OBJECTIVE: To compare the performance of one-view digital breast tomosynthesis (DBT) and two-view full-field digital mammography (FFDM) in the detection and characterization of breast lesions in a selective diagnostic population. METHODS: A total of 598 breasts of 319 diagnostic patients were prospectively enrolled. Participants underwent bilateral one-view, mediolateral oblique (MLO) DBT and two-view, craniocaudal and MLO FFDM. The sensitivity and specificity of these methods and their classification into correct Breast Imaging-Reporting and Data System (BI-RADS) categories were compared. These methods were also compared in patients subgrouped by mammographic parenchymal density. Receiver operating characteristic (ROC) curve analysis was performed using the probability of cancer scores. RESULTS: DBT had higher overall sensitivity than FFDM (88.7% vs 80.7%, p = 0.001). Subgroup analyses showed that DBT had significantly higher sensitivity in assessing dense breasts and invasive cancers than FFDM. The BI-RADS category assessment was significantly better for DBT than for FFDM. The differences between the two modalities in specificity (94.1% and 93.2% for FFDM and DBT) were not significant (p = 0.664). The area under the ROC curves using the probability of cancer scores were 0.93 [95% confidence interval (CI), 0.91-0.95] for FFDM and 0.96 (95% CI, 0.94-0.97) for DBT (p = 0.005). ROC curve analysis indicated that most of the increased performance of DBT was due to dense breasts. CONCLUSION: A beneficial effect on the detection and characterization of breast lesions was found for one-view DBT compared with two-view FFDM in a selective diagnostic population. Improvements were especially enhanced in females with dense breasts. These results need to be examined in studies using large-scale consecutive sampling of a diagnostic population. ADVANCES IN KNOWLEDGE: In this study, using selective diagnostic study cases, one-view DBT offered improved reader performance compared with two-view FFDM for detection and characterization of breast cancers.
OBJECTIVE: To compare the performance of one-view digital breast tomosynthesis (DBT) and two-view full-field digital mammography (FFDM) in the detection and characterization of breast lesions in a selective diagnostic population. METHODS: A total of 598 breasts of 319 diagnostic patients were prospectively enrolled. Participants underwent bilateral one-view, mediolateral oblique (MLO) DBT and two-view, craniocaudal and MLO FFDM. The sensitivity and specificity of these methods and their classification into correct Breast Imaging-Reporting and Data System (BI-RADS) categories were compared. These methods were also compared in patients subgrouped by mammographic parenchymal density. Receiver operating characteristic (ROC) curve analysis was performed using the probability of cancer scores. RESULTS: DBT had higher overall sensitivity than FFDM (88.7% vs 80.7%, p = 0.001). Subgroup analyses showed that DBT had significantly higher sensitivity in assessing dense breasts and invasive cancers than FFDM. The BI-RADS category assessment was significantly better for DBT than for FFDM. The differences between the two modalities in specificity (94.1% and 93.2% for FFDM and DBT) were not significant (p = 0.664). The area under the ROC curves using the probability of cancer scores were 0.93 [95% confidence interval (CI), 0.91-0.95] for FFDM and 0.96 (95% CI, 0.94-0.97) for DBT (p = 0.005). ROC curve analysis indicated that most of the increased performance of DBT was due to dense breasts. CONCLUSION: A beneficial effect on the detection and characterization of breast lesions was found for one-view DBT compared with two-view FFDM in a selective diagnostic population. Improvements were especially enhanced in females with dense breasts. These results need to be examined in studies using large-scale consecutive sampling of a diagnostic population. ADVANCES IN KNOWLEDGE: In this study, using selective diagnostic study cases, one-view DBT offered improved reader performance compared with two-view FFDM for detection and characterization of breast cancers.
Authors: Mitra Noroozian; Lubomir Hadjiiski; Sahand Rahnama-Moghadam; Katherine A Klein; Deborah O Jeffries; Renee W Pinsky; Heang-Ping Chan; Paul L Carson; Mark A Helvie; Marilyn A Roubidoux Journal: Radiology Date: 2011-10-13 Impact factor: 11.105
Authors: Margarita L Zuley; Andriy I Bandos; Marie A Ganott; Jules H Sumkin; Amy E Kelly; Victor J Catullo; Grace Y Rathfon; Amy H Lu; David Gur Journal: Radiology Date: 2012-11-09 Impact factor: 11.105
Authors: Gisella Gennaro; R Edward Hendrick; Alicia Toledano; Jean R Paquelet; Elisabetta Bezzon; Roberta Chersevani; Cosimo di Maggio; Manuela La Grassa; Luigi Pescarini; Ilaria Polico; Alessandro Proietti; Enrica Baldan; Fabio Pomerri; Pier Carlo Muzzio Journal: Eur Radiol Date: 2013-04-26 Impact factor: 5.315
Authors: S Mall; J Noakes; M Kossoff; W Lee; M McKessar; A Goy; J Duncombe; M Roberts; B Giuffre; A Miller; N Bhola; C Kapoor; C Shearman; G DaCosta; S Choi; J Sterba; M Kay; K Bruderlin; N Winarta; K Donohue; B Macdonell-Scott; F Klijnsma; K Suzuki; P Brennan; C Mello-Thoms Journal: Eur Radiol Date: 2018-05-30 Impact factor: 5.315
Authors: Xuan-Anh Phi; Alberto Tagliafico; Nehmat Houssami; Marcel J W Greuter; Geertruida H de Bock Journal: BMC Cancer Date: 2018-04-03 Impact factor: 4.430