Spanish researchers are close to perfecting an artificial intelligence (AI)-based system for improving the cell counting of bone marrow aspirates, it has been announced.
Madrid-based researchers have reported successful testing of the new technology, stating that the technology reduces analysis time but also variability between analysts.
The project has been financed by the European Union, and early findings were reported earlier this year in the journal Microscopy and Microanalysis.
The system uses smartphones rather than specialist devices for digitising images. The researchers say this should make it 鈥渟calable鈥� around the world.
The researchers reported: 鈥淏y taking advantage of this holistic digital system, it could be possible to implement the solution in any haematology department in the world without incorporating specific and complex medical electronic devices into the clinical workflow.鈥�
The developers say they believe the project could be a launching pad for developing further AI technologies for haematology in areas of diagnosis, selection of treatment and prognosis.
David Bermejo-Pel谩ez, a researcher at Madrid-based AI company Spotlab, said: 鈥淲e have specifically designed an artificial intelligence algorithm based on deep learning that is capable of automatically differentiating and counting different cell types in images of bone marrow samples.鈥�
Jes煤s Ledesma, a researcher at the Universidad Polit茅cnica de Madrid, said: 鈥淭he results obtained have shown that this technology considerably reduces the analysis time of bone marrow samples, as well as the variability between observers when analysing them.鈥�
Fellow researcher Mar铆a Linares, of the Universidad Complutense de Madrid, said: 鈥淭he developed system increases the efficiency and precision in the diagnosis of haematological diseases such as leukaemia or multiple myeloma鈥�.
Source:
Bermejo-Pel谩ez D, Rueda Charro S, Garc铆a Roa M, Trelles-Mart铆nez R, Bobes-Fern谩ndez A, Hidalgo Soto M, Garc铆a-Vicente R, Morales ML, Rodr铆guez-Garc铆a A, Ortiz-Ruiz A, Blanco S谩nchez A, Mousa Urbina A, 脕lamo E, Lin L, Dacal E, Cuadrado D, Postigo M, Vladimirov A, Garcia-Villena J, Santos A, Ledesma-Carbayo MJ, Ayala R, Mart铆nez-L贸pez J, Linares M, Luengo-Oroz M. (2024) 鈥淒igital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.鈥� Microscopy and Microanalysis, 1 February 2024, doi: 10.1093/micmic/ozad143.
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