Evidence map›Paper›PMID 26137896›Full record

ArticleInternational journal of computer assisted radiology and surgery2016

A computational approach to calculate personalized pennation angle based on MRI: effect on motion analysis.

Andra Chincisan, Karelia Tecante, Matthias Becker, Nadia Magnenat-Thalmann, Christof Hurschler, Hon Fai Choi

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Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Andra ChincisanMIRALab, University of Geneva, Geneva, Switzerland. chincisan@miralab.ch.
Karelia TecanteLaboratory for Biomechanics and Biomaterials, Orthopaedic Department, Hannover Medical School, Hanover, Germany.
Matthias BeckerMIRALab, University of Geneva, Geneva, Switzerland.
Nadia Magnenat-ThalmannMIRALab, University of Geneva, Geneva, Switzerland.
Christof HurschlerLaboratory for Biomechanics and Biomaterials, Orthopaedic Department, Hannover Medical School, Hanover, Germany.
Hon Fai ChoiMIRALab, University of Geneva, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMuscles are the primary component responsible for the locomotion and change of posture of the human body. The physiologic basis of muscle force production and movement is determined by the muscle architecture (maximum muscle force, [Formula: see text], optimal muscle fiber length, [Formula: see text], tendon slack length, [Formula: see text], and pennation angle at optimal muscle fiber length, [Formula: see text]). The pennation angle is related to the maximum force production and to the range of motion. The aim of this study was to investigate a computational approach to calculate subject-specific pennation angle from magnetic resonance images (MRI)-based 3D anatomical model and to determine the impact of this approach on the motion analysis with personalized musculoskeletal models.

methodsA 3D method that calculates the pennation angle using MRI was developed. The fiber orientations were automatically computed, while the muscle line of action was determined using approaches based on anatomical landmarks and on centroids of image segmentation. Three healthy male volunteers were recruited for MRI scanning and motion capture acquisition. This work evaluates the effect of subject-specific pennation angle as musculoskeletal parameter in the lower limb, focusing on the quadriceps group. A comparison was made for assessing the contribution of personalized models on motion analysis. Gait and deep squat were analyzed using neuromuscular simulations (OpenSim).

resultsThe results showed variation of the pennation angle between the generic and subject-specific models, demonstrating important interindividual differences, especially for the vastus intermedius and vastus medialis muscles. The pennation angle variation between personalized and generic musculoskeletal models generated significant variation in muscle moments and forces during dynamic motion analysis.

conclusionsA MRI-based approach to define subject-specific pennation angle was proposed and evaluated in motion analysis models. The significant differences obtained for the moments and muscle forces in quadriceps muscles indicate that a personalized approach in modeling the pennation angle can provide more individual details when investigating motion behaviors in specific subjects.

Indexed as

Patient-Specific ModelingRange of Motion, ArticularBiomechanical PhenomenaGaitHumansImaging, Three-DimensionalLower ExtremityMagnetic Resonance ImagingMuscle, SkeletalQuadriceps MuscleFascicle orientationMRIMuscleMuscle linePennation angleQuadriceps

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.