How AI is Revolutionizing MDS Diagnosis

Palak Dave, postdoctoral fellow at Moffitt Cancer Center and Research Institute, discusses the potential role of artificial intelligence (AI) in improving the accuracy of myelodysplastic syndromes (MDS) diagnosis.

Dave addressed the challenges of distinguishing MDS from pre-MDS conditions like idiopathic cytopenia of undetermined significance (ICUS) and clonal cytopenia of undetermined significance (CCUS) in a presentation of an innovative study at the 2024 American Society of Hematology (ASH) Annual Meeting and Exposition. The study explored how AI can help standardize and accelerate MDS diagnosis.

This approach consisted of using a deep learning model that analyzes bone marrow aspirate smear images, and early findings showed that the AI achieved about 70% accuracy in internal validation.

In addition, Dave discusses how this AI pipeline standardized bone marrow smear analysis.

Transcription:

0:10 | I would say the focus is not just on accuracy but also on standardization and speed. Experienced hematopathologists can achieve high diagnostic accuracy, but the process can be time-consuming. Additionally, there is inherent subjectivity among experts, which can lead to variability in diagnoses. By standardizing these processes, we can make them faster and more consistent, ultimately benefiting patients.

0:40 | So I can go into a little more depth when I say there exists subjectivity. Why does that exist? Basically, in these kinds of diseases, the hematopathologist looks at individual cells in the bone marrow aspirate smear and makes a decision about what category the cell belongs to, out of many categories and possible abnormalities. So in this visual review, there can be subjectivity. I may think it is Category A, and another person may think it is Category B, because the differences are very minute. So when a machine does it, it is kind of standardized.

Transcription was edited for clarity with AI.

REFERENCE:

Dave P, Rai J, Zhang L, et al. A deep-learning pipeline for diagnosis of myelodysplastic syndromes/neoplasms using bone marrow smears. Presented at the 2024 American Society of Hematology (ASH) Annual Meeting and Exposition; December 7-10; San Diego, CA; abstract 4991.