Narrative Review
Dental-dedicated magnetic resonance imaging for
pulpal and periapical diagnosis compared with cone beam computed tomography
Farnaz Namazi 1
Reese K. Williams 2
Vyas Yesha 2
Domenico Ricucci 3
Franklin Tay 4
https://doi.org/10.71347/cgrt75d8
1 Department of Oral Health and Diagnostic Sciences, Dental College of Georgia, Augusta University, Georgia, USA
2 Dental College of Georgia, Augusta University, USA
3 Private practice, Cetraro, Italy
4 Department of Endodontics, Dental College of Georgia, Augusta University, Augusta, GA, USA
Corresponding author:
Franklin Tay, Dental College of Georgia, Augusta University, Augusta, GA, USA.
Email: ftay@augusta.edu
Supplementary Material
Table of contents
1. Basic MRI physics relevant to dentistry
2. T1, T2, and proton density contrast
3. Field strength and its clinical implications
4. Dedicated coils and receive arrays
5. Image quality, spatial resolution, and scan time tradeoffs
6. Sequence families and task-specific protocols
7, References for Supplementary Material
1. Basic MRI physics relevant to dentistry
The experimental foundations of nuclear magnetic resonance were established independently by Felix Bloch and Edward Purcell, an achievement that was later recognized with the 1952 Nobel Prize in Physics (Bloch et al., 1946; Purcell et al., 1946). Magnetic resonance imaging forms images by detecting signals from hydrogen protons after they interact with a static magnetic field and a radiofrequency pulse applied perpendicular to the magnetic field (Berger, 2002). The radiofrequency energy is usually delivered as short pulses, each lasting microseconds. Hydrogen is especially suitable for MRI because it is abundant in biological tissues, particularly in water and organic compounds. Another reason is that the hydrogen nucleus has a magnetic moment that responds strongly to magnetic fields. This behavior arises from nuclear spin, an intrinsic quantum property of the hydrogen nucleus that gives it angular momentum and an associated magnetic moment. In the absence of an external magnetic field, the magnetic moments of hydrogen nuclei are randomly oriented. When a patient is placed within the scanner, the main static magnetic field, denoted by B0, causes a small excess of hydrogen nuclei to align in the lower-energy state oriented parallel to the magnetic field. This creates a net longitudinal magnetization (Grover et al., 2015).
These aligned nuclei do not remain stationary. They precess (rotate) around the direction of B0 at the Larmor frequency. The latter is described by the equation ω0 = γB0, where ω0 is the angular precessional frequency, γ is the gyromagnetic ratio, and B0 is the strength of the main magnetic field [S5]. This relationship is fundamental to MRI because resonance occurs only when the applied radiofrequency pulse matches this precessional rotational frequency. Once this condition is met, the radiofrequency pulse transfers energy to the hydrogen nuclei in the tissue, which tips the net magnetization away from its equilibrium position.
After the radiofrequency pulse is turned off, the excited spin system returns to equilibrium through relaxation and releases a measurable electromagnetic signal (Lugauer & Wetzl, 2018). This signal may be detected by radiofrequency coil operating at the Larmor frequency. In the ddMRI platform, a seven-channel phased-array dental coil receives signal from each element independently; elements are decoupled using preamplifier decoupling to minimize inter-element noise coupling, and individual signals are computationally combined to form the final image. Spatial encoding is then achieved by applying magnetic field gradients along the x, y, and z axes so that protons in different locations experience slightly different magnetic fields and therefore rotate at slightly different frequencies or phases. These spatial differences allow the origin of the signal to be localized and converted mathematically via Fourier transformation into image data. As a result, MRI depicts tissue according to proton behavior in a magnetic environment (Figure S1) and not according to X-ray attenuation or mineral density (Peper et al., 2016).
