Registration of clinical trials: Challenges for global regulation

In 2004 the International Committee of Medical Journal Editors (ICMJE) issued a statement indicating that from 1 July 2005 registration in a publicly accessible trials registry would be a condition of publication in an ICMJE member journal. The World Health Organisation is coordinating the International Clinical Trials Registry Platform (ICTRP) as a means of providing a standardised framework for registration. This article considers the practical challenges and opportunities that arise from these developments and considers the relevance of trial registration for women and minorities and for developing countries.

Motor Accident Insurance Act 1994 - whether vehicle in question a vehicle "for which registration is required"

In Gideona v Nominal Defendant [2005] QCA 261, the Queensland Court of Appeal reconsidered the question of what is the material time for determining whether registration of a motor vehicle is required. The Court declined to follow the decision in Kelly v Alford [1988] 1 Qd R 404; deciding that the material time was the time when the accident occurred.

Course experiences, satisfaction and career intent of final year pre-registration Australian pharmacy students

Background In Australia, the profession of pharmacy has undergone many changes to adapt to the needs of the community. In recent years, concerns have been raised with evidence emerging of workforce saturation in traditional pharmacy practice sectors. It is not known how current final year pharmacy students’ perceive the different pharmacy career paths in this changing environment. Hence investigating students’ current experiences with their pharmacy course, interaction with the profession and developing an understanding of their career intentions would be an important step, as these students would make up a large proportion of future pharmacy workforce Objective The objective of this study was thus to investigate final year students’ career perspectives and the reasons for choosing pharmacy, satisfaction with this choice of pharmacy as a tertiary course and a possible future career, factors affecting satisfaction and intention of future career paths. Methods A quantitative cross sectional survey of final year students from 3 Australian universities followed by a qualitative semi-structured interview of a convenience sample of final year students from the University of Sydney. Results ‘Interest in health and medicine’ was the most important reason for choosing pharmacy (n=238). The majority of students were ‘somewhat satisfied’ with the choice of pharmacy (35.7%) as a course and possible future career. Positive associations were found between satisfaction and reasons for joining pharmacy such as ‘felt pharmacy is a good profession’ (p=0.003) while negative associations included ‘joined pharmacy as a gateway to medicine or dentistry’ (p=0.001). Quantitate and qualitative results showed the most frequent perception of community pharmacy was ‘changing’ while hospital and pharmaceutical industry was described as ‘competitive’ and ‘research’ respectively. The highest career intention was community followed by hospital pharmacy. Conclusion Complex factors including university experiences are involved in shaping students’ satisfaction and perception of career. This may relate to challenges in the community pharmacy sector, job opportunities in hospital and limited understanding of the pharmaceutical industry. The results offer insight for the profession in terms of entry into various roles and also to pharmacy educators for their roles in shaping curricula and placement experiences that attract future graduates to defined career pathways in pharmacy.

Assessment of cone beam CT registration for prostate radiation therapy : fiducial marker and soft tissue methods

Introduction This investigation aimed to assess the consistency and accuracy of radiation therapists (RTs) performing cone beam computed tomography (CBCT) alignment to fiducial markers (FMs) (CBCTFM) and the soft tissue prostate (CBCTST). Methods Six patients receiving prostate radiation therapy underwent daily CBCTs. Manual alignment of CBCTFM and CBCTST was performed by three RTs. Inter-observer agreement was assessed using a modified Bland–Altman analysis for each alignment method. Clinically acceptable 95% limits of agreement with the mean (LoAmean) were defined as ±2.0 mm for CBCTFM and ±3.0 mm for CBCTST. Differences between CBCTST alignment and the observer-averaged CBCTFM (AvCBCTFM) alignment were analysed. Clinically acceptable 95% LoA were defined as ±3.0 mm for the comparison of CBCTST and AvCBCTFM. Results CBCTFM and CBCTST alignments were performed for 185 images. The CBCTFM 95% LoAmean were within ±2.0 mm in all planes. CBCTST 95% LoAmean were within ±3.0 mm in all planes. Comparison of CBCTST with AvCBCTFM resulted in 95% LoA of −4.9 to 2.6, −1.6 to 2.5 and −4.7 to 1.9 mm in the superior–inferior, left–right and anterior–posterior planes, respectively. Conclusions Significant differences were found between soft tissue alignment and the predicted FM position. FMs are useful in reducing inter-observer variability compared with soft tissue alignment. Consideration needs to be given to margin design when using soft tissue matching due to increased inter-observer variability. This study highlights some of the complexities of soft tissue guidance for prostate radiation therapy.

