Lack of centrioles and primary cilia in STIL(-/-) mouse embryos.

Although most animal cells contain centrosomes, consisting of a pair of centrioles, their precise contribution to cell division and embryonic development is unclear. Genetic ablation of STIL, an essential component of the centriole replication machinery in mammalian cells, causes embryonic lethality in mice around mid gestation associated with defective Hedgehog signaling. Here, we describe, by focused ion beam scanning electron microscopy, that STIL(-/-) mouse embryos do not contain centrioles or primary cilia, suggesting that these organelles are not essential for mammalian development until mid gestation. We further show that the lack of primary cilia explains the absence of Hedgehog signaling in STIL(-/-) cells. Exogenous re-expression of STIL or STIL microcephaly mutants compatible with human survival, induced non-templated, de novo generation of centrioles in STIL(-/-) cells. Thus, while the abscence of centrioles is compatible with mammalian gastrulation, lack of centrioles and primary cilia impairs Hedgehog signaling and further embryonic development.

Validation of anthropometric indices of adiposity against whole-body magnetic resonance imaging--a study within the German European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts.

BACKGROUND: In epidemiological studies, measures of body fat generally are obtained through anthropometric indices such as the body mass index (BMI), waist (WC), and hip circumferences (HC). Such indices, however, can only provide estimates of a person's true body fat content, overall or by adipose compartment, and may have limited accuracy, especially for the visceral adipose compartment (VAT). OBJECTIVE: To determine the extent to which different body adipose tissue compartments are adequately predicted by anthropometry, and to identify anthropometric measures alone, or in combination to predict overall adiposity and specific adipose tissue compartments, independently of age and body size (height). METHODS: In a sub-study of 1,192 participants of the German EPIC (European Prospective Investigation into Cancer and Nutrition) cohorts, whole-body MRI was performed to determine adipose and muscle tissue compartments. Additional anthropometric measurements of BMI, WC and HC were taken. RESULTS: After adjusting for age and height, BMI, WC and HC were better predictors of total body volume (TBV), total adipose tissue (TAT) and subcutaneous adipose tissue (SAT) than for VAT, coronary adipose tissue (CAT) and skeletal muscle tissue (SMT). In both sexes, BMI was the best predictor for TBV (men: r = 0.72 [0.68-0.76], women: r = 0.80 [0.77-0.83]) and SMT (men: r = 0.52 [0.45-0.57], women: r = 0.48 [0.41-0.54]). WC was the best predictor variable for TAT (r = 0.48 [0.41-0.54]), VAT (r = 0.44 [0.37-0.50]) and CAT (r = 0.34 [0.26-0.41]) (men), and for VAT (r = 0.42 [0.35-0.49]) and CAT (r = 0.29 [0.22-0.37]) (women). BMI was the best predictor for TAT (r = 0.49 [0.43-0.55]) (women). HC was the best predictor for SAT (men (r = 0.39 [0.32-0.45]) and women (r = 0.52 [0.46-0.58])). CONCLUSIONS: Especially the volumes of internal body fat compartments are poorly predicted by anthropometry. A possible implication may be that associations of chronic disease risks with the sizes of internal body fat as measured by BMI, WC and HC may be strongly underestimated.

Regular three-dimensional presentations improve in the identification of surgical liver anatomy - a randomized study.

