岩溶
软件
图像(数学)
有丝分裂指数
病理
神经母细胞瘤
索引(排版)
图像分析
人工智能
有丝分裂
图像处理
计算机科学
生物
医学
数字图像
细胞生物学
万维网
细胞培养
生物化学
遗传学
细胞凋亡
程序设计语言
程序性细胞死亡
作者
Guizhen Yu,Chongxiu Yu,Feng Xie,Mai He
标识
DOI:10.1177/10935266221093597
摘要
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.
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