the mainstay for the diagnosis and assessment of disease severity and chronicity. Accurate detection and quantification of liver fibrosis with architectural localization are essential for assessing the severity of NAFLD and its response to antifibrotic therapy in clinical trials. Conventional histological scoring systems for liver fibrosis are semiquantitative. Collagen proportionate area is morphometric by measuring the percentage of fibrosis on a continuous scale but is limited by the absence of architectural input. Ultra-fast laser microscopy, e.g., second harmonic generation (SHG) imaging, has enabled in-depth analysis of fibrillary collagen based on intrinsic optical signals. Quantification and calculation of different detailed variables of collagen fibers can be used to establish algorithm-based quantitative fibrosis scores (e.g. qFibrosis, q-FPs) in NAFLD. Artificial intelligence is being explored to further develop quantitative fibrosis scoring methods. SHG microscopy should be considered the new gold standard for the quantitative assessment of liver fibrosis, reaffirming the pivotal role of the liver biopsy in NAFLD, at least for the near-future. The ability of SHG-derived algorithms to intuitively detect subtle nuances in liver fibrosis changes over a continuous scale should be employed to redress the efficacy endpoint for fibrosis in NASH clinical trials. The current decrease by 1-point or more in fibrosis stage may not be realistic for the evaluation of therapeutic response to antifibrotic drugs in relatively short-term trials.

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