The Adjunct Screening With Tomosynthesis or Ultrasound in Women With Mammography-Negative Dense Breasts' interim analysis shows that ultrasound has better incremental BC detection than tomosynthesis in mammography-negative dense breasts at a similar FP-recall rate. However, future application of adjunct screening should consider that tomosynthesis detected more than 50% of the additional BCs in these women and could potentially be the primary screening modality.

Joint bleeding represents the most commonly reported type of hemorrhage in patients affected by hemophilia. Although the widespread use of prophylaxis has been able to significantly reduce the onset of arthropathy, it has been shown that a non-negligible percentage of patients develop degenerative changes in their joints despite this type of treatment. Thus, periodic monitoring of the joint status in hemophilia patients has been recommended to identify early arthropathic changes and prevent the development or progression of hemophilic arthropathy. Ultrasound (US) has proven able to detect and quantify the most relevant biomarkers of disease activity (i.e., joint effusion and synovial hypertrophy) and degenerative damages (i.e., osteo-chondral changes) by means of scoring scales of increasing disease severity. In the present review, we have detailed major literature evidence about the use of US to assess joint status in hemophilia patients, focusing on signs of disease activity and degenerative damages. In particular, we have discussed recent evidence about “point-of-care” use patients with hemophilia.

Given the increasingly important role of breast density as an independent risk factor for breast cancer, and the variable breast imaging tests that potentially provide measures for density. We compared breast tissue density on digital mammography (FFDM), digital breast tomosynthesis (DBT), and magnetic resonance imaging (MRI) using semi-automated automated software. These three imaging modalities have not been previously directly compared for estimating breast tissue density. Following informed consent from all participating women, FFDM, DBT, and MRI were performed. Breast percentage density was calculated with semi-automated software, and compared, for all three imaging modalities. 48 patients (mean age, 41 years; range, 35-67 years) underwent FFDM, DBT, and MRI. Percent FFDM, DBT, and MRI breast density measures showed a positive linear correlation, (r = 0.95 for MRI and DBT, P < 0.0001; r = 0.97, P < 0.0001 for FFDM and DBT; r = 0.87 for FFDM and MRI). Linear regression analysis related to MRI and DBT had a high r (2) = 0.89 (95 % CI = 0.88-0.99, P < 0.001). FFDM overestimated breast density in 15.1 % in comparison to DBT and in 16.2 % in comparison to MRI, or conversely each of DBT and MRI underestimated density (relative to FFDM) by 15.1 or 16.2 %, respectively. Differences in percentage breast density between FFDM and DBT, and between FFDM and MRI, were highly significant (P < 0.0001). Differences in percentage breast density between DBT and MRI were not significant (P > 0.05). Breast density measures using FFDM, DBT, or MRI were generally well-correlated, although differences were noted between estimates when comparing FFDM and DBT, and for estimates comparing FFDM and MRI. No signficant differences in percentage density were observed when comparing DBT and MRI. Our work highlight that differences between FFDM, DBT, and MRI should be considered when measuring percentage breast density.

PurposeTo compare MRI sequences for breast density measurements on a 3T MRI system using IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) as possible physiology-like reference.Materials and MethodsMRI examination was performed in 48 consecutive patients (mean age 41, years; range, 35–67 years) on a 3.0T scanner and 46 were included. All (fertile) women, were examined between days 5 and 15 of their menstrual cycle. MRI protocol included: T1-turbo spin-echo (T1-tSE), T2-turbo spin-echo (T2-tSE), VIBRANT (Volume Imaging for Breast Assessment) before and after injection of contrast media and IDEAL. Breast density was calculated with semi-automated software. Statistical analysis was performed with non-parametric tests.ResultsMean percentage of breast density calculated in each sequence was: T1-tSE  = 56%; T2-tSE  = 52%; IDEAL FatOnly  = 55%; IDEAL WaterOnly  = 53%, VIBRANT  = 55%. Significant differences were observed between T2-tSE and both T1-tSE (p<0.001), VIBRANT sequences (p = 0.009), T1-tSE and both IDEAL WaterOnly (p = 0.007) and IDEAL FatOnly (p = 0.047). Breast density percentage showed a positive linear correlation among different sequences: r≥0.93.ConclusionsDifferences exist between MRI sequences used to assess breast density percentage. T1-weighted sequences values were similar to IDEAL sequences.

At least 5.4% (15 of 278) of peripheral nerve US studies led to additional clinical or imaging assessment. Muscle Nerve 57: 65-69, 2018.

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1,2, Federico Pistoia1,2, Federico Zaottini1,2, Sonia Airaldi3, Maribel Miguel Perez4, Michelle Pansecchi1,2, Luca Tovt1,2, Sara Sanguinetti1,2, Ingrid Möller5, Alessandra Bruns6, Carlo Martinoli1,2

No abstract