Multiresolution spatiotemporal mechanical model of the heart as a prior to constrain the solution for 4D models of the heart.

In several nuclear cardiac imaging applications (SPECT and PET), images are formed by reconstructing tomographic data using an iterative reconstruction algorithm with corrections for physical factors involved in the imaging detection process and with corrections for cardiac and respiratory motion. The physical factors are modeled as coefficients in the matrix of a system of linear equations and include attenuation, scatter, and spatially varying geometric response. The solution to the tomographic problem involves solving the inverse of this system matrix. This requires the design of an iterative reconstruction algorithm with a statistical model that best fits the data acquisition. The most appropriate model is based on a Poisson distribution. Using Bayes Theorem, an iterative reconstruction algorithm is designed to determine the maximum a posteriori estimate of the reconstructed image with constraints that maximizes the Bayesian likelihood function for the Poisson statistical model. The a priori distribution is formulated as the joint entropy (JE) to measure the similarity between the gated cardiac PET image and the cardiac MRI cine image modeled as a FE mechanical model. The developed algorithm shows the potential of using a FE mechanical model of the heart derived from a cardiac MRI cine scan to constrain solutions of gated cardiac PET images

Assessment of the learning curve in health technologies: a systematic review

Objective: We reviewed and appraised the methods by which the issue of the learning curve has been addressed during health technology assessment in the past. Method: We performed a systematic review of papers in clinical databases (BIOSIS, CINAHL, Cochrane Library, EMBASE, HealthSTAR, MEDLINE, Science Citation Index, and Social Science Citation Index) using the search term "learning curve:" Results: The clinical search retrieved 4,571 abstracts for assessment, of which 559 (12%) published articles were eligible for review. Of these, 272 were judged to have formally assessed a learning curve. The procedures assessed were minimal access (51%), other surgical (41%), and diagnostic (8%). The majority of the studies were case series (95%). Some 47% of studies addressed only individual operator performance and 52% addressed institutional performance. The data were collected prospectively in 40%, retrospectively in 26%, and the method was unclear for 31%. The statistical methods used were simple graphs (44%), splitting the data chronologically and performing a t test or chi-squared test (60%), curve fitting (12%), and other model fitting (5%). Conclusions: Learning curves are rarely considered formally in health technology assessment. Where they are, the reporting of the studies and the statistical methods used are weak. As a minimum, reporting of learning should include the number and experience of the operators and a detailed description of data collection. Improved statistical methods would enhance the assessment of health technologies that require learning

Assessing the learning curve effect in health technologies: Lessons from the non-clinical literature

Introduction: Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment. It has been shown that the statistical methods used are relatively crude. Methods to describe learning curves in fields outside medicine, for example, psychology and engineering, may be better. Methods: To systematically search non–health technology assessment literature (for example, PsycLit and Econlit databases) to identify novel statistical techniques applied to learning curves. Results: The search retrieved 9,431 abstracts for assessment, of which 18 used a statistical technique for analyzing learning effects that had not previously been identified in the clinical literature. The newly identified methods were combined with those previously used in health technology assessment, and categorized into four groups of increasing complexity: a) exploratory data analysis; b) simple data analysis; c) complex data analysis; and d) generic methods. All the complex structured data techniques for analyzing learning effects were identified in the nonclinical literature, and these emphasized the importance of estimating intra- and interindividual learning effects. Conclusion: A good dividend of more sophisticated methods was obtained by searching in nonclinical fields. These methods now require formal testing on health technology data sets

Validation of the Beck Motivation Inventory in a Schizophrenia Sample

poster abstractObjectives: Low motivation is an obstacle to recovery for many individuals with schizophrenia, and assessing motivation remains challenging. The aim of this study was to examine the reliability and validity of a new measure of motivation, The Beck Motivation Inventory (BMI). The BMI is a 13-item measure created to assess self-reported behavior related to an individual’s ability to initiate and sustain task-related motivation, as opposed to relying on others to encourage task-related motivation. Methods: In a sample of 251 adult outpatients and inpatients with schizophrenia or schizoaffective disorder, the BMI was administered along with measures of social functioning and dependent and autonomy beliefs. A confirmatory factor analysis was conducted to test a two-factor model, which consisted of an inner- and other- directed motivation factor. The BMI’s internal consistency, test-retest reliability, and convergent and predictive validity were also assessed. Results: The BMI demonstrated acceptable internal consistency (α > .70) and adequate test-retest stability after six months (r > .5). Convergent validity was established with measures of dependent and autonomy beliefs, and predictive validity was demonstrated with a measure of social functioning. The two-factor model of the BMI was also supported. Conclusions: Results provide initial support for the validation of the BMI, suggesting that the BMI may be a useful and brief tool for evaluating behaviors linked to task-related motivation that may act as obstacles to recovery for individuals with schizophrenia

Beta3 integrin haplotype influences gene regulation and plasma von Willebrand factor activity

The Leu33Pro polymorphism of the gene encoding beta(3) integrin (ITGB3) is associated with acute coronary syndromes and influences platelet aggregation. Three common promoter polymorphisms have also been identified. The aims of this study were to (1) investigate the influence of the ITGB3 -400C/A, -425A/C and -468G/A promoter polymorphisms on reporter gene expression and nuclear protein binding and (2) determine genotype and haplotype associations with platelet alpha(IIb)beta(3) receptor density. Promoter haplotypes were introduced into an ITGB3 promoter-pGL3 construct by site directed mutagenesis and luciferase reporter gene expression analysed in HEL and HMEC-1 cells. Binding of nuclear proteins was assessed by electrophoretic mobility shift assay. The association of ITGB3 haplotype with platelet alpha(IIb)beta(3) receptor density was determined in 223 subjects. Species conserved motifs were identified in the ITGB3 promoter in the vicinity of the three polymorphisms. The GAA, GCC, AAC, AAA and ACC constructs induced approximately 50% increased luciferase expression relative to the GAC construct in both cell types. Haplotype analysis including Leu33Pro indicated five common haplotypes; no associations between ITGB3 haplotypes and receptor density were found. However, the GCC-Pro33 haplotype was associated with significantly higher vWF activity (128.6 [112.1-145.1]%) compared with all other haplotypes (107.1 [101.2-113.0]%, p=0.02). In conclusion, the GCC-Pro33 haplotype was associated with increased vWF activity but not with platelet alpha(IIb)beta(3) receptor density, which may indicate ITGB3 haplotype influences endothelial function

ALMA and Keck analysis of Fomalhaut field sources: JWST's Great Dust Cloud is a background object

At 7.7 pc, the A-type star Fomalhaut hosts a bright debris disk with multiple radial components. The disk is eccentric and misaligned, strongly suggesting that it is sculpted by interaction with one or more planets. Compact sources are now being detected with JWST, suggesting that new planet detections may be imminent. However, to confirm such sources as companions, common proper motion with the star must be established, as with unprecedented sensitivity comes a high probability that planet candidates are actually background objects. Here, ALMA and Keck observations of Fomalhaut are found to show significant emission at the same sky location as multiple compact sources in JWST MIRI coronagraphic observations, one of which has been dubbed the "Great Dust Cloud" because it lies within the outer belt. Since the ground-based data were obtained between 6 to 18 years prior to the JWST observations, these compact sources are unlikely to be common proper motion companions to Fomalhaut. More generally, this work illustrates that images collected at a range of wavelengths can be valuable for rejecting planet candidates uncovered via direct imaging with JWST.Comment: MNRAS in pres