US Surveillance of Regional Lymph Node Recurrence after Breast Cancer Surgery

US Surveillance of Regional Lymph Node Recurrence after Breast Cancer Surgery
Hee Jung Moon, Min Jung Kim, Eun-Kyung Kim, Byeong-Woo Park, Ji Hyun Youk, Jin Young Kwak, Joohyuk Sohn, and Seung-Il Kim
Radiology 2009;252 673-681
Link to Journal

Ipsilateral lymph node recurrence is a predictor of distant metastasis, and lymph node evaluation during breast US is useful for early detection of lymph node recurrence in asymptomatic patients

Breast Imaging Reporting and Data System Lexicon for US: Interobserver Agreement for Assessment of Breast Masses

Breast Imaging Reporting and Data System Lexicon for US: Interobserver Agreement for Assessment of Breast Masses
Nouf Abdullah, Benoit Mesurolle, Mona El-Khoury, and Ellen Kao
Radiology 2009;252 665-672
Link to Journal

Breast Imaging Reporting and Data System subdivisions 4a, 4b, and 4c were poorly reproducible among radiologists, reflecting the lack of clear and objective factors to guide classification of a lesion according to the degree of suspicion of malignancy

Cancers in BRCA1 and BRCA2 Carriers and in Women at High Risk for Breast Cancer: MR Imaging and Mammographic Features

Cancers in BRCA1 and BRCA2 Carriers and in Women at High Risk for Breast Cancer: MR Imaging and Mammographic Features
Fiona J. Gilbert, Ruth M. L. Warren, Gek Kwan-Lim, Deborah J. Thompson, Ros A. Eeles, D. Gareth Evans, Martin O. Leach, and For the United Kingdom Magnetic Resonance Imaging in Breast Screening (MARIBS) Study Group
Radiology 2009;252 358-368
Link to Journal

Our review of the images from prior MR imaging examinations shows that the cancers grow in size and that enhancement curves change from type 1 to type 2 or 3 and demonstrate greater signal enhancement over time

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model
Etta D. Pisano, Suddhasatta Acharyya, Elodia B. Cole, Helga S. Marques, Martin J. Yaffe, Meredith Blevins, Emily F. Conant, R. Edward Hendrick, Janet K. Baum, Laurie L. Fajardo, Roberta A. Jong, Marcia A. Koomen, Cherie M. Kuzmiak, Yeonhee Lee, Dag Pavic, Sora C. Yoon, Wittaya Padungchaichote, and Constantine Gatsonis
Radiology 2009;252 348-357

Link to Journal

Our analysis results suggest that, image contrast was the most important factor in the improved performance of digital mammography, as compared with screen-film mammography, in the Digital Mammographic Imaging Screening Trial

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model
Etta D. Pisano, Suddhasatta Acharyya, Elodia B. Cole, Helga S. Marques, Martin J. Yaffe, Meredith Blevins, Emily F. Conant, R. Edward Hendrick, Janet K. Baum, Laurie L. Fajardo, Roberta A. Jong, Marcia A. Koomen, Cherie M. Kuzmiak, Yeonhee Lee, Dag Pavic, Sora C. Yoon, Wittaya Padungchaichote, and Constantine Gatsonis
Radiology 2009;252 348-357

Link to Journal

Our analysis results suggest that, image contrast was the most important factor in the improved performance of digital mammography, as compared with screen-film mammography, in the Digital Mammographic Imaging Screening Trial