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Objective:Our objective was to compare care-seeking patterns in Mosul, Iraq, in 2018, 1 y after Islamic State of Iraq and Syria (ISIS) control, with findings from neighborhoods that had been sampled in 2017Methods:For this multi-stage randomized cluster household survey, we created one cluster in each of 20 neighborhoods randomly selected from the 40 neighborhoods in the 2016/17 survey; 12 in east Mosul, 8 in west Mosul. In each, 30 households were interviewed beginning at a randomly selected start house. Questions were derived from the 2016/2017 post-ISIS survey.Results:We interviewed the head of household or senior female in 600 households containing 3375 persons. One year after ISIS, some household demographic shifts had occurred. Diarrhea in children during the past 2 wk decreased from 50.1% to 7.5% (P < 0.001); however, cough/difficulty breathing increased from 15.5% to 33.6% (P < 0.01). Among adults, care-seeking for noncommunicable diseases increased from 22.3% to 43.5% (P < 0.001). Emotional and psychological complaints common in the previous survey were now nearly absent. Pregnancy complications diminished from 65.2% to 15.4% (P < 0.001).Conclusions:Communicable diseases predominated among children and noncommunicable diseases among adults. Access to health care substantially improved, although barriers remained. Satisfaction with services was mixed, with dissatisfaction expressed about testing, medicine access, and costs, but the work of health providers was rated highly.

Objective: Computer classification of sonographic BI-RADS features can aid differentiation of the malignant and benign masses. However, the variability in the diagnosis due to the differences in the observed features between the observations is not known. The goal of this study is to measure the variation in sonographic features between multiple observations and determine the effect of features variation on computer-aided diagnosis of the breast masses. Materials and Methods: Ultrasound images of biopsy proven solid breast masses were analyzed in three independent observations for BI-RADS sonographic features. The BI-RADS features from each observation were used with Bayes classifier to determine probability of malignancy. The observer agreement in the sonographic features was measured by kappa coefficient and the difference in the diagnostic performances between observations was determined by the area under the ROC curve, Az, and interclass correlation coefficient. Results: While some features were repeatedly observed, κ = 0.95, other showed a significant variation, κ = 0.16. For all features, combined intra-observer agreement was substantial, κ = 0.77. The agreement, however, decreased steadily to 0.66 and 0.56 as time between the observations increased from 1 to 2 and 3 months, respectively. Despite the variation in features between observations the probabilities of malignancy estimates from Bayes classifier were robust and consistently yielded same level of diagnostic performance, Az was 0.772 – 0.817 for sonographic features alone and 0.828 – 0.849 for sonographic features and age combined. The difference in the performance, ΔAz, between the observations for the two groups was small (0.003 – 0.044) and was not statistically significant (p < 0.05). Interclass correlation coefficient for the observations was 0.822 (CI: 0.787 – 0.853) for BI-RADS sonographic features alone and for those combined with age was 0.833 (CI: 0.800 – 0.862). Conclusion: Despite the differences in the BI- RADS sonographic features between different observations, the diagnostic performance of computer-aided analysis for differentiating breast masses did not change. Through continual retraining, the computer-aided analysis provides consistent diagnostic performance independent of the variations in the observed sonographic features.

Despite major advances in breast cancer imaging there is compelling need to reduce unnecessary biopsies by improving characterization of breast lesions. This study demonstrates the use of machine learning to enhance breast cancer diagnosis with multimodal ultrasound. Surgically proven solid breast lesions were studied using quantitative features extracted from grayscale and Doppler ultrasound images. Statistically different features from the logistic regression classifier were used train and test lesion differentiation by leave-one-out cross-validation. The area under the ROC curve (AUC) of the grayscale morphologic features was 0.85 (sensitivity = 87, specificity = 69). The diagnostic performance improved (AUC = 0.89, sensitivity = 79, specificity = 89) when Doppler features were added to the analysis. Reliability of the individual training cycles of leave-one-out cross-validation was tested by measuring dispersion from the mean model. Significant dispersion from the mean, representing weak learning, was observed in 11.3% of cases. Pruning the high-dispersion cases improved the diagnostic performance markedly (AUC 0.96, sensitivity = 92, specificity = 95). These results demonstrate the effectiveness of dispersion to identify weakly learned cases. In conclusion, machine learning with multimodal ultrasound including grayscale and Doppler can achieve high performance for breast cancer diagnosis, comparable to that of human observers. Identifying weakly learned cases can markedly enhance diagnosis.

This study investigates the use of hydralazine to enhance ultrasound hyperthermia for the treatment of hepatocellular carcinoma (HCC) by minimizing flow-mediated heat loss from the tumor. Murine HCC tumors were treated with a continuous mode ultrasound with or without an intravenous administration of hydralazine (5 mg/kg). Tumor blood flow and blood vessels were evaluated by contrast-enhanced ultrasound (CEUS) imaging and histology, respectively. Hydralazine markedly enhanced ultrasound hyperthermia through the disruption of tumor blood flow in HCC. Ultrasound treatment with hydralazine significantly reduced peak enhancement (PE), perfusion index (PI), and area under the curve (AUC) of the CEUS time-intensity curves by 91.9 ± 0.9%, 95.7 ± 0.7%, and 96.6 ± 0.5%, compared to 71.4 ± 1.9%, 84.7 ± 1.1%, and 85.6 ± 0.7% respectively without hydralazine. Tumor temperature measurements showed that the cumulative thermal dose delivered by ultrasound treatment with hydralazine (170.8 ± 11.8 min) was significantly higher than that without hydralazine (137.7 ± 10.7 min). Histological assessment of the ultrasound-treated tumors showed that hydralazine injection formed larger hemorrhagic pools and increased tumor vessel dilation consistent with CEUS observations illustrating the augmentation of hyperthermic effects by hydralazine. In conclusion, we demonstrated that ultrasound hyperthermia can be enhanced significantly by hydralazine in murine HCC tumors by modulating tumor blood flow. Future studies demonstrating the safety of the combined use of ultrasound and hydralazine would enable the clinical translation of the proposed technique.

