CFD Simulations for Pediatric Sleep Apnea

(OSA-MRI Trial)

Recruiting in Palo Alto (17 mi)

Overseen by Alister Bates, PhD

Age: < 65

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Phase 4

Recruiting

Sponsor: Children's Hospital Medical Center, Cincinnati

Disqualifiers: Adequately treated with CPAP, braces, others

No Placebo Group

Prior Safety Data

Approved in 4 Jurisdictions

Trial Summary

What is the purpose of this trial?

To create a validated computational tool to predict surgical outcomes for pediatric patients with obstructive sleep apnea (OSA). The first line of treatment for children with OSA is to remove their tonsils and adenoids; however, these surgeries do not always cure the patient. Another treatment, continuous positive airway pressure (CPAP) is only tolerated by 50% of children. Therefore, many children undergo surgical interventions aimed at soft tissue structures surrounding the airway, such as tonsils, tongue, and soft palate, and/or the bony structures of the face. However, the success rates of these surgeries is surprisingly low. Therefore, there a need for a tool to improve the efficacy and predict which surgical option is going to benefit each individual patient most effectively. Computational fluid dynamics (CFD) simulations of respiratory airflow in the upper airways can provide this predictive tool, allowing the effects of various surgical options to be compared virtually and the option most likely to improve the patient's condition to be chosen. Previous CFD simulations have been unable to provide information about OSA as they were based on rigid geometries, or did not include neuromuscular motion, a key component in OSA. This project uses real-time magnetic resonance imaging (MRI) to provide the anatomy and motion of the airway to the CFD simulation, meaning that the exact in vivo motion is modeled for the first time. Furthermore, since the modeling is based on MRI, a modality which does not use ionizing radiation, it is suitable for longitudinal assessment of patients before and after surgical procedures. In vivo validation of these models will be achieved for the first time through comparison of CFD-based airflow velocity fields with those generated by phase-contrast MRI of inhaled hyperpolarized 129Xe gas. This research is based on data obtained from sleep MRIs achieved with the subject under sedation. While sedating the patient post-operatively is slightly more than minimal risk, the potential benefits to each patient outweigh this risk. As 58% of patients have persistent OSA postsurgery and the average trajectory of OSA severity is an increase over time, post-operative imaging and modeling can benefit the patient by identifying the changes to the airway made during surgery and which anatomy should be targeted in future treatments.

Do I have to stop taking my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment for pediatric obstructive sleep apnea?

Research shows that adenotonsillectomy, a surgical treatment for obstructive sleep apnea (OSA) in children, can change airflow characteristics and reduce airway collapse, although it is only successful in about 50% of obese children. Computational fluid dynamics (CFD) can help identify which patients might benefit most from surgery, potentially improving treatment outcomes. ^{1 2 3 4 5}

Is CFD simulation for pediatric sleep apnea safe for children?

The research does not provide specific safety data for CFD simulations in children with sleep apnea, but it discusses using these simulations to predict surgical outcomes and improve treatment planning, which suggests they are used as a non-invasive tool rather than a direct treatment. ^{1 2 4 6 7}

How does the treatment using CFD simulations for pediatric sleep apnea differ from other treatments?

This treatment is unique because it uses computational fluid dynamics (CFD) to model and predict the effectiveness of surgical interventions like adenotonsillectomy in children with obstructive sleep apnea, potentially improving the selection of patients who will benefit most from surgery. ^{1 2 3 4 5}

Eligibility Criteria

This trial is for children aged 5-18 with obstructive sleep apnea (OSA) who haven't improved after tonsil and adenoid removal, or those who can't tolerate CPAP therapy. It's also open to kids needing surgery for OSA as per a surgeon's assessment. Kids with braces/metal rods, well-managed on CPAP, or unable to undergo MRI are excluded.

Inclusion Criteria

I may have a blocked airway due to issues like a large tongue or small jaw.

I am between 5 and 18 years old.

My parents chose surgery for me without trying CPAP first.

Exclusion Criteria

My child cannot have sedatives due to health reasons.

Standard MRI exclusion criteria as set forth by the CCHMC Department of Radiology

My child is successfully treated with CPAP.

