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

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details. Identifier: NCT01902407
Recruitment Status : Recruiting
First Posted : July 18, 2013
Last Update Posted : July 2, 2017
National Heart, Lung, and Blood Institute (NHLBI)
Information provided by (Responsible Party):
Children's Hospital Medical Center, Cincinnati

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.

Subjects will be in the research study for approximately a year. Participation in this research study will involves a screening visit and 1 overnight sleep study (PSG) for research purposes that will be done before airway surgery. During the research sleep study, a measurement will be taken for airway resistance. 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
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 Type : Observational
Estimated Enrollment : 73 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Dynamic Computational Modeling of Obstructive Sleep Apnea in Down Syndrome
Study Start Date : March 2011
Estimated Primary Completion Date : December 2018
Estimated Study Completion Date : December 2019

Resource links provided by the National Library of Medicine

Down syndrome and OSA
Children and young adults with Down Syndrome who also have Obstructive Sleep Apnea

Primary Outcome Measures :
  1. Measurement of critical closing pressure of the airway-Sleep MRI [ Time Frame: Day 1 ]
    Measured in mmH2O

Information from the National Library of Medicine

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Ages Eligible for Study:   1 Year to 21 Years   (Child, Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Children and young adults with Down syndrome and OSA

Inclusion Criteria:

  • Down Syndrome
  • Ages 1-24 years
  • Post T&A of 3 months or greater that can also include lingual tonsillectomy.
  • OSA with Obstructive Index (OI) of 4 or higher and undergoing work up for regrowth of adenoid tissue, enlarged lingual tonsils, macroglossia, and/or glossoptosis

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT01902407

Contact: Angela Duggins, RN, BSN 513-636-5033

United States, Ohio
Cincinnati Children's Hospital Medical Center Recruiting
Cincinnati, Ohio, United States, 45229
Contact: Kathleen Fields, BA, RC         
Principal Investigator: Raouf S Amin, MD         
Sponsors and Collaborators
Children's Hospital Medical Center, Cincinnati
National Heart, Lung, and Blood Institute (NHLBI)
Principal Investigator: Raouf Amin, MD Children's Hospital Medical Center, Cincinnati

Publications automatically indexed to this study by Identifier (NCT Number):
Responsible Party: Children's Hospital Medical Center, Cincinnati Identifier: NCT01902407     History of Changes
Other Study ID Numbers: CIN001-Dymosa
R01HL105206-01 ( U.S. NIH Grant/Contract )
First Posted: July 18, 2013    Key Record Dates
Last Update Posted: July 2, 2017
Last Verified: June 2017

Keywords provided by Children's Hospital Medical Center, Cincinnati:
Critical closing pressure
Down syndrome
Obstructive Sleep Apnea
Sleep MRI

Additional relevant MeSH terms:
Sleep Apnea Syndromes
Down Syndrome
Sleep Apnea, Obstructive
Pathologic Processes
Respiration Disorders
Respiratory Tract Diseases
Signs and Symptoms, Respiratory
Signs and Symptoms
Sleep Disorders, Intrinsic
Sleep Wake Disorders
Nervous System Diseases
Intellectual Disability
Neurobehavioral Manifestations
Neurologic Manifestations
Abnormalities, Multiple
Congenital Abnormalities
Chromosome Disorders
Genetic Diseases, Inborn