Fig. S1. Basic principles of MRI signal generation and image formation relevant to dentoalveolar imaging. 1. In the presence of the main static magnetic field (B0), hydrogen nuclei develop a net longitudinal magnetization because a small excess occupies the lower-energy state aligned parallel to the field. 2. These nuclei undergo precessional motion around B0 at the Larmor frequency (ω0 = γB0). 3. When a radiofrequency pulse is applied at the resonant frequency, the net magnetization is tipped away from equilibrium. 4. After the pulse is switched off, relaxation generates a measurable signal recorded as the free-induction decay. 5. Magnetic field gradients encode spatial position by introducing location-dependent differences in frequency and phase, and Fourier transformation converts the raw signal into image data. In dentoalveolar tissues, this process yields stronger signal from soft tissues with more mobile hydrogen, whereas enamel, dentin, and cortical bone typically appear dark on conventional MRI because of low mobile water content and rapid signal decay. RF: radiofrequency.
This difference between signal-rich soft tissues and signal-poor mineralized tissues is especially important in dentistry because dentomaxillofacial tissues differ markedly in proton density and molecular mobility. Soft tissues such as dental pulp, gingiva, bone marrow, muscles, and inflammatory exudates contain abundant mobile hydrogen and can therefore generate measurable signals (Vaddi et al., 2025). In contrast, enamel, dentin, and cortical bone contain relatively little mobile water and show very rapid signal decay. These features explain why highly mineralized tissues appear dark or poorly defined on conventional MRI sequences (Vaddi et al., 2025). The biological composition of dental tissues therefore has a direct effect on signal generation and image contrast. Practical evidence of this contrast behavior has already been demonstrated in intraoral MRI studies, in which the pulp, gingiva, cancellous bone, periodontal tissues, and the inferior alveolar nerve are visualized more effectively than with conventional X-ray-based methods (Flügge et al., 2016).
Another physical limitation arises from the extremely short transverse relaxation times (T2) of highly mineralized tissues (Idiyatullin et al., 2011). Dentin has a mean T2 of approximately 200 microseconds (μs), while enamel is as low as 60 μs. Standard MRI sequences such as spin echo often require over 1 millisecond (1000 μs) to perform radiofrequency excitation and gradient switching for spatial encoding. Because T2 decay is much faster (under 400 μs) than this encoding time, the magnetic resonance signal vanishes before it can be detected, resulting in a dark "black zone" in the image (Rai et al., 2025). This is the major reason why conventional MRI has historically been stronger for soft tissue assessment than for hard tissue visualization in dentistry. It also explains the growing importance of short-echo, ultrashort-echo, and zero-echo time approaches in dental MRI research. This is because these methods are designed to capture signal before rapid decay makes it inaccessible (Kavrakova et al., 2026).
These physical principles remain unchanged in ddMRI. However, the imaging system is configured to use them more effectively for the dental region. Dedicated hardware, localized receive arrays, restricted fields of view, and task-specific pulse sequences are used to maximize signal capture from teeth, jaws, and adjacent soft tissues, without compromising clinically acceptable scan times (Greiser et al., 2024). Hence, ddMRI is best understood as a more targeted application of the same physical principles to a small and technically demanding anatomic region.
2. T1, T2, and proton density contrast
After excitation by a radiofrequency pulse, the proton spin system returns to equilibrium through two relaxation processes. T1 relaxation, or longitudinal relaxation, describes recovery of magnetization along the main magnetic field (i.e. the z-axis) (Gaeta et al., 2024). T2 relaxation, or transverse relaxation, describes loss of phase coherence in the transverse (xy) plane (Wáng et al., 2023). Image contrast depends on how strongly tissues differ in these relaxation properties and in proton density (Bansal et al., 2013).
