Objective: Because of the importance of breast imaging as a radiology subspecialty and concerns about malpractice, the purpose of our study is to provide a detailed portrait of breast imaging specialists, their professional activities and practices, and information on all radiologists who interpret mammograms.
Materials And Methods: We analyzed data from the American College of Radiology's 2003 Survey of Radiologists, a large, stratified random sample survey that achieved a 63% response. Responses were weighted to make them representative of all radiologists in the United States.
Results: Approximately 10% of all radiologists, or 2,700-2,800 radiologists, are breast imaging specialists, but 61% of radiologists interpret mammograms, and only approximately 30% of mammograms are interpreted by breast imaging specialists. Of radiologists who reported that breast imaging was their primary specialty, only 21% took a fellowship in the field (much lower than for other subspecialties), 59% spent > or = 50% of their clinical work time in the specialty, 82% interpret > or = 2,000 mammograms annually, and only 11% (also well below other subspecialties) report that the main subspecialty society (the Society of Breast Imaging) is one of the two most important professional organizations for them. On average, breast imaging specialists, like other radiologists, report that their workload is about as heavy as desired. Their level of enjoyment of radiology does not differ significantly from average.
Conclusion: Breast imaging appears not to be as strongly organized to raise awareness of and support for its problems as are other subspecialties. Although others find evidence of likely future problems, breast imaging specialists are not currently overworked or less satisfied in their profession than other radiologists, despite relatively low revenue generation and a particularly high risk of a malpractice lawsuit.
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http://dx.doi.org/10.2214/AJR.05.1858 | DOI Listing |
FASEB J
January 2025
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Milk is a multifaceted biofluid that is essential for infant nutrition and development, yet its cellular and bioactive components, particularly maternal milk cells, remain understudied. Early research on milk cells indicated that they cross the infant's intestinal barrier and accumulate within systemic organs. However, due to the absence of modern analytical techniques, these studies were limited in scope and mechanistic analysis.
View Article and Find Full Text PDFMol Carcinog
January 2025
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
The standard therapy for locally unresectable advanced non-small cell lung cancer (NSCLC) is comprised of chemoradiotherapy (CRT) before immunotherapy (IO) consolidation. However, how to predict treatment outcomes and recognize patients that will benefit from IO remain unclear. This study aimed to identify prognostic biomarkers by integrating computed tomography (CT)-based radiomics and genomics.
View Article and Find Full Text PDFJpn J Clin Oncol
January 2025
Department of Obstetrics and Gynecology, Tohoku University School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan.
Objectives: To identify a method for breast cancer (BC) surveillance in patients with epithelial ovarian cancer (EOC) with germline BRCA1/2 pathogenic variants (gBRCA1/2m) and the incidence of BC after EOC in the era of broad PARP inhibitors use.
Methods: We retrospectively analyzed the data on EOC patients who had gBRCA1/2m by genetic testing between January 2017 and August 2023 in our single center.
Results: Of 125 patients with EOC, 33 had gBRCA1/2m.
Radiol Case Rep
March 2025
Longstreet Clinic, Breast Surgery, 725 Jesse Jewell Parkway, Gainesville, GA 30501 USA.
Adenoid cystic carcinoma (ACC) of the breast is an exceptionally rare malignancy, accounting for less than 0.1% of all breast cancers. Despite its favorable prognosis, optimal management remains undefined due to its rarity and lack of consensus guidelines.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective: To develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).
Materials And Methods: A total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] = 194, brain metastases of breast cancer [BMBC] = 108, brain metastases of gastrointestinal tumor [BMGiT] = 48) and test sets (BMLC = 50, BMBC = 27, BMGiT = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE).
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