BreastScreen Reader Assessment Strategy, Medical Imaging Science, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, New South Wales, Australia.
Medical Imaging Science, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, New South Wales, Australia.
Asia Pac J Clin Oncol. 2022 Aug;18(4):441-447. doi: 10.1111/ajco.13686. Epub 2021 Nov 23.
In many western countries, there is good evidence documenting the performance of radiologists reading digital breast tomosynthesis (DBT) images. However, the diagnostic efficiency of Chinese radiologists using DBT, particularly type of errors being made and type of cancers being missed, is understudied. This study aims to investigate the pattern of diagnostic errors across different lesion types produced by Chinese radiologists diagnosing from DBT images. Australian radiologists will be used as a benchmark.
Twelve Chinese radiologists read a DBT test set and located each perceived cancer lesion. True positives, false positives (FP), true negatives and false negatives (FN) were generated. The same test set was also read by 14 Australian radiologists. Z-scores and Pearson correlations were used to compare interpretation of lesions and identification of normal appearances between two groups of radiologists.
Architectural distortions (p < .001) and stellate masses (p = .02) were more difficult for Chinese radiologists to correctly diagnose compared to their Australian counterparts. Chinese readers categorised more FPs as discrete masses (p < .001) and fewer FPs as architectural distortions (p < .001) comparing with Australian radiologists. The percentages of FN for each cancer case were not correlated (r = 0.37, p = .18) but the percentages of FP for each normal case were moderately correlated (r = 0.52, p = .02) between two groups of readers.
Architectural distortions and stellate masses were challenging to Chinese radiologists when reading DBT. Our findings proposed the need of development of training and education programs focussing on imaging cases tailored for specific groups of readers with certain interpretation patterns.
在许多西方国家，有大量证据证明放射科医生阅读数字乳腺断层合成（DBT）图像的表现。然而，中国放射科医生使用 DBT 的诊断效率，特别是他们所犯的错误类型和遗漏的癌症类型，还没有得到充分研究。本研究旨在调查中国放射科医生诊断 DBT 图像时不同病变类型的诊断错误模式。将使用澳大利亚放射科医生作为基准。
12 名中国放射科医生阅读 DBT 测试集并定位每个感知到的癌症病变。生成真阳性、假阳性（FP）、真阴性和假阴性（FN）。同样的测试集也由 14 名澳大利亚放射科医生阅读。使用 Z 分数和 Pearson 相关系数比较两组放射科医生对病变的解释和对正常表现的识别。
与澳大利亚同行相比，中国放射科医生更难正确诊断出结构扭曲（p<0.001）和星状肿块（p=0.02）。与澳大利亚放射科医生相比，中国读者将更多的 FP 归类为离散肿块（p<0.001），将更少的 FP 归类为结构扭曲（p<0.001）。每个癌症病例的 FN 百分比没有相关性（r=0.37，p=0.18），但每个正常病例的 FP 百分比在两组读者之间中度相关（r=0.52，p=0.02）。
当阅读 DBT 时，结构扭曲和星状肿块对中国放射科医生来说具有挑战性。我们的研究结果表明，需要开发培训和教育计划，重点是针对具有特定解释模式的特定读者群体的成像病例。
