Performance Evaluation Study of a Novel Digital Microscopy System for the Quantitative Analysis of Bone Marrow Aspirates

Background. We report here a trial in progress for the evaluation of a novel system aimed to provide an all-digital standardized bone marrow aspirate (BMA) analysis, Scopio Labs X100, empowered by artificial intelligence (AI) based cell pre-classification. Current methods for the analysis and reporting of BMA specimens are based on analog microscopy, as whole slide imaging at x100 magnification is not practically available. The lack of uniformity between experts in the field, originating from a subjective manual review, can lead to inconsistencies in disease diagnosis and classification, and thereby affect treatment and clinical outcomes. For example, ICSH and WHO guidelines require that at least 500 cells should be counted in at least two smears when a precise percentage of an abnormal cell type is required for diagnosis and classification. It is also recommended that in order reduce imprecision from sampling error, the total number of cells counted in the differential should be increased, specifically if the abnormal cell count is very close to a critical threshold for disease stratification or response assessment. For the general evaluation of hematopoiesis, Myeloid to Erythroid (M:E) ratio is reported. Considering the complexity of the manual BMA analysis, even more so in routine laboratory settings with competitive turnaround times, a digital transformation can sustain the desired standardization, and increase sensitivity and efficiency in routine workflow.