Investigation of the Effectiveness of an Algorithm as an Auxiliary Method in Intraoperative Consultations of Central Nervous System Tumors.

IF 1.1 Q4 PATHOLOGY
Emel Cakir, Ismail Saygin, Ayten Livaoglu, Gizem Teoman, Zeynep Sagnak Yilmaz, Arife Cicek Malat, Muserref Muge Ustaoglu
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引用次数: 0

Abstract

Objective: One of the most difficult areas in a surgical pathology practice is intraoperative consultation. In a previous study, we proposed an algorithm that provides a systematic approach to intraoperative consultation for central nervous system tumors. Our aim was to demonstrate the effectiveness of this algorithm.

Material and methods: 102 cases were selected from intraoperative consultation procedures performed at our institution between 2012 and 2020. The algorithm was tested by five observers. The observers examined the smears and frozen sections without the algorithm, and then with the algorithm.

Results: The percentage change in the rate of correct diagnoses made by the four observers (O) increased after using the algorithm (O2: 8%, O3: 5%, O4: 8% and O5: 13%), but decreased for only one observer (O1) (5%). The most common error made by the four observers was `grading of glial tumors` (O1: 40%; O2: 23%; O4: 40% and O5: 27.5%), and this group of errors was mostly corrected by using the algorithm (O1: 33%; O2: 3.8%; O4: 23% and O5: 10%). For two observers (O2 and O5), a statistically significant change in diagnostic levels was observed after using the algorithm (p=0.024 and p=0.040; respectively). In addition, thanks to the use of the algorithm, a high degree of agreement was found between the observers` diagnoses (77.7%, p < 0.001).

Conclusion: In the intraoperative consultation of central nervous system lesions, algorithms can help to increase the accuracy of the diagnosis and reduce interobserver variability. This study demonstrates that an algorithmic approach is an effective method for pathologists in intraoperative consultation procedures.

将算法作为中枢神经系统肿瘤术中会诊辅助方法的有效性研究
目的:手术病理实践中最困难的领域之一是术中会诊。在之前的一项研究中,我们提出了一种为中枢神经系统肿瘤术中会诊提供系统方法的算法。我们的目的是证明该算法的有效性。材料与方法:我们从 2012 年至 2020 年期间在本院进行的术中会诊手术中选取了 102 个病例。该算法由五名观察员进行测试。观察者在未使用该算法的情况下检查涂片和冰冻切片,然后在使用该算法的情况下检查涂片和冰冻切片:结果:使用该算法后,四名观察员(O)的诊断正确率百分比变化有所增加(O2:8%;O3:5%;O4:8%;O5:13%),但只有一名观察员(O1)的诊断正确率有所下降(5%)。四位观察者最常见的错误是 "胶质瘤分级"(O1:40%;O2:23%;O4:40% 和 O5:27.5%),这组错误大多在使用算法后得到纠正(O1:33%;O2:3.8%;O4:23% 和 O5:10%)。两名观察员(O2 和 O5)在使用算法后,诊断水平发生了显著变化(分别为 p=0.024 和 p=0.040)。此外,由于使用了该算法,观察者的诊断结果高度一致(77.7%,p < 0.001):结论:在中枢神经系统病变的术中会诊中,算法有助于提高诊断的准确性并减少观察者之间的差异性。这项研究表明,算法方法是病理学家在术中会诊程序中的一种有效方法。
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来源期刊
CiteScore
1.90
自引率
10.00%
发文量
23
审稿时长
14 weeks
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