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Automated Tumor Count for Mitosis-Karyorrhexis Index Determination in Neuroblastoma Using Whole Slide Image and
Guizhen Yu1, Chao Yu2, Feng Xie3
1Data Science Program of Whiting School of Engineering, 96895The Johns Hopkins University, Baltimore, MD, USA.
Introduction:
Mitosis-karyorrhexis index (MKI) is important for risk stratification workup of neuroblastic tumors. MKI is calculated by estimating the denominator (5000 tumor cells). We hypothesized that whole slide image (WSI) with appropriate digital image analytical software could provide an objective aid to pathologist's MKI workup.
Materials & Methods:
With IRB approval, sixteen cases of neuroblastic tumors as convenient cases were used. H&E slides were scanned at 40X using an Aperio Scanscope AT2 scanner and stored in SVS format. Digital photos were also taken and stored in TIFF format. Qupath, an open source image analytical software, was used to annotate, define region of interest (ROI) and automatically count the cells within ROI.
Results:
With selected parameters, Qupath was able to provide cell count using both WSI (.svs) and digital images (.TIFF). Comparison of automated count and eyeball manual count generated precision above .96, recall above .96, F1 scores above .98, with false positive rate ranging from .6 to 3.7%, and false negative rate from .6 to 3.8%. Compared to original pathological report, automated tumor cell count led to lower MKI in 3 of 16 cases (18.8%) and change of "unfavorable histology" to "favorable" in one case (1/16, 6.3%).
Conclusion:
Combination of WSI (or digital images) with Qupath is able to provide an automated, objective and consistent way for cell count to facilitate pathologist's MKI determination in neuroblastic tumors' workup and research.
