Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.
David Bermejo-PeláezSandra Rueda CharroMaría García RoaRoberto Trelles-MartínezAlejandro Bobes-FernándezMarta Hidalgo SotoRoberto García-VicenteMaría Luz MoralesAlba Rodríguez-GarcíaAlejandra Ortiz-RuizAlberto Blanco SánchezAdriana Mousa UrbinaElisa ÁlamoLin LinElena DacalDaniel CuadradoMaría PostigoAlexander VladimirovJaime Garcia-VillenaAndrés SantosMaría Jesús Ledesma-CarbayoRosa AyalaJoaquín Martínez-LópezMaría LinaresMiguel Á Luengo-OrozPublished in: Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada (2024)
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.