- Main
Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells
Published Web Location
https://doi.org/10.1038/s41598-022-15364-7Abstract
To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-