Fig. 7: Images from the breast tissue samples that were scanned ex vivo at 9.4T, and Histo-μSim parametric maps. | Communications Biology

Fig. 7: Images from the breast tissue samples that were scanned ex vivo at 9.4T, and Histo-μSim parametric maps.

From: Histology-informed microstructural diffusion simulations for MRI cancer characterisation—the Histo-μSim framework

Fig. 7

Panel (a) on top: b = 0 image and HE sections. Moving clock-wise: week 9 MMTV-PyM breast tumour (top left), non-cancerous breast (top right), week 11 MMTV-PyM breast tumour (bottom right), week 14 MMTV-PyM breast tumour (bottom left). Second row (b–d): IC fraction fin (b); volume-weighted cell size index vCScyl∣MC (c); intrinsic IC diffusivity D0∣in (d). Third row (e, f): intrinsic EC diffusivity D0∣ex (e); cell membrane permeability κ (f). For each metric, we show results on the four breast specimens. Examples of histological tiles in different ROIs are also included, alongside with corresponding quantitative histological indices and mean MRI metrics for each ROIs. The coefficient of determination R2 between measured dMRI signals and signals predicted through Histo-μSim model fitting is reported for the shown ROIs, alongside Histo-μSim and histological metrics. Areas with high concentration of fat (resulting in very low b = 0 signal due to fat suppression) were not included in the parametric map computation.

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