Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases

Abstract

Artificial intelligence; Bone marrow aspirates; Digital microscopy

Inteligencia artificial; Aspirados de médula ósea; Microscopía digital

Intel·ligència artificial; Aspirats de medul·la òssia; Microscòpia digital

Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.

This project has been partially funded by the European Union's Horizon 2020 research and innovation program under grant agreement No. 881062; the European Union - NextgenerationEU under the “Plan de Recuperación, Transformación y Resiliencia” of the Spanish Government, the Instituto de Salud Carlos III (ISCIII) under grants PMPTA22/00169, PMPTA22/00088, PMPTA22/00041, PMPTA22/00023, PMPTA22/00101; and the Centro para el Desarrollo Tecnológico y la Innovación (CDTI) under grant EXP 00156466 / IDI-20230066. D.B.-P. was supported by grant PTQ2020-011340/AEI/10.13039/501100011033 funded by the Spanish State Investigation Agency. R.G.-V. holds a Formación de Profesorado Universitario (FPU19/04933) grant from the Ministry of Science, Innovation and Universities of Spain Government. A.R.-G. holds the FEHH 2021 research grant from the Spanish Society of Haematology. L.L. was supported by a predoctoral grant IND2019/TIC-17167 (Comunidad de Madrid, Spain).