BACKGROUND: Three-dimensional (3D) presentations enhance the understanding of complex anatomical structures. However, it has been shown that two dimensional (2D) "key views" of anatomical structures may suffice in order to improve spatial understanding. The impact of real 3D images (3Dr) visible only with 3D glasses has not been examined yet. Contrary to 3Dr, regular 3D images apply techniques such as shadows and different grades of transparency to create the impression of 3D.This randomized study aimed to define the impact of both the addition of key views to CT images (2D+) and the use of 3Dr on the identification of liver anatomy in comparison with regular 3D presentations (3D). METHODS: A computer-based teaching module (TM) was used. Medical students were randomized to three groups (2D+ or 3Dr or 3D) and asked to answer 11 anatomical questions and 4 evaluative questions. Both 3D groups had animated models of the human liver available to them which could be moved in all directions. RESULTS: 156 medical students (57.7% female) participated in this randomized trial. Students exposed to 3Dr and 3D performed significantly better than those exposed to 2D+ (p < 0.01, ANOVA). There were no significant differences between 3D and 3Dr and no significant gender differences (p > 0.1, t-test). Students randomized to 3D and 3Dr not only had significantly better results, but they also were significantly faster in answering the 11 anatomical questions when compared to students randomized to 2D+ (p < 0.03, ANOVA). Whether or not "key views" were used had no significant impact on the number of correct answers (p > 0.3, t-test). CONCLUSION: This randomized trial confirms that regular 3D visualization improve the identification of liver anatomy.

The Medical Imaging Interaction Toolkit: challenges and advances : 10 years of open-source development.

PURPOSE: The Medical Imaging Interaction Toolkit (MITK) has been available as open-source software for almost 10 years now. In this period the requirements of software systems in the medical image processing domain have become increasingly complex. The aim of this paper is to show how MITK evolved into a software system that is able to cover all steps of a clinical workflow including data retrieval, image analysis, diagnosis, treatment planning, intervention support, and treatment control. METHODS: MITK provides modularization and extensibility on different levels. In addition to the original toolkit, a module system, micro services for small, system-wide features, a service-oriented architecture based on the Open Services Gateway initiative (OSGi) standard, and an extensible and configurable application framework allow MITK to be used, extended and deployed as needed. A refined software process was implemented to deliver high-quality software, ease the fulfillment of regulatory requirements, and enable teamwork in mixed-competence teams. RESULTS: MITK has been applied by a worldwide community and integrated into a variety of solutions, either at the toolkit level or as an application framework with custom extensions. The MITK Workbench has been released as a highly extensible and customizable end-user application. Optional support for tool tracking, image-guided therapy, diffusion imaging as well as various external packages (e.g. CTK, DCMTK, OpenCV, SOFA, Python) is available. MITK has also been used in several FDA/CE-certified applications, which demonstrates the high-quality software and rigorous development process. CONCLUSIONS: MITK provides a versatile platform with a high degree of modularization and interoperability and is well suited to meet the challenging tasks of today's and tomorrow's clinically motivated research.

Automatic quantification of subcutaneous and visceral adipose tissue from whole-body magnetic resonance images suitable for large cohort studies.

PURPOSE: To develop an automated method with which to distinguish metabolically different adipose tissues in a large number of subjects using whole-body magnetic resonance imaging (MRI) datasets for improving the understanding of chronic disease risk predictions associated with distinct adipose tissue compartments. MATERIALS AND METHODS: In all, 314 participants were scanned using a 1.5T MRI-scanner with a 2-point Dixon whole-body sequence. Image segmentation was automated using standard image processing techniques and knowledge-based methods. Abdominal adipose tissue was separated into subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) by statistical shape models. Bone marrow was removed to provide a more accurate measurement of adipose tissue. To assess segmentation accuracy, ground-truth segmentations in 52 images were performed manually by one operator. Due to the high effort of manual delineation, manual segmentation was limited to seven slices per volume. RESULTS: Volumetric differences were 3.30 ± 2.97% and 6.22 ± 5.28% for SAT and VAT, respectively. The systematic error shows an overestimation of 4.22 ± 7.01% for VAT and 0.37 ± 4.45% for SAT. Coefficients-of-variation from repeated measurements were: 3.50 ± 2.93% for VAT and 0.35 ± 0.26% for SAT. The approach of removing bone marrow worked well in most body regions. Only occasionally the method failed for knees and/or shinbone, which resulted in an overestimation of SAT by 3.14 ± 1.45%. CONCLUSION: We developed a fully automatic process to assess SAT and VAT in whole-body MRI data. The method can support epidemiological studies investigating the relationship between excess body fat and chronic diseases.