scholarly journals Statistical shape modelling of hip and lumbar spine morphology and their relationship in the MRC National Survey of Health and Development

2017 ◽  
Vol 231 (2) ◽  
pp. 248-259 ◽  
Author(s):  
Anastasia V. Pavlova ◽  
Fiona R. Saunders ◽  
Stella G. Muthuri ◽  
Jennifer S. Gregory ◽  
Rebecca J. Barr ◽  
...  
Keyword(s):  
Lumbar Spine ◽  
National Survey ◽  
Shape Modelling ◽  
Spine Morphology ◽  
Statistical Shape ◽  
Health And Development ◽  
Statistical Shape Modelling

scholarly journals Minimal medical imaging can accurately reconstruct geometric bone models for musculoskeletal models

2018 ◽  
Author(s):  
Edin K. Suwarganda ◽  
Laura E. Diamond ◽  
David J. Saxby ◽  
David G. Lloyd ◽  
A. Killen Bryce ◽  
...  
Keyword(s):  
Motion Capture ◽  
Linear Scaling ◽  
Bone Segmentation ◽  
Shape Modelling ◽  
Distance Error ◽  
Musculoskeletal Models ◽  
Subject Specific ◽  
Statistical Shape ◽  
Statistical Shape Modelling ◽  
Complete Sets

AbstractAccurate representation of subject-specific bone anatomy in lower-limb musculoskeletal models is important for human movement analyses and simulations. Mathematical methods can reconstruct geometric bone models using incomplete imaging of bone by morphing bone model templates, but the validity of these methods has not been fully explored. The purpose of this study was to determine the minimal imaging requirements for accurate reconstruction of geometric bone models. Complete geometric pelvis and femur models of 14 healthy adults were reconstructed from magnetic resonance imaging through segmentation. From each complete bone segmentation, three sets of incomplete segmentations (set 1 being the most incomplete) were created to test the effect of imaging incompleteness on reconstruction accuracy. Geometric bone models were reconstructed from complete sets, three incomplete sets, and two motion capture-based methods. Reconstructions from (in)complete sets were generated using statistical shape modelling, followed by host-mesh and local-mesh fitting through the Musculoskeletal Atlas Project Client. Reconstructions from motion capture-based methods used positional data from skin surface markers placed atop anatomic landmarks and estimated joint centre locations as target points for statistical shape modelling and linear scaling. Accuracy was evaluated with distance error (mm) and overlapping volume similarity (%) between complete bone segmentation and reconstructed bone models, and statistically compared using a repeated measure analysis of variance (p<0.05). Motion capture-based methods produced significantly higher distance error than reconstructions from (in)complete sets. Pelvis volume similarity reduced significantly with the level of incompleteness: complete set (92.70±1.92%), set 3 (85.41±1.99%), set 2 (81.22±3.03%), set 1 (62.30±6.17%), motion capture-based statistical shape modelling (41.18±9.54%), and motion capture-based linear scaling (26.80±7.19%). A similar trend was observed for femur volume similarity. Results indicate that imaging two relevant bone regions produces overlapping volume similarity > 80% compared to complete segmented bone models. These findings have implications for improving movement analysis and simulation with subject-specific musculoskeletal models.

scholarly journals 422 STATISTICAL SHAPE MODELLING REVEALS FOCAL PATTERN OF CARTILAGE LOSS IN OAI PROGRESSION COHORT

2008 ◽  
Vol 16 ◽  
pp. S183-S184 ◽  
Author(s):  
M.A. Bowes ◽  
T.G. Williams ◽  
C.J. Taylor ◽  
C.E. Hutchinson ◽  
R.A. Maciewicz ◽  
...  
Keyword(s):  
Cartilage Loss ◽  
Shape Modelling ◽  
Statistical Shape ◽  
Focal Pattern ◽  
Statistical Shape Modelling

scholarly journals Significant morphological change in osteoarthritic hips identified over 6–12 months using statistical shape modelling

2018 ◽  
Vol 26 (6) ◽  
pp. 783-789 ◽  
Author(s):  
R.J. Barr ◽  
J.S. Gregory ◽  
K. Yoshida ◽  
S. Alesci ◽  
R.M. Aspden ◽  
...  
Keyword(s):  
Morphological Change ◽  
Shape Modelling ◽  
Statistical Shape ◽  
Statistical Shape Modelling

scholarly journals Variation in lifting kinematics related to individual intrinsic lumbar curvature: an investigation in healthy adults

2018 ◽  
Vol 4 (1) ◽  
pp. e000374 ◽  
Author(s):  
Anastasia V Pavlova ◽  
Judith R Meakin ◽  
Kay Cooper ◽  
Rebecca J Barr ◽  
Richard M Aspden
Keyword(s):  
Lumbar Spine ◽  
Knee Flexion ◽  
Healthy Adults ◽  
Spinal Curvature ◽  
Shape Modelling ◽  
Spine Shape ◽  
Statistical Shape ◽  
Distribution Mode ◽  
Lifting Kinematics ◽  
Curvature Distribution

ObjectiveLifting postures are frequently implicated in back pain. We previously related responses to a static load with intrinsic spine shape, and here we investigate the role of lumbar spine shape in lifting kinematics.MethodsThirty healthy adults (18–65 years) performedfreestyle,stoopandsquatlifts with a weighted box (6–15 kg, self-selected) while being recorded by Vicon motion capture. Internal spine shape was characterised using statistical shape modelling (SSM) from standing mid-sagittal MRIs. Associations were investigated between spine shapes quantified by SSM and peak flexion angles.ResultsTwo SSM modes described variations in overall lumbar curvature (mode 1 (M1), 55% variance) and the evenness of curvature distribution (mode 2 (M2), 12% variance). M1 was associated with greater peak pelvis (r=0.38, p=0.04) and smaller knee flexion (r=–0.40, p=0.03) angles; individuals with greater curviness preferred to lift with a stooped lifting posture. This was confirmed by analysis of those individuals with very curvy or very straight spines (|M1|>1 SD). There were no associations between peak flexion angles and mode scores instooporsquattrials (p>0.05). Peak flexion angles were positively correlated betweenfreestyleandsquattrials but not betweenfreestyleandstooporsquatandstoop, indicating that individuals adjusted knee flexion while maintaining their preferred range of lumbar flexion and that ‘squatters’ adapted better to different techniques than ‘stoopers’.ConclusionSpinal curvature affects preferred lifting styles, and individuals with curvier spines adapt more easily to different lifting techniques. Lifting tasks may need to be tailored to an individual’s lumbar spine shape.

Prediction of normal glenoid morphology with statistical shape modelling

2016 ◽  
Vol 102 (7) ◽  
pp. S181-S182
Author(s):  
Steve Berger ◽  
Alexandre Terrier ◽  
Fabio Becce ◽  
Alain Farron ◽  
Philippe Büchler
Keyword(s):  
Shape Modelling ◽  
Statistical Shape ◽  
Glenoid Morphology ◽  
Statistical Shape Modelling
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