Background and Objective: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and its current management relies heavily on locoregional therapy for curative therapy, bridge to transplant, and palliative therapy. Locoregional therapies include ablation and hepatic artery therapies such as embolization and radioembolization. In this study we evaluate the feasibility of using novel antivascular ultrasound (AVUS) as a noninvasive locoregional therapy to reduce perfusion in HCC lesions in a rat model and, monitor the effect with contrast-enhanced ultrasound imaging. Methods: HCC was induced in 36 Wistar rats by the ingestion of 0.01% diethylnitrosamine (DEN) for 12 weeks. Two therapy regimens of AVUS were evaluated. A primary regimen (n = 19) utilized 2-W/cm2, 3-MHz ultrasound (US) for 6 minutes insonation with 0.7 ml of microbubbles administered as an intravenous bolus. An alternate dose at half the primary intensity, sonication time, and contrast concentration was evaluated in 11 rats to assess the efficacy of a reduced dose. A control group (n = 6) received a sham therapy. Tumor perfusion was measured before and after AVUS with nonlinear contrast ultrasound (NLC) and power Doppler (PD). The quantitative perfusion measures included perfusion index (PI), peak enhancement (PE), time to peak (TTP), and perfusion area from NLC and PD scans. Total tumor area perfused during the scan was measured by a postprocessing algorithm called delta projection. Tumor histology was evaluated for signs of tissue injury and for vascular changes using CD31 immunohistochemistry. Results: DEN exposure induced autochthonous hepatocellular carcinoma lesions in all rats. Across all groups prior to therapy, there were no significant differences in the nonlinear contrast observations of peak enhancement and perfusion index. In the control group, there were no significant differences in any of the parameters after sham treatment. After the primary AVUS regimen, there were significant changes in all parameters (p ≤ 0.05) indicating substantial decreases in tumor perfusion. Peak enhancement in nonlinear contrast scans showed a 37.9% ± 10.1% decrease in tumor perfusion. Following reduced-dose AVUS, there were no significant changes in perfusion parameters, although there was a trend for the nonlinear contrast observations of peak enhancement and perfusion index to increase. Conclusion: This study translated low-intensity AVUS therapy into a realistic in vivo model of HCC and evaluated its effects on the tumor vasculature. The primary dose of AVUS tested resulted in significant vascular disruption and a corresponding reduction in tumor perfusion. A reduced dose of AVUS, on the other hand, was ineffective at disrupting perfusion but demonstrated the potential for enhancing tumor blood flow. Theranostic ultrasound, where acoustic energy and microbubbles are used to monitor the tumor neovasculature as well as disrupt the vasculature and treat lesions, could serve as a potent tool for delivering noninvasive, locoregional therapy for hepatocellular carcinoma.

A retrospective single-center study was performed to assess the performance of ultrasound image-based texture analysis in differentiating angiomyolipoma (AML) from renal cell carcinoma (RCC) on incidental hyperechoic renal lesions. Ultrasound reports of patients from 2012 to 2017 were queried, and those with a hyperechoic renal mass5 cm in diameter with further imaging characterization and/or pathological correlation were included. Quantitative texture analysis was performed using a model including 18 texture features. Univariate logistic regression was used to identify texture variables differing significantly between AML and RCC, and the performance of the model was measured using the area under the receiver operating characteristic (ROC) curve. One hundred thirty hyperechoic renal masses in 127 patients characterized as RCCs (25 [19%]) and AMLs (105 [81%]) were included. Size (odds ratio [OR] = 0.12, 95% confidence interval [CI]: 0.04-0.43, p0.001) and 4 of 18 texture features, including entropy (OR = 0.09, 95% CI: 0.01-0.81, p = 0.03), gray-level non-uniformity (OR = 0.12, 95% CI: 0.02-0.72, p = 0.02), long-run emphasis (OR = 0.49, 95% CI: 0.27-0.91, p = 0.02) and run-length non-uniformity (OR = 2.18, 95% CI: 1.14-4.16, p = 0.02) were able to differentiate AMLs from RCCs. The area under the ROC curve for the performance of the model, including texture features and size, was 0.945 (p0.001). Ultrasound image-based textural analysis enables differentiation of hyperechoic RCCs from AMLs with high accuracy, which improves further when combined with tumor size.

