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Artificial intelligence-assisted mapping of proliferation centers allows the distinction of accelerated phase from large cell transformation in chronic lymphocytic leukemia

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Abstract

Chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL) is characterized morphologically by numerous small lymphocytes and pale nodules composed of prolymphocytes and paraimmunoblasts known as proliferation centers (PCs). Patients with CLL can undergo transformation to a more aggressive lymphoma, most often diffuse large B-cell lymphoma (DLBCL), known as Richter transformation (RT). An accelerated phase of CLL (aCLL) also may be observed which correlates with subsequent transformation to DLBCL, and may represent an early stage of transformation. Distinguishing PCs in CLL from aCLL or RT can be diagnostically challenging, particularly in small needle biopsy specimens. Available guidelines pertaining to distinguishing CLL from its’ progressive forms are limited, subject to the morphologist’s experience and are often not completely helpful in the assessment of scant biopsy specimens. To objectively assess the extent of PCs in aCLL and RT, and enhance diagnostic accuracy, we sought to design an artificial intelligence (AI)-based tool to identify and delineate PCs based on feature analysis of the combined individual nuclear size and intensity, designated here as the heat value. Using the mean heat value from the generated heat value image of all cases, we were able to reliably separate CLL, aCLL and RT with sensitive diagnostic predictive values.

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Fig. 1: Digital slide staining normalization.
Fig. 2: Nuclear segementation.
Fig. 3: Generation of heat values by integrating nuclear size and intensity analysis.
Fig. 4: Heatmap generation based on heat values per tile for each of the three disease entities.

Data availability

All the original data of this study will be available upon reasonable request to the corresponding authors, including, but not limited to, a request to reproduce results in this manuscript.

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Funding

This study was supported by the grant from the National Cancer Institute (R00CA218667).

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S.E.H., P.C., J.W., and J.D.K. conceptualized the idea. S.E.H. and P.C. wrote the initial version of the manuscript. J.W. and J.D.K. supervised experimentation and re-iterations, and created the final version of the manuscript. L.J.M. and J.D.H. provided critical evaluation of the final version of the manuscript.

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Correspondence to Jia Wu or Joseph D. Khoury.

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El Hussein, S., Chen, P., Medeiros, L.J. et al. Artificial intelligence-assisted mapping of proliferation centers allows the distinction of accelerated phase from large cell transformation in chronic lymphocytic leukemia. Mod Pathol 35, 1121–1125 (2022). https://doi.org/10.1038/s41379-022-01015-9

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