Architectural and dynamic features are important in breast MR imaging interpretation. Multivariate models involving feature assessment have a diagnostic accuracy superior to that of qualitative characterization of the dynamic enhancement pattern.

MR imaging findings are a stronger predictor of pathologic response to NACT than clinical assessment, with the greatest advantage observed with the use of volumetric measurement of tumor response early in treatment.

AMMOGRAPHY IS THE PRImary imaging modality used to detect clinically occult breast cancer. However, mammography has limitations in both sensitivity and specificity that have led to exploration of other imaging techniques. Magnetic resonance imaging (MRI) has been evaluated for breast imaging because of its value for assessing soft tissues of the body. Breast MRI is performed before and after injection of a gadoliniumbased contrast agent. 1,2 Additional lesions seen by MRI that are not visible on the mammogram have been reported to be present in between 27% and 37% of patients. 3,4 The use of MRI to evaluate women with mammographically or clinically suspicious breast lesions who are undergoing biopsy has shown high potential, with the reported sensitivities of MRI for breast cancer from larger single center studies ranging from 88% to 95%. 5-12 Thus, there has been considerable enthusiasm for breast MRI and use of the procedure for Medicare patients increased almost 3-fold between 2001 (3440 examinations) and 2003 (10 115 examinations). 13 However, the reported specificity of MRI is variable, ranging from 30% to For editorial comment see p 2779.

Cardiac muscle adapts well to changes in loading conditions. For example, left ventricular (LV) hypertrophy may be induced physiologically (via exercise training) or pathologically (via hypertension or valvular heart disease). If hypertension is treated, LV hypertrophy regresses, suggesting a sensitivity to LV work. However, whether physical inactivity in nonathletic populations causes adaptive changes in LV mass or even frank atrophy is not clear. We exposed previously sedentary men to 6 (n = 5) and 12 (n = 3) wk of horizontal bed rest. LV and right ventricular (RV) mass and end-diastolic volume were measured using cine magnetic resonance imaging (MRI) at 2, 6, and 12 wk of bed rest; five healthy men were also studied before and after at least 6 wk of routine daily activities as controls. In addition, four astronauts were exposed to the complete elimination of hydrostatic gradients during a spaceflight of 10 days. During bed rest, LV mass decreased by 8.0 +/- 2.2% (P = 0.005) after 6 wk with an additional atrophy of 7.6 +/- 2.3% in the subjects who remained in bed for 12 wk; there was no change in LV mass for the control subjects (153.0 +/- 12.2 vs. 153.4 +/- 12.1 g, P = 0.81). Mean wall thickness decreased (4 +/- 2.5%, P = 0.01) after 6 wk of bed rest associated with the decrease in LV mass, suggesting a physiological remodeling with respect to altered load. LV end-diastolic volume decreased by 14 +/- 1.7% (P = 0.002) after 2 wk of bed rest and changed minimally thereafter. After 6 wk of bed rest, RV free wall mass decreased by 10 +/- 2.7% (P = 0.06) and RV end-diastolic volume by 16 +/- 7.9% (P = 0.06). After spaceflight, LV mass decreased by 12 +/- 6.9% (P = 0.07). In conclusion, cardiac atrophy occurs during prolonged (6 wk) horizontal bed rest and may also occur after short-term spaceflight. We suggest that cardiac atrophy is due to a physiological adaptation to reduced myocardial load and work in real or simulated microgravity and demonstrates the plasticity of cardiac muscle under different loading conditions.

).q RSNA, 2015 Purpose:To evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence-free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR). Materials and Methods:This HIPAA-compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrastenhanced MR imaging before treatment (examination 1), after one cycle (examination 2), midtherapy (examination 3), and before surgery (examination 4). Functional tumor volume (FTV), computed from MR images by using enhancement thresholds, and change from baseline (DFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB), while controlling for age, race, and hormone receptor (HR)/ human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics. Results:Female patients (n = 162) with FTV and RFS were included. Conclusion:Breast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.q RSNA, 2015

BACKGROUNDThe authors compared the performance of screening mammography versus magnetic resonance imaging (MRI) in women at genetically high risk for breast cancer.METHODSThe authors conducted an international prospective study of screening mammography and MRI in asymptomatic, genetically high‐risk women age ≥ 25 years. Women with a history of breast cancer were eligible for a contralateral screening if they had been diagnosed within 5 years or a bilateral screening if they had been diagnosed > 5 years previously. All examinations (MRI, mammography, and clinical breast examination [CBE]) were performed within 90 days of each other.RESULTSIn total, 390 eligible women were enrolled by 13 sites, and 367 women completed all study examinations. Imaging evaluations recommended 38 biopsies, and 27 biopsies were performed, resulting in 4 cancers diagnosed for an overall 1.1% cancer yield (95% confidence interval [95%CI], 0.3–2.8%). MRI detected all four cancers, whereas mammography detected one cancer. The diagnostic yield of mammography was 0.3% (95%CI, 0.01–1.5%). The yield of cancer by MRI alone was 0.8% (95%CI, − 0.3–2.0%). The biopsy recommendation rates for MRI and mammography were 8.5% (95%CI, 5.8–11.8%) and 2.2% (95%CI, 0.1–4.3%).CONCLUSIONSScreening MRI in high‐risk women was capable of detecting mammographically and clinically occult breast cancer. Screening MRI resulted in 22 of 367 of women (6%) who had negative mammogram and negative CBE examinations undergoing biopsy, resulting in 3 additional cancers detected. MRI also resulted in 19 (5%) false‐positive outcomes, which resulted in benign biopsies. Cancer 2005. © 2005 American Cancer Society.

Screening MR imaging had a higher biopsy rate but helped detect more cancers than either mammography or US. US had the highest false-negative rate compared with mammography and MR, enabling detection of only one in six cancers in high-risk women.

Prospective and retrospective magnetic resonance (MR) imaging (0.35-T) interpretations were compared with final diagnoses in 110 patients suspected to have osteomyelitis. Diagnostic criteria of dark marrow on T1-weighted images and bright marrow on short-tau inversion-recovery images yielded a prospective sensitivity of 98% and a prospective specificity of 75%. Sixty percent of uncomplicated septic joint effusions demonstrated abnormal marrow signal intensity that was mistaken for osteomyelitis. Retrospective review revealed that overall specificity could be improved to 82% without loss of sensitivity if increased marrow signal intensity on T2-weighted images were included as an additional criterion. Specificity may be further increased by use of knowledge of morphologic patterns that distinguish various forms of osteomyelitis. Ten patients (9%) had potential pitfall diagnoses (eg, fracture, infarction, healed infection) that mimic osteomyelitis. MR imaging can be sensitive and specific for osteomyelitis if characteristic appearances and pitfall diagnoses are incorporated into the diagnostic criteria.