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The objective of this study was to perform preliminary validation of MRI-based joint contact modeling methodology in the radiocarpal joints by comparison with the results of invasive radiocarpal contact measurements in three cadaver experiments. For each experiment, either Pressurex film or a Tekscan sensor was placed into the radiocarpal joints during a simulated grasp. Computer models were based on magnetic resonance imaging (MRI) of the cadaver specimens without load as well as on images acquired with the same loading used for the direct measurements. Geometric surface models of the radius, scaphoid, and lunate (including cartilage) were constructed from the images acquired without load. The carpal bone motions from the unloaded to the loaded state were determined using threedimensional (3D) voxel image registration. Cartilage thickness was assumed to be uniform at 1.0 mm with an effective compressive modulus of 4 MPa. Resulting . Downloaded from www.worldscientific.com by UNIVERSITE LIBRE DE BRUXELLES on 08/10/15. For personal use only.162 B. R. Thoomukuntla et al. directly from MR images acquired with load and compared to model data. Qualitatively, there was good correspondence between the MRI-based model data and experimental data, with consistent relative size, shape, and location of radioscaphoid and radiolunate contact areas. Quantitative comparison of model and experimental data was reasonable, but less consistent. Contact area from the MRI-based model was always similar to the contact area measured directly from the MR images. With additional experiments, we believe that MRI-based joint contact modeling will soon be fully validated in the radiocarpal joints.

Background: Post-stroke depression poses an important challenge for patients and delays reintegration to societal roles. Earlier identification of patients at higher risk for depression based on clinical imaging would allow a tailored treatment approach. Methods: We conducted machine-learning based lesion-symptom mapping (LSM) using a retrospective cohort of 477 patients with first-ever acute ischemic stroke (AIS) presenting to a large cerebrovascular center from 2013-2019 with mild motor impairment defined by mRS 0-2. Patient Health Questionnaire (PHQ-9) depression scale was collected within 60 days of index stroke. The location and volume of AIS lesions on brain MRI were analyzed using a machine-learning based algorithm coupled with the FreeSurfer parcellation package. LSM after random field theory-based multiple comparison correction was conducted to examine the association of AIS location and volume with PHQ-9 scale, adjusting for patient age, sex and NIHSS. Results: AIS in the right temporal, parietal, occipital lobes and the right basal ganglia were associated with depressive symptoms (Figure A). Sensitivity analysis excluding those with significant sleep disturbance (n=24) demonstrated that strokes in the right frontal and parietal lobes were associated with severe depression measured by PHQ-9>10 (Figure B). Conclusions: This hypothesis generating study was suggestive of a neuroanatomic basis for the development of post-stroke depression. Further studies in a larger dataset are needed to confirm these associations. The methods will help to predict those patients at higher risk for post-stroke depression, allowing for earlier intervention and recovery.