Background and objective Lung ultrasound is an inherently user‐dependent modality that could benefit from quantitative image analysis. In this pilot study we evaluate the use of computer‐based pleural line (p‐line) ultrasound features in comparison to traditional lung texture (TLT) features to test the hypothesis that p‐line thickening and irregularity are highly suggestive of coronavirus disease 2019 (COVID‐19) and can be used to improve the disease diagnosis on lung ultrasound. Methods Twenty lung ultrasound images, including normal and COVID‐19 cases, were used for quantitative analysis. P‐lines were detected by a semiautomated segmentation method. Seven quantitative features describing thickness, margin morphology, and echo intensity were extracted. TLT lines were outlined, and texture features based on run‐length and gray‐level co‐occurrence matrix were extracted. The diagnostic performance of the 2 feature sets was measured and compared using receiver operating characteristics curve analysis. Observer agreements were evaluated by measuring interclass correlation coefficients (ICC) for each feature. Results Six of 7 p‐line features showed a significant difference between normal and COVID‐19 cases. Thickness of p‐lines was larger in COVID‐19 cases (6.27 ± 1.45 mm) compared to normal (1.00 ± 0.19 mm), P

Hepatocellular carcinoma (HCC) is a highly vascular solid tumor. We have previously shown that ultrasound (US) therapy significantly reduces tumor vascularity. This study monitors US-induced changes in tumor oxygenation on murine HCC by photoacoustic imaging (PAI). Oxygen saturation and total hemoglobin were assessed by PAI before and after US treatments performed at different intensities of continuous wave (CW) bursts and pulsed wave (PW) bursts US. PAI revealed significant reduction both in HCC oxygen saturation and in total hemoglobin, proportional to the US intensity. Both CW bursts US (1.6 W/cm2) and the PW bursts US (0.8 W/cm2) significantly reduced HCC oxygen saturation and total hemoglobin which continued to diminish with time following the US treatment. The effects of US therapy were confirmed by power Doppler and histological examination of the hemorrhage in tumors. By each measure, the changes observed in US-treated HCC were more prevalent than those in sham-treated tumors and were statistically significant. In conclusion, the results show that US is an effective vascular-targeting therapy for HCC. The changes in oxygenation induced by the US treatment can be noninvasively monitored longitudinally by PAI without the use of exogenous image-enhancing agents. The combined use of PAI and the therapeutic US has potential for image-guided vascular therapy for HCC.

The response of hepatocellular carcinoma (HCC) to anti-vascular ultrasound therapy (AVUS) can be affected by the inherent differences in tumor vascular structure, and the functionality of tumor vessels at the time of treatment. In this study, we evaluate the hypothesis that repeated subsequent AVUS therapies are a possible approach to overcome these factors and improve the therapeutic efficacy of AVUS. HCC was induced in 30 Wistar rats by oral ingestion of diethylnitrosamine (DEN) for 12 weeks. A total of 24 rats received treatment with low intensity, 2.8 MHz ultrasound with an intravenous injection of microbubbles. Treated rats were divided into three groups: single therapy group (ST), 2-days subsequent therapy group (2DST), and 7-days subsequent therapy group (7DST). A sham control group did not receive ultrasound therapy. Tumor perfusion was measured by quantitative contrast-enhanced ultrasound (CEUS) nonlinear and power-Doppler imaging. Tumors were harvested for histologic evaluation of ultrasound-induced vascular changes. ANOVA was used to compare the percent change of perfusion parameters between the four treatment arms. HCC tumors treated with 2DST showed the largest reduction in tumor perfusion, with 75.3% reduction on average for all perfusion parameters. The ST group showed an average decrease in perfusion of 54.3%. The difference between the two groups was significant p &lt, 0.001. The 7DST group showed a reduction in tumor perfusion of 45.3%, which was significant compared to the 2DST group (p &lt, 0.001) but not different from the ST group (p = 0.2). The use of subsequent targeted AVUS therapies applied shortly (two days) after the first treatment enhanced the anti-vascular effect of ultrasound. This gain, however, was lost for a longer interval (1 week) between the therapies, possibly due to tumor necrosis and loss of tumor viability. These findings suggest that complex interplay between neovascularization and tumor viability plays a critical role in treatment and, therefore, must be actively monitored following treatment by CEUS for optimizing sequential treatment.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation therapy require increased tumor perfusion for a better response. In this study we investigate the hypothesis that different dose models of antivascular ultrasound therapy (AVUS) can have opposite effects on hepatocellular carcinoma (HCC) tumor blood flow. HCC was induced in 22 Wistar rats by ingestion of diethylnitrosamine (DEN) for 12 weeks. Rats received AVUS treatment at low and high doses. Low dose group received 1 watt/cm(2) ultrasound for 1 min with 0.2 mL microbubbles injected IV. High dose group received 2 watts/cm(2) for 2 min with 0.7 mL microbubbles IV. A sham group did not receive any treatment. Tumor perfusion was measured before and after AVUS with contrast-enhanced ultrasound. Quantitative perfusion measures: perfusion index (PI) and peak enhancement (PE) were obtained from each AVUS dose. After high-dose AVUS, PE and PI decreased by an average of 58.1 ± 4.9% and 49.1 ± 6.5 % respectively. Conversely, following low dose AVUS, PE and PI increased from baseline by an average of 47.8 ± 4.5% % and 20.3 ± 2.4 %, respectively. The high-dose AVUS therapy decreased tumoral perfusion, an effect that could be used for noninvasive ischemic therapy. Conversely, low-dose therapy increased tumor perfusion, which may improve drug delivery or radiation therapy. These opposite therapy effects can support multiple roles for AVUS in cancer therapy by tunable modulation of blood flow in tumors.

