Diffusion-weighted MR imaging can help differentiate benign from malignant hepatic lesions. The use of two b values in one direction could be sufficient for the design of MR sequences in the liver.

Context: Low bone mass may increase risk of fracture. Several chronic medical conditions, medications, and lifestyle factors affect bone mineral accrual. Appropriate reference values are essential for identification of children with bone deficits.Objective: Our objective was to establish reference curves for bone mineral content (BMC) and density (BMD) in children. Design and Setting:The Bone Mineral Density in Childhood Study is an ongoing longitudinal study in which measurements are obtained annually at five clinical centers in the United States.Participants: Participants included 1554 healthy children (761 male, 793 female), ages 6 -16 yr, of all ethnicities. Main Outcome Measures:Scans of the whole body, lumbar spine, hip, and forearm were obtained using dual-energy x-ray absorptiometry. Percentile curves based on three annual measurements were generated using the LMS statistical procedure.Results: BMC of the whole body and lumbar spine and BMD of the whole body, lumbar spine, total hip, femoral neck, and forearm are given for specific percentiles by sex, age, and race (Black vs. nonBlack). BMC and BMD were higher for Blacks at all skeletal sites (P Ͻ 0.0001). BMC and BMD increased with age, and a plateau was not evident by age 16 (girls) or age 17 (boys). The variation in BMC and BMD also increased with age.Conclusions: Age-, race-, and sex-specific reference curves can be used to help identify children with bone deficits and for monitoring changes in bone in response to chronic diseases or therapies. (J Clin Endocrinol Metab

Background Assessing the volume of mammographic density might more accurately reflect the amount of breast volume at risk of malignant transformation and provide a stronger indication of risk of breast cancer than methods based on qualitative scores or dense breast area. Methods We prospectively collected mammograms for women undergoing screening mammography. We determined the diagnosis of subsequent invasive or ductal carcinoma in situ (DCIS) for 275 cases, selected 825 controls matched for age, ethnicity, and mammography system, and assessed three measures of breast density: percent dense area, fibroglandular volume, and percent fibroglandular volume. Results After adjustment for familial breast cancer history, body mass index, history of breast biopsy, and age at first live birth, the odds ratios for breast cancer risk in the highest versus lowest measurement quintiles were 2.5 (95% CI: 1.5, 4.3) for percent dense area, 2.9 (95% CI: 1.7, 4.9) for fibroglandular volume, and 4.1 (95% CI: 2.3, 7.2) for percent fibroglandular volume. Net reclassification indexes for density measures plus risk factors versus risk factors alone were 9.6% (P=0.07) for percent dense area, 21.1% (P=0.0001) for fibroglandular volume, and 14.8% (P=0.004) for percent fibroglandular volume. Fibroglandular volume improved the categorical risk classification of 1 in 5 women for both women with and without breast cancer. Conclusion Volumetric measures of breast density are more accurate predictors of breast cancer risk than risk factors alone and than percent dense area. Impact Risk models including dense fibroglandular volume may more accurately predict breast cancer risk than current risk models.