ArticleScientific reports2024
An automatic tracking method to measure the mandibula movement during real time MRI.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Deep learning reconstruction for temporomandibular joint MRI: diagnostic interchangeability, image quality, and scan time reduction.European radiology · 2026Article
- Instantaneous center of rotation, the first step to build up the digital laboratory of complex motions.PloS one · 2025Article
- Assessing sagittal discrepancies using beta angle, ANB angle and WITS appraisal: A cephalometric study.Bioinformation · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients' specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (LMS) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for LMS. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. LMS tracking was 76% faster and showed significantly better superimposition (0.0289 ± 0.0058) than MT (0.059 ± 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1° apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.