Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.11.02.565254

The Influence of Knee Varus Deformity on the Kinematic and Dynamic Characteristics of Musculoskeletal Models During Gait

Abstract

BackgroundMusculoskeletal modeling has paved the way of measuring kinematic and kinetic variables during motions. Nonetheless, since the commonly-used generic models are created based on averaged data; thus, they cannot accurately mimic subjects with skeletal deformities. To overcome this obstacle, one can build personalized models based on subjects MRI or CT scan data, which is both time and money consuming. The other promising way is to manipulate generic models and create semi-personalized models to match with the individuals skeletal system at the joint of interest. Research QuestionCan a semi-personalized model reduce marker error in gait analysis? How a semi-personalized model differentiates the ROM of the lower limb joints and muscle activation pattern while having varus deformity? MethodWe developed the varus-valgus tool (freely available on: https://simtk.org/projects/var-val-tool) in MATLAB using OpenSim Application Programming Interface (API) to incorporate varus-valgus deformity in the generic OpenSim models. A 36-year-old female subject with a complaint of knee pain participated in our study. The subject had 6.5 and 11.9 degrees of varus in the right and left leg, respectively. A semi-personalized model of the subject was first created using generic OpenSim models. Then, markers error during Inverse Kinematic (IK), joints Range of Motion (ROM) and the activation of Tensor Fasciae Latae (TFL), a knee adductor, and Gracilis, a knee abductor, were calculated and compared between a semi-personalized model and a generic model. ResultsSignificant difference was observed in markers error during IK between generic and semipersonalized models (p<0.05). Substantial alterations were found in the ROM of the hip, knee and ankle joints while using semi-personalized model. Moreover, the activation pattern of TFL experienced a dramatic rise whereas Gracilis saw a fall during each gait cycle in semi-personalized models. SignificanceImplementing varus-valgus deformity in the generic models substantially reduces markers error which leads to more accurate results. It was observed that semi-personalized models showed different ROM compared to generic ones.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tabeiy, S., Karimpour, M., Shirvani, A., Sherafat Vaziri, A.. 2023-11-04. The Influence of Knee Varus Deformity on the Kinematic and Dynamic Characteristics of Musculoskeletal Models During Gait. https://doi.org/10.1101/2023.11.02.565254

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

SpiraMed: A Stereotactic Helix-based Therapy Delivery system for the Human Brain

Stereotactic needle-based delivery remains the standard for local administration of Advanced Therapy Medicinal Products (ATMPs) to the human brain. ATMP administration typically involves multiple trajectories, presenting cumulative risks and prolonging surgery. Reflux-prone, patchy therapy coverage compromises clinical results. We demonstrate a novel approach, deploying a helical delivery catheter via a single access trajectory per target, referred to as SpiraMed. Helix retraction is synchronised with therapy delivery, enabling comprehensive target coverage in seconds. Helix pitch and diameter can be precisely tailored to patient-specific target volume and vascular anatomy, as part of the preoperative stereotactic surgical planning process. Testing in agarose phantoms, live sheep and cadaveric human brain confirms enhanced therapy delivery volume, delivery speed and target coverage, with reductions in reflux and predicted risk of bleeding complication. SpiraMed represents a new paradigm, promising to help deliver on the transformative potential of cell and gene therapies across the spectrum of human CNS disease.

bioengineering↗

Normative Modeling of Molecular-Enriched Functional Connectivity for Detecting Deviations from Healthy Brain Aging

Inter-individual variability in adult brain aging can obscure early pathological alterations and is only partly represented by population-average or scalar brain-aging measures. We combined Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) with normative modeling (NM) to derive spatially resolved, molecularly informed deviation scores for dopamine transporter (DAT)-, norepinephrine transporter (NET)-, and serotonin transporter (SERT)-enriched resting-state functional connectivity (FC). We first evaluated whether these normative models could be transferred to independently processed external data through local calibration and then explored whether the resulting deviation profiles differed with cerebral amyloid burden in cognitively unimpaired older adults. Hierarchical Bayesian regression (HBR) models with a SHASHb likelihood were estimated separately for 204 cortical molecular-enriched FC features in 4,152 healthy adults (18.0--89.8 years) from seven publicly available neuroimaging datasets and evaluated in a held-out healthy test set. Pretrained models were locally adapted to three AMYPAD-PNHS acquisition batches using cognitively unimpaired, amyloid-negative participants (global Clinical Dementia Rating [CDR] = 0; Centiloid [CL] [lt] 10). The independent primary comparison contrasted participants with intermediate amyloid burden (10 [&le;] CL [lt] 30; n = 111) and amyloid-positive participants (CL [&ge;] 30; n = 66); secondary analyses tested linear associations with continuous CL within participants with CL [&ge;] 10. Of 204 normative reference models, 199 (97.5%) met the predefined diagnostic criteria; median held-out explained variance (EXPV) was 0.174. Of 612 feature-by-batch transfers, 541 (88.4%) met the strict transfer-diagnostic criteria. In the primary false discovery rate (FDR)-controlled regional analysis, DAT-enriched right caudal middle frontal cortex showed lower locally standardized deviation scores in the intermediate-amyloid-burden group than in the amyloid-positive group (adjusted difference = -0.582, q = 0.016). DAT extreme-deviation burden was also greater in the intermediate-amyloid-burden group (difference = 0.032, q = 0.044). The right frontal effect was reproduced with model-native scores across the three acquisition batches (pooled standardized effect = -0.698, q = 0.010). No NET- or SERT-enriched regional difference between these two groups survived FDR correction, and no regional or subject-level linear association with continuous CL values survived FDR correction in the CL [&ge;] 10 group. Normative modeling can provide spatially resolved reference distributions of molecular-enriched FC that are deployable in independently processed external data when local adaptation, calibration, and feature-level transfer diagnostics are incorporated. The AMYPAD-PNHS application identified modest, spatially selective, and molecular-system-specific categorical differences during a cognitively unimpaired stage of amyloid accumulation, while continuous analyses within CL [&ge;] 10 did not support a linear association. These findings support a methodological basis for distributed application of molecular-enriched normative models and motivate independent and longitudinal evaluation of their biological relevance.

bioengineering↗

AC-Diff: Anatomy-Contrast Disentangled Diffusion for Multi-Vendor Liver MRI Harmonization

Magnetic resonance imaging (MRI) exhibits substantial scanner and protocol dependent appearance variations, making harmonization challenging without distorting patient specific anatomy, particularly in abdominal imaging. We propose AC-Diff, an anatomy--contrast disentangled diffusion framework that formulates MRI harmonization as a factor-specific generative intervention. Using aligned multi-contrast supervision and cross-patient factor swapping, AC-Diff learns to separate anatomical structure from acquisition-dependent contrast. Unlike conventional image or latent diffusion, AC-Diff restricts stochastic generation to the contrast subspace while the source anatomy bypasses diffusion and is directly reused during reconstruction. Experiments on an in-house multi-vendor cohort and the external Duke Liver MRI dataset demonstrate improved target-domain alignment with strong structural preservation. In downstream liver segmentation, AC-Diff improves Dice from 0.942 for the original inputs to 0.954 for the harmonized images. These results support contrast-specific latent generation as a promising approach to anatomy-preserving MRI harmonization.

bioengineering↗