基于锥光束乳腺CT测量乳腺密度的可靠性研究

Reliability of breast density estimation based on cone beam breast CT

目的:探讨基于锥光束乳腺CT(cone beam breast CT,CBBCT)的阈值分割法测量乳腺密度的准确性,及其对乳腺腺体分类和乳腺癌筛查的意义。方法:回顾性分析2012年5月至2013年9月于天津医科大学肿瘤医院行乳腺X线检查(mammography,MG)及CBBCT检查的195例患者的影像学资料,其中64例患者的64侧乳腺符合入组条件。依据BI-RADS中乳腺构成的分类标准对其进行分类并得到多数报告;基于其CBBCT图像进行阈值分割法测量乳腺密度,并得到手动修正后乳腺密度。1个月后重复上述步骤。采用组内相关系数(intraclass correlation coefficient,ICC)比较观察者内、观察者间、阈值分割法测量与手动修正、非致密类及致密类乳腺测量结果之间的一致性。结果:阈值分割法测量乳腺密度的观察者内和观察者间ICC值分别为0.9624(95%CI:0.9388~0.9770)和0.9666(95%CI:0.9500~0.9785);手动修正测量观察者内和观察者间ICC值分别为0.9750(95%CI:0.9592~0.9847)和0.9775(95%CI:0.9661~0.9855);阈值分割法与手动修正测量之间ICC值为0.9962(95%CI:0.9983~0.9977);非致密类和致密类乳腺阈值分割法与手动修正之间ICC值分别为0.9497(95%CI:0.7072~0.9914)和0.9983(95%CI:0.9971~0.9990)。结论:基于CBBCT图像的阈值分割法是一种较为稳定且准确的计算机辅助测量乳腺密度的方法,未来有望应用于大规模乳腺癌筛查,并为乳腺癌风险的预测提供更多信息。

Objective： To investigate the accuracy of a threshold-based segmentation method based on cone beam breast CT（CBBCT）images in breast density measurement, and its value for breast-type classification and breast cancer screening. Methods： A retrospective analysis of 195 patients who had undergone CBBCT examination at Tianjin Medical University Cancer Institute and Hospital between May 2012 and August 2014 was performed. A total of 64 breasts were analyzed. On the basis of the classification criteria for breast density in BI-RADS, they were classified into four types and the majority report was reported. Breast density was measured by the threshold-based segmentation method based on CBBCT images and corrected manually to obtain the corrected breast density. A month later, the procedure was repeated. Intra-class correlation coefficients（ICCs） were used to compare the intra-observer and interobserver consistencies of threshold-based segmentation and manually corrected breast density measurement results for non-dense and dense breasts. Results： For threshold-based segmentation measurements the intra-observer and inter-observer ICC values were0.0.9624（95% CI： 0.9388~0.9770） and 0.9666（95% CI： 0.9500~0.9785）. For manually corrected measurements, the intra-observer and inter-observer ICC values were 0.9750（95% CI： 0.9592~0.9847） and 0.9775（95% CI： 0.9661~0.9855）. The ICC between the threshold-based segmentation method and manual correction was 0.9962（95% CI： 0.9983~0.9977）. The ICC values of thresholdbased and manually corrected measurement in non-dense and dense breasts were 0.9497（95% CI：0.7072-0.9914） and 0.9983（95% CI：0.9971-0.9990）, respectively. Conclusions： The threshold-based segmentation method based on CBBCT is a reliable and accurate computer-aided method of measuring breast density. It is expected to be applied in large-scale screening of breast cancer and to provide more information for predicting the risk of breast cancer.