A novel coronavirus (2019-nCoV) was identified as the cause of a cluster of pneumonia in Wuhan, China at the end of 2019. Since then more than four million confirmed cases of coronavirus disease 2019 (COVID-19) have been reported around the globe. The current gold standard for etiological diagnosis is reverse transcription polymerase chain reaction (rRT-PCR) analysis of respiratory tract specimens, but the test has a high false-negative rate due to both nasopharyngeal swab sampling error and viral burden. Hence diagnostic imaging has emerged as a fundamental component of current management of COVID-19 patients. Currently, high-resolution computed tomography (CT) is the main imaging tool for primary diagnosis and evaluation of disease severity in patients. Lung ultrasound (LUS) imaging has become a safe bedside imaging alternative that does no expose the patient to radiation, and minimizes the risk of contamination. Although the number of studies to date are limited, LUS findings have demonstrated high diagnostic sensitivity and accuracy, comparable to those of chest CT scans. In this article we review the current state of art of LUS in evaluating pulmonary changes induced by COVID-19. The goal is to identify characteristic sonographic findings most suited for the diagnosis of COVID-19 pneumonia infections.

Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, and limited options for therapy. The goal of this study is to evaluate the potential of machine learning with quantitative ultrasound image features for the diagnosis of TN breast cancer. Ultrasonic and clinical data of 140 surgically confirmed breast cancer cases were analyzed retrospectively for the diagnosis of TN and non-TN (NTN) subtypes. The subtypes were classified based on the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Ultrasound image features were measured from the grayscale and color Doppler images and used with logistic regression for classification by machine learning. Leave-one-out cross validation was used to train and test the differentiation. Diagnostic performance was measured by the area under receiver operating characteristic (ROC) curve, and sensitivity and specificity determined at the Youdons index. Of the twelve grayscale and Doppler features measured, eight were found to be statistically different for the TN and NTN subtypes (p

The purpose of this study was to assess the feasibility of acoustic radiation force impulse shear wave velocity and textural features for characterizing abdominal wall musculature and to identify subject-related and technique-related factors that can potentially affect measurements. Median shear wave velocity measurements for the right external abdominal oblique were the same (1.89 ± 0.16 m/s) for both the active group (healthy volunteers with active lifestyles) and the control group (age and body mass index-matched volunteers from an ongoing hernia study). When corrected for thickness, the ratio of right external abdominal oblique shear wave velocity -to-muscle thickness was significantly higher in the control group than in the active volunteers (4.33 s-1 versus 2.88 s-1; p value 0.006). From the textural features studied for right external abdominal oblique, 8 features were found to be statistically different between the active and control groups. In conclusion, shear wave velocity is a feasible and reliable technique to evaluate the stiffness of the abdominal wall musculature. Sonographic texture features add additional characterization of abdominal wall musculature.

OBJECTIVES/GOALS: The detection of liver fibrotic changes at an early and reversible stage is essential to prevent its progression to end-stage cirrhosis and hepatocellular carcinoma. Liver biopsy, which is the current gold standard for fibrosis assessment, is accompanied by several complications due to its invasive nature in addition to sampling errors and reader variability. In this study, we evaluate the use of quantitative parameters extracted from hybrid ultrasound and photoacoustic imaging to detect and monitor fibrotic changes in a DEN rat model. METHODS/STUDY POPULATION: Liver fibrotic changes were induced in 34 Wistar male rats by oral administration of Diethylnitrosamine (DEN) for 12 weeks. 22 rats were imaged with B-mode ultrasound at 3 different time points (baseline, 10 weeks and 13 weeks) for monitoring liver texture changes. Texture features studied included tissue echointensity (liver brightness normalized to kidney brightness) and tissue heterogeneity. 12 rats were imaged with photoacoustic imaging at 4 time points (baseline, 5 wks, 10 wks, and 13 wks) to look at changes in tissue oxygenation. Hemoglobin oxygen saturation (sO2A) and hemoglobin concentration (HbT) in the right and left lobes of the liver were measured. 8 rats were used as controls. Liver tissue samples were obtained following 13 weeks from DEN start time for METAVIR histopathology staging of fibrosis. RESULTS/ANTICIPATED RESULTS: Texture features studied showed an increase with time in DEN rats. Normalized echointensity increased from 0.28 ± 0.06 at baseline to 0.46 ± 0.10 at 10 weeks (p < 0.0005) and 0.53 ± 0.15 at 13 weeks in DEN rats (p < 0.0005). In the control rats, echointensity remained at an average of 0.25 ± 0.05 (p = 0.31). Tissue heterogeneity increased over time in the DEN-exposed rats from a baseline of 208.7 ± 58.3 to 344.6 ± 52.9 at 10 weeks (p < 0.0005) and 376.8 ± 54.9 at 13 weeks (p = 0.06) however it stayed constant at 225.7 ± 37.6 in control rats (p = 0.58). The quantitative analyses of the photoacoustic signals showed that blood oxygen saturation significantly increased with time. At 5 weeks sO2AvT increased by 53.83 % (± 0.25), and HbT by 35.31 % (± 0.07). Following 10 weeks of DEN; sO2AvT by 92.04 % (± 0.29), and HbT by 55.24 % (± 0.1). All increases were significant p < 0.05. In the 13th week, however, the values of all of these parameters were lower than those in the 10th week, however, the decrease was statistically insignificant. DISCUSSION/SIGNIFICANCE OF IMPACT: Quantitative features from B-mode ultrasound and photoacoustic imaging consistently increased over time corresponding to hepatic damage, inflammation and fibrosis progressed. The use of this hybrid imaging method in clinical practice can help meet the significant need for noninvasive assessment of liver fibrosis.

