COVARIATE-ADJUSTED NONPARAMETRIC ANALYSIS OF MAGNETIC RESONANCE IMAGES USING MARKOV CHAIN MONTE CARLO

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain that are difficult to capture parametrically. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our non-parametric method to remove potential bias due to the observed covariates is presented.

Virtopsy - the concept of a centralized database in forensic medicine for analysis and comparison of radiological and autopsy data

Recent developments in clinical radiology have resulted in additional developments in the field of forensic radiology. After implementation of cross-sectional radiology and optical surface documentation in forensic medicine, difficulties in the validation and analysis of the acquired data was experienced. To address this problem and for the comparison of autopsy and radiological data a centralized database with internet technology for forensic cases was created. The main goals of the database are (1) creation of a digital and standardized documentation tool for forensic-radiological and pathological findings; (2) establishing a basis for validation of forensic cross-sectional radiology as a non-invasive examination method in forensic medicine that means comparing and evaluating the radiological and autopsy data and analyzing the accuracy of such data; and (3) providing a conduit for continuing research and education in forensic medicine. Considering the infrequent availability of CT or MRI for forensic institutions and the heterogeneous nature of case material in forensic medicine an evaluation of benefits and limitations of cross-sectional imaging concerning certain forensic features by a single institution may be of limited value. A centralized database permitting international forensic and cross disciplinary collaborations may provide important support for forensic-radiological casework and research.

Selective immunisation strategy to protect newborns at risk for transmission of hepatitis B: retrospective audit of vaccine uptake

BACKGROUND: 90% of newborns infected perinatally will develop chronic hepatitis B infection with the risk of liver cirrhosis or hepatocellular carcinoma. In Switzerland, screening of all pregnant women for hepatitis B virus (HBV) has been recommended since 1983. Neonates at risk for perinatally acquired HBV are passively and actively immunised immediately after birth as well as at 1 and 6 months of age. The objective of this study was to evaluate the proportion of newborns immunised in accordance with the proposed vaccination schedule. METHODS: Patient records of 3997 mothers who gave birth to a liveborn infant during a two-year period at Zürich University Hospital were screened by computer. 128 women were identified as HBsAg positive or anti-HBc alone positive. Of 133 infants born to these mothers, complete data were available for 94 (71%). RESULTS: Immunisation was started in 88 infants (94%), but only in 78 (83%) within the first 24 hours of life. 85 (90%) received the 2nd immunisation but only 72 (77%) within the given time limit. 80 (85%) of the infants received the 3rd immunisation but only 69 (73%) within the correct time limit. In summary, only 51 (54%) of the infants at risk for HBV infection were immunised correctly (immunoglobulin within 24 hours and active prophylaxis at 0, 1 and 6 months). CONCLUSIONS: The success of the immunisation strategy following maternal screening and selective immunisation of newborns at risk for HBV infection is limited for various reasons (lack of screening results at birth, problems with correct documentation and communication). To overcome these drawbacks, selective vaccination strategy should be improved and general vaccination strategy, including infants, should be reconsidered.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

[Survival, clinical data and quality of life 10 years after heart transplantation: a prospective study]

AIM: To study prospectively patients after heart transplantation with respect to quality of life, mortality, morbidity, and clinical parameters before and up to 10 years after the operation. METHODS: Sixty patients (47.9 +/- 10.9 years, 57 men, 3 women) were transplanted at the University of Vienna Hospital, Department for Heart and Thorax Surgery and were included in this study. They were assessed when set on the waiting list, then exactly one, 5 and 10 years after the transplantation. The variables evaluated included physical and emotional complaints, well-being, mortality and morbidity. In the sample of patients who survived 10 years (n = 23), morbidity (infections, malignancies, graft arteriosclerosis, and rejection episodes) as well as quality of life were evaluated. RESULTS: Actuarial survival rates were 83.3, 66.7, 48.3% at 1, 5, and 10 years after transplantation, respectively. During the first year, infections were the most important reasons for premature death. As a cause of mortality, malignancies were found between years 1 and 5, and graft arteriosclerosis between years 5 and 10. Physical complaints diminished significantly after the operation, but grew significantly during the period from 5 to 10 years (p < 0.001). However, trembling (p < 0.05) and paraesthesies (p < 0.01) diminished continuously. Emotional complaints such as depression and dysphoria (both p < 0.05) increased until the tenth year after their nadir at year 1. In long-time survivors, 3 malignancies (lung, skin, thyroidea) were diagnosed 6 to 9 years postoperatively. Three patients (13%) had signs of graft arteriosclerosis at year 10; 9 (40%) patients suffered from rejection episodes during the course of 10 years. There were no serious rejection episodes deserving immediate therapy. Quality of life at 10 years is good in these patients. CONCLUSIONS: Heart transplantation is a successful therapy for patients with terminal heart disease. Long-term survivors feel well after 10 years and report a good quality of life.

Ultra-high-resolution dual-source CT for forensic dental visualization-discrimination of ceramic and composite fillings

Dental identification is the most valuable method to identify human remains in single cases with major postmortem alterations as well as in mass casualties because of its practicability and demanding reliability. Computed tomography (CT) has been investigated as a supportive tool for forensic identification and has proven to be valuable. It can also scan the dentition of a deceased within minutes. In the present study, we investigated currently used restorative materials using ultra-high-resolution dual-source CT and the extended CT scale for the purpose of a color-encoded, in scale, and artifact-free visualization in 3D volume rendering. In 122 human molars, 220 cavities with 2-, 3-, 4- and 5-mm diameter were prepared. With presently used filling materials (different composites, temporary filling materials, ceramic, and liner), these cavities were restored in six teeth for each material and cavity size (exception amalgam n = 1). The teeth were CT scanned and images reconstructed using an extended CT scale. Filling materials were analyzed in terms of resulting Hounsfield units (HU) and filling size representation within the images. Varying restorative materials showed distinctively differing radiopacities allowing for CT-data-based discrimination. Particularly, ceramic and composite fillings could be differentiated. The HU values were used to generate an updated volume-rendering preset for postmortem extended CT scale data of the dentition to easily visualize the position of restorations, the shape (in scale), and the material used which is color encoded in 3D. The results provide the scientific background for the application of 3D volume rendering to visualize the human dentition for forensic identification purposes.

Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine

BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.