DYMOSA: Computer Models of Airways in Children and Young Adults With Sleep Apnea and Down Syndrome

Sponsor

Children's Hospital Medical Center, Cincinnati (Other)

Overall Status

Enrolling by invitation

CT.gov ID

NCT01902407

Collaborator

National Heart, Lung, and Blood Institute (NHLBI) (NIH)

Enrollment

Location

201

Duration (Months)

0.4

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

The purpose of this research study is to develop a way of predicting with computers how surgery on the airway will affect night time breathing called Obstructive Sleep Apnea (OSA) in children with Down Syndrome.

A research measurement for airway resistance will also be done during the clinical sleep MRI. The airway resistance measurement will take about 10 minutes and is done during sleep. The airway resistance measurement is called critical closing pressure (Pcrit).

Condition or Disease	Intervention/Treatment	Phase
Down Syndrome Obstructive Sleep Apnea

Detailed Description

This is a proof-of-concept study to determine if a dynamic computational model can be used to predict surgical outcomes. If the results from the study are positive, they can be used to help design a larger subsequent study. The purpose of this research is to develop a computational model that simulates OSA and different surgical treatments for OSA in children and young adults with DS. Thus, the only population that will be studied is children and young adults with DS who have persistent OSA despite having previously undergone T&A.

Obstructive sleep apnea (OSA) occurs in 50-100% of patients with Down syndrome (DS) and can significantly cause and exacerbate medical problems in these patients. Current surgical management of children with DS is imperfect. There are variable surgical success rates for both first line surgery of palatine tonsillectomy and adenoidectomy (T&A) as well as secondary surgeries performed if and when T&A fails. There is a critical need for a diagnostic modality that takes into account airway anatomy, tissue compliance, and collapsibility to be able to predict surgical outcome and improve surgical planning in these patients. Our central hypothesis is that upper airway flow-structure interaction (FSI) modeling using three-dimensional (3-D) computational simulations from dynamic magnetic resonance imaging (MRI or MR) data can be used to predict surgical outcomes for children with DS who have OSA despite previous T&A. The long-term goal is to improve surgical outcome of children with Down syndrome and OSA by creating an accurate FSI predictive model. Such a diagnostic tool would help tailor surgical procedures to be more effective as well as identify and avoid unnecessary or unhelpful surgical procedures. These created models can in future be adjusted and applied to other populations with OSA. Our specific aims include: 1) In children with Down syndrome and persistent OSA despite previous T&A, to collect data characterizing upper airway anatomy, tissue compliance, and collapsibility; 2) to generate and validate individualized dynamic FSI models for each child and 3) to use the validated dynamic computational models to predict the success of surgical treatment on children with Down syndrome who have persistent OSA despite previous T&A. This work is innovative as it uses dynamic rather than static MR imaging data and applies a unique computational model that accurately captures the unsteadiness of the flow and accounts for the interaction between the airflow and the surrounding airway flexible structures.

Research components will involve two parts of the project. The first will be the generation, validation and use of computational models from MRI data. The second is the measure of critical closing pressure (Pcrit) on DS subjects who are at least three months post T&A, have OSA and are being evaluated for possible additional airway surgery. The measurement of Pcrit will be done during the research PSG (in the Sleep Center) and during the clinical sleep MRI (in the MRI suite). Pcrit measurements will be acquired with the use of a Continuous Positive Air Pressure (CPAP) mask during sleep. Additionally, to measure improvement in OSA based on quality of life (QOL) and sleep, the Obstructive Sleep Apnea questionnaire (OSA18) will be administered both preoperatively and postoperatively.

Study Design

Study Type:

Observational

Anticipated Enrollment :

73 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

Dynamic Computational Modeling of Obstructive Sleep Apnea in Down Syndrome

Study Start Date :

Mar 1, 2011

Anticipated Primary Completion Date :

Dec 1, 2027

Anticipated Study Completion Date :

Dec 1, 2027

Arms and Interventions

Arm	Intervention/Treatment
Diagnostic MRI and CT scan of the airway All patients seen at CCHMC (up to 90 years of age) who are scheduled to have a clinical sleep MRI or CT scan for their OSA airway or lung disease. Scheduled for both Sleep diagnostic tests (Sleep MRI and CT scans).

Outcome Measures

Primary Outcome Measures

Measurement of critical closing pressure of the airway-Sleep MRI [Day 1]
Measured in mmH2O

Eligibility Criteria

Criteria

Ages Eligible for Study:

1 Year to 90 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

All patients seen at CCHMC (up to 90 years of age) who are scheduled to have a clinical sleep MRI or CT scan for their OSA airway or lung disease.
Both Sleep diagnostic tests (Sleep MRI and CT scans).

Exclusion Criteria:

Those patients whose body weight (>350 pounds) or circumference is greater than what can be safely accommodated by the MRI scanner
Patients with pacemakers or other non-MRI compatible devices
Patients with extensive dental hardware that causes MR artifact obscuring visualization of the area of interest.
Body Mass Index (BMI) > 40