title: Tomosynthesis-detected Architectural Distortion: Management Algorithm with Radiologic-Pathologic Correlation.
abstract: As use of digital breast tomosynthesis becomes increasingly widespread, new management challenges are inevitable because tomosynthesis may reveal suspicious lesions not visible at conventional two-dimensional (2D) full-field digital mammography. Architectural distortion is a mammographic finding associated with a high positive predictive value for malignancy. It is detected more frequently at tomosynthesis than at 2D digital mammography and may even be occult at conventional 2D imaging. Few studies have focused on tomosynthesis-detected architectural distortions to date, and optimal management of these distortions has yet to be well defined. Since implementing tomosynthesis at our institution in 2011, we have learned some practical ways to assess architectural distortion. Because distortions may be subtle, tomosynthesis localization tools plus improved visualization of adjacent landmarks are crucial elements in guiding mammographic identification of elusive distortions. These same tools can guide more focused ultrasonography (US) of the breast, which facilitates detection and permits US-guided tissue sampling. Some distortions may be sonographically occult, in which case magnetic resonance imaging may be a reasonable option, both to increase diagnostic confidence and to provide a means for image-guided biopsy. As an alternative, tomosynthesis-guided biopsy, conventional stereotactic biopsy (when possible), or tomosynthesis-guided needle localization may be used to achieve tissue diagnosis. Practical uses for tomosynthesis in evaluation of architectural distortion are highlighted, potential complications are identified, and a working algorithm for management of tomosynthesis-detected architectural distortion is proposed.
authors.affiliation: From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).
authors.forename: Melissa A
authors.initials: MA
authors.lastname: Durand
authors.affiliation: From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).
authors.forename: Steven
authors.initials: S
authors.lastname: Wang
authors.affiliation: From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).
authors.forename: Regina J
authors.initials: RJ
authors.lastname: Hooley
authors.affiliation: From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).
authors.forename: Madhavi
authors.initials: M
authors.lastname: Raghu
authors.affiliation: From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).
authors.forename: Liane E
authors.initials: LE
authors.lastname: Philpotts
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging* / Q000473:pathology; D018275:Carcinoma, Lobular / Q000000981:diagnostic imaging / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D061705:Image-Guided Biopsy; D008279:Magnetic Resonance Imaging; D008327:Mammography / Q000379:methods*; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement / Q000379:methods*; D013238:Stereotaxic Techniques