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| ID | Type | Description | Link |
|---|---|---|---|
| R01DE028554 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of Dental and Craniofacial Research (NIDCR) | NIH |
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The purpose of this study is to use computers to simulate airflow in 3D construction of your nasal cavity generated from cone beam CT images. The results from computer simulations will help researchers identify the severity of cleft-induced nasal dysfunction and assess the impact of current treatment in restoring breathing function. The ultimate goal is to improve post-surgery outcomes to restore nasal breathing function to normal levels.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Unilateral Cleft Lip Nasal Deformity (uCLND) | uCLND patients who are scheduled to undergo surgical treatment for nasal obstruction as standard of care. |
| |
| Healthy Subjects | Existing data from healthy subjects with no prior symptoms of nasal obstruction used to create normative ranges for comparison to uCLND cohort. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Surgical repair for nasal obstruction | Procedure | Patient reported quality of life questionnaires |
|
| Measure | Description | Time Frame |
|---|---|---|
| Validation of computational fluid dynamics simulation with breathing measurement | Percent agreement between computational fluid dynamics simulated nasal resistance and nasal resistance from rhinomanometry breathing measurement | 6 months |
| Validation of computational fluid dynamics simulation with in vitro experiment | Percent agreement between computational fluid dynamics simulated nasal resistance and nasal resistance measurement from in vitro experiment of 3D printed plastic nasal replica | 6 months |
| Effectiveness of current surgery in restoring nasal function based on volumetric airflow | Analysis of significant difference in volumetric airflow rate between pre-surgery and post-surgery data from computational fluid dynamics simulations of patient-specific 3D nasal models generated from cone-beam computed tomography images. | 6 months |
| Effectiveness of current surgery in restoring nasal function based on nasal resistance | Analysis of significant difference in nasal resistance between pre-surgery and post-surgery data from computational fluid dynamics simulations of patient-specific 3D nasal models generated from cone-beam computed tomography images | 6 months |
| Effectiveness of current surgery in restoring nasal function based on nasal heat flux | Analysis of significant difference in nasal heat flux between pre-surgery and post-surgery data from computational fluid dynamics simulations of patient-specific 3D nasal models generated from cone-beam computed tomography images. | 6 months |
| Effectiveness of current surgery in restoring nasal function based on nasal moisture flux |
| Measure | Description | Time Frame |
|---|---|---|
| Change in patient-reported outcome (PRO) measures | Change PRO measures as measured by NOSE questionnaire | baseline, 2 weeks, 8 weeks, 6 months, 12 months |
| Change in patient-reported outcome (PRO) measures |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with unilateral cleft lip nasal deformity scheduled to undergo elective surgery for nasal obstruction at the Duke Cleft and Craniofacial Center.
Existing CBCT imaging data and QOL measures previously collected on healthy subjects will be used for comparison. Healthy subjects will not be prospectively enrolled in the study.
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| Name | Affiliation | Role |
|---|---|---|
| Dennis Frank-Ito, PhD | Duke University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Duke University Medical Center and affiliated practices | Durham | North Carolina | 27710 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37130297 | Derived | Russel SM, Chiang H, Finlay JB, Shah R, Marcus JR, Jang DW, Abi Hachem R, Goldstein BJ, Frank-Ito DO. Characterizing Olfactory Dysfunction in Patients with Unilateral Cleft Lip Nasal Deformities. Facial Plast Surg Aesthet Med. 2023 Nov-Dec;25(6):457-465. doi: 10.1089/fpsam.2022.0367. Epub 2023 May 2. |
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| ID | Term |
|---|---|
| D002971 | Cleft Lip |
| D015508 | Nasal Obstruction |
| ID | Term |
|---|---|
| D008047 | Lip Diseases |
| D009059 | Mouth Diseases |
| D009057 | Stomatognathic Diseases |
| D009056 | Mouth Abnormalities |
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| ID | Term |
|---|---|
| D014945 | Wound Healing |
| D000071066 | Patient Reported Outcome Measures |
| ID | Term |
|---|---|
| D012038 | Regeneration |
| D001686 | Biological Phenomena |
| D019538 | Health Care Surveys |
| D011795 | Surveys and Questionnaires |
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Analysis of significant difference in nasal moisture flux between pre-surgery and post-surgery data from computational fluid dynamics simulations of patient-specific 3D nasal models generated from cone-beam computed tomography images. |
| 6 months |
| Anatomical sites of greatest nasal obstruction | Analysis on agreement of computational fluid dynamics identified anatomical sites of greatest nasal obstruction from pre-surgery 3D nasal models and actual surgical anatomical sites. CFD identified sites of greatest nasal obstruction are regions in the airway with highest nasal resistance. | 6 months |
| Computational fluid dynamics based optimized treatment options for unilateral cleft lip nasal deformity patients based on volumetric airflow | Creation of virtual surgery nasal airway models based on computational fluid dynamics identified anatomical sites of greatest nasal obstruction. Computational fluid dynamics generated unilateral left and right side percent asymmetric will be computed used to identify the top three virtual surgery nasal airway models with best treatment potentials for unilateral cleft lip nasal deformity patients | 6 months |
| Computational fluid dynamics based optimized treatment options for unilateral cleft lip nasal deformity patients based on nasal resistance | Creation of virtual surgery nasal airway models based on computational fluid dynamics identified anatomical sites of greatest nasal obstruction. Computed nasal resistance will be used to identify the top three virtual surgery nasal airway models with best treatment potentials for unilateral cleft lip nasal deformity patients | 6 months |
| Computational fluid dynamics based optimized treatment options for unilateral cleft lip nasal deformity patients based on nasal heat flux | Creation of virtual surgery nasal airway models based on computational fluid dynamics identified anatomical sites of greatest nasal obstruction. Computed nasal moisture flux will be used to identify the top three virtual surgery nasal airway models with best treatment potentials for unilateral cleft lip nasal deformity patients | 6 months |
Change PRO measures as measured by SCHNOS questionnaire
| baseline, 2 weeks, 8 weeks, 6 months, 12 months |
| Change in patient-reported outcome (PRO) measures | Change PRO measures as measured by CLEFT-Q questionnaire | baseline, 2 weeks, 8 weeks, 6 months, 12 months |
| in vitro analysis for top three virtual surgery nasal models with best treatment based on nasal pressure | in vitro analysis from 3D printed plastic nasal replica of top three virtual surgery nasal models with best treatment potential will be done using unilateral airflow pressure. | 6 months |
| in vitro analysis for top three virtual surgery nasal models with best treatment based on unilateral volumetric airflow | in vitro analysis from 3D printed plastic nasal replica of top three virtual surgery nasal models with best treatment potential will be done using unilateral volumetric airflow rate. | 6 months |
| D018640 |
| Stomatognathic System Abnormalities |
| D000013 | Congenital Abnormalities |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |
| D009668 | Nose Diseases |
| D012140 | Respiratory Tract Diseases |
| D000402 | Airway Obstruction |
| D012131 | Respiratory Insufficiency |
| D012120 | Respiration Disorders |
| D010038 | Otorhinolaryngologic Diseases |
| D003625 |
| Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D006302 | Health Services Research |
| D006285 | Health Planning |
| D004472 | Health Care Economics and Organizations |
| D063868 | Patient Outcome Assessment |
| D017063 | Outcome Assessment, Health Care |
| D010043 | Outcome and Process Assessment, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
| D017531 | Health Care Evaluation Mechanisms |
| D011634 | Public Health |
| D004778 | Environment and Public Health |