Adjustments in Shoulder and Back Kinematics during Repetitive Palletizing Tasks.

Repetitive task performance is a leading cause of musculoskeletal injuries among order-picking workers in warehouses. The repetition of lifting tasks increases the risk of back and shoulder injuries among these workers. While lifting in this industry is composed of loaded and unloaded picking and placing, the existing literature does not address the separate analysis of the biomechanics of the back and shoulder for these events. To that end, we investigated the kinematics of the back and shoulder movements of nine healthy male participants who performed three sessions of a simulated de/palletization task. Their back and shoulder kinematics were sensed using an optical motion capture system to determine the back inclination and shoulder flexion. Comparison of the kinematics between the first and last sessions indicated statistically significant changes in the timings, angles, coordination between the back and shoulder, and moments around the shoulder (p<0.05). The majority of the significant changes were observed during the loaded events, which confirms the importance of the separation of these events for biomechanical analysis. This finding suggests that focusing worker evaluation on the loaded periods can provide important information to detect kinematic changes that may affect musculoskeletal injury risk.

Evaluation of Two Fast Virtual Stenting Algorithms for Intracranial Aneurysm Flow Diversion.

BACKGROUND: Endovascular treatment of intracranial aneurysms (IAs) by flow diverter (FD) stents depends on flow modification. Patient-specific modeling of FD deployment and computational fluid dynamics (CFD) could enable a priori endovascular strategy optimization. We developed a fast, simplistic, expansion-free balls-weeping algorithm to model FDs in patientspecific aneurysm geometry. However, since such strong simplification could result in less accurate simulations, we also developed a fast virtual stenting workflow (VSW) that explicitly models stent expansion using pseudo-physical forces. METHODS: To test which of these two fast algorithms more accurately simulates real FDs, we applied them to virtually treat three representative patient-specific IAs. We deployed Pipeline Embolization Device into 3 patient-specific silicone aneurysm phantoms and simulated the treatments using both balls-weeping and VSW algorithms in computational aneurysm models. We then compared the virtually deployed FD stents against experimental results in terms of geometry and post-treatment flow fields. For stent geometry, we evaluated gross configurations and porosity. For post-treatment aneurysmal flow, we compared CFD results against experimental measurements by particle image velocimetry. RESULTS: We found that VSW created more realistic FD deployments than balls-weeping in terms of stent geometry, porosity and pore density. In particular, balls-weeping produced unrealistic FD bulging at the aneurysm neck, and this artifact drastically increased with neck size. Both FD deployment methods resulted in similar flow patterns, but the VSW had less error in flow velocity and inflow rate. CONCLUSION: In conclusion, modeling stent expansion is critical for preventing unrealistic bulging effects and thus should be considered in virtual FD deployment algorithms. Also endowed with its high computational efficiency and superior accuracy, the VSW algorithm is a better candidate for implementation into a bedside clinical tool for FD deployment simulation.

Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm.

BACKGROUND: Computer modeling of endovascular coiling intervention for intracranial aneurysm could enable a priori patient-specific treatment evaluation. To that end, we previously developed a finite element method (FEM) coiling technique, which incorporated simplified assumptions. To improve accuracy in capturing real-life coiling, we aimed to enhance the modeling strategies and experimentally test whether improvements lead to more accurate coiling simulations. METHODS: We previously modeled coils using a pre-shape based on mathematical curves and mechanical properties based on those of platinum wires. In the improved version, to better represent the physical properties of coils, we model coil pre-shapes based on how they are manufactured, and their mechanical properties based on their spring-like geometric structures. To enhance the deployment mechanics, we include coil advancement to the aneurysm in FEM simulations. To test if these new strategies produce more accurate coil deployments, we fabricated silicone phantoms of 2 patient-specific aneurysms in duplicate, deployed coils in each, and quantified coil distributions from intra-aneurysmal cross-sections using coil density (CD) and lacunarity (L). These deployments were simulated 9 times each using the original and improved techniques, and CD and L were calculated for cross-sections matching those in the experiments. To compare the 2 simulation techniques, Euclidean distances (dMin, dMax, and dAvg) between experimental and simulation points in standardized CD-L space were evaluated. Univariate tests were performed to determine if these distances were significantly different between the 2 simulations. RESULTS: Coil deployments using the improved technique agreed better with experiments than the original technique. All dMin, dMax, and dAvg values were smaller for the improved technique, and the average values across all simulations for the improved technique were significantly smaller than those from the original technique (dMin: p = 0.014, dMax: p = 0.013, dAvg: p = 0.045). CONCLUSION: Incorporating coil-specific physical properties and mechanics improves accuracy of FEM simulations of endovascular intracranial aneurysm coiling.

The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography.

Calculation of fractional flow reserve (FFR) based on computational fluid dynamics (CFD) requires reconstruction of patient-specific coronary geometry and estimation of hyperemic flow rate. Coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) are two dominating imaging modalities used for the geometrical reconstruction. Our aim was to investigate the impact of image resolution as inherently associated with these two imaging modalities on geometrical reconstruction and subsequent FFR calculation. Patients with mild or intermediate coronary stenoses who underwent both CCTA and ICA were included. CCTA images were acquired either by 320-row area detector CT or by 128-slice dual-source CT. Two geometrical models were reconstructed separately from CCTA and ICA, from which FFRCTA and FFRQCA were subsequently calculated using CFD simulations, applying the same hyperemic flow rate derived from the ICA images at the inlet boundaries. A total of 57 vessels in 41 patients were analyzed. Average diameter stenosis was 43.4 ± 10.8 % by 3D QCA. Reasonably good correlation between FFRCTA and FFRQCA was observed (r = 0.71, p < 0.001). The difference between FFRCTA and FFRQCA was correlated with the deviation between minimal lumen areas by CCTA and by ICA (ρ = 0.34, p = 0.01), but not with plaque volume (ρ = -0.09, p = 0.51) or calcified plaque volume (ρ = 0.01, p = 0.95). Applying the cutoff value of ≤0.8 to both FFRCTA and FFRQCA, the agreement between FFRCTA and FFRQCA in discriminating functional significant stenoses was moderate (kappa 0.47, p < 0.001). Disagreement was found in 10 (17.5 %) vessels. Acceptable correlation between FFRCTA and FFRQCA was observed, while their agreement in distinguishing functional significant stenosis was moderate. Our results suggest that image resolution has a significant impact on FFR computation.