Tracheomalacia
Conditions
Keywords
Tracheomalacia in Children
Brief summary
The purpose of this pilot interventional study is to evaluate the use of Dynamic Airway Computed Tomography (DA-CT) for diagnosis of tracheomalacia in children 0-18 years for whom flexible bronchoscopy has been performed. The primary aims are to evaluate the diagnostic accuracy, image quality, and radiation exposure of DA-CT as a potential noninvasive alternative to the gold standard of flexible bronchoscopy in the diagnosis of tracheomalacia. The results from this pilot study will help to estimate sample size for a larger-scale study with more precise estimates of DA-CT diagnostic potential.
Interventions
DEVICEDynamic Airway CT scan (DA-CT)
Patient will be asked to perform movements during the scan.
Sponsors
NYU Langone Health
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
0 Years to 18 Years
Healthy volunteers
No
Inclusion criteria
* Participants 0-18 years old, with * Clinically indicated flexible bronchoscopy has been performed
Exclusion criteria
* Pregnancy or breastfeeding * Unable to undergo CT scanning without sedation * Patients with tracheostomy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Severity of dynamic narrowing on Flexible Bronchoscopy | Through study completion, an average of 1 year | Video recordings and images will be deidentified and reviewed by pediatric pulmonologists and scores averaged. Severity of dynamic narrowing will be classified as follows: mild: 50%-74%, moderate: 75%-89%, severe: \>90%. |
| Severity of Maximal Airway Change (MAC) on DA-CT | Through study completion, an average of 1 year | Severity of MAC will be classified as follows: mild: 33%-49%, moderate: 50%-66%, severe: \>67%. This outcome will be measured using the following equation: MAC = tracheal cross-sectional (CSA) at narrowed segment in inspiration/CSA of trachea at thoracic inlet in inspiration |
| Severity of Excessive dynamic airway collapse (EDAC) on DA-CT | Through study completion, an average of 1 year | Severity of EDAC will be classified as follows: mild: 50%-74%, moderate: 75%-89%, severe: \>90%. This outcome will be measured using the following equation: EDAC = CSA at airway segment in expiration/CSA at same location in inspiration |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Qualitative Analysis of DA-CT delineation of large airways based on 5-point Likert scale | Through study completion, an average of 1 year | 5-point Likert scale will be used as follows: (1) Very Poor, (2) Poor, (3) Fair, (4) Good, (5) Excellent |
| Qualitative Analysis of DA-CT delineation of small airways based on 5-point Likert scale | Through study completion, an average of 1 year | 5-point Likert scale will be used as follows: (1) Very Poor, (2) Poor, (3) Fair, (4) Good, (5) Excellent |
| Contrast-to-noise-ratio (CNR) of DA-CT scanners | Through study completion, an average of 1 year | This outcome will be measured using the following equation: CNR = (mean Hounsfield Units (HU) in the artery regions of interest (ROI) - mean HU in the tracheal air column ROI) / image noise inside the trachea. |
| Radiation exposure of DA-CT scanners | Through study completion, an average of 1 year | The effective dose (in mSv) will be automatically calculated with tissue weighting factors |
| Qualitative Analysis of DA-CT noise texture based on 5-point Likert scale | Through study completion, an average of 1 year | 5-point Likert scale will be used as follows: (1) Very Poor, (2) Poor, (3) Fair, (4) Good, (5) Excellent |
| Qualitative Analysis of DA-CT Image Quality based on 5-point Likert scale | Through study completion, an average of 1 year | 5-point Likert scale will be used as follows: (1) Very Poor, (2) Poor, (3) Fair, (4) Good, (5) Excellent |
| Qualitative Analysis of DA-CT image noise based on 5-point Likert scale | Through study completion, an average of 1 year | 5-point Likert scale will be used as follows: (1) Very Poor, (2) Poor, (3) Fair, (4) Good, (5) Excellent |
Countries
United States
Contacts
Primary ContactSoumia Hammouda
Outcome results
None listed