側頭下顎筋のMRI特性と顎関節症重症度との相関：多峰性定量的研究

This study aims to investigate the correlation between MRI-derived characteristics of the lateral pterygoid muscle (LPM) and the severity of temporomandibular disorders (TMD) using advanced multimodal MRI techniques.

TMD patients and healthy volunteers underwent bilateral temporomandibular joint (TMJ) MRI scans using a 3.0 T scanner between June 2023 to February 2024. The imaging protocol included conventional sequences, T2 mapping, and T1-weighted Dixon sequences. Participants were categorized into: healthy controls without disc displacement (NC-woDD), TMD without disc displacement (TMD-woDD), TMD with reducible disc displacement (TMD-DDwR), and TMD with irreducible disc displacement (TMD-DDwoR). LPM signal intensity parameters (T2 values, fat fraction) and morphological features (thickness, length, width) were measured by independent observers. Statistical analyses were performed to compare parameter differences among the groups and to evaluate correlations with age and BMI. Inter- and intra-observer agreement was also assessed.

A total of 214 joints from 107 TMD patients and 78 joints from 39 healthy control subjects were assessed. Excellent inter-observer agreement was achieved. Compared with the NC-woDD group, T2 values were significantly elevated in the TMD-woDD, TMD-DDwR, and TMD-DDwoR groups (all P < 0.05). Fat fractions were significantly elevated in the TMD-DDwR and TMD-DDwoR groups versus both the NC-woDD and TMD-woDD groups (P < 0.05). While LPM length, width, and thickness showed a decreasing trend in TMD-DDwR and TMD-DDwoR groups compared to NC-woDD, these morphological differences were not statistically significant among other group comparisons.

Quantitative MRI parameters (T2 mapping and Dixon-based fat fraction) are sensitive indicators of LPM alterations in TMD and correlate with disorder severity. The integrated use of these quantitative and morphological MRI assessments provides a more comprehensive evaluation of LPM involvement in TMD, which may aid in early detection and progression monitoring, offering valuable insights for clinical management.