Low-intensity ultrasound (US) with microbubbles (uB) has been shown to disrupt the tumor neovasculature. The purpose of this study was to investigate the treatment effects of antivascular ultrasound (AVUS) in a realistic autochthonous rat model of hepatocellular carcinoma (HCC) using multimodal contrast-enhanced ultrasound imaging. HCC was induced in rats via by ingestion of diethylnitrosamine and treated with low intensity ultrasound in the presence of microbubbles. Tumor perfusion was assessed by linear-contrast, nonlinear-contrast and power Doppler ultrasound imaging before and after AVUS treatment. The tumor area perfused and hemodynamic characteristics were measured from time-dilution curves of the contrast agent. Histology of the treated samples was assessed for hemorrhage and necrosis induced by vascular disruption.All modes of contrast-enhanced imaging showed reduction in tumor vascularity following AVUS treatment. Perfusion area peak-enhancement and perfusion index were attenuated by 17% to 54% and the reduction in each measure was significant (p

Hepatic fibrosis and cirrhosis are a growing global health problem with increasing mortality rates. Early diagnosis and staging of hepatic fibrosis represent a major challenge. Currently liver biopsy is the gold standard for fibrosis assessment; however, biopsy requires an invasive procedure and is prone to sampling error and reader variability. In the current study we investigate using quantitative analysis of computer-extracted features of B-mode ultrasound as a non-invasive tool to characterize hepatic fibrosis. Twenty-two rats were administered diethylnitrosamine (DEN) orally for 12 weeks to induce hepatic fibrosis. Four control rats did not receive DEN. B-mode ultrasound scans sampling throughout the liver were acquired at baseline, 10, and 13 weeks. Computer extracted quantitative parameters representing brightness (echointensity, hepatorenal index) and variance (heterogeneity, anisotropy) of the liver were studied. DEN rats showed an increase in echointensity from 37.1 ± SD 7.8 to 53.5 ± 5.7 (10 w) to 57.5 ± 6.1 (13 w), while the control group remained unchanged at an average of 34.5 ± 4.5. The three other features studied increased similarly over time in the DEN group. Histologic analysis showed METAVIR fibrosis grades of F2-F4 in DEN rats and F0-F1 in controls. Increasing imaging parameters correlated with increasing METAVIR grades, and anisotropy showed the strongest correlation (ρ = 0.58). Sonographic parameters combined using multiparametric logistic regression were able to differentiate between clinically significant and insignificant fibrosis. Quantitative B-mode ultrasound imaging can be implemented in clinical settings as an accurate non-invasive tool for fibrosis assessment.

Background Widespread devastation to structures and households in Mosul occurred during the three years of ISIS control and the military liberation campaign by Iraqi forces assisted by coalition forces. Military operations, particularly airstrikes, resulted in a greater loss of life than during ISIS control. In 2016/17, we assessed living circumstances in Mosul immediately following defeat of ISIS. In September 2018, we reassessed many of the same indicators in Mosul households to determine the extent of recovery. Methods For the 2018 survey, a random selection of 20 clusters were drawn from the 40 clusters surveyed in 2016/17. Of these 20 clusters, 12 were in east Mosul and 8 in west Mosul, the same proportion as the original survey. In each cluster, 30 households were interviewed. No households were included in both surveys. A team of four interviewers collected information using questions adapted from the 2016/17 questionnaire. Results Among the 3375 persons from the 600 households in the 2018 survey, there had been 18 deaths reported in the year since the end of ISIS control, a mortality rate of 6.1/1000 (CI95% [2.4–9.8]). This compares with a mortality rate of 30.7/1000 (CI95% [28.3–33.2]) during ISIS control and liberation. Fifteen deaths were from disease, one from a non-intentional injury and two deaths due to intentional violence. Damage to dwellings had been fully repaired in only 22 (5.5%) of houses, mostly in less damaged east Mosul. Dramatic improvements in access to water and electricity have occurred, with three quarters of households reporting uninterrupted access to both. The previously reported large number of early marriages among household members stopped with the departure of ISIS. Of the 31 household marriages reported over a 12-month follow on study, 6 (19.4%) involved a female member of the household. This compares with 131 household males and 688 household females married during ISIS occupation. If marriages had continued at the same rate as for ISIS years during our one-year follow-on study, there would have been and expected 24 marriages of household males and 126 marriages of household females (OD 32.8, CI95%[10.5102.8]) p < 0.001. There were 657 children reported by households to be in primary school. However, by household listing there were only 380 of children in the usual primary school age range (6–11), suggesting older children are catching up on primary schooling missed during ISIS years. One report of physical violence between spouses occurred. By comparison, the adjusted number of reported violent spousal events during ISIS control and military action would have been 72.7 (OR 316.7, CI95% [44.42259.9]), p < 0.001. Reported complications of pregnancy also declined (OR 10.3, CI95% [5.4,19.4], p Conclusions Substantial improvements in household measures have occurred since the end of ISIS control and military action, though much remains for full recovery. Many household members are now employed, primary school attendance is high and early marriage of girls was not found. There are fewer reported complications of pregnancy than in the previous study.

