Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea.
Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea.
AJR Am J Roentgenol. 2022 Jan;218(1):42-51. doi: 10.2214/AJR.21.26506. Epub 2021 Aug 11.
Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-thesis (DBT) and artificial intelligence-based computer-aided detection (AI-CAD) after breast-conserving therapy (BCT) has not been widely investigated. The purpose of our study was to assess the impact of additional DBT or AI-CAD on recall rate and diagnostic performance in women undergoing mammographic surveillance after BCT. This retrospective study included 314 women (mean age, 53.3 ± 10.6 [SD] years; four with bilateral breast cancer) who underwent BCT followed by DBT (mean interval from surgery to DBT, 15.2 ± 15.4 months). Three breast radiologists independently reviewed images in three sessions: digital mammography (DM), DM with DBT (DM plus DBT), and DM with AI-CAD (DM plus AI-CAD). Recall rates and diagnostic performance were compared between DM, DM plus DBT, and DM plus AI-CAD using the readers' mean results. Of the 314 women, six breast recurrences (three ipsilateral and three contralateral) had developed at the time of surveillance mammography. The ipsilateral breast recall rate was lower for DM plus AI-CAD (1.9%) than for DM (11.2%) or DM plus DBT (4.1%) ( < .001). The contralateral breast recall rate was significantly lower for DM plus AI-CAD (1.5%, < .001) than for DM (6.6%) but for not DM plus DBT (2.7%, = .08). In the ipsilateral breast, accuracy was higher for DM plus AI-CAD (97.0%) than for DM (88.5%) or DM plus DBT (94.8%) ( < .05); specificity was higher for DM plus AI-CAD (98.3%) than for DM (89.3%) or DM plus DBT (96.1%) ( < .05); sensitivity was significantly lower for DM plus AI-CAD (22.2%) than for DM (66.7%, = .03) but not DM plus DBT (22.2%, > .99). In the contralateral breast, accuracy was significantly higher for DM plus AI-CAD (97.1%) than for DM (92.5%, < .001) but not DM plus DBT (96.1%, = .25); specificity was significantly higher for DM plus AI-CAD (98.6%) than for DM (93.7%, < .001) but not DM plus DBT (97.5%) ( = .09); sensitivity was not different between DM (33.3%), DM plus DBT (22.2%), and DM plus AI-CAD (11.1%) ( > .05). After BCT, adjunct DBT or AI-CAD reduced recall rates and improved accuracy in the ipsilateral and contralateral breasts compared with DM. In the ipsilateral breast, the addition of AI-CAD resulted in a lower recall rate and higher accuracy than the addition of DBT. AI-CAD may help address the challenges of interpreting post-BCT surveillance mammograms.
术后乳房 X 线摄影术由于术后变形和血肿而存在解读挑战。在保乳治疗 (BCT) 后应用数字乳腺断层合成术 (DBT) 和基于人工智能的计算机辅助检测 (AI-CAD) 尚未得到广泛研究。我们的研究目的是评估在接受 BCT 后进行乳房 X 线摄影术监测的女性中,额外的 DBT 或 AI-CAD 是否会影响召回率和诊断性能。这项回顾性研究包括 314 名女性(平均年龄 53.3 ± 10.6 [SD] 岁;4 名双侧乳腺癌),她们接受了 BCT 后进行了 DBT(从手术到 DBT 的平均间隔时间为 15.2 ± 15.4 个月)。三位乳腺放射科医生在三个阶段独立地对图像进行了评估:数字乳腺 X 线摄影术 (DM)、DM 加 DBT (DM 加 DBT) 和 DM 加 AI-CAD (DM 加 AI-CAD)。使用读者的平均结果比较了 DM、DM 加 DBT 和 DM 加 AI-CAD 之间的召回率和诊断性能。在接受监测性乳房 X 线摄影术的 314 名女性中,有 6 例乳房复发(3 例同侧,3 例对侧)。DM 加 AI-CAD 的同侧乳房召回率(1.9%)低于 DM(11.2%)或 DM 加 DBT(4.1%)(<.001)。DM 加 AI-CAD 的对侧乳房召回率(1.5%,<.001)明显低于 DM(6.6%)但不低于 DM 加 DBT(2.7%,=.08)。在同侧乳房中,DM 加 AI-CAD 的准确性(97.0%)高于 DM(88.5%)或 DM 加 DBT(94.8%)(<.05);DM 加 AI-CAD 的特异性(98.3%)高于 DM(89.3%)或 DM 加 DBT(96.1%)(<.05);DM 加 AI-CAD 的敏感性(22.2%)明显低于 DM(66.7%,=.03)但不低于 DM 加 DBT(22.2%,>.99)。在对侧乳房中,DM 加 AI-CAD 的准确性(97.1%)明显高于 DM(92.5%,<.001)但不高于 DM 加 DBT(96.1%,=.25);DM 加 AI-CAD 的特异性(98.6%)明显高于 DM(93.7%,<.001)但不高于 DM 加 DBT(97.5%)(=.09);DM(33.3%)、DM 加 DBT(22.2%)和 DM 加 AI-CAD(11.1%)之间的敏感性没有差异(>.05)。在 BCT 后,与 DM 相比,附加的 DBT 或 AI-CAD 降低了同侧和对侧乳房的召回率并提高了准确性。在同侧乳房中,添加 AI-CAD 导致的召回率降低和准确性提高均优于添加 DBT。AI-CAD 可能有助于解决解读保乳治疗后监测性乳房 X 线摄影术的挑战。