denture; MRS: magnetic resonance spectroscopy; PDLM: periodontal ligament mechanoreceptor; SA: slowly adapting; TMD: temporomandibular disorders; TN: trigeminal neuropathy; TNP: trigeminal neuropathic pain; WM: white matter.
a The survey is performed using Google Scholar, with the date of publication ranged from 1 January 2010 to 30 May 2021.
Table 1.3 Selected findings (since 2010) of brain imaging research related to the clinical disciplines of dentistrya.
| Clinical topics a | Potential clinical implications | Source |
|---|---|---|
| Prosthodontic treatment | For edentulous patients, reduced prefrontal activation associated with tooth loss may be prevented by chewing with a denture. | Kamiya et al. (2016) |
| Prosthodontic treatment | The adaptation to replacement of dentures may be associated with changes in brain activity during oral motor tasks. | Luraschi et al. (2013) |
| Prosthodontic treatment | Adaptative chewing experience induced by palate coverage was associated with changes in brain activity associated with motor learning. | Inamochi et al. (2017) |
| Dental implant | In rats, tooth loss and installing dental implants may be associated with neuroplasticity at the facial somatosensory/motor region. | Avivi‐Arber et al. (2015) |
| Dental implant | Osseoperception may be associated with the brain and the processing of primary and secondary somatosensory areas. | Habre‐Hallage et al. (2012) |
| Orthodontic treatment | Functional appliances may work as exercise devices for neuromuscular changes associated with muscle adaptation and brain activation. | Ozdiler et al. (2019) |
| Orthodontic treatment | In rats, inflammation induced by tooth movement may relate to the activity of the somatosensory cortex and insula, which may be associated with higher sensitivity to pain. | Horinuki et al. (2015) |
| Occlusion | Occlusal discomfort may be associated with attention and/or self‐regulation of the uncomfortable somatosensory experience. | Ono et al. (2015) |
| Occlusion | Regulation of occlusal force and periodontal sensation was modulated by prefrontal activity. | Kishimoto et al. (2019) |
| Periodontal treatment | In rats, mechanical and electrical stimuli may respectively excite activation at the primary and secondary somatosensory cortices. | Kaneko et al. (2017) |
| Periodontal and systemic health | Periodontal inflammatory/infectious burden is associated with the accumulation of amyloid‐β plaques, a key feature of Alzheimer's disease. | Kamer et al. (2015) |
| Periodontal and systemic health | Poor periodontal health may be associated with lacunar infarction, a potential cause of dementia. | Taguchi et al. (2013) |
a All the search was performed using PubMed, with date of publication ranged from 1 January 2010 to 31 May 2021.
1.2.3.2 Non‐invasive Methods – Different Focuses of Brain Features
Neuroimaging in the modern days highlights a non‐invasive procedure. For example, no surgical procedure is required for scanning the brain. However, for a non‐surgical approach, subjects may still be exposed to ionizing radiation. The diverse methods can be broadly categorized according to what brain features to be assessed. Computed tomography (CT) and magnetic resonance imaging (MRI) primarily focus on imaging brain structure. As an application of X‐ray imaging, CT may be the tool that dentists are primarily familiar with. It is advantageous in providing a good contrast on the bone tissue which is particularly useful for surgical procedures of dental treatment. In contrast, the MRI assesses the brain based on the water molecules (or strictly speaking, the hydrogen nuclei of the water molecules) in brain tissue. An MRI scanner detects the electromagnetic signals derived from the change of nuclear spinning of hydrogen nuclei. MRI can ‘map’ brain structure because the physical events can be affected by the density of protons (i.e. the hydrogen nuclei) and the relaxation processes associated with the biochemical features of brain tissue (e.g. containing less or more fat). Therefore, different anatomical features (e.g. fat‐containing neural fibres and water‐containing cerebrospinal fluid [CSF]) can be contrasted in MRI images. This advantage enables MRI the primary tool to investigate the morphology, including the size and shape, of the anatomical structure of the brain (Jenkinson and Chappell 2018). In contrast to the structure‐oriented methods, functional approaches focus on detecting the neurophysiological or brain signals associated with mental functions. The approaches include electroencephalogram (EEG), magnetoencephalography (MEG), positron emission tomography (PET), and functional MRI (fMRI), as discussed below.
1.2.3.3 Non‐invasive Methods – Different Sources of Brain Signals
In contrast to structural neuroimaging, functional neuroimaging focuses on the brain signals associated with mental functions. These function‐focusing methods can be categorized into two broad domains. Firstly, EEG and MEG are the methods that directly assess the magneto‐electrical signals from the brain. Both methods rely on the use of an array of strategically deployed sensors on the surface of one's head to collect weak magneto‐electrical signals from the brain. Both methods focus on the magnetic/electrical events of neural activity associated with mental functions. Secondly, PET and fMRI are the methods that assess the metabolic events of the brain, which can be inferred as a surrogated index of neural activity (Gazzaniga et al. 2019). PET assesses the change in metabolic events associated with cerebral blood flow (CBF) by detecting the dynamics of the radioactive‐labelled tracer injected into subjects. fMRI, in contrast, detects the change of the proportion between the oxygenated and deoxygenated haemoglobin as a metabolic index, which is indirectly associated with the change of neural activity (see Chapter 2). Notably, both methods focus on quantifying the relative change of brain signals between different conditions (e.g. when subjects perceive painful vs. non‐painful stimuli). Therefore, the PET and MRI signals do not assess absolute metabolic activity and may not be interpreted as the actual level of neural activity (Gazzaniga et al. 2019).
1.2.4 Structural MRI Methods
Due to the widespread use of MRI in neuroimaging of the human brain, the following section focuses on the application of MRI in the investigation of both structural and functional
