PURPOSE Mammography is not always available or feasible. The purpose of this systematic review and meta-analysis is to assess the diagnostic performance of ultrasound as a primary tool for early detection of breast cancer. MATERIALS AND METHODS For this systematic review and meta-analysis, we comprehensively searched PubMed and SCOPUS to identify articles from January 2000 to December 2018 that included data on the performance of ultrasound for detection of breast cancer. Studies evaluating portable, handheld ultrasound as an independent detection modality for breast cancer were included. Quality assessment and bias analysis were performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity analyses and meta-regression were used to explore heterogeneity. The study protocol has been registered with the international prospective register of systematic reviews (PROSPERO identifier: CRD42019127752). RESULTS Of the 526 identified studies, 26 were eligible for inclusion. Ultrasound had an overall pooled sensitivity and specificity of 80.1% (95% CI, 72.2% to 86.3%) and 88.4% (95% CI, 79.8% to 93.6%), respectively. When only low- and middle-income country data were considered, ultrasound maintained a diagnostic sensitivity of 89.2% and specificity of 99.1%. Meta-analysis of the included studies revealed heterogeneity. The high sensitivity of ultrasound for the detection of breast cancer was not statistically significantly different in subgroup analyses on the basis of mean age, risk, symptoms, study design, bias level, and study setting. CONCLUSION Given the increasing burden of breast cancer and infeasibility of mammography in certain settings, we believe these results support the potential use of ultrasound as an effective primary detection tool for breast cancer, which may be beneficial in low-resource settings where mammography is unavailable.

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Purpose:To compare routine ROI analysis and three different histogram analyses in the grading of glial neoplasms. The hypothesis is that histogram methods can provide a robust and objective technique for quantifying perfusion data in brain gliomas. Current region-of-interest (ROI)-based methods for the analysis of dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC MRI) data are operator-dependent. Materials and Methods:A total of 92 patients underwent conventional and DSC MRI. Multiple histogram metrics were obtained for cerebral blood flow (CBF), cerebral blood volume (CBV), and relative CBV (rCBV) maps using tumoral (T), peritumoral (P), and total tumoral (TT) analysis. Results were compared to histopathologic grades. Statistical analysis included Mann-Whitney (MW) tests, Spearman rank correlation coefficients, logistic regression, and McNemar tests. Results:The maximum value of rCBV (rCBV max ) showed highly significant correlation with glioma grade (r ϭ 0.734, P Ͻ 0.001). The strongest histogram correlations (P Ͻ 0.0001) occurred with rCBV T SD (r ϭ 0.718), rCBV P SD 25 (r ϭ 0.724) and rCBV TT SD 50 (r ϭ 0.685). Multiple rCBV T , rCBV P , and rCBV TT histogram metrics showed significant correlations. CBF and CBV histogram metrics were less strongly correlated with glioma grade than rCBV histogram metrics. HISTOGRAM ANALYSIS is a quantitative technique used in a number of neuroimaging studies but is most commonly used in magnetization transfer ratio studies of patients with diffuse cerebral disease such as multiple sclerosis (1-4). Dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC MRI) is an established technique in the evaluation of cerebral glial neoplasms. Relative cerebral blood volume (rCBV) measurements show reliable correlation with tumor grade and histopathologic findings of tumor neovascularity (5-16). Perfusion data is most commonly analyzed using multiple small region-of-interest (ROI) measurements, an operator-dependent method. ROI measurement of tumor rCBV has shown good reproducibility, but nevertheless remains operator-dependent and somewhat subjective, with an unavoidable component of interobserver and intraobserver variability. Reliable, reproducible data may only be obtained by experienced operators. Therefore, developing a more objective method that simplifies the analysis may allow even inexperienced operators to obtain reproducible data. Importantly, as surrogate imaging markers for angiogenesis are being investigated to determine the efficacy of antiangiogenic therapies (17), intra-and interinstitutional reproducibility becomes crucial, particularly when performing multicenter clinical trials using DSC MRI. The hypothesis is that histogram methods are comparable to, if not superior to current ROI-based methods for calculating the maximum value of rCBV (rCBV max ) in the prediction of glioma grade. We compare three methods of histogram analysis using both ROI- Conclusion

BACKGROUND AND PURPOSE: MR imaging can measure tissue perfusion and the integrity of the blood-brain barrier. We hypothesize that a combined measure of cerebral blood volume and vascular permeability using vascular-space occupancy (VASO) MR imaging, a recently developed imaging technique, is of diagnostic value for predicting tumor grade.