Robust and generalizable segmentation of human functional tissue units

Godwin, L. L.; Ju, Y.; Sood, N.; Jain, Y.; Quardokus, E. M.; Bueckle, A.; Longacre, T.; Horning, A. M.; Lin, Y.; Esplin, E. D.; Hickey, J. W.; Snyder, M. P.; Patterson, N. H.; Spraggins, J. M.; Borner, K.

doi:10.1101/2021.11.09.467810

bioRxiv · 10.1101/2021.11.09.467810

Robust and generalizable segmentation of human functional tissue units

Godwin, L. L.·Ju, Y.·Sood, N.·Jain, Y.·Quardokus, E. M.·Bueckle, A.·Longacre, T.·Horning, A. M.·Lin, Y.·Esplin, E. D.·Hickey, J. W.·Snyder, M. P.·Patterson, N. H.·Spraggins, J. M.·Borner, K.

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Abstract

The Human BioMolecular Atlas Program aims to compile a reference atlas for the healthy human adult body at the cellular level. Functional tissue units (FTU, e.g., renal glomeruli and colonic crypts) are of pathobiological significance and relevant for modeling and understanding disease progression. Yet, annotation of FTUs is time consuming and expensive when done manually and existing algorithms achieve low accuracy and do not generalize well. This paper compares the five winning algorithms from the "Hacking the Kidney" Kaggle competition to which more than a thousand teams from sixty countries contributed. We compare the accuracy and performance of the algorithms on a large-scale renal glomerulus Periodic acid-Schiff stain dataset and their generalizability to a colonic crypts hematoxylin and eosin stain dataset. Results help to characterize how the number of FTUs per unit area differs in relationship to their position in kidney and colon with respect to age, sex, body mass index (BMI), and other clinical data and are relevant for advancing pathology, anatomy, and surgery.

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Godwin, L. L., Ju, Y., Sood, N., Jain, Y., Quardokus, E. M., Bueckle, A., Longacre, T., Horning, A. M., Lin, Y., Esplin, E. D., Hickey, J. W., Snyder, M. P., Patterson, N. H., Spraggins, J. M., Borner, K.. 2021-11-11. Robust and generalizable segmentation of human functional tissue units. https://doi.org/10.1101/2021.11.09.467810

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