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Data Collection Pre-Surgery

Collect data characterizing upper airway anatomy, motion, and airflow using MRI and other measurements

4 weeks

Multiple visits for imaging and data collection

Surgical Intervention and Post-Surgery Data Collection

Perform surgical interventions and collect post-surgery data to assess changes in airway anatomy and function

12 weeks

Multiple visits for surgery and follow-up imaging

Follow-up

Participants are monitored for safety and effectiveness after treatment

12 weeks

Regular follow-up visits for monitoring

Treatment Details

Interventions

• 129-Xe (Other)
• Improving Outcomes in Pediatric Obstructive Sleep Apnea With Computational Fluid Dynamics (Other)

Trial Overview The study aims to develop a computational tool using Computational Fluid Dynamics (CFD) simulations based on real-time MRI data. This tool will predict which surgical options might best improve pediatric OSA by modeling airflow in the upper airways more accurately than previous methods.

Participant Groups

Group I: Phase 2 - Contrast 129Xe MRI ages 3-18 Experimental Treatment 1 Intervention

The research team plans to collect data characterizing upper airway anatomy, motion, and airflow. In patients, these data may be recorded before and after surgery. The data may include some or all of the following: (1) Static and dynamic proton MRI of the airway. (2) Respiratory airflow measurements. (3) Data from clinical PSGs. (5) Measurements may be repeated at different levels of CPAP.

Group II: Phase 1 - Contrast 129Xe MRI ages 5-18 Experimental Treatment 1 Intervention

The research team will collect data characterizing upper airway anatomy, motion, and airflow. In patients, these data may be recorded before and after surgery. The data may include some or all of the following: (1) Static and dynamic proton MRI of the airway. (2) Respiratory airflow measurements. (3) Phase contrast MRI of inhaled gas. (4) Data from clinical PSGs. (5) Measurements may be repeated at different levels of CPAP.

Improving Outcomes in Pediatric Obstructive Sleep Apnea With Computational Fluid Dynamics is already approved in United States, United States, European Union, European Union for the following indications:

🇺🇸 Approved in United States as Tonsillectomy and Adenoidectomy for:

• Pediatric Obstructive Sleep Apnea

🇺🇸 Approved in United States as CPAP and BPAP for:

• Pediatric Obstructive Sleep Apnea
• Moderate to Severe Sleep Apnea

🇪🇺 Approved in European Union as Tonsillectomy and Adenoidectomy for:

• Pediatric Obstructive Sleep Apnea

🇪🇺 Approved in European Union as CPAP and BPAP for:

• Pediatric Obstructive Sleep Apnea
• Moderate to Severe Sleep Apnea

Find a Clinic Near You

Research Locations Nearby Select from list below to view details:

Cincinnati Children's Hospital Medical Center Cincinnati, OH

Who Is Running the Clinical Trial?

Children's Hospital Medical Center, Cincinnati Lead Sponsor

National Institutes of Health (NIH) Collaborator

References

1. England pubmed.ncbi.nlm.nih.gov

Computational fluid dynamics study in children with obstructive sleep apnea. [2023] This study aims to identify characteristics in image-based computational fluid dynamics (CFD) in children with obstructive sleep apnea (OSA).

2. England pubmed.ncbi.nlm.nih.gov

Computational Modeling of Airway Obstruction in Sleep Apnea in Down Syndrome: A Feasibility Study. [2018] Current treatment options are successful in 40% to 60% of children with persistent obstructive sleep apnea after adenotonsillectomy. Residual obstruction assessments are largely subjective and do not clearly define multilevel obstruction. We endeavor to use computational fluid dynamics to perform virtual surgery and assess airflow changes in patients with Down syndrome and persistent obstructive sleep apnea. Three-dimensional airway models were reconstructed from respiratory-gated computed tomography and magnetic resonance imaging. Virtual surgeries were performed on 10 patients, mirroring actual surgeries. They demonstrated how surgical changes affect airflow resistance. Airflow and upper airway resistance was calculated from computational fluid dynamics. Virtual and actual surgery outcomes were compared with obstructive apnea-hypopnea index values. Actual surgery successfully treated 6 of 10 patients (postoperative obstructive apnea-hypopnea index

