Gonial angle – Key to gender prediction: A CBCT study in Bathinda, Punjab

Introduction: Forensic anthropology frequently relies on skeletal remains to estimate biological attributes such as sex, age, and ancestry. Among various anatomical landmarks, the gonial angle—formed by the intersection of the mandibular ramus and body—has emerged as a promising parameter for gender estimation, especially when conventional skeletal features (pelvis and cranium) are unavailable. Methods: This retrospective and prospective CBCT-based study was conducted across Oral Radiology centers in Bathinda, Punjab. Scans were analyzed using Vatech CBCT systems with Ez-Dent software to measure the gonial angle in male and female subjects. The study also evaluated associated parameters such as bone density and masticatory musculature differences between sexes. Results: Preliminary findings revealed that males exhibited significantly smaller gonial angles compared to females, correlating with stronger musculature and denser bone structure. In contrast, females showed larger gonial angles, possibly attributed to decreased bone density from hormonal and osteoporotic influences. Conclusions: The gonial angle serves as a reliable morphological indicator for sex determination, particularly in fragmented skeletal remains. CBCT provides accurate three-dimensional visualization and measurement, enhancing the forensic applicability of mandibular metrics in gender identification.

Authors

Institutions

Publication Details

Journal
Indian Journal of Dental Research
Published
2026-03-01
DOI
https://doi.org/10.4103/ijdr_202637s1_abs_24
Primary Topic
Forensic Anthropology and Bioarchaeology Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gonial angle – Key to gender prediction: A CBCT study in Bathinda, Punjab

Bhavika Sain
Indian Journal of Dental Research
Forensic Anthropology and Bioarchaeology Studies
article

Gonial angle – Key to gender prediction: A CBCT study in Bathinda, Punjab

Bhavika Sain
article en

Abstract

Introduction: Forensic anthropology frequently relies on skeletal remains to estimate biological attributes such as sex, age, and ancestry. Among various anatomical landmarks, the gonial angle—formed by the intersection of the mandibular ramus and body—has emerged as a promising parameter for gender estimation, especially when conventional skeletal features (pelvis and cranium) are unavailable. Methods: This retrospective and prospective CBCT-based study was conducted across Oral Radiology centers in Bathinda, Punjab. Scans were analyzed using Vatech CBCT systems with Ez-Dent software to measure the gonial angle in male and female subjects. The study also evaluated associated parameters such as bone density and masticatory musculature differences between sexes. Results: Preliminary findings revealed that males exhibited significantly smaller gonial angles compared to females, correlating with stronger musculature and denser bone structure. In contrast, females showed larger gonial angles, possibly attributed to decreased bone density from hormonal and osteoporotic influences. Conclusions: The gonial angle serves as a reliable morphological indicator for sex determination, particularly in fragmented skeletal remains. CBCT provides accurate three-dimensional visualization and measurement, enhancing the forensic applicability of mandibular metrics in gender identification.

Indian Journal of Dental ResearchVol. 37(Suppl 1)
Manubhai Patel Dental College and Hospital (IN)
Gender equality
Openalex Percentile: Top 7%
Forensic Anthropology and Bioarchaeology Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.