Clinical validation of an automated vessel-segmentation software of the extracranial-carotid arteries based on 3D-MRA: A prospective study

OBJECTIVES: To determine the accuracy of automated vessel-segmentation software for vessel-diameter measurements based on three-dimensional contrast-enhanced magnetic resonance angiography (3D-MRA). METHOD: In 10 patients with high-grade carotid stenosis, automated measurements of both carotid arteries were obtained with 3D-MRA by two independent investigators and compared with manual measurements obtained by digital subtraction angiography (DSA) and 2D maximum-intensity projection (2D-MIP) based on MRA and duplex ultrasonography (US). In 42 patients undergoing carotid endarterectomy (CEA), intraoperative measurements (IOP) were compared with postoperative 3D-MRA and US. RESULTS: Mean interoperator variability was 8% for measurements by DSA and 11% by 2D-MIP, but there was no interoperator variability with the automated 3D-MRA analysis. Good correlations were found between DSA (standard of reference), manual 2D-MIP (rP=0.6) and automated 3D-MRA (rP=0.8). Excellent correlations were found between IOP, 3D-MRA (rP=0.93) and US (rP=0.83). CONCLUSION: Automated 3D-MRA-based vessel segmentation and quantification result in accurate measurements of extracerebral-vessel dimensions.

Semi-automatic segmentation of fetal cardiac cavities: progress towards an automated fetal echocardiogram

OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.

Lifestyle factors and colorectal cancer risk (1): systematic review and meta-analysis of associations with body mass index

OBJECTIVE: Excess body weight, defined by body mass index (BMI), may increase the risk of colorectal cancer. As a prerequisite to the determination of lifestyle attributable risks, we undertook a systematic review and meta-analysis of prospective observational studies to quantify colorectal cancer risk associated with increased BMI and explore for differences by gender, sub-site and study characteristics. METHOD: We searched MEDLINE and EMBASE (to December 2007), and other sources, selecting reports based on strict inclusion criteria. Random-effects meta-analyses and meta-regressions of study-specific incremental estimates were performed to determine the risk ratio (RR) and 95% confidence intervals (CIs) associated with a 5 kg/m(2) increase in BMI. RESULTS: We analysed 29 datasets from 28 articles, including 67,361 incident cases. Higher BMI was associated with colon (RR 1.24, 95% CIs: 1.20-1.28) and rectal (1.09, 1.05-1.14) cancers in men, and with colon cancer (1.09, 1.04-1.12) in women. Associations were stronger in men than in women for colon (P < 0.001) and rectal (P = 0.005) cancers. Associations were generally consistent across geographic populations. Study characteristics and adjustments accounted for only moderate variations of associations. CONCLUSION: Increasing BMI is associated with a modest increased risk of developing colon and rectal cancers, but this modest risk may translate to large attributable proportions in high-prevalence obese populations. Inter-gender differences point to potentially important mechanistic differences, which merit further research.

The lifestyle of our kids (LOOK) project: outline of methods

This methods paper outlines the overall design of a community-based multidisciplinary longitudinal study with the intent to stimulate interest and communication from scientists and practitioners studying the role of physical activity in preventive medicine. In adults, lack of regular exercise is a major risk factor in the development of chronic degenerative diseases and is a major contributor to obesity, and now we have evidence that many of our children are not sufficiently active to prevent early symptoms of chronic disease. The lifestyle of our kids (LOOK) study investigates how early physical activity contributes to health and development, utilizing a longitudinal design and a cohort of eight hundred and thirty 7-8-year-old (grade 2) school children followed to age 11-12 years (grade 6), their average family income being very close to that of Australia. We will test two hypotheses, that (a) the quantity and quality of physical activity undertaken by primary school children will influence their psychological and physical health and development; (b) compared with existing practices in primary schools, a physical education program administered by visiting specialists will enhance health and development, and lead to a more positive perception of physical activity. To test the first hypothesis we will monitor all children longitudinally over the 4 years. To test the second we will involve an intervention group of 430 children who receive two 50min physical education classes every week from visiting specialists and a control group of 400 who continue with their usual primary school physical education with their class-room teachers. At the end of grades 2, 4, and 6 we will measure several areas of health and development including blood risk factors for chronic disease, cardiovascular structure and function, physical fitness, psychological characteristics and perceptions of physical activity, bone structure and strength, motor control, body composition, nutritional intake, influence of teachers and family, and academic performance.

Lifestyle and stroke risk: a review

PURPOSE OF REVIEW: In recent years, many epidemiological studies have given new insights into old and new lifestyle factors that influence the risk of cerebrovascular events. In this review, we refer to the most important articles to highlight recent advances, especially those important for stroke prevention. RECENT FINDINGS: This review focuses on the most recent studies that show the association of environmental factors, nutrition, alcohol, tobacco, education, lifestyle and behavior with the risk of vascular disease, including ischemic stroke and cerebral hemorrhage. The link between air pollution and stroke risk has become evident. Low education levels and depression are established as risk factors. This is also true for heavy alcohol consumption, although moderate drinking may be protective. Active and passive smoking are independent risk factors, and a smoking ban in public places has already reduced cardiovascular events in the short term. Physical activity reduces stroke risk; overweight increases it. However, clinical trials to assess the effect of weight reduction on stroke risk are still lacking. Fruits, vegetables, fish, fibers, low-fat dairy products, potassium and low sodium consumption are known and recommended to reduce cardiovascular risk. Data on omega 3 fatty acid, folic acid and B vitamins are inconsistent, and antioxidants are not recommended. SUMMARY: Stroke can be substantially reduced by an active lifestyle, cessation of smoking and a healthy diet. Both public and professional education should promote the awareness that a healthy lifestyle and nutrition have the potential to reduce the burden of stroke.

Space–oriented EEG segmentation reveals changes in brain electric–field maps under the influence of a nootropic drug

Map landscape-based segmentation of the sequences of momentary potential distribution maps (42-channel recordings) into brain microstates during spontaneous brain activity was used to study brain electric field spatial effects of single doses of piracetam (2.9, 4.8, and 9.6 g Nootropil® UCB and placebo) in a double-blind study of five normal young volunteers. Four 15-second epochs were analyzed from each subject and drug condition. The most prominent class of microstates (covering 49% of the time) consisted of potential maps with a generally anterior-posterior field orientation. The map orientation of this microstate class showed an increasing clockwise deviation from the placebo condition with increasing drug doses (Fisher's probability product, p < 0.014). The results of this study suggest the use of microstate segmentation analysis for the assessment of central effects of medication in spontaneous multichannel electroencephalographic data, as a complementary approach to frequency-domain analysis.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Fully automatic X-ray image segmentation via joint estimation of image displacements.

We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.

Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.