Research Papers

Experimental and Numerical Characterization of the Mechanical Masseter Muscle Response During Biting

[+] Author and Article Information
J. Weickenmeier

Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305;
Department of Mechanical and
Process Engineering,
ETH Zurich,
Zurich 8092, Switzerland
e-mail: weickenmeier@stanford.edu

M. Jabareen

Faculty of Civil and Environmental Engineering,
Technion—Israel Institute of Technology,
Haifa 3200003, Israel

B. J. D. Le Révérend

Nestlé Research Center,
Rte du Jorat 57,
CH-1000 Lausanne 26,
Lausanne CH-3008, Switzerland

M. Ramaioli

Department of Chemical and
Process Engineering,
University of Surrey,
Guildford GU2 7XH, UK

E. Mazza

Swiss Federal Laboratories for
Materials Science and Technology—EMPA,
Duebendorf 8600, Switzerland;
Department of Mechanical and
Process Engineering,
ETH Zurich,
Zurich 8092, Switzerland

1Corresponding author.

Manuscript received April 8, 2017; final manuscript received July 28, 2017; published online September 28, 2017. Assoc. Editor: Michael Detamore.

J Biomech Eng 139(12), 121007 (Sep 28, 2017) (10 pages) Paper No: BIO-17-1146; doi: 10.1115/1.4037592 History: Received April 08, 2017; Revised July 28, 2017

Predictive simulations of the mastication system would significantly improve our understanding of temporomandibular joint (TMJ) disorders and the planning of cranio-maxillofacial surgery procedures. Respective computational models must be validated by experimental data from in vivo characterization of the mastication system's mechanical response. The present pilot-study demonstrates the feasibility of a combined experimental and numerical procedure to validate a computer model of the masseter muscle. An experimental setup is proposed that provides a simultaneous bite force measurement and ultrasound-based visualization of muscle deformation. The direct comparison of the experimentally observed and numerically predicted muscle response demonstrates the predictive capabilities of such anatomically accurate biting models. Differences between molar and incisor biting are investigated; muscle deformation is recorded for three different bite forces in order to capture the effect of increasing muscle fiber recruitment. The three-dimensional (3D) muscle deformation at each bite position and force-level is approximatively reconstructed from ultrasound measurements in five distinct cross-sectional areas (four horizontal and one vertical cross section). The experimental work is accompanied by numerical simulations to validate the predictive capabilities of a constitutive muscle model previously formulated. An anatomy-based, fully 3D model of the masseter muscle is created from magnetic resonance images (MRI) of the same subject. The direct comparison of experimental and numerical results revealed good agreement for maximum bite forces and masseter deformations in both biting positions. The present work therefore presents a feasible in vivo measurement system to validate numerically predicted masseter muscle contractions during mastication.

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Grahic Jump Location
Fig. 3

Illustration of the experimental setup for the measurements of muscle deformation during contraction. The force sensor allows for real-time measurements of the current bite force in the specific biting locations. At the same time, ultrasound imaging is used to capture muscle shape changes in multiple cross sections of the muscle depending on biting position and bite force. 3D muscle shape is approximated by six measurement planes as indicated on the gel pad and FE mesh of the masseter. The ultrasound image shows the relaxed horizontal cross section of the masseter muscle in position H3. Yellow points indicate the outer contour of the masseter muscle. Muscle dimensions are measured for comparison with values reported in literature. Standoff gel-pads, skin, and fatty tissue layers are clearly visible, and the ramus of the mandible appears as a white layer inferior to the muscle's cross section.

Grahic Jump Location
Fig. 2

FE model generation of the mastication system. (a) MRI-based segmentation of skull, mandible, and the masseter muscle, (b) anatomically detailed representation of bone structures and the masseter, and (c) boundary conditions defining the kinematic constraints on the masseter muscle: nodes at the top of the masseter are fixed to represent the anchoring with the cranium; bottom nodes are kinematically coupled to the degrees-of-freedom of the condyle head of the TMJ. In the FE model a reference point is defined on the condyle head which controls the degrees-of-freedom of the rigid mandible. Images (d) through (h) visualize individual steps in the semi-automatic procedure of mesh development. The rough outer contour of the muscle is transformed into a sufficiently refined, hexahedral FE mesh. The finest mesh with 6144 elements (h) is used for all subsequent simulations.

Grahic Jump Location
Fig. 1

Anatomical representation of the mastication system including the muscles of mastication, the hyoid muscle group, TMJ, mandible, and skull. The mastication muscles are often separated into the group of (a) jaw opening muscles consisting of the lateral pterygoid (purple) and hyoid muscle groups (red, blue, and green) and (b) jaw closing muscle group comprised of masseter (orange), temporalis (blue), and medial pterygoid muscle (green). Anatomical images adapted from Williams [1] (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).

Grahic Jump Location
Fig. 4

(a) and (b) Masseter cross-sectional area change during molar and incisor biting in the horizontal plane H3. The subject repeats at least two biting cycles per video sequence and is required to reach a bite force of 50 N, 100 N, and 200 N in three individual video sequences. The optical flow algorithm tracks the manually segmented muscle contour through the entire image sequence. The inlet visualizes the procedure to determine relaxed and contracted cross-sectional muscle area. Through k-means clustering each curve is split into two groups, shown in orange and gray, for which the median is calculated, shown by dashed gray and orange lines, to obtain the data shown in (c) and (d). (c) and (d) Cross-sectional areas in the five different measurement planes for molar and incisor biting. Bite force dependent evolution of area is compared to the respective reference area before muscle activation. K-means clustering is used to separate each curve into two subsets which are associated with the mean reference cross-sectional area and the median cross-sectional area at the respective bite force. For the bite force of 200 N, no measurement data are available for horizontal cross sections H2 and H4 due to muscle fatigue, avoidance of sensor damage, and increased measurement uncertainty.

Grahic Jump Location
Fig. 5

Numerical simulation of biting including the differentiation between (a) molar and (b) incisor biting. The mechanical model described the jaw kinematics that depend on the biting location. In case of (a) molar biting the jaw must retract. In contrast, the jaw must protrude in the case of (b) incisor biting. This influences the initial shape of the masseter muscle before closing of the mouth as it is visualized by the resting state of the muscle (solid blue mesh) and the masseter shape at the beginning of biting (transparent green mesh).

Grahic Jump Location
Fig. 6

(a) and (b) Numerically predicted muscle deformation in terms of area change for increasing bite force. There is noticeable variation in the simulated shape change depending on biting position and measurement location within the masseter muscle. Cross-sectional area is approximated by the convex hull encasing the nodes of the masseter surface intersecting with the respective measurement planes. The experimentally observed cross-sectional area of the masseter in the resting state (t = 0, reference area) is shown. (c) and (d) Comparison of numerically predicted and experimentally observed muscle deformation with respect to bite force. Deformation shown in terms of normalized cross-sectional area of (a) the average of H2 and H3 and (b) the vertical measurement plane V.



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