In practical terms, T1-weighted imaging emphasizes differences in longitudinal recovery, whereas T2-weighted imaging emphasizes differences in transverse decay. T1-weighted contrast reflects how quickly longitudinal magnetization recovers after excitation. T2-weighted contrast reflects how quickly transverse magnetization decays as proton spins lose phase coherence. T2-weighted sequences are therefore more sensitive to fluid-rich tissues and pathologic processes associated with edema, inflammation, or altered water content (Alzola-Aldamizetxebarria et al., 2022). In this context, water-sensitive contrast refers to sequence behavior that accentuates tissues with higher mobile water content, thereby increasing the visibility of edema, inflammation, marrow change, and fluid-rich soft tissues relative to adjacent mineralized tissues. For example, in dentomaxillofacial imaging, short tau inversion recovery (STIR) and other fat-suppressed T2-weighted sequences can make inflammatory marrow change, periapical edema, and fluid-rich soft tissue abnormalities more conspicuous than on non-fat-suppressed images. This effect is achieved by removing the high signal intensity of fatty tissue that can otherwise obscure subtle pathology (Palosaari & Tervonen, 2002). Adipose tissue appears bright on many MRI sequences and may mask lesions that also show high signal intensity. By nulling the fat signal, these techniques increase contrast-to-noise ratio and improve visualization of water-rich lesions, cartilage, and ligaments. These techniques are particularly useful for musculoskeletal imaging and neuroimaging (Bley et al., 2010; Del Grande et al., 2014; Gaddikeri et al., 2018).
These MRI contrast principles are especially relevant in oral tissues because tissue composition varies extensively (Figure S2). Structures with more mobile hydrogen such as the dental pulp, gingiva, marrow, synovial fluid, and inflammatory exudates generate measurable signal and often become visible on conventional MRI. In contrast, enamel, dentin, and cortical bone have very short transverse relaxation times and rapidly lose signal, which explains their low signal intensity or absence on standard sequences (Vaddi et al., 2025). The marked differences in tissue water content and proton mobility therefore determine whether a structure appears bright, intermediate, or dark on dental MRI.
Proton density refers to the concentration of mobile hydrogen protons (mostly present in water and fat) per unit volume of tissue. It is another fundamental MRI contrast mechanism. Proton density-weighted sequences generate relatively high signal from tissues containing more mobile hydrogen. These sequences minimize some of the contrast effects created by strong T1 or T2weighting. Repetition time (TR) is the interval between successive radiofrequency excitation pulses applied to the same region, whereas echo time (TE) is the interval between the excitation pulse and the peak of the measured magnetic resonance signal. Together, these parameters strongly influence image contrast by controlling the extent of longitudinal recovery and transverse signal decay prior to signal acquisition. In practical terms, a short TR and short TE produce greater T1 weighting, a long TR and long TE produce greater T2 weighting, and a long TR with a short TE produces greater proton density weighting (Runge & Heverhagen, 2022).
Fig. S2. Approximate T2 relaxation behavior and expected MRI conspicuity of selected dentoalveolar features. Relaxation behavior shown is conceptual and approximate. Values are field-strength dependent and vary with sequence design, temperature, tissue composition, and physiological or pathological state. This figure is intended as a contrast map, not a strict reference table.
By using a long TR (~2000 to 5000 ms) to minimize T1 effects and a short TE (~10 to 20 ms) to minimize T2 effects, proton density-weighted sequences emphasize differences in mobile proton concentration and make tissues such as synovial fluid, fat, and cartilage appear relatively bright (Morbée et al., 2022). This contrast behavior is especially useful in musculoskeletal imaging because it provides clear distinction between fluid-rich and solid structures. In dentomaxillofacial imaging, the same principle has been incorporated into ddMRI protocols for anatomic visualization of the temporomandibular joint and localized dentoalveolar regions (Greiser et al., 2024).
3. Field strength and its clinical implications
Field strength directly affects signal behavior, scan efficiency, artifact severity, and equipment requirements. In general, higher magnetic field strengths provide more signal and can improve signal-to-noise ratio and spatial resolution. This has historically made 1.5 T and 3 T systems dominant in dental MRI research. Earlier in vivo dental MRI work relied largely on 1.5 T systems (Niraj et al., 2016). Later research increasingly used 3 T platforms to improve visualization of finer structures within clinically feasible acquisition times (Assaf et al., 2014; Han et al., 2025).
