Numerical Human Model to Predict Side Impact Thoracic Trauma

Forbes, Patrick A.; Cronin, Duane S.; Deng, Yih–Charng; Boismenu, M.

doi:10.1007/1-4020-3796-1_45

Cited by 9 publications

(10 citation statements)

References 12 publications

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“…The parameter ℎ is the mask height here set to 4 . For each tag voxel with orthogonal neighbors a tag surface point can be derived using the orthogonal weighted average:…”

Section: Ii-8mentioning

confidence: 99%

“…The latter is of interest in the current study since the work presented here is part of a study aiming to use inverse analysis of MRI based indentation experiments for the non-invasive evaluation of detailed constitutive models for skeletal muscle tissue. Non-invasive mechanical property analysis is important for a wide range of applications including impact biomechanics [4], rehabilitation engineering [5], tissue engineering [6], surgical simulation [7] and tumor detection [8]. However the evaluation of detailed constitutive models describing the complex mechanical (anisotropic, non-linear and viscoelastic) properties of soft tissues requires detailed experimental deformation measurements capturing the complex (anisotropic, non-linear and timevarying) nature of the soft tissue deformation.…”

Section: Introductionmentioning

confidence: 99%

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Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation

Moerman¹,

Sprengers²,

Simms³

et al. 2012

Medical Physics

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Purpose: Typically SPAtial Modulation of the Magnetization (SPAMM) tagged MRI requires many repeated motion cycles limiting the applicability to highly repeatable tissue motions only. This paper describes the validation of a novel SPAMM tagged MRI and post-processing frame work for the measurement of complex and dynamic 3D soft tissue deformation following just 3 motion cycles. Techniques are applied to indentation induced deformation measurement of the upper arm and a silicone gel phantom.Methods: A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non-segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of 3 mutually orthogonal tagging directions, thus requiring only 3 repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface triplet triangle intersections. The dynamic deformation measurements were validated using indentation tests (~20 mm deep at 12 mm/s) on a silicone gel soft tissue phantom containing contrasting markers which provide a reference measure of deformation. In addition, the techniques were evaluated in-vivo for dynamic skeletal muscle tissue deformation measurement during indentation of the biceps region of the upper arm in a volunteer. Results:For the phantom and volunteer tag point location precision were 44 µm and 92 µm respectively resulting in individual displacements precisions of 61 µm and 91 µm respectively. For both the phantom and volunteer data cumulative displacement measurement accuracy could be evaluated and the difference between initial and final locations showed a mean and standard deviation of 0.44 mm and 0.59 mm for the phantom and 0.40 mm and 0.73 mm for the human data. Finally accuracy of (cumulative) displacement was evaluated using marker tracking in the silicone gel phantom. Differences between true and predicted marker locations showed a mean of 0.35 mm and a standard deviation of 0.63 mm. Conclusions:A novel SPAMM tagged MRI and fully automatic post-processing framework for the measurement of complex 3D dynamic soft tissue deformation following just 3 repeated motion cycles was presented. The techniques demonstrate dynamic measurement of complex 3D soft tissue deformation at sub-voxel accuracy and precision and were validated for 3.3-3.6Hz sampling of deformation speeds up to 12 mm/s.

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“…The parameter ℎ is the mask height here set to 4 . For each tag voxel with orthogonal neighbors a tag surface point can be derived using the orthogonal weighted average:…”

Section: Ii-8mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation

Moerman¹,

Sprengers²,

Simms³

et al. 2012

Medical Physics

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“…Finite element models of the human body in compression are used in impact biomechanics (Forbes et al, 2005 ;van Rooij et al, 2003;Verver et al, 2004); in rehabilitation engineering (Krouskop et al, 1987;Linder-Ganz et al, 2007;Mak et al, 2001) and for simulation of surgical procedures (Guccione et al, 2001;Keeve et al, 1998). Such models require knowledge of body tissue mechanical properties.…”

Section: Introductionmentioning

confidence: 99%

Viscoelastic properties of passive skeletal muscle in compression—Cyclic behaviour

Loocke

Simms

Lyons

2009

Journal of Biomechanics

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The compressive properties of skeletal muscle are important in impact biomechanics, rehabilitation engineering and surgical simulation. However, the mechanical behaviour of muscle tissue in compression remains poorly characterised. In this paper, the time-dependent properties of passive skeletal muscle were investigated using a combined experimental and theoretical approach. Uniaxial ramp and hold compression tests were performed in vitro on fresh porcine skeletal muscle at various rates and orientations of the tissue fibres. Results show that above a very small compression rate, the viscoelastic component plays a significant role in muscle mechanical properties; it represents approximately 50% of the total stress reached at a compression rate of 0.5%s -1 . A stiffening effect with compression rate is observed especially in directions closer to the muscle fibres. Skeletal muscle viscoelastic behaviour is thus dependent on compression rate and fibre orientation.A model is proposed to represent the observed experimental behaviour which is based on the quasi-linear viscoelasticity framework. A previously developed Strain dependent Young's Moduli formulation was extended with Prony series to account for the tissue viscoelastic properties. Parameters of the model were obtained by fitting to stress-relaxation data obtained in the muscle fibre, cross-fibre and 45° directions. The model then successfully predicted stress-relaxation behaviour at 60° from the fibre direction (errors < 25%). Simultaneous fitting to data obtained at compression rates of 0.5, 1 and 10%s -1 was performed and the model provided a good fit to the data as well as good predictions of muscle behaviour at rates of 0.05 and 5%s -1 (errors < 25%).3

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“…The non-invasive investigation of soft tissue mechanical properties allows for the validation of detailed constitutive laws enabling derivation of in-vivo tissue loading conditions and prediction of injury. Hence it has a wide array of applications including impact biomechanics [4], rehabilitation engineering [5] and surgical simulation [6].…”

Section: Introductionmentioning

confidence: 99%

A novel MRI compatible soft tissue indentor and fibre Bragg grating force sensor

Moerman

Sprengers

Nederveen

et al. 2013

Medical Engineering & Physics

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Numerical Human Model to Predict Side Impact Thoracic Trauma

Cited by 9 publications

References 12 publications

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation

Viscoelastic properties of passive skeletal muscle in compression—Cyclic behaviour

A novel MRI compatible soft tissue indentor and fibre Bragg grating force sensor

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