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using real-time multi-slice MRI during CPAP

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1 using real-time multi-slice MRI during CPAP
Evaluation of upper airway neuromuscular reflex and passive collapsibility using real-time multi-slice MRI during CPAP Weiyi Chen, Krishna S. Nayak, Magnetic Resonance Engineering Laboratory Motivation & Introduction Results Obstructive sleep apnea (OSA) is a heterogeneous disorder characterized by repetitive upper airway (UA) collapse during sleep1. Key pathophysiologic causes likely include airway collapsibility and muscle responsiveness. Continues positive airway pressure (CPAP) is the most widely used treatment for OSA. We apply a simultaneous multi-slice (SMS) real-time (RT) MRI technique2 to quantify UA changes, by alternating CPAP level between therapeutic and sub-therapeutic levels. Fig. 1. Representative data from a healthy control and an OSA patient Experiments Experiments: Four adolescent OSA patients (3M/1F) Three healthy volunteers (3M) CPAP level was alternated between a pre-titrated therapeutic and a sub-therapeutic level.   Acquisition: GE EXCITE HD23 3T clinical scanner with a 6-ch carotid coil. SMS golden angle radial CAIPIRINHA fast GRE sequence2. 1mm in-plane spatial resolution and 3 simultaneous slices, with 96ms temporal resolution. Data Analysis: A semi-automated region growing algorithm to segment the airway. Upper airway loop gain (UALG) represents the stability of neuromuscular reflex system to recover from sudden ventilation reduction. The fluctuation of airway area (FAA) represents the passive collapsibility of upper airway. Fig. 2. SMS RT-MRI during rapid CPAP change Discussion & Conclusion Directly measured active (UALG) and passive (FAA) traits with specific airway location, and simultaneously visualizing collapse dynamics. Observations reinforce the need for personalized treatment for OSA patients3. The proposed experiment can help locate the most collapsible airway sites, with specific possible reasons (anatomical or physiological). Eckert, D. J, et al. Defining phenotypic causes of obstructive sleep apnea: Identification of novel therapeutic targets. Am. J. Respir. Crit. Care Med. 188, 996–1004 (2013). Wu, Z., Chen, W., Khoo, M. C. K., Davidson Ward, S. L. & Nayak, K. S. Evaluation of upper airway collapsibility using real-time MRI. J. Magn. Reson. Imaging 44, 158–167 (2016). Pack, A. I. Application of Personalized, Predictive, Preventative, and Participatory (P4) Medicine to Obstructive Sleep Apnea. A Roadmap for Improving Care? Ann. Am. Thorac. Soc. 13, 1456–1467 (2016) grant sponsor: NIH; grant number: R01- HL


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