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使用全玻片图像和图像分析软件 Qupath 自动计算神经母细胞瘤有丝分裂-核分解指数中的肿瘤数量。

Automated Tumor Count for Mitosis-Karyorrhexis Index Determination in Neuroblastoma Using Whole Slide Image and Qupath, an Image Analytic Software.

机构信息

Data Science Program of Whiting School of Engineering, 96895The Johns Hopkins University, Baltimore, MD, USA.

Oak Brook Business Consulting, Eagan, MN, USA.

出版信息

Pediatr Dev Pathol. 2022 Sep-Oct;25(5):526-537. doi: 10.1177/10935266221093597. Epub 2022 May 14.

DOI:10.1177/10935266221093597
PMID:35570824
Abstract

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.

摘要

简介

有丝分裂-核碎指数(MKI)对神经母细胞瘤的风险分层工作很重要。MKI 通过估计分母(5000 个肿瘤细胞)来计算。我们假设全玻片图像(WSI)与适当的数字图像分析软件结合可以为病理学家的 MKI 工作提供客观的辅助。

材料与方法

在获得机构审查委员会批准后,我们使用了 16 例神经母细胞瘤作为方便病例。使用 Aperio Scanscope AT2 扫描仪以 40X 扫描 H&E 载玻片,并以 SVS 格式存储。还拍摄了数字照片并以 TIFF 格式存储。使用开源图像分析软件 Qupath 来注释、定义感兴趣区域(ROI)并自动计算 ROI 内的细胞数。

结果

使用选定的参数,Qupath 能够使用 WSI(.svs)和数字图像(.TIFF)提供细胞计数。自动计数与眼球手动计数的比较产生了精度高于.96、召回率高于.96、F1 分数高于.98 的结果,假阳性率范围为.6 至 3.7%,假阴性率范围为.6 至 3.8%。与原始病理报告相比,在 16 例中的 3 例(18.8%)中,自动肿瘤细胞计数导致 MKI 降低,在 1 例(6.3%)中“不良组织学”改变为“良好”。

结论

WSI(或数字图像)与 Qupath 的结合能够为细胞计数提供一种自动化、客观和一致的方法,有助于病理学家在神经母细胞瘤的工作中确定 MKI,并促进研究。

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