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Review Article

Thermal Pain in Teeth: Electrophysiology Governed by Thermomechanics

[+] Author and Article Information
Min Lin

The Key Laboratory of Biomedical Information
Engineering of Ministry of Education,
School of Life Science and Technology,
Xi'an Jiaotong University,
Xi'an 710049, China;
Bioinspired Engineering
and Biomechanics Center,
Xi'an Jiaotong University,
Xi'an 710049, China

Guy M. Genin

Department of Neurological Surgery,
and School of Engineering,
Washington University,
St. Louis, MO 63110;
Department of Mechanical Engineering
and Materials Science,
Washington University,
St. Louis, MO 63130

Feng Xu

The Key Laboratory of Biomedical Information
Engineering of Ministry of Education,
School of Life Science and Technology,
Xi'an Jiaotong University,
Xi'an 710049, China;
Bioinspired Engineering
and Biomechanics Center,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: fengxu@mail.xjtu.edu.cn

TianJian Lu

Bioinspired Engineering
and Biomechanics Center,
Xi'an Jiaotong University,
Xi'an 710049, China
e-mail: tjlu@mail.xjtu.edu.cn

1Corresponding author.

Manuscript received July 26, 2013; final manuscript received February 1, 2014; published online April 18, 2014. Assoc. Editor: Francois Barthelat.

Appl. Mech. Rev 66(3), 030801 (Apr 18, 2014) (14 pages) Paper No: AMR-13-1054; doi: 10.1115/1.4026912 History: Received July 26, 2013; Revised February 01, 2014

Thermal pain arising from the teeth is unlike that arising from anywhere else in the body. The source of this peculiarity is a long-standing mystery that has begun to unravel with recent experimental measurements and, somewhat surprisingly, new thermomechanical models. Pain from excessive heating and cooling is typically sensed throughout the body through the action of specific, heat sensitive ion channels that reside on sensory neurons known as nociceptors. These ion channels are found on tooth nociceptors, but only in teeth does the pain of heating differ starkly from the pain of cooling, with cold stimuli producing more rapid and sharper pain. Here, we review the range of hypotheses and models for these phenomena, and focus on what is emerging as the most promising hypothesis: pain transduced by fluid flowing through the hierarchical structure of teeth. We summarize experimental evidence, and critically review the range of heat transfer, solid mechanics, fluid dynamics, and electrophysiological models that have been combined to support this hypothesis. While the results reviewed here are specific to teeth, this class of coupled thermomechanical and neurophysiological models has potential for informing design of a broad range of thermal therapies and understanding of a range of biophysical phenomena.

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Figures

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Fig. 1

Tooth structure and neuron innervation. (Reprinted Quintessence International with permission from Europe PubMed Center.) (a) Cut-away image of a human tooth illustrating several key composite layers; (b) SEM image of dentine showing solid dentine material and dentinal microtubules running perpendicularly from the pulpal wall toward dentine-enamel junction; (c) schematic of the innervation of a dentinal microtubule. The pulpal terminus of a dentinal microtubule usually contains the terminus of a nociceptor and a process extended by an odontoblast. The terminal fibril of the nociceptor ends with a terminal bead that is rich in ion channels that are sensitive to noxious stimuli including heat and shear stress.

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Fig. 2

Experimentally recorded neural discharge patterns under hot or cold stimulations. (Reprinted from Archives of Oral Biology with permission from Elsevier.) (a) Neural discharge pattern (voltage trace, top) following heating from 37 °C to 55 °C for 12 s (temperature trace, middle) and a cooling back to 37 °C; (b) neural discharge pattern following cooling from 37 °C to 5 °C for 15 s and a re-warming to 37 °C.

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Fig. 3

The three dominant hypotheses explaining differences between pain associated with heating and cooling. (a) The neural theory, in which differences arise from hot- and cold-sensitive ion channels on the terminal fibril of a nociceptor; (b) the odontoblastic transduction theory, in which signals transduced by odontoblasts are conveyed to the terminal fiber of a nociceptor; (c) the hydrodynamic theory, in which thermally induced dentinal fluid flow over the terminal bead of a nociceptor plays an important role in thermal pain transduction.