Paternal postnatal depressive symptoms, infant sleeping and feeding behaviors, and rigid parental regulation : a correlational study

Paternal postnatal depression (PND) is now recognized as a serious and prevalent problem, associated with poorer well-being and functioning of all family members. Aspects of infant temperament, sleeping and feeding perceived by parents as problematic are associated with maternal PND, however, less is known about paternal PND. This study investigated depressive symptoms (Edinburgh postnatal depression scale (EPDS)) in 219 fathers of infants aged from 1 to 24 weeks (median 7.0 weeks). Infant predictor variables were sleeping problems, feeding problems and both mother and father reported temperament. Control variables were partner’s support, other support and life events. Rigidity of parenting beliefs regarding infant regulation was also measured as a potential moderating factor. Infant feeding difficulties were associated with paternal depressive symptoms, subsuming the variance associated with both sleep problems and temperament. This relationship was not moderated by regulation beliefs. It was concluded that infant feeding is important to fathers. Fathers of infants with feeding difficulties may not be able to fulfill their idealized construction of involved fatherhood. Role incongruence may have an etiological role in paternal PND.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

Cone location and correction of keratoconus with rigid gas-permeable contact lenses

Purpose To evaluate the influence of cone location and corneal cylinder on RGP corrected visual acuities and residual astigmatism in patients with keratoconus. Methods In this prospective study, 156 eyes from 134 patients were enrolled. Complete ophthalmologic examination including manifest refraction, Best spectacle visual acuity (BSCVA), slit-lamp biomicroscopy was performed and corneal topography analysis was done. According to the cone location on the topographic map, the patients were divided into central and paracentral cone groups. Trial RGP lenses were selected based on the flat Sim K readings and a ‘three-point touch’ fitting approach was used. Over contact lens refraction was performed, residual astigmatism (RA) was measured and best-corrected RGP visual acuities (RGPVA) were recorded. Results The mean age (±SD) was 22.1 ± 5.3 years. 76 eyes (48.6%) had central and 80 eyes (51.4%) had paracentral cone. Prior to RGP lenses fitting mean (±SD) subjective refraction spherical equivalent (SRSE), subjective refraction astigmatism (SRAST) and BSCVA (logMAR) were −5.04 ± 2.27 D, −3.51 ± 1.68 D and 0.34 ± 0.14, respectively. There were statistically significant differences between central and paracentral cone groups in mean values of SRSE, SRAST, flat meridian (Sim K1), steep meridian (Sim K2), mean K and corneal cylinder (p-values < 0.05). Comparison of BSCVA to RGPVA shows that vision has improved 0.3 logMAR by RGP lenses (p < 0.0001). Mean (±SD) RA was −0.72 ± 0.39 D. There were no statistically significant differences between RGPVAs and RAs of central and paracentral cone groups (p = 0.22) and (p = 0.42), respectively. Pearson's correlation analysis shows that there is a statistically significant relationship between corneal cylinder and BSCVA and RGPVA, However, the relationship between corneal cylinder and residual astigmatism was not significant. Conclusions Cone location has no effect on the RGP corrected visual acuities and residual astigmatism in patients with keratoconus. Corneal cylinder and Sim K values influence RGP-corrected visual acuities but do not influence residual astigmatism.

A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Statistically assisted fluid registration algorithm - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.

A lagrangian formulation for statistical fluid registration

We defined a new statistical fluid registration method with Lagrangian mechanics. Although several authors have suggested that empirical statistics on brain variation should be incorporated into the registration problem, few algorithms have included this information and instead use regularizers that guarantee diffeomorphic mappings. Here we combine the advantages of a large-deformation fluid matching approach with empirical statistics on population variability in anatomy. We reformulated the Riemannian fluid algorithmdeveloped in [4], and used a Lagrangian framework to incorporate 0 th and 1st order statistics in the regularization process. 92 2D midline corpus callosum traces from a twin MRI database were fluidly registered using the non-statistical version of the algorithm (algorithm 0), giving initial vector fields and deformation tensors. Covariance matrices were computed for both distributions and incorporated either separately (algorithm 1 and algorithm 2) or together (algorithm 3) in the registration. We computed heritability maps and two vector and tensorbased distances to compare the power and the robustness of the algorithms.

A nonconservative Lagrangian framework for statistical fluid registration - SAFIRA

In this paper, we used a nonconservative Lagrangian mechanics approach to formulate a new statistical algorithm for fluid registration of 3-D brain images. This algorithm is named SAFIRA, acronym for statistically-assisted fluid image registration algorithm. A nonstatistical version of this algorithm was implemented, where the deformation was regularized by penalizing deviations from a zero rate of strain. In, the terms regularizing the deformation included the covariance of the deformation matrices Σ and the vector fields (q). Here, we used a Lagrangian framework to reformulate this algorithm, showing that the regularizing terms essentially allow nonconservative work to occur during the flow. Given 3-D brain images from a group of subjects, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the nonstatistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the nonconservative terms, creating four versions of SAFIRA. We evaluated and compared our algorithms' performance on 92 3-D brain scans from healthy monozygotic and dizygotic twins; 2-D validations are also shown for corpus callosum shapes delineated at midline in the same subjects. After preliminary tests to demonstrate each method, we compared their detection power using tensor-based morphometry (TBM), a technique to analyze local volumetric differences in brain structure. We compared the accuracy of each algorithm variant using various statistical metrics derived from the images and deformation fields. All these tests were also run with a traditional fluid method, which has been quite widely used in TBM studies. The versions incorporating vector-based empirical statistics on brain variation were consistently more accurate than their counterparts, when used for automated volumetric quantification in new brain images. This suggests the advantages of this approach for large-scale neuroimaging studies.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.