Related Experiment Video
Updated: May 7, 2026

Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry
Published on: December 9, 2025
Nasal anthropometry on facial computed tomography scans for rhinoplasty in koreans
Kyung Min Moon1, Geon Cho, Ha Min Sung
1Department of Plastic and Reconstructive Surgery, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea.
Background:
Cephalometric analysis is essential for planning treatment in maxillofacial and aesthetic facial surgery. Although photometric analysis of the Korean nose has been attempted in the past, anthropometry of the deeper nasal structures in the same population based on computerized tomography (CT) has not been published. We therefore measured three anthropometric parameters of the nose on CT scans in our clinical series of patients.
Methods:
We conducted the current retrospective study of a total of 100 patients (n=100) who underwent a CT-guided radiological measurement at our institution during a period ranging from January of 2008 to August of 2010. In these patients, we took three anthropometric measurements: the nasofrontal angle, the pyramidal angle, and the linear distance between the nasion and the tip of the nasal bone.
Results:
The mean nasofrontal angle was 131.14° in the male patients and 140.70° in the female patients. The mean linear distance between the nasion and the tip of the nasal bone was 21.28 mm and 18.02 mm, respectively. The mean nasal pyramidal angle was 112.89° and 103.25° at the level of the nasal root, 117.49° and 115.60° at the middle level of the nasal bone, and 127.99° and 125.04° at the level of the tip of the nasal bone, respectively.
Conclusions:
In conclusion, our data will be helpful in the preparation of silicone implants for augmentation and/or corrective rhinoplasty in ethnic Korean people.
More Related Videos
08:03Midface Hypoplasia and Cranial Base Morphology in Syndromic Craniosynostosis: A Comparative Analysis Study Using a Predictive Regression Model
Published on: November 4, 2025
05:49Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024