Construction of an Automatic Quantification Method for Bone Marrow Cellularity Using Image Analysis Software.

Although rapid, the evaluation of bone marrow (BM) cellularity is semi-quantitative and largely dependent upon visual estimates. We aimed to construct an automatic quantification method using image analysis software. We used hematoxylin and eosin (HE)-stained specimens of BM biopsies and clots from patients who underwent BM examination at Tottori University Hospital from 2020 to 2022. We compared image analysis (Methods A, B, and C) with visual estimates in pathology reports of 91 HE specimens in 54 cases (29 males, 25 females), including 38 biopsy and 53 clot specimens. Cellularity was visually scored as hypocellular (n = 17), normocellular (n = 44), or hypercellular (n = 30). Compared with the visual estimates, intraclass correlation coefficients for Methods A, B, and C were 0.80, 0.85, and 0.88, respectively. The most appropriate values were obtained with Method C which detected both non-fatty and cell nuclear areas.