Objective Impairment of flow-mediated dilation of the brachial artery is a marker of endothelial dysfunction and often predisposes atherosclerosis and cardiovascular events. In this study, we propose a user-guided automated approach for monitoring arterial cross-section during hyperemic response to improve reproducibility and sensitivity of flow-mediated dilation. Material and methods Ultrasound imaging of the brachial artery was performed in 11 volunteers in cross-sectional and in 5 volunteers in longitudinal view. During each examination, images were recorded continuously before and after inducing ischemia. Time-dilation curves of the brachial lumen cross-section were measured by user-guided automated segmentation of brachial images with the feed-forward active contour (FFAC) algorithm. %FMD was determined by the ratio of peak dilation to the baseline value. Each measurement was repeated twice in two sessions 1 h apart on the same arm to evaluate the reproducibility of the measurements. The intra-subject variation in flow-mediated dilation between two sessions (subject-specific) and inter-group variation in flow-mediated dilation with all the subjects within a session grouped together (group-specific) were measured for FFAC. The FFAC measurements were compared with the conventional diameter measurements made using echo tracking in longitudinal views. Results Flow-mediated dilation values for cross-sectional area were greater than those measured by diameter dilation: 33.1% for cross-sectional area compared to 22.5% for diameter. Group-specific flow-mediated dilation measurements for cross-sectional area were highly reproducible: 33.2% vs. 33.0% ( p > 0.05) with coefficient of variation CV of 0.4%. The group-specific flow-mediated dilations measured by echo tracking for the two sessions were 21.1 vs. 23.9% with CV of 9%. Subject-specific CV for cross-sectional area by FFAC was 10% ± 2% versus 24% ± 10% for the conventional approach. Using correlation as a metric of evaluation also showed better performance for cross-sectional imaging: correlation coefficient, R, between two sessions for cross-sectional area was 0.92 versus 0.72 for the conventional approach based on diameter measurements. Conclusion Peak dilation area measured by continuous automated monitoring of cross-sectional area of the brachial artery provides more reproducible and higher-sensitivity measurement of flow-mediated dilation compared to the conventional approach of using vascular diameter measured using longitudinal imaging.

Purpose The objectives of our study were to assess the accuracy of hepatorenal index (HRI) in detection and grading of hepatic steatosis and to evaluate various factors that can affect the HRI measurement. Methods Forty-five patients, who had undergone an abdominal sonographic examination within 30 days of liver biopsy, were enrolled. The HRI was calculated as the ratio of the mean brightness levels of the liver and renal parenchymas. The effect of the measurement technique on the HRI was evaluated by using various sizes, depths, and locations of the regions of interest (ROIs) in the liver. The measurements were obtained by two observers. The HRI was compared with the subjective grading of steatosis. Results The optimal HRI cutoff to detect steatosis was 2.01, yielding a sensitivity of 62.5% and specificity of 95.2%. Subjective grading had a sensitivity of 87.5% and specificity of 62.5%. HRIs of the hepatic steatosis group were statistically different from the no-steatosis group (p

Chronic liver inflammation progressively evokes fibrosis and cirrhosis resulting in compromised liver function, and often leading to cancer. Early diagnosis and staging of fibrosis is crucial because the five-year survival rate of early-stage liver cancer is high. This study investigates the progression of hepatic fibrosis induced in rats following ingestion of diethylnitrosamine (DEN). Changes in oxygen saturation and hemoglobin concentration resulting from chronic inflammation were assayed longitudinally during DEN ingestion by photoacoustic imaging (PAI). Accompanying liver tissue changes were monitored simultaneously by B-mode sonographic imaging. Oxygen saturation and hemoglobin levels in the liver increased over 5 weeks and peaked at 10 weeks before decreasing at 13 weeks of DEN ingestion. The oxygenation changes were accompanied by an increase in hepatic echogenicity and coarseness in the ultrasound image. Histology at 13 weeks confirmed the development of severe fibrosis and cirrhosis. The observed increase in PA signal representing enhanced blood oxygenation is likely an inflammatory physiological response to the dietary DEN insult that increases blood flow by the development of neovasculature to supply oxygen to a fibrotic liver during the progression of hepatic fibrosis. Assessment of oxygenation by PAI may play an important role in the future assessment of hepatic fibrosis.

Our objective was to assess the role of quantitative Doppler vascularity in differentiating malignant and benign thyroid nodules. Color Doppler images of 100 nodules were analyzed for three metrics: vascular fraction area, mean flow velocity index and flow volume index in three regions (nodule center, nodule rim and surrounding parenchyma). Vascular fraction area and flow volume index were higher in malignant than benign nodules in both the central and rim regions, whereas flow velocity index was equivalent in both regions. Of the three vascularity metrics studied, the vascular fraction area of the central region was most effective in predicting malignancy, with a sensitivity of 0.90 ± 0.05, specificity of 0.88 ± 0.13, positive predictive value of 0.84 ± 0.14, negative predictive value of 0.92 ± 0.03 and accuracy of 0.89 ± 0.08. Quantitative Doppler vascularity of the nodule center yielded a high level of discrimination between benign and malignant nodules and, thus, has the greatest potential to contribute to gray-scale assessment of thyroid cancer.

