# Computational modeling of the mature unilateral cleft lip nasal deformity for objective assessment of patient nasal function and treatment outcomes

> **NIH NIH R01** · DUKE UNIVERSITY · 2022 · $371,039

## Abstract

PROJECT SUMMARY / ABSTRACT
In the Western world where the long surgical history of cleft lip repair dates back to 17th century, restoring form
and function in the unilateral cleft lip nasal deformity (uCLND) is acknowledged as among the most difficult
remaining surgical challenges. Further, compared to the aesthetic aspects of the mature uCLND deformity, the
functional implications of uCLND have received limited attention. Although cleft-lip- and/or palate-induced
nasal obstruction was first described over 86 years ago, almost no progress has been made to improve
treatment outcomes associated with nasal breathing. An estimated 70% of cleft individuals have impaired
functional nasal breathing and upwards of 80% “mouth-breathe”. Structural abnormalities in uCLND create
multiple sites of airway obstruction; the inability to accurately identify the most relevant obstructive sites for
correction to yield optimal patient outcome is arguably the biggest diagnostic dilemma hindering functional
advancement in treating uCLND. Our long-term goal is to restore nasal breathing function to normative levels
in post-surgical cleft patients by developing a computational modeling platform to aid surgeons to optimize
treatment outcomes. The rationale underlying our application is that once it is known to what extent and
severity each of the different sites of airway obstructive deformities impede nasal breathing, post-surgical
improvement in nasal function to a normative baseline will be attainable in uCLND patients. Based on the
strength of our preliminary data, the following Specific Aims are proposed: [1] Determine effectiveness of
current nasal surgical procedure(s) for skeletally mature uCLND patients in restoring nasal function to healthy
normative ranges; and [2] Optimize treatment options for uCLND via identification and digital correction of
greatest obstructive sites. The culmination of this research will provide a scientific basis for successful
treatment of cleft-induced nasal breathing dysfunction because, significantly, our contributions will provide [1]
objective evidence for why current interventions may not completely restore nasal function to normative levels,
and [2] treatment options with the potential to optimize patient outcomes using computational methods.

## Key facts

- **NIH application ID:** 10369059
- **Project number:** 5R01DE028554-04
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Dennis Onyeka Frank-Ito
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $371,039
- **Award type:** 5
- **Project period:** 2019-04-01 → 2025-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10369059

## Citation

> US National Institutes of Health, RePORTER application 10369059, Computational modeling of the mature unilateral cleft lip nasal deformity for objective assessment of patient nasal function and treatment outcomes (5R01DE028554-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10369059. Licensed CC0.

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