Influence of Smoothing on Voxel-Based Mesh Accuracy in Micro-Finite Element

The interest in automatic volume meshing for finite element analysis (FEA) has grown more since the appearance of microfocus CT (μCT), due to its high resolution, which allows for the assessment of mechanical behaviour at a high precision. Nevertheless, the basic meshing approach of generating one hexahedron per voxel produces jagged edges. To prevent this effect, smoothing algorithms have been introduced to enhance the topology of the mesh. However, whether smoothing also improves the accuracy of voxel-based meshes in clinical applications is still under question. There is a trade-off between smoothing and quality of elements in the mesh. Distorted elements may be produced by excessive smoothing and reduce accuracy of the mesh. In the present work, influence of smoothing on the accuracy of voxel-based meshes in micro-FE was assessed. An accurate 3D model of a trabecular structure with known apparent mechanical properties was used as a reference model. Virtual CT scans of this reference model (with resolutions of 16, 32 and 64 μm) were then created and used to build voxel-based meshes of the microarchitecture. Effects of smoothing on the apparent mechanical properties of the voxel-based meshes as compared to the reference model were evaluated. Apparent Young’s moduli of the smooth voxel-based mesh were significantly closer to those of the reference model for the 16 and 32 μm resolutions. Improvements were not significant for the 64 μm, due to loss of trabecular connectivity in the model. This study shows that smoothing offers a real benefit to voxel-based meshes used in micro-FE. It might also broaden voxel-based meshing to other biomechanical domains where it was not used previously due to lack of accuracy. As an example, this work will be used in the framework of the European project ContraCancrum, which aims at providing a patient-specific simulation of tumour development in brain and lungs for oncologists. For this type of clinical application, such a fast, automatic, and accurate generation of the mesh is of great benefit.

Grey-matter abnormalities in boys with Tourette syndrome: magnetic resonance imaging study using optimised voxel-based morphometry

The genesis of Tourette syndrome is still unknown, but a core role for the pathways of cortico-striatal-thalamic-cortical circuitry (CSTC) is supposed. Volume-rendering magnetic resonance imaging data-sets were analysed in 14 boys with Tourette syndrome and 15 age-matched controls using optimised voxel-based morphometry. Locally increased grey-matter volumes (corrected P < 0.001) were found bilaterally in the ventral putamen. Regional decreases in grey matter were observed in the left hippocampal gyrus. This unbiased analysis confirmed an association between striatal abnormalities and Tourette syndrome, and the hippocampal volume alterations indicate an involvement of temporolimbic pathways of the CSTC in the syndrome.

Comparison of voxel-based 3-D MRI analysis and subtraction ictal SPECT coregistered to MRI in focal epilepsy

While voxel-based 3-D MRI analysis methods as well as assessment of subtracted ictal versus interictal perfusion studies (SISCOM) have proven their potential in the detection of lesions in focal epilepsy, a combined approach has not yet been reported. The present study investigates if individual automated voxel-based 3-D MRI analyses combined with SISCOM studies contribute to an enhanced detection of mesiotemporal epileptogenic foci. Seven consecutive patients with refractory complex partial epilepsy were prospectively evaluated by SISCOM and voxel-based 3-D MRI analysis. The functional perfusion maps and voxel-based statistical maps were coregistered in 3-D space. In five patients with temporal lobe epilepsy (TLE), the area of ictal hyperperfusion and corresponding structural abnormalities detected by 3-D MRI analysis were identified within the same temporal lobe. In two patients, additional structural and functional abnormalities were detected beyond the mesial temporal lobe. Five patients with TLE underwent epileptic surgery with favourable postoperative outcome (Engel class Ia and Ib) after 3-5 years of follow-up, while two patients remained on conservative treatment. In summary, multimodal assessment of structural abnormalities by voxel-based analysis and SISCOM may contribute to advanced observer-independent preoperative assessment of seizure origin.

Prospective longitudinal voxel-based morphometry study of major depressive disorder in young individuals at high familial risk

BACKGROUND Previous neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development. METHOD Unaffected individuals (16-25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls ('low risk', n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures. RESULTS Significant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline. CONCLUSIONS These longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.