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Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.
Yoon, Jung Hyun; Kim, Eun-Kyung; Kim, Ga Ram; Han, Kyunghwa; Moon, Hee Jung.
Affiliation
  • Yoon JH; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea.
  • Kim EK; Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea.
  • Kim GR; Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea.
  • Han K; Department of Radiology, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
  • Moon HJ; Department of Radiology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, 20 Ilsan-ro, Wonju 220-701, Korea.
AJR Am J Roentgenol ; 218(1): 42-51, 2022 01.
Article in En | MEDLINE | ID: mdl-34378399
ABSTRACT
BACKGROUND. 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. OBJECTIVE. 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. METHODS. 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. 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%) (p < .001). The contralateral breast recall rate was significantly lower for DM plus AI-CAD (1.5%, p < .001) than for DM (6.6%) but for not DM plus DBT (2.7%, p = .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%) (p < .05); specificity was higher for DM plus AI-CAD (98.3%) than for DM (89.3%) or DM plus DBT (96.1%) (p < .05); sensitivity was significantly lower for DM plus AI-CAD (22.2%) than for DM (66.7%, p = .03) but not DM plus DBT (22.2%, p > .99). In the contralateral breast, accuracy was significantly higher for DM plus AI-CAD (97.1%) than for DM (92.5%, p < .001) but not DM plus DBT (96.1%, p = .25); specificity was significantly higher for DM plus AI-CAD (98.6%) than for DM (93.7%, p < .001) but not DM plus DBT (97.5%) (p = .09); sensitivity was not different between DM (33.3%), DM plus DBT (22.2%), and DM plus AI-CAD (11.1%) (p > .05). CONCLUSION. 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. CLINICAL IMPACT. AI-CAD may help address the challenges of interpreting post-BCT surveillance mammograms.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence / Mammography / Radiographic Image Interpretation, Computer-Assisted / Mastectomy, Segmental / Neoplasm Recurrence, Local Type of study: Diagnostic_studies / Observational_studies / Screening_studies Limits: Adult / Aged / Aged80 / Female / Humans / Middle aged Language: En Journal: AJR Am J Roentgenol Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence / Mammography / Radiographic Image Interpretation, Computer-Assisted / Mastectomy, Segmental / Neoplasm Recurrence, Local Type of study: Diagnostic_studies / Observational_studies / Screening_studies Limits: Adult / Aged / Aged80 / Female / Humans / Middle aged Language: En Journal: AJR Am J Roentgenol Year: 2022 Document type: Article