Clinical Research Directory

Morphometric and Morphological Analysis of Cervical Vertebrae in Disc Displacement

Temporomandibular disorders (TMDs) are multifactorial clinical conditions affecting the masticatory muscles, the temporomandibular joint (TMJ), and the surrounding structures. The most common subtype is disc displacement, which is characterized by an abnormal position of the articular disc. Magnetic resonance imaging (MRI) is considered the gold standard for the diagnosis of disc displacement because it provides excellent soft tissue contrast, allows direct visualization of the disc, and enables dynamic evaluation. The parallel nature of mandibular and head-neck movements reflects the functional relationship between the temporomandibular and cervical neuromuscular systems. In addition, various craniofacial skeletal anomalies have been reported to be associated with disorders of the cervical vertebrae. TMD restricts mandibular movements and causes pain in the surrounding muscles, which may lead to referred pain in the neck, shoulder, and cervical muscles, thereby affecting head posture. Head and neck postural abnormalities are closely associated with cervical pain and dysfunction related to TMD. This relationship is thought to be bidirectional and can be explained through biomechanical, neurological, and pathophysiological mechanisms. In particular, upper cervical vertebral dysfunctions and changes in head position may influence the severity of TMD symptoms. For this purpose, lateral cephalometric radiography is frequently used to evaluate the hyoid position and the cervical spine in relation to the TMJ. Upper cervical vertebral anomalies and craniofacial morphological characteristics can be analyzed using these images.

Comparison of Digital Analysis and Artificial Intelligence for Cephalometric Tracing

This study aims to evaluate the accuracy and reliability of artificial intelligence (AI)-based cephalometric analysis compared with digital manual tracing. A total of 100 standardized lateral cephalometric radiographs will be analyzed using Delta-Dent software with manual landmark identification and three fully automated AI-based systems (WebCeph, QuantX, and Smartee). Sagittal, vertical, dental, and soft tissue cephalometric parameters will be compared among the different methods. Statistical analysis will assess inter-method agreement and the clinical relevance of any observed discrepancies. The study seeks to determine whether AI-based systems provide measurements comparable to conventional digital tracing and whether they can be considered reliable adjunctive tools in orthodontic diagnosis and treatment planning.