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Fig. 4

Idealized models for the thermomechanics of tooth heating. (Reprinted from Archives of Oral Biology with permission from Elsevier.) (a) One-dimensional, three-layer tooth model; (b) one-dimensional, two-layer tooth model; (c) individual dentinal microtubule; (4) representative area sectioned from (c) illustrating deformation of the dentinal microtubule wall. DM: dentine matrix; TW: microtubule wall before deformation; TWC: microtubule wall following compressive thermal stress induced deformation; TWT: microtubule wall following tensile thermal stress induced deformation.

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Fig. 5

Microscale model of tooth physiology. (Reprinted from PLoS ONE with permission from PLoS.) (a) A slightly outward displacement of an OP and its CB in response to “outward” flow from the dentinal microtubule into the pulpal space; (b) a slightly inward displacement of an odontoblastic process and its cell body in response to “inward” flow from the pulpal space into the dentinal microtubule; (c) an idealization used to estimate fluid shear stresses on the TB of a nociceptor TF associated with DFF. NF: nerve firing.

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Fig. 6

Simulated temperature and thermal stress change as a function of time at the enamel surface, the DEJ and the pulpal wall following 5 °C cold saline ((a) and (b)) and 80 °C hot saline ((c) and (d)) stimulation on an enamel surface. (Reprinted from Archives of Oral Biology with permission from Elsevier.) Thermal stimulation for 5 s was followed by natural convection for35 s in a 25 °C room temperature. The heat transfer coefficient in the simulations was 10 W/(m2K). Initial condition: entire tooth at body temperature (37 °C). Boundary condition: bottom of pulp layer kept at body temperature (37 °C).

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Fig. 7

Estimates of how dentinal fluid flow velocity changes following thermal stimulation. Experimentally measured time course of dentinal fluid flow velocity (a) and corresponding temperature variation (b), (reprinted from Archives of Oral Biology with permission from Elsevier); simulated dentinal fluid flow velocity as a function of time for thermal stimulation on exposed dentine surface (c) and enamel surface (d). Heating: 55 °C, 3 s duration; cooling: 5 °C, 3 s duration, rewarming: 37 °C, (reprinted from Ref. [2] with permission from Elsevier).

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Fig. 8

Simulated dentinal fluid flow velocity as a function of time during thermal stimulation. (Reprinted from Archives of Oral Biology with permission from Elsevier.) Solid line: cooling at 5 °C, 15 s duration, followed by rewarming at 37 °C. Dashed line: heating at 55 °C, 12 s duration, followed by rewarming at 37 °C.

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Fig. 9

Estimated shear stress on a terminal bead compared to experimentally measured neural discharge rates. (Reprinted from PLoS ONE with permission from PLoS.) Dentinal fluid flow induces shear stress over the terminal bead of a nociceptor. The maximum estimated shear stress experienced by the terminal bead (line with, filled symbols) correlates with neural discharge rate (line with, open symbols) over a range of dentinal fluid flow velocities (negative for inward flow from the dentinal microtubules into the pulp; positive for outward flow from the pulp into the dentinal microtubules).

Grahic Jump Location
Fig. 10

Variations in nociceptor membrane potential induced by an outward flow velocity (from the pulp into the dentinal microtubules) of 611.6 m/s. (Reprinted from PLoS ONE, Archives of Oral Biology, and The Journal of Physiology with permission from PLoS, Elsevier, and John Wiley and Sons respectively). (a) Simulated action potential; ((b) and (c)) experimental measurements by Vongsavan and Matthews [18] and Andrew and Matthews [9], respectively. N is the number of neural firing impulses in 5 s.

Grahic Jump Location
Fig. 11

Comparison of simulated and measured nociceptor frequency responses. (Reprinted from PLoS ONE and The Journal of Physiology with permission from PLoS and John Wiley and Sons respectively). The data of Andrew and Matthews [9] can be well predicted by a the series of models reviewed in this article that embody the hydrodynamic theory.

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