Identifying gaps in disease knowledge among patients with peripheral artery disease.

OBJECTIVE: An individual's understanding of disease risk factors and outcomes is important for the ability to make healthy lifestyle choices and decisions about disease treatment. Peripheral artery disease (PAD) is a condition with increasing global prevalence and high risk of adverse patient outcomes. This study seeks to understand the adequacy of disease understanding in patients with PAD. METHODS: This was an observational study of patients with PAD recruited from vascular surgery outpatient clinic and PAD clinical studies at a single academic medical center over an 8-month period. A 44-item paper survey assessed demographic and socioeconomic information, knowledge of personal medical history, PAD risk factors, consequences of PAD, and health education preferences. Patients with documented presence of PAD were offered the survey. Patients unable to complete the survey or provide informed consent were not considered eligible. Disease "awareness" was defined as correct acknowledgement of the presence or absence of a disease, including PAD, in the personal medical history. "PAD knowledge score" was the percentage of correct responses to questions on general PAD risk factors and consequences. Of 126 eligible patients, 109 participated. Bivariate analysis was used to study factors associated with awareness of PAD diagnosis. Factors associated with the PAD knowledge score were studied using the Pearson correlation coefficient, two-sample t test, or one-way analysis of variance. P value < .05 was considered statistically significant. RESULTS: The mean participant age was 69.4 ± 11.0 years, and 39.4% (n = 43) were female. Most participants (78.9%; n = 86) had critical limb-threatening ischemia. Only 65.4% (n = 70) of participants were aware of a diagnosis of PAD, which was less than their awareness of related comorbidities. Factors positively associated with PAD diagnosis awareness were female sex (81.4% vs 54.7%; P = .004) and history of percutaneous leg revascularization (78.6% vs 47.9%; P = .001). Among 17 patients who had undergone major leg amputation, 35% (n = 6) were unaware of a diagnosis of PAD. PAD knowledge scores correlated positively with an awareness of PAD diagnosis (59.1% vs 48.7%; P = .02) and negatively with a history of hypertension (53.4% vs 68.1%; P = .001). Most participants (86.5%; n = 90) expressed a desire to be further educated on PAD. The most popular education topics were dietary recommendations, causes, and treatment for PAD. CONCLUSIONS: Patients with PAD have deficits in their awareness of this diagnosis and general knowledge about PAD. Future research priorities should further define these deficits and their causes in order to inform new strategies that foster information-seeking behavior and effective educational programs for PAD.

Inflammatory Cell Dynamics after Murine Femoral Artery Wire Injury: A Multi-Parameter Flow Cytometry-Based Analysis.

An acute inflammatory response following arterial surgery for atherosclerosis, such as balloon angioplasty, stenting, and surgical bypass, is an important driver of neointimal hyperplasia after arterial injury, which leads to recurrent ischemia. However, a comprehensive understanding of the dynamics of the inflammatory infiltrate in the remodeling artery is difficult to attain due to the shortcomings of conventional methods such as immunofluorescence. We developed a 15-parameter flow cytometry method to quantitate leukocytes and 13 leukocyte subtypes in murine arteries at 4 time points after femoral artery wire injury. Live leukocyte numbers peaked at 7 days, which preceded the peak neointimal hyperplasia lesion at 28 days. Neutrophils were the most abundant early infiltrate, followed by monocytes and macrophages. Eosinophils were elevated after 1 day, while natural killer and dendritic cells gradually infiltrated over the first 7 days; all decreased between 7 and 14 days. Lymphocytes began accumulating at 3 days and peaked at 7 days. Immunofluorescence of arterial sections demonstrated similar temporal trends of CD45+ and F4/80+ cells. This method allows for the simultaneous quantitation of multiple leukocyte subtypes from small tissue samples of injured murine arteries and identifies the CD64+Tim4+ macrophage phenotype as being potentially important in the first 7 days post-injury.

Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CT.

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D convolution using population training information of contrast-enhanced liver, spleen and kidneys was applied to multiphase data to initialize the 4D graph and adapt to patient-specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance, enhancement, shape and location on organ segmentation. All four abdominal organs were segmented robustly and accurately with volume overlaps over 93.6% and average surface distances below 1.1mm.

Tumor burden analysis on computed tomography by automated liver and tumor segmentation.

The paper presents the automated computation of hepatic tumor burden from abdominal computed tomography (CT) images of diseased populations with images with inconsistent enhancement. The automated segmentation of livers is addressed first. A novel 3-D affine invariant shape parameterization is employed to compare local shape across organs. By generating a regular sampling of the organ's surface, this parameterization can be effectively used to compare features of a set of closed 3-D surfaces point-to-point, while avoiding common problems with the parameterization of concave surfaces. From an initial segmentation of the livers, the areas of atypical local shape are determined using training sets. A geodesic active contour corrects locally the segmentations of the livers in abnormal images. Graph cuts segment the hepatic tumors using shape and enhancement constraints. Liver segmentation errors are reduced significantly and all tumors are detected. Finally, support vector machines and feature selection are employed to reduce the number of false tumor detections. The tumor detection true position fraction of 100% is achieved at 2.3 false positives/case and the tumor burden is estimated with 0.9% error. Results from the test data demonstrate the method's robustness to analyze livers from difficult clinical cases to allow the temporal monitoring of patients with hepatic cancer.