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Background: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images. Aim: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI. Method: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1-C2; C2/3) on SC and brain images and the entire cervical cord (C1-C7) on SC images only. Results: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1-C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p >_ 0.006 at the C1-C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings. Conclusion: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.

\(\bf Background:\) Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images. \(\bf Aim:\) To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI. \(\bf Method:\) One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1–C2; C2/3) on SC and brain images and the entire cervical cord (C1–C7) on SC images only. \(\bf Results:\) CSA estimates were significantly smaller using SCT compared to NQL and ASM (\(\it p\) < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1–C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1–C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings. \(\bf Conclusion:\) For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.

Background Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.

Highlights • Thalamus atrophy is associated with cognitive impairment in multiple sclerosis. • This was confirmed by automated and manual segmentations, but effect sizes varied. • The algorithms work in a multi-center setting. • Automated techniques exhibit proportional bias with respect to thalamus size. • Differences between vendors can affect the robustness of these associations., Background and rationale Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values

\(\bf Background:\) In early multiple sclerosis (MS), thalamus atrophy and decreased integrity of the thalamocortical white matter (WM) tracts have been observed. \(\bf Objective:\) To investigate the temporal association between thalamus volume and WM damage in the thalamocortical tract in subjects with early MS. \(\bf Methods:\) At two time points, 72 subjects with early MS underwent T1, FLAIR and diffusion tensor imaging. Thalamocortical tracts were identified with probabilistic tractography using left and right thalamus as seed regions. Regression analysis was performed to identify predictors of annual percentage change in both thalamus volumes and integrity of the connected tracts. \(\bf Results:\) Significant atrophy was seen in left and right thalamus (\(\it p\) < 0.001) over the follow-up period (13.7 \(\pm\) 4.8 months), whereas fractional anisotropy (FA) and mean diffusivity (MD) changes of the left and right thalamus tracts were not significant, although large inter-subject variability was seen. Annual percentage change in left thalamus volume was significantly predicted by baseline FA of the left thalamus tracts (\(\it F\)(1.71) = 4.284, (\(\it p\) = 0.042; while no such relation was found for the right thalamus. Annual percentage change in FA or MD of the thalamus tracts was not predicted by thalamus volume or any of the demographic parameters. \(\bf Conclusion:\) Over a short follow-up time, thalamus atrophy could be predicted by decreased integrity of the thalamic tracts, but changes in the integrity of the thalamic tracts could not be predicted by thalamus volume. This is the first study showing directionality in the association between thalamus atrophy and connected WM tract damage. These results need to be verified over longer follow-up periods.

Simulation of endoscopic navigation in the narrow nasal cavity poses important challenges to the computation of adequate and near-realistic collision response and haptic feedback because extensive multidirectional contact and massive tissue deformations are inevitable. We present a virtual coupling algorithm that provides stable collision response as well as intuitive and smooth haptic interaction in all phases of the simulation. In each iteration, continuous collision detection between the point shell representing the surface of the virtual patient anatomy and the endoscope, represented by a cylinder, is performed. This allows for rolling back the instrument movement to the point in time the first collision occurred. Subsequently, a relaxation process locally optimizes the position and orientation of the instrument. A novel method of applying contact forces to colliding tissues and thus triggering appropriate deformations improves the fluency of navigation. This paper describes the algorithm and presents experimental results.

Symposium on Computer Simulation in Medicine(CompMed), Boucherville, Quebec, May 16-18, 2007

The 15th Annual Medicine Meets Virtual Reality Conference, Long Beach, California, February 6-9, 2007

The 15th Annual Medicine Meets Virtual Reality Conference, Long Beach, California, February 06-09, 2007

The objective of this research was to determine whether low performance haptic hardware leads to the same surgical task performance compared to more expensive hardware in a virtual reality surgical simulator for laparoscopy. VR surgical simulators are currently being introduced in leading teaching hospitals around the world. While they provide great potential for improvement over current laparoscopic skills training methods, a major barrier to large-scale acceptance is their high cost. Therefore this study is performed to determine whether a reduction in quality and therefore cost can be obtained without affecting surgical task performance. To perform user test at different levels of haptic quality, we developed software that can introduce friction, cogging, force saturation, inertia, and backlash into the haptic loop, simulating the characteristics of less expensive hardware on a high-end haptic interface. This software avoids the need for an expensive hardware redesign, while it allows varying the different parameters on a continuous scale, independent from each other, and within a realistic range. In a pilot study expert surgeons performed a clip application (2 participants) and a dissection task (3 participants) on commercial haptic hardware and VR laparoscopic software. Each surgeon performed the task(s) 3 times under 5 different settings while forces and kinematic data were recorded. Two settings were picked from the ones mentioned above; the other three consisted of the unaltered high fidelity setting, zero force feedback, and a combination of force saturation, cogging, friction, and inertia. We compared tissue-interaction forces, velocities, tool-tip path lengths, and completion times between the high fidelity setting and each of the other 7 settings. At a significance level of 0.05 a Friedman test showed that only the no force feedback condition was significantly different from the high fidelity condition in applied 95 percentile forces. In the clip application task both 50 percentile, and 95 percentile forces were significantly different in the no force feedback condition compared to high fidelity. None of the other settings showed significant differences in any of the performance measures. These preliminary results suggest that low performance components can be used in haptic hardware for laparoscopy without affecting task performance, potentially creating a significant cost reduction.