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contributor authorCharles, James P.
contributor authorMoon, Chan-Hong
contributor authorAnderst, William J.
date accessioned2019-09-18T09:05:31Z
date available2019-09-18T09:05:31Z
date copyright4/22/2019 12:00:00 AM
date issued2019
identifier issn0148-0731
identifier otherbio_141_06_060905
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4258754
description abstractAccurate individualized muscle architecture data are crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor imaging (DTI) magnetic resonance (MR) imaging has emerged as a promising method of gathering muscle architecture data in vivo; however, its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here, we provide a validation of the method of using anatomical magnetic resonance imaging (MRI) and DTI to gather muscle architecture data in vivo by directly comparing those data obtained from MR scans of three human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences, respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.
publisherAmerican Society of Mechanical Engineers (ASME)
titleDetermining Subject-Specific Lower-Limb Muscle Architecture Data for Musculoskeletal Models Using Diffusion Tensor Imaging
typeJournal Paper
journal volume141
journal issue6
journal titleJournal of Biomechanical Engineering
identifier doi10.1115/1.4040946
journal fristpage60905
journal lastpage060905-9
treeJournal of Biomechanical Engineering:;2019:;volume( 141 ):;issue: 006
contenttypeFulltext


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