Noninvasive assessment of liver inflammation in metabolic dysfunction associated steatohepatitis using MR cytometry

Fig. 1. Comparison of MRI-Derived cellular properties from Histology-Based Simulations Across Tissue Types and SNR Levels. Fitted cell sizes (top row) and densities (bottom row) from histology-based simulated diffusion signals for normal liver tissues, steatosis, and stroma (a combination of inflammatory cells and fibrosis) at three different SNR levels (10, 20, and 50, from left to right). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 as measured by one-way analysis of variance (ANOVA) with Bonferroni correction.

Fig. 2. Representative Cellular Maps from Histology and MRI in Fixed Human Liver Specimens. β-Catenin stained histological pictures (A–E) and corresponding MRI (F, H) and histology-derived maps (G, I) of cell size and cellularity from two human liver specimens, including a sample with moderate steatosis and a sample with MASH.

Fig. 3. Microstructural Differences Identified by MRI and Histology. Box-and-whisker plots of histology-derived cell sizes (A), cellularities (B), and fat fractions (C) and MRI-derived cell sizes (D) and cellularities (E) for liver ROIs with different pathologies. For all the Box-and-whisker plots, the 25th–75th percentiles are blocked by the box, the red bands inside the box are the mean values, and the whiskers mark the SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 as measured by one-way analysis of variance (ANOVA) with the Bonferroni correction.

Fig. 4. Maps of MRI-derived fat fraction, cell size and cell density for five healthy subjects. Note that blank spots on the parametric maps represent imaging voxels that do not show apparent diffusion time dependency due to either poor signal-to-noise ratios or being dominated by fluids (e.g., blood vessels). The binary threshold map highlights imaging voxels with cell size < 10 µm and cell density > 30 × 104/mm3 in red and displays all other voxels in green. The red dots are hypothesized to visualize the severity of inflammation.

Fig. 5. Maps of MRI-derived fat fraction, cell size and cell density for five MASH patients. Note that blank spots on the parametric maps represent imaging voxels that do not show apparent diffusion time dependency due to either poor signal-to-noise ratios or being dominated by fluids (e.g., blood vessels). The binary threshold map highlights imaging voxels with cell size < 10 µm and cell density > 30 × 104/mm3 in red and displays all other voxels in green. The red dots are hypothesized to visualize the severity of inflammation. MASH livers exhibit scattered or intense red dots throughout the liver.

Fig. 6. Average Signal Decay Depicting Diffusion Time Dependency. The average perfusion-free signal decay and their fittings for regions split by thresholds of cell size at 10 µm and cell density at 30 × 104/mm3, for 5 subjects with MASH.

Fig. 7. MRI-Derived Cell Size and Density Distinguish Healthy from MASH. Box-and-whisker plots of voxel fractions with cell size < 10 µm and cell density > 30 x 104/mm3 for healthy subjects and MASH patients. For all the Box-and-whisker plots, the 25th–75th percentiles are blocked by the box, the red bands inside the box are the mean values, and the whiskers mark the SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 as measured by one-way analysis of variance (ANOVA) with Bonferroni correction.