Nevertheless, higher field strength is not exclusively advantageous in dentistry. As field strength increases, magnetic susceptibility artifacts, radiofrequency heating concerns, and material-related distortions may also increase (Cortes et al., 2015; Tang & Yamamoto, 2023; Sfondrini et al., 2023). These features result in degradation of image quality near restorations, implants, and air-tissue interfaces (Vaddi et al., 2025; Johannsen et al., 2025). This tradeoff is particularly important in the oral cavity where metallic restorative and prosthodontic materials and complex interfaces are common. Lower field strength can therefore improve robustness in some dentomaxillofacial applications, even if intrinsic signal is lower.
The current ddMRI concept uses a 0.55 T scanner, which reflects a deliberate balance instead of a technical compromise. Greiser et al. (2024) selected this field strength because it reduces siting demands, lowers shielding requirements, decreases scanner weight, and reduces fringe field constraints. Contemporary acquisition and reconstruction methods are then employed to help recover image quality. The same technical report emphasized that low-field imaging becomes clinically plausible only when combined with a dental surface coil, restricted field of view, and accelerated acquisition strategies.
Recent comparative work reinforces this task-specific view of field strength. In temporomandibular joint imaging, a 0.55 T ddMRI system with a custom surface coil produced image quality that was rated similarly to a 1.5 T system using a standard head and neck coil (Nixdorf et al., 2025). This finding suggests that field strength alone does not determine diagnostic value. Coil geometry, pulse sequence optimization, and workflow adaptation can offset some of the usual disadvantages of low-field imaging.
4. Dedicated coils and receive arrays
The radiofrequency coil is central to ddMRI because it determines how efficiently signal is transmitted to and received from the region of interest. General head and neck coils are designed for broad anatomic coverage, which is suitable for medical imaging but inefficient for small, high-resolution dentomaxillofacial targets. Dedicated dental coils improve local signal reception by bringing the receiving elements closer to the teeth, jaws, and adjacent soft tissues. A recent study reported that MRI performed with a dedicated 15-channel dental coil provided significantly better image quality and accuracy in the assessment of head and neck cancer than the standard coil. This improvement was especially evident in cases of bone invasion (Burck et al., 2026).
The ddMRI platform designed by Greiser et al. (2024) uses a 7-channel dental surface coil with a rigid central housing and flexible lateral wing extensions that conform to the face. This arrangement was designed to maximize sensitivity over the dentomaxillofacial area and minimize signal collection from surrounding anatomy that is diagnostically irrelevant. The array layout also permits parallel imaging. This feature enables simultaneous signal detection from multiple coil elements and faster acquisition through coil sensitivity-based reconstruction.
The importance of coil specialization was already clear prior to the emergence of the current ddMRI platform. In an early clinically oriented study, Flügge et al. (2016) used a wireless inductively coupled intraoral coil with “fast low-angle shot” (FLASH) sequences on a 3 T whole-body system. The authors showed that pulp, gingiva, cancellous bone, periodontium, and the inferior alveolar nerve could be visualized within acquisition times of less than 7 min. That study also demonstrated strong agreement between MRI, cone beam computed tomography, and histological sections. The results indicated that coil adaptation could markedly improve intraoral MRI feasibility even before low-field ddMRI was introduced.
A recent ddMRI review divided dental coils into extraoral surface coils and intraoral coils, each with different strengths (Vaddi et al., 2025). Extraoral coils provide broader coverage and are better suited for multi-structure imaging, orthodontic tasks, and broader dentomaxillofacial assessment. Intraoral coils provide higher local signal-to-noise ratio and finer resolution. However, their coverage is restricted, and placement is more technique-sensitive (Özen et al., 2026; Xiao et al., 2026). For that reason, coil selection in dental MRI involves matching coil geometry and coverage to the specific diagnostic target.