Purpose To assess the diagnostic performance of a leak-plugging segmentation method that we have developed for delineating breast masses on ultrasound images. Materials and methods Fifty-two biopsy-proven breast lesion images were analyzed by three observers using the leak-plugging and manual segmentation methods. From each segmentation method, grayscale and morphological features were extracted and classified as malignant or benign by logistic regression analysis. The performance of leak-plugging and manual segmentations was compared by: size of the lesion, overlap area ( Oa) between the margins, and area under the ROC curves ( Az). Results The lesion size from leak-plugging segmentation correlated closely with that from manual tracing ( R2 of 0.91). Oa was higher for leak plugging, 0.92 ± 0.01 and 0.86 ± 0.06 for benign and malignant masses, respectively, compared to 0.80 ± 0.04 and 0.73 ± 0.02 for manual tracings. Overall Oa between leak-plugging and manual segmentations was 0.79 ± 0.14 for benign and 0.73 ± 0.14 for malignant lesions. Az for leak plugging was consistently higher (0.910 ± 0.003) compared to 0.888 ± 0.012 for manual tracings. The coefficient of variation of Az between three observers was 0.29% for leak plugging compared to 1.3% for manual tracings. Conclusion The diagnostic performance, size measurements, and observer variability for automated leak-plugging segmentations were either comparable to or better than those of manual tracings.

OBJECTIVES/SPECIFIC AIMS: Preliminary animal studies showed that low-intensity ultrasound (US) coincident with intravascularly administered microbubbles locally disrupts tumor vasculature. This study translates the novel therapy of antivascular ultrasound (AVUS) into an autochthonous model of hepatocellular carcinoma (HCC). The differential effects produced by AVUS at low and high doses are evaluated. METHODS/STUDY POPULATION: HCC was induced in 12 Wistar rats by ingestion of 0.01% diethylnitrosamine in drinking water for 12 weeks. Rats received AVUS treatment at low and high doses. Low dose group (n=6) received 1 W/cm2 US for 1 minute with 0.2 mL microbubbles injected IV. High dose group (n=6) received 2 W/cm2 for 2 minute with 0.7 mL microbubbles IV. Perfusion was measured before and after AVUS with contrast-enhanced ultrasound (CE-US) and power Doppler (PD-US). Peak enhancement (PE) and perfusion index (PI) were measured from each US mode. Histology after sacrifice or natural death was compared to pre/post US. Analysis of H&E and trichrome sections was evaluated for percent area of hemorrhage and findings of tissue injury and repair including inflammation, necrosis, and fibrosis. RESULTS/ANTICIPATED RESULTS: After high dose AVUS, PE, and PI of CE-US decreased from baseline by an average of 33.3% and 29.7%, respectively. Histology showed extensive tissue injury (hemorrhage, necrosis, fibrosis) in 58% of tumor cross-sectional area. Conversely, low dose AVUS increased PE and PI of CE-US by an average of 39.3% and 67.8%, respectively. Histology showed smaller areas of microhemorrhage Versus large pools of hemorrhage (only 17% area). PD-US changes were similar to CE-US. DISCUSSION/SIGNIFICANCE OF IMPACT: In summary, the opposing effects of AVUS observed at 2 doses allows for multiple roles in tumor therapy. Enhanced perfusion at a low dose may improve drug delivery or radiation therapy. Whereas, vascular disruption at high doses of AVUS may allow noninvasive ischemic therapy. Furthermore, AVUS is ripe for translation given the use its component parts clinically: low-intensity long-tone burst for physiotherapy and microbubbles as an US contrast agent. Thus, AVUS should be evaluated for translation of its differential effects into noninvasive therapies for HCC and other tumors.

A retrospective study was performed to evaluate the diagnostic value of tumor-to-cortex echogenicity ratio (TCER) in the characterization of hyper-echoic renal masses. The radiology database was queried between 2012 and 2014 for hyper-echoic renal masses on the basis of defined exclusion and inclusion criteria. Each included mass was characterized as either an angiomyolipoma (AML) or a non-AML based on pre-defined criteria. The ratio of renal mass echogenicity to that of adjacent renal cortex (TCER) was calculated for each mass using commercially available software. A total of 70 masses in 65 patients were identified, including 49 AMLs. TCER values >2.26 were associated with a sensitivity and specificity of 81.6% and 71.4%, respectively, for diagnosis of AML. Moreover, TCER values >3.98 resulted in 100% specificity for AML diagnosis with a sensitivity of 28.6%. These findings suggest that the TCER may be a valuable tool for the characterization of hyper-echoic renal masses.

