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

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

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%

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

Issues with threshold masking in voxel-based morphometry of atrophied brains

There is great interest in using automatic computational neuroanatomy tools to study ageing and neurodegenerative disease. Voxel-Based Morphometry (VBM) is one of the most widely used of such techniques. VBM performs voxel-wise statistical analysis of smoothed spatially normalised segmented Magnetic Resonance Images. There are several reasons why the analysis should include only voxels within a certain mask. We show that one of the most commonly used strategies for defining this mask runs a major risk of excluding from the analysis precisely those voxels where the subjects’ brains were most vulnerable to atrophy. We investigate the issues related to mask construction, and recommend the use of alternative strategies which greatly decrease this danger of false negatives