5. Image quality, spatial resolution, and scan time tradeoffs
Image quality in ddMRI depends on the balance among signal-to-noise ratio, contrast-to-noise ratio, spatial resolution, field of view, and acquisition time (Dentsply Sirona & Siemens Healthineers, 2024). These variables are interdependent. Smaller voxels improve spatial resolution but reduce signal-to-noise ratio. Larger fields of view provide broader coverage but dilute spatial detail. Thinner slices reduce partial-volume effects but may increase noise and prolong scanning time. The clinical challenge in ddMRI is to balance these competing demands in a way that remains useful for dentistry.
The ddMRI platform reported by Greiser et al. (2024) addressed this problem by separating protocols according to diagnostic task instead of applying one universal acquisition. Large-field three-dimensional (3D) scout and orthodontic protocols were used when broader anatomic coverage was required. Conversely, high-resolution 2D and small-volume 3D acquisitions were reserved for localized endodontic, periodontal, extraction, and inflammatory assessments. According to the protocol, reconstructed resolution ranged from 1.4 × 1.4 × 1.0 mm for scout imaging to 0.2 × 0.2 × 2.5 mm for selected temporomandibular joint and localized dentoalveolar tasks. Acquisition times generally ranged between about 1 and 4 min per sequence.
This task-based strategy is one of the most important differences between ddMRI and conventional medical MRI use in dentistry. Rather than imaging a large anatomic region at one fixed resolution, the field of view and sequence parameters are adjusted according to whether the goal is panoramic overview, local inflammatory assessment, temporomandibular joint evaluation, or high-resolution dentoalveolar anatomy (Greiser et al., 2024). This reduces unnecessary coverage and allows scan time to be spent where detail is actually needed.
Acceleration methods are also essential. Greiser and colleagues incorporated parallel imaging, compressed sensing, and advanced reconstruction approaches, including deep learning-based denoising, to shorten acquisition and improve apparent image quality (Greiser et al., 2024). The importance of these methods is clear in low-field imaging, where signal is inherently lower than at 1.5 T or 3 T. In ddMRI, clinically acceptable examination times are achieved by combining localized coils, limited fields of view, accelerated acquisition, and sequence-specific optimization.
6. Sequence families and task-specific protocols
A magnetic resonance sequence is a predefined pattern of radiofrequency pulses, gradient applications, and timing parameters that determines how image contrast is generated and which tissues are emphasized. In dental MRI, sequence choice determines whether the examination emphasizes anatomy, inflammatory change, neurovascular structures, or mineralized tissue approximation. The published ddMRI platform uses a compact set of task-based sequences rather than a large menu of interchangeable options. In its current form, ddMRI relies mainly on proton density-weighted imaging, conventional T1- and T2-weighted imaging, short tau inversion recovery (STIR), and a volumetric scout sequence (Greiser et al., 2024; Han et al., 2025).
6.1 Sequences currently employed in ddMRI
a. Proton density-weighted sequences: PD-TSE and PD-SPACE
Proton density-weighted imaging forms the main anatomic layer of the currently published ddMRI protocol architecture. In the technical framework proposed by Greiser et al. (2024), 3D “proton density-weighted sampling perfection with application-optimized contrasts using different flip-angle evolutions” (PD-SPACE) was used for broad overview imaging. Two-dimensional proton density-weighted turbo spin-echo (PD-TSE) was used for localized dentoalveolar assessment. These sequence families recur in orthodontic, endodontic, periodontal, and extraction-related protocols (Han et al., 2025).
b. Conventional T1- and T2-weighted imaging
Conventional T1-weighted and T2-weighted imaging remains part of ddMRI because proton density-weighted imaging alone cannot fully characterize tissue state. T1-weighted imaging is useful for anatomic definition, marrow characterization, and lesion boundaries. T2-weighted imaging is useful for fluid-rich tissues, cystic content, edema-related change, and other water-dominant abnormalities (Flügge et al., 2016; Han et al., 2025]. These sequences function mainly as complementary tissue-characterization layers. They are especially relevant when the diagnostic question concerns marrow composition, lesion content, pulpal or periapical fluid signal, or temporomandibular joint soft tissue. They add biologic and structural context to the proton density-weighted backbone of the ddMRI protocol (Greiser et al., 2024).