3. United States pubmed.ncbi.nlm.nih.gov

Computational fluid dynamics modeling of the upper airway of children with obstructive sleep apnea syndrome in steady flow. [2013] Computational fluid dynamic (CFD) analysis was used to model the effect of airway geometry on internal pressure in the upper airway of three children with obstructive sleep apnea syndrome (OSAS), and three controls. Model geometry was reconstructed from magnetic resonance images obtained during quiet tidal breathing, meshed with an unstructured grid, and solved at normative peak resting flow. The unsteady Reynolds-averaged Navier-Stokes equations were solved with steady flow boundary conditions in inspiration and expiration, using a two-equation low-Reynolds number turbulence model. Model results were validated using an in-vitro scale model, unsteady flow simulation, and reported nasal resistance measurements in children. Pharynx pressure drop strongly correlated to airway area restriction. Inspiratory pressure drop was primarily proportional to the square of flow, consistent with pressure losses due to convective acceleration caused by area restriction. On inspiration, in OSAS pressure drop occurred primarily between the choanae and the region where the adenoids overlap the tonsils (overlap region) due to airway narrowing, rather than in the nasal passages; in controls the majority of pressure drop was in the nasal passages. On expiration, in OSAS the majority of pressure drop occurred between the oropharynx (posterior to the tongue) and overlap region, and local minimum pressure in the overlap region was near atmospheric due to pressure recovery in the anterior nasopharynx. The results suggest that pharyngeal airway shape in children with OSAS significantly affects internal pressure distribution compared to nasal resistance. The model may also help explain regional dynamic airway narrowing during expiration.

4. United States pubmed.ncbi.nlm.nih.gov

Computational modeling of upper airway before and after adenotonsillectomy for obstructive sleep apnea. [2008] Adenotonsillectomy, the first-line surgical treatment for obstructive sleep apnea (OSA) in children, is successful in only 50% of obese children. Computational fluid dynamics tools, which have been applied to differentiate OSA patients from those without OSA based on the airway flow characteristics, can be potentially used to identify patients likely to benefit from surgical intervention. We present computational modeling of the upper airway before and after adenotonsillectomy in an obese female adolescent with OSA. The subject underwent upper airway imaging on a 1.5 Tesla magnetic resonance imaging (MRI) scanner, and three-dimensional airway models were constructed using airway boundary coordinates from cross-sectional MRI scans. Our results using computational simulations indicate that, in an obese child, the resolution of OSA after adenotonsillectomy is associated with changes in flow characteristics that result in decreased pressure differentials across the airway walls and thus lower compressive forces that predispose to airway collapse. Application of such findings to an obese child seeking surgical treatment for OSA can potentially lead to selection of the surgical procedure most likely to result in OSA resolution. Effective intervention for OSA in this high-risk group will result in reduction in morbidity and the public health concerns associated with OSA.

5. England pubmed.ncbi.nlm.nih.gov

Evaluation of human obstructive sleep apnea using computational fluid dynamics. [2023] Obstructive sleep apnea (OSA) severity might be correlated to the flow characteristics of the upper airways. We aimed to investigate the severity of OSA based on 3D models constructed from CT scans coupled with computational fluid dynamics (CFD) simulations. The CT scans of seven adult patients diagnosed with OSA were used to reconstruct the 3D models of the upper airways and CFD modeling and analyses were performed. Results from the fluid simulations were compared with the apnea-hypopnea index. Here we show a correlation between a CFD-based parameter, the adjusted pressure coefficient (Cp*), and the respective apnea-hypopnea index (Pearson's r = 0.91, p = 0.004), which suggests that the anatomical-based model coupled with CFD could provide functional and localized information for different regions of the upper airways.

6. United States pubmed.ncbi.nlm.nih.gov

Constructing a patient-specific computer model of the upper airway in sleep apnea patients. [2018] The use of computer simulation to develop a high-fidelity model has been proposed as a novel and cost-effective alternative to help guide therapeutic intervention in sleep apnea surgery. We describe a computer model based on patient-specific anatomy of obstructive sleep apnea (OSA) subjects wherein the percentage and sites of upper airway collapse are compared to findings on drug-induced sleep endoscopy (DISE).

7. United States pubmed.ncbi.nlm.nih.gov

Use of computational modeling to predict responses to upper airway surgery in obstructive sleep apnea. [2018] Despite the well-recognized consequences of obstructive sleep apnea (OSA), its treatment remains unsatisfactory. Therapeutic strategies are complicated by often poor adherence in the case of continuous positive airway pressure or the highly variable efficacy in the case of many upper airway surgeries. Computational models of the upper airway using finite element analysis to simulate the effects of various anatomic and physiologic manipulations on pharyngeal mechanics could be helpful in predicting surgical success.