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

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.

Inclusion Criteria:

1. 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.

2. 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