The object of this study was to utilize a novel feed-forward active contour (FFAC) algorithm to find a reproducible technique for analysis of brachial artery reactivity. Flow-mediated dilation (FMD) is an important marker of vascular endothelial function but has not been adopted for widespread clinical use given its technical limitations, including inter-observer variability and differences in technique across clinical sites. We developed a novel FFAC algorithm with the goal of validating a more reliable standard. Forty-six healthy volunteers underwent FMD measurement according to the standard technique. Ultrasound videos lasting 5–10 seconds each were obtained pre-cuff inflation and at minutes 1 through 5 post-cuff deflation in longitudinal and transverse views. Automated segmentation using the FFAC algorithm with initial boundary definition from three different observers was used to analyze the images to measure diameter/cross-sectional area over the cardiac cycle. The %FMD was calculated for average, minimum, and maximum diameters/areas. Using the FFAC algorithm, the population-specific coefficient of variation (CV) at end-diastole was 3.24% for transverse compared to 9.96% for longitudinal measurements; the subject-specific CV was 15.03% compared to 57.41%, respectively. For longitudinal measurements made via the conventional method, the population-specific CV was 4.77% and subject-specific CV was 117.79%. The intraclass correlation coefficient (ICC) for transverse measurements was 0.97 (95% CI: 0.95–0.98) compared to 0.90 (95% CI: 0.84–0.94) for longitudinal measurements with FFAC and 0.72 (95% CI: 0.51–0.84) for conventional measurements. In conclusion, transverse views using the novel FFAC method provide less inter-observer variability than traditional longitudinal views. Improved reproducibility may allow adoption of FMD testing in a clinical setting. The FFAC algorithm is a robust technique that should be evaluated further for its ability to replace the more limited conventional technique for measurement of FMD.

The objectives of our study were to assess the accuracy of hepatorenal index (HRI) in detection and grading of hepatic steatosis and to evaluate various factors that can affect the HRI measurement.Forty-five patients, who had undergone an abdominal sonographic examination within 30 days of liver biopsy, were enrolled. The HRI was calculated as the ratio of the mean brightness levels of the liver and renal parenchymas. The effect of the measurement technique on the HRI was evaluated by using various sizes, depths, and locations of the regions of interest (ROIs) in the liver. The measurements were obtained by two observers. The HRI was compared with the subjective grading of steatosis.The optimal HRI cutoff to detect steatosis was 2.01, yielding a sensitivity of 62.5% and specificity of 95.2%. Subjective grading had a sensitivity of 87.5% and specificity of 62.5%. HRIs of the hepatic steatosis group were statistically different from the no-steatosis group (p 0.05). However, there was no statistically significant difference between mild steatosis and no-steatosis groups (p value = 0.72). There was a strong correlation between different HRIs based on variable placements of ROIs, except when the ROIs were positioned randomly. Interclass correlation coefficient for measurements performed by two observers was 0.74 (confidence interval: 0.58-0.86).The HRI is an effective tool for detecting hepatic steatosis. It provides similar accuracy for different methods of ROI placement (except for random placement) and has good interobserver agreement. It, however, is unable to effectively differentiate between absent and mild steatosis. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 44:580-586, 2016.

The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound.

Objectives The purpose of this study was to develop a quantitative approach for combining individual American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) sonographic features of breast masses for assessing the overall probability of malignancy. Methods Sonograms of solid breast masses were analyzed by 2 observers blinded to patient age, mammographic features, and lesion pathologic findings. BI-RADS sonographic features were determined by using American College of Radiology criteria. A naive Bayes model was used to determine the probability of malignancy of all the sonographic features together and with age and BI-RADS mammographic features. The diagnostic performance for various combinations was evaluated by using the area under the receiver operating curve (Az). Results Sonographic features had high positive and negative predictive values. The Az values for BI-RADS sonographic features for the 2 observers ranged from 0.772 to 0.884, which increased to 0.866 to 0.924 when used with patient age and BI-RADS mammographic features. The benefit of adding age and mammographic information was more marked for the observer with lower initial diagnostic performance. Age-specific analysis showed that diagnostic performance varied with age, with higher performance for patients aged 45 years and younger and patients older than 60 years compared to those aged 46 to 60 years. In 85% of cases, the diagnosis of the observers matched. When the consensus between the observers was used for diagnostic decisions, a high level of diagnostic performance (Az, 0.954) was achieved. Conclusions A naive Bayes model provides a systematic approach for combining sonographic features and other patient characteristics for assessing the probability of malignancy to differentiate malignant and benign breast masses.

To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view.Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle.FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure.FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depthmore » by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.« less

Purpose: The overall goal of this study is to develop a computer‐based image analysis system for breast ultrasound that may aid physicians in differentiating benign and malignant masses with higher confidence and thus help in reducing unnecessary biopsies. Towards this goal we describe an approach that combines two independent probabilistic classifiers to improve diagnosis of breast masses. Methods: B‐scan images of 266 patients with biopsy proven breast masses were analyzed for margin grayscale and shape features. These features were used with two statistical methods, logistic regression and naive Bayes, to classify the lesions as malignant and benign. The diagnostic performance of the ultrasound image features was evaluated by using them alone and by combining them with mammographic BI‐RADS categories and patient age. The probability predictions of the two classifiers were compared to assess consensus between them. The performances of the classifiers were evaluated using area under the curve (AUC) of the ROC Receiver Operating Characteristic. Training and testing were performed using leave‐one‐out validation. Results: The results showed that combined features outperformed the individual features. Logistic regression performed slightly better than naive Bayes (AUC: 0.902 ± 0.023 vs. 0.865 ± 0.027, p < 0.03). The agreement between the two models at different decision thresholds was stable at ∼88 %. The reaming 12% were treated as the cases that needed further diagnostic investigation. Treating each algorithm as an independent observer and using the consensus between the two models as the criterion for mass differentiation demonstrated a reduction in biopsy by 48% could be achieved at the cost of missed malignancies in 2% cases. Conclusion: Computer‐based image analysis of breast ultrasound images can aid the differentiation of benign and malignant masses and help in improving biopsy yields. NIH grant R01 CA130946