Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches

Troter, Arnaud Le; Fouré, Alexandre; Guye, Maxime; Confort‐Gouny, Sylviane; Mattei, Jean‐Pierre; Gondin, Julien; Salort‐Campana, Emmanuelle; Bendahan, David

doi:10.1007/s10334-016-0535-6

Cited by 63 publications

(77 citation statements)

References 37 publications

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“…Landmarks‐based 3‐D warp deformation fields were used to impose strong constraints in order to increase the accuracy of the previous reported method (Le Troter et al . ).…”

Section: Methodsmentioning

confidence: 97%

Spatial difference can occur between activated and damaged muscle areas following electrically‐induced isometric contractions

Fouré

Troter

Ogier

et al. 2019

The Journal of Physiology

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Key points T2 mapping combined to image registration and statistical parametric mapping analysis is a suitable methodology to accurately localize and compare the extent of both activated and damaged muscle areas. Activated muscle areas following electrically‐induced isometric contractions are superficial, but damaged regions are muscle specific and can be related to the muscle morphology and/or the relative spatial position within a muscle group leading to potential intramuscular muscle shear strain. Tissues other than active skeletal muscle fibres can be altered during unaccustomed neuromuscular electrical stimulation‐induced isometric contractions. Abstract Skeletal muscle isometric contractions induced by neuromuscular electrical stimulation (NMES) exercise can generate damage within activated muscles. This study aimed at comparing the localization and the extent of NMES‐activated muscle areas and induced damage regions using magnetic resonance imaging. Thirteen healthy subjects performed a single bout of NMES‐induced isometric contractions known to induce a decrease in maximal voluntary isometric contraction (MVC) and increase in muscle volume and transverse relaxation time (T2). All the parameters were measured before, immediately after (POST), 7 days (D7), 14 days (D14) and 21 days (D21) after the NMES session. Spatial normalization of T2 maps were performed to compare the localization of muscle activation areas and damaged muscle regions from statistical mapping analyses. A significant decrease in MVC was found at POST (−26 ± 9%) and in delayed time at D7 (−20 ± 6%) and D14 (−12 ± 5%). Although muscle activation was statistically detected through T2 increase at POST in superficial parts of the two muscles located beneath the stimulation electrodes (i.e. vastus lateralis and vastus medialis), alterations quantified in a delayed time from increased T2 were mainly located in the deep muscle region of the vastus lateralis (+57 ± 24% of mean T2) and superficial area of the vastus medialis (+24 ± 16% of mean T2) at D7 and were still observed in whole muscle at D21. The discrepancy between activated and damaged areas in the vastus lateralis implies that tissues other than active skeletal muscle fibres were altered during unaccustomed NMES‐induced isomeric contractions.

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“…Landmarks‐based 3‐D warp deformation fields were used to impose strong constraints in order to increase the accuracy of the previous reported method (Le Troter et al . ).…”

Section: Methodsmentioning

confidence: 97%

Spatial difference can occur between activated and damaged muscle areas following electrically‐induced isometric contractions

Fouré

Troter

Ogier

et al. 2019

The Journal of Physiology

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“…We mainly showed that with the initial input of only two manually segmented slices, the automated segmentation of the QF muscles was accurate on a large part of the thigh. According to the metrics reported in Table 1, our method provided better results as compared to the full multi-atlas based automatic approach Le Troter et al initially proposed for the same muscle group [7] with average DSC values ranging from 0.72 to 0.94. We expect an even better accuracy of our method using a larger amount of manually-segmented slices as initial input.…”

Section: Qualitative and Quantitative Validationmentioning

confidence: 99%

“…Sdika et al [6] recently demonstrated the reliability of a multi-atlas segmentation approach for the automatic segmentation and volume quantification of individual leg muscles in rat. Le Troter et al [7] evaluated the potential of this approach for quantification of individual muscle volume and reported the corresponding utilization for longitudinal studies in human. They illustrated that a fully-automated method was appropriate for large muscle groups but not for individual muscles and proposed a single-atlas based method as an alternative solution.…”

Section: Introductionmentioning

confidence: 99%

Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches

Ogier

Sdika

Fouré

et al. 2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-Manual and automated segmentation of individual muscles in magnetic resonance images have been recognized as challenging given the high variability of shapes between muscles and subjects and the discontinuity or lack of visible boundaries between muscles. In the present study, we proposed an original algorithm allowing a semi-automatic transversal propagation of manually-drawn masks. Our strategy was based on several ascending and descending non-linear registration approaches which is similar to the estimation of a Lagrangian trajectory applied to manual masks. Using several manually-segmented slices, we have evaluated our algorithm on the four muscles of the quadriceps femoris group. We mainly showed that our 3D propagated segmentation was very accurate with an averaged Dice similarity coefficient value higher than 0.91 for the minimal manual input of only two manually-segmented slices.

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“…Despite the fact that there are significant progresses made in automatic segmentation of muscles from MR images [5,11,13,15,17–19,22,28,30], only a few methods have been introduced before to address the problem of automatic segmentation of muscles from CT data [9,10,12,20,20,29]. The published CT muscle segmentation methods can be classified into two categories: 2D methods and 3D methods.…”

Section: Introductionmentioning

confidence: 99%

Fully automatic segmentation of paraspinal muscles from 3D torso CT images via multi-scale iterative random forest classifications

Kamiya

Kume

et al. 2018

Int J CARS

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Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches

Cited by 63 publications

References 37 publications

Spatial difference can occur between activated and damaged muscle areas following electrically‐induced isometric contractions

Spatial difference can occur between activated and damaged muscle areas following electrically‐induced isometric contractions

Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches

Fully automatic segmentation of paraspinal muscles from 3D torso CT images via multi-scale iterative random forest classifications

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