Journal of Pathology Informatics Journal of Pathology Informatics
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TECHNICAL NOTE
Year : 2015  |  Volume : 6  |  Issue : 1  |  Page : 2

Development and validation of an app-based cell counter for use in the clinical laboratory setting


1 Department of Pathology and Laboratory Medicine, The University of California, San Francisco Medical Center, San Francisco, CA 94143-0102, USA
2 Department of Pathology and Laboratory Medicine, The University of California, San Francisco School of Medicine, San Franacisco, CA 94117, USA
3 Department of Epidemiology and Biostatistics, The University of California, San Francisco, San Francisco, CA 94107-1762, California, USA

Correspondence Address:
Alexander C Thurman
Department of Pathology and Laboratory Medicine, The University of California, San Francisco Medical Center, San Francisco, CA 94143-0102
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2153-3539.150252

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Introduction: For decades cellular differentials have been generated exclusively on analog tabletop cell counters. With the advent of tablet computers, digital cell counters - in the form of mobile applications ("apps") - now represent an alternative to analog devices. However, app-based counters have not been widely adopted by clinical laboratories, perhaps owing to a presumed decrease in count accuracy related to the lack of tactile feedback inherent in a touchscreen interface. We herein provide the first systematic evidence that digital cell counters function similarly to standard tabletop units. Methods: We developed an app-based cell counter optimized for use in the clinical laboratory setting. Paired counts of 188 peripheral blood smears and 62 bone marrow aspirate smears were performed using our app-based counter and a standard analog device. Differences between paired data sets were analyzed using the correlation coefficient, Student's t-test for paired samples and Bland-Altman plots. Results: All counts showed excellent agreement across all users and touch screen devices. With the exception of peripheral blood basophils (r = 0.684), differentials generated for the measured cell categories within the paired data sets were highly correlated (all r ≥ 0.899). Results of paired t-tests did not reach statistical significance for any cell type (all P > 0.05), and Bland-Altman plots showed a narrow spread of the difference about the mean without evidence of significant outliers. Conclusions: Our analysis suggests that no systematic differences exist between cellular differentials obtained via app-based or tabletop counters and that agreement between these two methods is excellent.


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