Related Experiment Video
Updated: Jul 11, 2026

Quantification of Orofacial Phenotypes in Xenopus
Published on: November 6, 2014
Assessment of the cleft nasal deformity using a regression equation
Soo Chan Kim1, Ki Chang Nam, Dong Kyun Rah
1Electronic Technology Institute, Hankyong National University, Anseong, Korea.
A new method using digital images objectively assesses cleft nasal deformity surgical outcomes. This simple, reproducible tool provides quantitative results for both surgeons and laypersons, improving outcome evaluation.
Area of Science:
- Plastic Surgery
- Medical Imaging
- Quantitative Assessment
Background:
- Cleft nasal deformity presents a significant surgical challenge.
- Objective and reproducible assessment of surgical outcomes is crucial for evaluating treatment efficacy.
Purpose of the Study:
- To propose an objective and simple method for assessing surgical outcomes of cleft nasal deformity.
- To utilize two-dimensional digital images for outcome evaluation.
Main Methods:
- Plastic surgeons and laypersons evaluated cleft nasal deformity images.
- A novel assessment tool and regression equation were developed and validated.
- Reproducibility of the proposed method was compared to subjective surgeon grading.
Main Results:
- The layperson-based method showed higher correlation coefficients (.90) compared to surgeon grading (.80).
- The proposed method demonstrated better grade reproducibility (9.6%) than subjective surgeon assessment (14.6%).
Conclusions:
- The developed assessment tool offers a simple, reproducible, quantitative, and objective method for evaluating cleft nasal deformity surgical outcomes.
- This tool can be effectively used by both surgeons and laypersons with two-dimensional photographs.
More Related Videos
07:16Finite Element Analysis Model for Assessing Expansion Patterns from Surgically Assisted Rapid Palatal Expansion
Published on: October 20, 2023
08:03Midface Hypoplasia and Cranial Base Morphology in Syndromic Craniosynostosis: A Comparative Analysis Study Using a Predictive Regression Model
Published on: November 4, 2025