FIGURE 1. Proposed thrombus composition prediction compared to the current practice. Conventionally thrombus composition is manually analyzed though stained bright-field (BF) images. Our framework fusing ODT and DL provides label-free and fully-automated prediction of the composition. Scale bar = 500 µm.
This work exploits the high-resolution and quantitative 3D imaging capability of ODT, which extract various quantitative biophysical properties from the RI distribution.[10] These strengths of label-free imaging and ODT had been demonstrated in histological studies [12-17], including kidney cancer,[18] kidney injury,[19] and intestinal inflammation.[20] The use of refractive index as reproducible and quantitative imaging contrast has strengths when combined with DL. Recently, various cellular and subcellular RI distributions have been analyzed using the combination of HT and DL, including cellular segmentation,[21-23] the detection of biological compartments,[24-26] and domain translations.[27,28]
Our approach facilitates label-free and automated examination of an AIS thrombus by utilizing DL to predict the composition of the thrombus from a 3D RI tomogram. We validated the prediction from each of the three unstained thrombus slices by comparing to a successive slice that is Hematoxylin and Eosin (H&E) stained. An accuracy of 95% was achieved in the patch-wise classification when compared to board-certified pathologists’ annotation. Furthermore, the spatial distribution of thrombus composition was in high agreement with the annotation over the entire slide, highlighting the scope for whole-slide analyses. We expect that our study will enable rapid and quantitative evaluation of thrombus composition, aiding clinicians in treating AIS efficiently.