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采用时间分析的计算机辅助诊断以改善放射科医生对乳腺钼靶肿块病变的解读

Computer-aided diagnosis with temporal analysis to improve radiologists' interpretation of mammographic mass lesions.

作者信息

Timp Sheila, Varela Celia, Karssemeijer Nico

机构信息

Department of Radiology, Radboud University, Nijmegen Medical Centre, HB Nijmegen, The Netherlands.

出版信息

IEEE Trans Inf Technol Biomed. 2010 May;14(3):803-8. doi: 10.1109/TITB.2010.2043296. Epub 2010 Apr 15.

Abstract

The purpose of this study was to evaluate the effect of independent reading with computer-aided diagnosis (CAD) and independent double reading on radiologists' performance to characterize mass lesions on serial mammograms. Six radiologists rated 198 cases, 99 benign and 99 malignant. For each case, the mammograms from two consecutive screening rounds were available. The mass was visible on the prior view in 40% of the cases. Independently, a CAD programe also rated each mass lesion making use of information from prior and current views. The following reading situations were compared: single reading, independent reading with CAD, and independent double reading. Independent reading with CAD was implemented by averaging the scaled ratings from each radiologist and the scaled CAD scores. We implemented independent double reading by averaging the scaled scores from two radiologists. Results were evaluated using receiver-operating characteristic (ROC) methodology and multiple reader multiple case analysis. The average performance, measured as the area under the ROC curve (A(z) value), was 0.80 for the single-reading mode. For independent double reading, the average performance improved to 0.81. This improvement was not significant. For independent interpretation with CAD, the average performance significantly increased to 0.83 (P < 0.05). We conclude that CAD technology with temporal analysis has the potential to help radiologists with the task of discriminating between benign and malignant masses.

摘要

本研究的目的是评估在乳腺钼靶连续摄影中,使用计算机辅助诊断(CAD)的独立阅片以及独立双人阅片对放射科医生鉴别乳腺肿块病变表现的影响。六位放射科医生对198例病例进行了评级,其中99例为良性,99例为恶性。对于每个病例,可获得连续两轮筛查的乳腺钼靶图像。在40%的病例中,先前的图像上可见肿块。独立地,一个CAD程序也利用先前和当前图像的信息对每个肿块病变进行评级。比较了以下阅片情况:单人阅片、使用CAD的独立阅片以及独立双人阅片。使用CAD的独立阅片通过对每位放射科医生的标准化评级和标准化CAD分数进行平均来实现。我们通过对两位放射科医生的标准化分数进行平均来实施独立双人阅片。使用受试者操作特征(ROC)方法和多读者多病例分析对结果进行评估。以ROC曲线下面积(A(z)值)衡量的平均表现,单人阅片模式为0.80。对于独立双人阅片,平均表现提高到0.81。这种提高并不显著。对于使用CAD的独立解读,平均表现显著提高到0.83(P < 0.05)。我们得出结论,具有时间分析功能的CAD技术有潜力帮助放射科医生完成鉴别良性和恶性肿块的任务。

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