Ryoko Ohashi1, Michinobu Nagao2, Izumi Nakamura2, Takahiro Okamoto3, Shuji Sakai2. 1. Department of Diagnostic Imaging and Nuclear Medicine, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan. ohashi.ryoko@twmu.ac.jp. 2. Department of Diagnostic Imaging and Nuclear Medicine, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan. 3. Department of Breast and Endocrine Surgery, Tokyo Women's Medical University, Tokyo, Japan.
Abstract
BACKGROUND: The aim of this study was to determine if the diagnostic performance of breast lesion examinations could be improved using both digital breast tomosynthesis (DBT) and conventional digital mammography (CDM). METHODS: Our institutional review board approved the protocol, and patients were provided the opportunity to opt out of the study. A total of 628 patients aged 22-91 years with abnormal screening results or clinical symptoms were consecutively enrolled between June 2015 and March 2016. All patients underwent DBT and CDM, and 1164 breasts were retrospectively analyzed by three radiologists who interpreted the results based on the Breast Imaging Reporting and Data System. Categories 4 and 5 were considered positive, and pathological results were the gold standard. The diagnostic performance of CDM and CDM plus DBT was compared using the mean areas under the receiver operating characteristic (ROC) curves. RESULTS: A total of 100 breast cancer cases were identified. The areas under the ROC curves were 0.9160 (95% confidence interval 0.8779-0.9541) for CDM alone and 0.9376 (95% confidence interval 0.9019-0.9733) for CDM plus DBT. The cut-off values for both CDM alone and CDM plus DBT measurements were 4, with sensitivities of 61.0% (61/100) and 83.0% (83/100), respectively, and specificities of 99.1% (1054/1064) and 98.9% (1052/1064), respectively. CDM yielded 39 false-negative diagnoses, while CDM plus DBT identified breast cancer in 22 of those cases (56.4%). CONCLUSION: The combination of DBT and CDM for the diagnosis of breast cancer in women with abnormal examination findings or clinical symptoms proved effective and should be used to improve the diagnostic performance of breast cancer examinations.
BACKGROUND: The aim of this study was to determine if the diagnostic performance of breast lesion examinations could be improved using both digital breast tomosynthesis (DBT) and conventional digital mammography (CDM). METHODS: Our institutional review board approved the protocol, and patients were provided the opportunity to opt out of the study. A total of 628 patients aged 22-91 years with abnormal screening results or clinical symptoms were consecutively enrolled between June 2015 and March 2016. All patients underwent DBT and CDM, and 1164 breasts were retrospectively analyzed by three radiologists who interpreted the results based on the Breast Imaging Reporting and Data System. Categories 4 and 5 were considered positive, and pathological results were the gold standard. The diagnostic performance of CDM and CDM plus DBT was compared using the mean areas under the receiver operating characteristic (ROC) curves. RESULTS: A total of 100 breast cancer cases were identified. The areas under the ROC curves were 0.9160 (95% confidence interval 0.8779-0.9541) for CDM alone and 0.9376 (95% confidence interval 0.9019-0.9733) for CDM plus DBT. The cut-off values for both CDM alone and CDM plus DBT measurements were 4, with sensitivities of 61.0% (61/100) and 83.0% (83/100), respectively, and specificities of 99.1% (1054/1064) and 98.9% (1052/1064), respectively. CDM yielded 39 false-negative diagnoses, while CDM plus DBT identified breast cancer in 22 of those cases (56.4%). CONCLUSION: The combination of DBT and CDM for the diagnosis of breast cancer in women with abnormal examination findings or clinical symptoms proved effective and should be used to improve the diagnostic performance of breast cancer examinations.
Entities:
Keywords:
Breast cancer; Conventional digital mammography; Digital breast tomosynthesis; False negative; Screening