Cephalometric Parameters in Skeletal Discrepancy Assessment: An Integrative Review
Alka Dubey *
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
Ram K Ratre
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
Gauravardhan Kulkarni
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
Varsha Dogra
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
Bhumika Daheriya
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
V. Shafna
Department of Orthodontics and Dentofacial Orthopaedics, GDC, Indore, India.
*Author to whom correspondence should be addressed.
Abstract
Cephalometric radiography remains the principal diagnostic tool for characterising the anteroposterior, vertical, and transverse relationships of the craniofacial skeleton in orthodontic and orthognathic practice. Since the introduction of standardised cephalometry in the early twentieth century, a large family of angular and linear parameters has been proposed, each attempting to overcome the shortcomings of its predecessors. This integrative review synthesises the current evidence on cephalometric parameters used to assess skeletal discrepancy, tracing their historical development, comparing their diagnostic validity and reliability, and examining recent advances in three-dimensional imaging, soft tissue analysis, growth-related assessment, and artificial intelligence-assisted landmark detection. The literature indicates that no single parameter is universally superior. Angular measures such as the ANB angle remain widely used despite documented sensitivity to nasion position and jaw rotation, while linear alternatives such as the Wits appraisal are influenced by occlusal plane variability. Newer indicators, including the Beta, W, Yen, and Pi measurements, demonstrate improved discriminatory power in several comparative studies but require broader population validation. Cone-beam computed tomography has enabled three-dimensional quantification of skeletal relationships, addressing projection and superimposition errors inherent in two-dimensional radiographs, although radiation dose and cost considerations limit routine use. Digital tracing platforms and convolutional neural network-based landmark detection systems now approach or match manual tracing accuracy, offering efficiency gains without consistently sacrificing precision. Persistent limitations include population-specific normative variation, inconsistent reference plane selection, and a scarcity of longitudinal data linking cephalometric indices to long-term treatment stability. Clinicians are advised to interpret cephalometric findings within a multi-parameter framework rather than relying on any single measurement, and future research should prioritise standardised reporting, external validation of automated systems, and integration of three-dimensional and soft tissue data into unified diagnostic protocols.
Keywords: Cephalometrics, skeletal discrepancy, malocclusion, orthodontic diagnosis, cone-beam computed tomography, artificial intelligence