A comparison of Voxel compression mapping & longitudinal Voxel-Based morphometry

Clinical motivation: Serial brain imaging can reveal patterns of change over time with important clinical implications for neurodegenerative disease [1]. We investigate the performance of four analysis methods, in terms of a comparison of 20 patients with probable AD to 20 age- and sex-matched controls, characterising differences in change from baseline to later scans

ZnO microtubes

Microtubes of ZnO have been produced using sputter coating and a fugitive phase technique. ZnO was sputtered onto polyester fibers by dc magnetron sputtering, and the polyester fiber fugitive phase was subsequently burned out by annealing in air or oxygen. Tubes with an inside diameter of 23 μm and a length of 3 cm were obtained. The 3 to 6 μm thick walls of the tubes exhibited a [002] radial textur

Ten simple rules for reporting voxel-based morphometry studies

Voxel-based morphometry [Ashburner, J. and Friston, K.J., 2000. Voxel-based morphometry—the methods. NeuroImage 11(6 Pt 1), 805–821] is a commonly used tool for studying patterns of brain change in development or disease and neuroanatomical correlates of subject characteristics. In performing a VBM study, many methodological options are available; if the study is to be easily interpretable and repeatable, the processing steps and decisions must be clearly described. Similarly, unusual methods and parameter choices should be justified in order to aid readers in judging the importance of such options or in comparing the work with other studies. This editorial suggests core principles that should be followed and information that should be included when reporting a VBM study in order to make it transparent, replicable and useful

Diffeomorphic demons using normalized mutual information, evaluation on multimodal brain MR images

The demons algorithm is a fast non-parametric non-rigid registration method. In recent years great efforts have been made to improve the approach; the state of the art version yields symmetric inverse-consistent largedeformation diffeomorphisms. However, only limited work has explored inter-modal similarity metrics, with no practical evaluation on multi-modality data. We present a diffeomorphic demons implementation using the analytical gradient of Normalised Mutual Information (NMI) in a conjugate gradient optimiser. We report the first qualitative and quantitative assessment of the demons for inter-modal registration. Experiments to spatially normalise real MR images, and to recover simulated deformation fields, demonstrate (i) similar accuracy from NMI-demons and classical demons when the latter may be used, and (ii) similar accuracy for NMI-demons on T1w-T1w and T1w-T2w registration, demonstrating its potential in multi-modal scenarios

Longitudinal multivariate tensor- and searchlight-based morphometry using permutation testing

Tensor based morphometry [1] was used to detect statistically significant regions of neuroanatomical change over time in a comparison between 36 probable Alzheimer's Disease patients and 20 age- and sexmatched controls. Baseline and twelve-month repeat Magnetic Resonance images underwent tied spatial normalisation [10] and longitudinal high-dimensional warps were then estimated. Analyses involved univariate and multivariate data derived from the longitudinal deformation fields. The most prominent findings were expansion of the fluid spaces, and contraction of the hippocampus and temporal region. Multivariate measures were notably more powerful, and have the potential to identify patterns of morphometric difference that would be overlooked by conventional mass-univariate analysis

Evaluation of local and global atrophy measurement techniques with simulated Alzheimer's disease data

The main goal of this work was to evaluate several well-known methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of atrophy in brain structures using Magnetic Resonance images. For that purpose, we have generated realistic simulated Alzheimer's disease images in which volume changes are modelled with a Finite Element thermoelastic model, which mimic the patterns of change obtained from a cohort of 19 real controls and 27 probable Alzheimer's disease patients. SIENA and BSI results correlate very well with gold standard data (BSI mean absolute error <0.29%; SIENA <0.44%). Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD registration technique provided more satisfactory results than the fluid one. Mean absolute error differences between volume changes given by the FFD-based technique and the gold standard were: sulcal CSF <2.49%; lateral ventricles 2.25%; brain <0.36%; hippocampi <0.42%

Longitudinal Voxel-based morphometry with unified segmentation: evaluation on simulated Alzheimer’s disease

The goal of this work is to evaluate Voxel-Based Morphometry and three longitudinally-tailored methods of VBM.We use a cohort of simulated images produced by deforming original scans using a Finite Element Method, guided to emulate Alzheimer-like changes. The simulated images provide quite realistic data with a known pattern of spatial atrophy, with which VBM’s findings can be meaningfully compared. We believe this is the first evaluation of VBM for which anatomically-plausible ‘gold-standard’ results are available. The three longitudinal VBM methods have been implemented within the unified segmentation framework of SPM5; one of the techniques is a newly developed procedure, which shows promising potential

Pt/Ti/SiO2/Si substrates

Pt/Ti/SiO2/Si structures have been studied to investigate the structural, chemical, and microstructural changes that occur during annealing. Grain growth of the as-deposited Pt columns was observed after annealing at 650 °C, and extensive changes in the Pt microstructure were apparent following a 750 °C anneal for 20 min. In addition, two types of defects were identified on the surfaces of annealed substrates. Defect formation was retarded when the surface was covered with a ferroelectric film. Concurrent with the annealing-induced Pt microstructure changes, Ti from the adhesion layer between the Pt and the SiO2 migrated into the Pt layer and oxidized. It was shown with spectroscopic ellipsometry and Auger electron spectroscopy that for long annealing times, the titanium oxide layer can reach the Pt surface. Consequently, at the processing temperatures utilized in preparing many ferroelectric thin films, the substrate is not completely inert or immobile. The changes associated with Ti migration could be especially problematic in techniques that require the substrate to be heated prior to film depositio

Phenomenological model of diffuse global and regional atrophy using finite-element methods

The main goal of this work is the generation of ground-truth data for the validation of atrophy measurement techniques, commonly used in the study of neurodegenerative diseases such as dementia. Several techniques have been used to measure atrophy in cross-sectional and longitudinal studies, but it is extremely difficult to compare their performance since they have been applied to different patient populations. Furthermore, assessment of performance based on phantom measurements or simple scaled images overestimates these techniques' ability to capture the complexity of neurodegeneration of the human brain. We propose a method for atrophy simulation in structural magnetic resonance (MR) images based on finite-element methods. The method produces cohorts of brain images with known change that is physically and clinically plausible, providing data for objective evaluation of atrophy measurement techniques. Atrophy is simulated in different tissue compartments or in different neuroanatomical structures with a phenomenological model. This model of diffuse global and regional atrophy is based on volumetric measurements such as the brain or the hippocampus, from patients with known disease and guided by clinical knowledge of the relative pathological involvement of regions and tissues. The consequent biomechanical readjustment of structures is modelled using conventional physics-based techniques based on biomechanical tissue properties and simulating plausible tissue deformations with finite-element methods. A thermoelastic model of tissue deformation is employed, controlling the rate of progression of atrophy by means of a set of thermal coefficients, each one corresponding to a different type of tissue. Tissue characterization is performed by means of the meshing of a labelled brain atlas, creating a reference volumetric mesh that will be introduced to a finite-element solver to create the simulated deformations. Preliminary work on the simulation of acquisition artefa- - cts is also presented. Cross-sectional and