RESUMO
Bone marrow aspiration (BMA) smear analysis is essential for diagnosis, treatment and monitoring of a variety of benign and neoplastic hematological conditions. Currently this analysis is performed by manual microscopy. We conducted a multi-center study to validate a computational microscopy approach with an artificial intelligence (AI)-driven decision support system. A total of 795 BMA specimens (615 Romanowsky-stained and 180 Prussian blue-stained) from patients with neoplastic and other clinical conditions were analyzed, comparing the performance of the Scopio Labs X100 Full Field BMA system (test method) with manual microscopy (reference method). The system provided an average of 1385±536 (range 0-3131) cells per specimen for analysis. An average of 39.98±19.64 fields of view (range 0-140) per specimen were selected by the system for analysis, of them 87±21% (range 0-100%) were accepted by the qualified operators. These regions were included in an average of 17.62±7.24 regions of interest (range 1-50) per specimen. The efficiency, sensitivity, and specificity for primary and secondary marrow aspirate characteristics (maturation, morphology, and count assessment), as well as overall inter-user agreement, were evaluated. The test method showed high correlation with the reference method for comprehensive BMA evaluation, both on Romanowsky (90.85% efficiency, 81.61% sensitivity; specificity 92.88%) and Prussian blue (90.0% efficiency, 81.94% sensitivity; 93.38% specificity) stained samples. The overall agreement between the test and reference method for BMA assessment was 91.1%. For repeatability and reproducibility, all standard deviations and coefficients of variation values were below the pre-defined acceptance criteria both for discrete measurements (CV below 20%) and for differential measurements (SD below 5%). The high degree of correlation between the digital decision support system and manual microscopy demonstrates the potential of this system to provide a high-quality, accurate digital BMA analysis, -expediting expert review and diagnosis of BMA specimens, with practical applications including remote BMA evaluation, and possibly new opportunities for the research of normal and neoplastic hematopoiesis.
RESUMO
BACKGROUND: Current digital cell imaging systems perform peripheral blood smear (PBS) analysis in limited regions of the PBS and require the support of manual microscopy without achieving full digital microscopy. We report a multicenter study that validated the Scopio Labs X100 Full Field PBS, a novel digital imaging system that utilizes a full field view approach for cell recognition and classification, in a decision support system mode. METHODS: We analyzed 335 normal and 310 abnormal PBS from patients with various clinical conditions and compared the performance of Scopio's Full Field PBS as the test method, with manual PBS analysis as the reference method. Deming regression analysis was utilized for comparisons of WBC and platelet estimates. Measurements of WBC and platelet estimation accuracy along with the agreement on RBC morphology evaluation were performed. Reproducibility and repeatability (R&R) of the system were also evaluated. RESULTS: Scopio's Full Field PBS WBC accuracy was evaluated with an efficiency of 96.29%, sensitivity of 87.86%, and specificity of 97.62%. The agreement between the test and reference method for RBC morphology reached 99.77%, and the accuracy for platelet estimation resulted in an efficiency of 94.89%, sensitivity of 90.00%, and specificity of 96.28%, with successful R&R tests. The system enabled a comprehensive review of full field PBS as shown in representative samples. CONCLUSIONS: Scopio's Full Field PBS showed a high degree of correlation of all tested parameters with manual microscopy. The novel full field view of specimens facilitates the long-expected disengagement between the digital application and the manual microscope.