James J J, Giannotti E, Chen Y
Nottingham Breast Institute, Nottingham University Hospitals, Nottingham NG5 1PB, UK.
Nottingham Breast Institute, Nottingham University Hospitals, Nottingham NG5 1PB, UK.
Clin Radiol. 2018 Oct;73(10):886-892. doi: 10.1016/j.crad.2018.05.028. Epub 2018 Jun 30.
To evaluate the diagnostic performance of computer-aided detection (CAD)-enhanced synthetic mammograms in comparison with standard synthetic mammograms and full-field digital mammography (FFDM).
A CAD-enhanced synthetic mammogram, a standard synthetic mammogram, and FFDM were available in 68 breast-screening cases recalled for soft-tissue abnormalities (masses, parenchymal deformities, and asymmetric densities). Two radiologists, blinded to image type and final assessment outcome, retrospectively read oblique and craniocaudal projections for each type of mammogram. The resulting 204 pairs of 2D images were presented in random order and scored on a five-point scale (1, normal to 5, malignant) without access to the Digital breast tomosynthesis (DBT) slices. Receiver operating characteristic (ROC) curve analysis was performed.
There were 34 biopsy-proven malignancies and 34 normal/benign cases. Diagnostic accuracy was significantly improved for the CAD-enhanced synthetic mammogram compared to the standard synthetic mammogram (area under the ROC curve [AUC]=0.846 and AUC=0.683 respectively, p=0.004) and compared to the conventional 2D FFDM (AUC=0.724, p=0.027). The CAD-enhanced synthetic mammogram had the highest diagnostic accuracy for all soft-tissue abnormalities, and for malignant lesions sensitivity was not affected by tumour size. For all 68 cases, there was an average of 3.2 areas enhanced per image. For the 34 cancer cases, 97.4% of lesions were correctly enhanced, with 2.1 false areas enhanced per image.
CAD enhancement significantly improves performance of synthetic 2D mammograms and also exhibits improved diagnostic accuracy compared to conventional 2D FFDM.
评估计算机辅助检测(CAD)增强合成乳腺X线摄影与标准合成乳腺X线摄影及全视野数字乳腺X线摄影(FFDM)相比的诊断性能。
在68例因软组织异常(肿块、实质变形和不对称密度)而被召回的乳腺筛查病例中,可获得CAD增强合成乳腺X线摄影、标准合成乳腺X线摄影和FFDM。两名对图像类型和最终评估结果不知情的放射科医生,对每种类型乳腺X线摄影的斜位和头尾位投照进行回顾性阅读。将得到的204对二维图像随机排列,并在不查看数字乳腺断层合成(DBT)切片的情况下,以五点量表(1,正常至5,恶性)进行评分。进行了受试者操作特征(ROC)曲线分析。
有34例经活检证实为恶性肿瘤,34例为正常/良性病例。与标准合成乳腺X线摄影相比(ROC曲线下面积[AUC]分别为0.846和0.683,p = 0.004),以及与传统二维FFDM相比(AUC = 0.724,p = 0.027),CAD增强合成乳腺X线摄影的诊断准确性显著提高。CAD增强合成乳腺X线摄影对所有软组织异常具有最高的诊断准确性,对于恶性病变,敏感性不受肿瘤大小的影响。在所有68例病例中,每张图像平均有3.2个增强区域。在34例癌症病例中,97.4%的病变被正确增强,每张图像有2.1个假增强区域。
CAD增强显著提高了合成二维乳腺X线摄影的性能,并且与传统二维FFDM相比,诊断准确性也有所提高。