# Novel 3D Quantitative Dynamic MRI to Characterize Obstructive Sleep Apnea

> **NIH NIH R01** · UNIVERSITY OF IOWA · 2024 · $426,717

## Abstract

SUMMARY
An estimated 30-70% of obstructive sleep apnea (OSA) patients are intolerant to first-line
continuous positive airway pressure (CPAP) therapy for a variety of reasons. A variety of
alternatives to CPAP exist, including the 2014 FDA approved hypoglossal nerve stimulation
(HNS) therapy. The current clinical practice to screen OSA patients for HNS surgery is to
perform a drug induced sleep endoscopy (DISE) procedure to assess airway collapse.
However, DISE is challenged by several limitations including potential alteration of natural
airway collapse due to the inserted endoscope, the lack of imaging surrounding soft-tissue, the
lack of simultaneously imaging the full 3D extent of the upper airway, and the purely qualitative
interpretation of airway collapse. Despite these challenges, it is mainly used because there is no
better alternative. In this proposal, we propose to address this gap by systematically developing
a novel 3D dynamic MRI (3D-DMRI) scheme capable of quantitating airway collapse during
sleep. We propose a novel scheme that synergistically combine (a) parallel imaging via
dedicated airway coils, (b) motion robust 3D stack of spiral encoding, (c) learning based spatio-
temporal regularization, and (e) quantitative analysis to extract imaging phenotypes to
characterize 3D airway collapse. In Aim 1, we will develop the scheme and systematically
validate it on a cohort of OSA patients being screened for HNS therapy. In Aim 2, we will
develop a deep transfer learning based segmentation scheme to extract 3D-DMRI based
phenotypes that characterize spatio-temporal patterns of airway collapse. In Aim 3, we will
assess the clinical utility of our scheme to characterize the pattern of airway shaping and
collapse both in the awake and sleep state, and will evaluate it against existing DISE clinical
protocol. In aim 4, we will determine if the 3D-DMRI derived imaging-based biomarkers are
predictive of clinical outcomes of HNS therapy. This study will leverage the principal
investigator’s expertise in rapid upper-airway MRI, along with collaborators’ interdisciplinary
expertise in otorhinolaryngology, clinical sleep medicine, image analysis. Successful completion
of this study will showcase the feasibility of MRI-based “virtual endoscopy” and immediately lead
to several clinical trials for OSA. Specifically, we anticipate having demonstrated 3D-DMRI to be
an effective alternative to DISE for determining the eligibility of patients with OSA for HNS, and
show preliminary evidence if these biomarkers are predictive for HNS treatment success.

## Key facts

- **NIH application ID:** 10859931
- **Project number:** 1R01HL173483-01
- **Recipient organization:** UNIVERSITY OF IOWA
- **Principal Investigator:** Sajan Goud Lingala
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $426,717
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10859931

## Citation

> US National Institutes of Health, RePORTER application 10859931, Novel 3D Quantitative Dynamic MRI to Characterize Obstructive Sleep Apnea (1R01HL173483-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10859931. Licensed CC0.

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