acePerformance Evaluation of an Artificial Intelligence-Assisted Digital Morphology System for Bone Marrow Aspirate Examination
Introduction: Morphological examination of bone marrow aspirates (BMA) remains essential for the diagnosis of hematologic diseases, but conventional microscopy is labor-intensive and subject to interobserver variability. Methods: A total of 158 samples from patients were analyzed. Differential counts obtained by optical microscopy were compared with those of the CellaVision BMA Application used according to its intended workflow of automated preclassification followed by expert review. The two methods were compa…
In 158 patient samples, automated preclassification plus expert review gave differential counts comparable with conventional microscopy for most nucleated cells, with 96.8% to 99.4% agreement at key decision thresholds.
Agreement was weaker for basophils and plasma cells, and sensitivity at the 20% blast threshold was only 77.3%, so expert review remains necessary.
The findings come from a single-center series and the system was assessed only within an expert-reviewed workflow, so expert review and further validation remain necessary.
Evidence
- Peer-reviewedInternational Journal of Laboratory Hematology2026-10-14
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Truvace Impact Record TRV-2026-1411, v1: “Performance Evaluation of an Artificial Intelligence-Assisted Digital Morphology System for Bone Marrow Aspirate Examination.” Truvace, 2026-10-15. /record/TRV-2026-1411 (accessed at citation time). sha256 9822a5e93ce803c1…
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