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意大利 COVID-19 疫情期间的数字病理学:调查研究。

Digital Pathology During the COVID-19 Outbreak in Italy: Survey Study.

机构信息

Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy.

Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy.

出版信息

J Med Internet Res. 2021 Feb 22;23(2):e24266. doi: 10.2196/24266.

Abstract

BACKGROUND

Transition to digital pathology usually takes months or years to be completed. We were familiarizing ourselves with digital pathology solutions at the time when the COVID-19 outbreak forced us to embark on an abrupt transition to digital pathology.

OBJECTIVE

The aim of this study was to quantitatively describe how the abrupt transition to digital pathology might affect the quality of diagnoses, model possible causes by probabilistic modeling, and qualitatively gauge the perception of this abrupt transition.

METHODS

A total of 17 pathologists and residents participated in this study; these participants reviewed 25 additional test cases from the archives and completed a final psychologic survey. For each case, participants performed several different diagnostic tasks, and their results were recorded and compared with the original diagnoses performed using the gold standard method (ie, conventional microscopy). We performed Bayesian data analysis with probabilistic modeling.

RESULTS

The overall analysis, comprising 1345 different items, resulted in a 9% (117/1345) error rate in using digital slides. The task of differentiating a neoplastic process from a nonneoplastic one accounted for an error rate of 10.7% (42/392), whereas the distinction of a malignant process from a benign one accounted for an error rate of 4.2% (11/258). Apart from residents, senior pathologists generated most discrepancies (7.9%, 13/164). Our model showed that these differences among career levels persisted even after adjusting for other factors.

CONCLUSIONS

Our findings are in line with previous findings, emphasizing that the duration of transition (ie, lengthy or abrupt) might not influence the diagnostic performance. Moreover, our findings highlight that senior pathologists may be limited by a digital gap, which may negatively affect their performance with digital pathology. These results can guide the process of digital transition in the field of pathology.

摘要

背景

向数字病理学的转变通常需要数月甚至数年才能完成。当 COVID-19 疫情迫使我们突然转向数字病理学时,我们正在熟悉数字病理学解决方案。

目的

本研究旨在定量描述突然向数字病理学的转变可能如何影响诊断质量,通过概率建模来确定可能的原因,并定性评估这种突然转变的感知。

方法

共有 17 名病理学家和住院医师参与了这项研究;这些参与者额外审查了 25 个来自档案的测试病例,并完成了最后的心理调查。对于每个病例,参与者执行了几个不同的诊断任务,记录了他们的结果并与使用金标准方法(即传统显微镜)进行的原始诊断进行了比较。我们使用概率建模进行了贝叶斯数据分析。

结果

总共包含 1345 个不同项目的整体分析得出,使用数字幻灯片的错误率为 9%(117/1345)。区分肿瘤性过程与非肿瘤性过程的任务错误率为 10.7%(42/392),而区分恶性过程与良性过程的任务错误率为 4.2%(11/258)。除了住院医师外,高级病理学家还产生了大多数差异(7.9%,13/164)。我们的模型表明,即使在调整其他因素后,职业水平之间的这些差异仍然存在。

结论

我们的研究结果与之前的研究结果一致,强调过渡的持续时间(即漫长或突然)可能不会影响诊断性能。此外,我们的研究结果强调,高级病理学家可能受到数字差距的限制,这可能会对他们使用数字病理学的表现产生负面影响。这些结果可以指导病理学领域的数字化过渡过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7d9/7901595/5644ccdbd607/jmir_v23i2e24266_fig1.jpg

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