c. STIR and other inflammation-sensitive protocols
Short tau inversion recovery (STIR) and related fat-suppressed sequences are used in ddMRI when the main target is inflammatory activity. Fat suppression reduces bright marrow and soft-tissue fat signal and increases the visibility of edema, marrow reaction, and fluid-rich tissue change. This is particularly relevant in periapical, periodontal, pulpal, and temporomandibular joint imaging, where inflammatory change may extend beyond the morphologic abnormality visible on X-ray-based imaging (Flügge et al., 2023; Greiser et al., 2024; Han et al., 2025). In the published ddMRI platform, STIR is not used in isolation (Greiser et al., 2024). It is paired with proton density-weighted or conventional anatomic sequences to highlight biological activity.
d. GRE-VIBE scout imaging and protocol assembly
The current ddMRI workflow begins with a 3D gradient-echo volumetric interpolated breath-hold examination (GRE-VIBE) scout sequence. This sequence is not intended for detailed diagnosis. Its role is rapid orientation and localization before other task-specific sequences are selected. After the scout, the examination is narrowed according to the clinical question, with combinations of PD-SPACE, PD-TSE, T1-weighted TSE, T2-weighted TSE, PD-weighted fat-suppressed TSE, and T2-weighted STIR TSE sequences used as needed (Greiser et al., 2024; Han et al., 2025).
6.2 Sequence families from broader dental MRI literature with potential for future ddMRI incorporation
The broader dental MRI literature includes several sequence families that are not part of the present published ddMRI core but may become relevant in future platforms. These sequences are important because they address limitations of conventional dental MRI, especially in cortical visualization, mineralized tissue depiction, and neurovascular assessment.
a. DESS and related high-resolution dentoalveolar imaging
Dual-echo steady-state (DESS) imaging has been used in dental MRI for impacted teeth, inferior alveolar nerve visualization, and preoperative planning. Its main attraction is that it combines relatively sharp dentoalveolar anatomy with neurovascular visibility. This makes it particularly relevant to posterior mandibular imaging and third molar assessment (Flügge et al., 2023; Al-Haj Husain et al., 2024). At present, DESS is best viewed as a possible future expansion sequence instead of part of the established ddMRI core.
b. Black bone MRI
Black bone MRI refers to short-echo, low-flip-angle gradient-echo approaches that depict cortical bone as a sharply defined dark contour. These methods have been explored for craniofacial surface rendering, cephalometric assessment, and computed tomography-like osseous visualization without ionizing radiation (Chong et al., 2021; Flügge et al., 2023). Their main use is cortical contour depiction instead of inflammatory characterization.
c. UTE and ZTE imaging
Ultrashort echo time (UTE) and zero echo time (ZTE) imaging were developed to improve the visibility of short-T2 tissues such as enamel, dentin, and cortical bone. By capturing signal very early, they provide a route toward more direct imaging of mineralized tissues than conventional dental MRI sequences usually allow (Parize et al., 2024). These approaches are especially relevant for future ddMRI development in bone-dominant tasks such as implant assessment, cortical evaluation, and computed tomography-like hard-tissue rendering (Al-Haj Husain et al., 2024).
d. StarVIBE and other CT-like MRI approaches
StarVIBE and other computed tomography-like gradient-echo approaches belong to the broader dentomaxillofacial MRI field rather than the current ddMRI sequence package. Their value lies in rapid volumetric acquisition, motion robustness, and more computed tomography-like depiction of osseous boundaries. These approaches are relevant because they point toward future radiation-free imaging strategies for bone-oriented dentomaxillofacial tasks (Chong et al., 2021; Al-Haj Husain et al., 2025, 2026).
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