PERSPECTIVES ON THE USE OF TRACTOGRAPHY IN PATIENTS WITH TEMPOROMANDIBULAR DISORDERS: A LITERATURE REVIEW - Pekhno, Vasyl; Liakhovska, Anastasiia; Riebienkov, Stanislav; Sulik, Roman; Riabko, Ivan (Eastern Ukrainian Medical Journal, 2026)
Aim: To analyze current literature on the application of diffusion tensor imaging (DTI) and fiber tractography in patients with temporomandibular joint disorders (TMD), focusing on both central and peripheral neural pathways involved in pain modulation, nociceptive transmission and sensorimotor integration. Materials and Methods: A systematic literature search was conducted using scientific databases (e.g., PubMed, Scopus, Google Scholar) with keywords such as “diffusion tensor imaging,” “DTI,” “tractography,” “temporomandibular disorders (TMD),” and “orofacial pain”. The review encompasses studies reporting quantitative DTI parameters – fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) – and correlates these measures with clinical outcomes in TMD patients. Both central structures (cerebral hemispheres, brainstem-pain modulatory hubs) and peripheral structures (trigeminal nerve, masseter and lateral pterygoid muscles) are evaluated. Results: Early investigations primarily focused on microstructural alterations in the trigeminal nerve, revealing changes in white matter integrity that correlate with nociceptive signal transmission and disease. Recent studies have extended these analyses to central pathways, with advanced DTI techniques mapping brainstem fibers such as the rostral ventromedial medulla (RVM) and periaqueductal gray (PAG), which play a pivotal role in descending pain modulation. DTI also demonstrates tract-specific abnormalities in temporomandibular disorder: bilaterally reduced FA in the trigeminal nerves, elevated MD/RD in pain-related white matter (e.g., posterior limb of the internal capsule), and disrupted connectivity in limbic–sensorimotor circuits (including the uncinate fasciculus). Quantitative DTI parameters have demonstrated significant differences between TMD patients and healthy controls, indicating increased ADC and altered FA values in both peripheral and central pathways. Peripheral analyses further highlight increased ADC and subgroup-specific FA reduction in the lateral pterygoid and masseter muscles, particularly in anterior disc displacement without reduction (ADDWoR). Integration of DTI data with functional MRI further elucidates neuroplastic changes following therapeutic interventions, such as occlusal splint therapy, and correlates these changes with improvements in pain perception and sensorimotor function. Discussion: The evidence suggests that DTI is a promising tool for identifying early neural alterations associated with TMD and for monitoring the efficacy of treatment modalities. Unlike non-specific chronic pain syndromes, TMD exhibits distinctive DTI signatures involving trigemino-thalamo-cortical projections, brainstem modulatory circuits (PAG–RVM), and peripheral muscle fibers. These tract-specific changes support the concept of TMD as both a peripheral and central pain disorder. However, challenges remain in optimizing data processing and standardizing acquisition protocols to enhance the reproducibility and clinical utility of DTI metrics. Future studies should also integrate multimodal imaging and advanced models (e.g., diffusion spectrum imaging, NODDI) to improve specificity and support biomarker development. Conclusions: Diffusion tensor imaging and fiber tractography provide valuable quantitative insights into the neural alterations underlying TMD. These techniques have significant potential for improving diagnostic accuracy, tailoring individualized treatment strategies, and monitoring neuroplastic changes related to pain modulation and rehabilitation. DTI metrics, such as reduced FA and increased MD in trigeminal and brainstem tracts, combined with peripheral muscle abnormalities, may serve as candidate biomarkers for TMD. Further research is needed to refine image processing algorithms and integrate multimodal imaging data for advancing clinical applications in TMD management.