Su Hyun Lee1, Jung Min Chang1, Sung Ui Shin1, A Jung Chu2, Ann Yi3, Nariya Cho1, Woo Kyung Moon1. 1. 1 Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea. 2. 2 Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea. 3. 3 Department of Radiology, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
Abstract
OBJECTIVE: To evaluate imaging features of breast cancers on digital breast tomosynthesis (DBT) according to molecular subtype and to determine whether the molecular subtype affects breast cancer detection on DBT. METHODS: This was an institutional review board--approved study with a waiver of informed consent. DBT findings of 288 invasive breast cancers were reviewed according to Breast Imaging Reporting and Data System lexicon. Detectability of breast cancer was quantified by the number of readers (0-3) who correctly detected the cancer in an independent blinded review. DBT features and the cancer detectability score according to molecular subtype were compared using Fisher's exact test and analysis of variance. RESULTS: Of 288 invasive cancers, 194 were hormone receptor (HR)-positive, 48 were human epidermal growth factor receptor 2 (HER2) positive and 46 were triple negative breast cancers. The most common DBT findings were irregular spiculated masses for HR-positive cancer, fine pleomorphic or linear branching calcifications for HER2 positive cancer and irregular masses with circumscribed margins for triple negative breast cancers (p < 0.001). Cancer detectability on DBT was not significantly different according to molecular subtype (p = 0.213) but rather affected by tumour size, breast density and presence of mass or calcifications. CONCLUSION: Breast cancers showed different imaging features according to molecular subtype; however, it did not affect the cancer detectability on DBT. Advances in knowledge: DBT showed characteristic imaging features of breast cancers according to molecular subtype. However, cancer detectability on DBT was not affected by molecular subtype of breast cancers.
OBJECTIVE: To evaluate imaging features of breast cancers on digital breast tomosynthesis (DBT) according to molecular subtype and to determine whether the molecular subtype affects breast cancer detection on DBT. METHODS: This was an institutional review board--approved study with a waiver of informed consent. DBT findings of 288 invasive breast cancers were reviewed according to Breast Imaging Reporting and Data System lexicon. Detectability of breast cancer was quantified by the number of readers (0-3) who correctly detected the cancer in an independent blinded review. DBT features and the cancer detectability score according to molecular subtype were compared using Fisher's exact test and analysis of variance. RESULTS: Of 288 invasive cancers, 194 were hormone receptor (HR)-positive, 48 were humanepidermal growth factor receptor 2 (HER2) positive and 46 were triple negative breast cancers. The most common DBT findings were irregular spiculated masses for HR-positive cancer, fine pleomorphic or linear branching calcifications for HER2 positive cancer and irregular masses with circumscribed margins for triple negative breast cancers (p < 0.001). Cancer detectability on DBT was not significantly different according to molecular subtype (p = 0.213) but rather affected by tumour size, breast density and presence of mass or calcifications. CONCLUSION:Breast cancers showed different imaging features according to molecular subtype; however, it did not affect the cancer detectability on DBT. Advances in knowledge: DBT showed characteristic imaging features of breast cancers according to molecular subtype. However, cancer detectability on DBT was not affected by molecular subtype of breast cancers.
Authors: Bo Kyoung Seo; Etta D Pisano; Cherie M Kuzimak; Marcia Koomen; Dag Pavic; Yeonhee Lee; Elodia B Cole; Juneyoung Lee Journal: Acad Radiol Date: 2006-10 Impact factor: 3.173
Authors: Antonio C Wolff; M Elizabeth H Hammond; Jared N Schwartz; Karen L Hagerty; D Craig Allred; Richard J Cote; Mitchell Dowsett; Patrick L Fitzgibbons; Wedad M Hanna; Amy Langer; Lisa M McShane; Soonmyung Paik; Mark D Pegram; Edith A Perez; Michael F Press; Anthony Rhodes; Catharine Sturgeon; Sheila E Taube; Raymond Tubbs; Gail H Vance; Marc van de Vijver; Thomas M Wheeler; Daniel F Hayes Journal: J Clin Oncol Date: 2006-12-11 Impact factor: 44.544
Authors: Wei-Tse Yang; Mark Dryden; Kristine Broglio; Michael Gilcrease; Shaheenah Dawood; Peter J Dempsey; Vicente Valero; Gabriel Hortobagyi; Deann Atchley; Banu Arun Journal: Breast Cancer Res Treat Date: 2007-11-17 Impact factor: 4.872
Authors: Angela A Luck; Andrew J Evans; Jonathan J James; Emad A Rakha; E Claire Paish; Andrew R Green; Ian O Ellis Journal: AJR Am J Roentgenol Date: 2008-08 Impact factor: 3.959
Authors: Brigid K Killelea; Anees B Chagpar; Jennifer Bishop; Nina R Horowitz; Carla Christy; Theodore Tsangaris; Madhavi Raghu; Donald R Lannin Journal: Ann Surg Oncol Date: 2013-08-22 Impact factor: 5.344