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Novel non-invasive assessment of upper airway inflammation in obstructive sleep apnea using positron emission tomography/magnetic resonance imaging

  • Sleep Breathing Physiology and Disorders • Original Article
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Abstract

Purpose

To develop a novel non-invasive technique to quantify upper airway inflammation using positron emission tomography/magnetic resonance imaging (PET/MRI) in patients with obstructive sleep apnea (OSA).

Methods

Patients with treatment naïve moderate-to-severe OSA underwent [18F]-fluoro-2-deoxy-d-glucose (FDG) PET/MRI. Three readers independently performed tracings of the pharyngeal soft tissue on MRI. Standardized uptake values (SUV) were generated from region of interest (ROI) tracings on corresponding PET images. Background SUV was measured from the sternocleidomastoid muscle. SUV and target-to-background (TBR) were compared across readers using intraclass correlation coefficient (ICC) analyses. SUV from individual image slices were compared between each reader using Bland–Altman plots and Pearson correlation coefficients. All tracings were repeated by one reader for assessment of intra-reader reliability.

Results

Five participants completed our imaging protocol and analysis. Median age, body mass index, and apnea–hypopnea index were 41 years (IQR 40.5–68.5), 32.7 kg/m2 (IQR 28.1–38.1), and 30.7 event per hour (IQR 19.5–48.1), respectively. The highest metabolic activity regions were consistently localized to palatine or lingual tonsil adjacent mucosa. Twenty-five ICC met criteria for excellent agreement. The remaining three were TBR measurements which met criteria for good agreement. Head-to-head comparisons revealed strong correlation between each reader.

Conclusions

Our novel imaging technique demonstrated reliable quantification of upper airway FDG avidity. This technology has implications for future work exploring local airway inflammation in individuals with OSA and exposure to pollutants. It may also serve as an assessment tool for response to OSA therapies.

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Data availability

All imaging and statistical analyses are presented in the current study. Full dataset used for analyses can be made available on request.

Code availability

Not applicable.

Abbreviations

AHI:

Apnea–hypopnea index

BMI:

Body mass index

CPAP:

Continuous positive airway pressure

CT:

Computed tomography

EDS:

Excessive daytime sleepiness

EMR:

Electronic medical record

ESS:

Epworth sleepiness scale

FDG:

[18F]-fluoro-2-deoxy-d-glucose

GFR:

Glomerular filtration rate

HSAT:

Home sleep apnea testing

ICC:

Intraclass correlation coefficient

IQR:

Interquartile range

MRI:

Magnetic resonance imaging

OSA:

Obstructive sleep apnea

PAT:

Peripheral arterial tonometry

PET:

Positron emission tomography

pRDI:

Peripheral arterial tonometry-respiratory disturbance index

PSG:

Polysomnography

ROI:

Region of interest

SCM:

Sternocleidomastoid

SUV:

Standardized uptake values

TBR:

Target-to-background ratio

TOF:

Time-of-flight

References

  1. Senaratna CV, Perret JL, Lodge CJ et al (2017) Prevalence of obstructive sleep apnea in the general population: a systematic review. Sleep Med Rev 34:70–81. https://doi.org/10.1016/j.smrv.2016.07.002

    Article  PubMed  Google Scholar 

  2. Eckert DJ, Malhotra A (2008) Pathophysiology of adult obstructive sleep apnea. Proc Am Thorac Soc 5(2):144–153. https://doi.org/10.1513/pats.200707-114MG

    Article  PubMed  PubMed Central  Google Scholar 

  3. Sekosan M, Zakkar M, Wenig BL, Olopade CO, Rubinstein I (1996) Inflammation in the uvula mucosa of patients with obstructive sleep apnea. Laryngoscope 106(8):1018–1020. https://doi.org/10.1097/00005537-199608000-00021

    Article  CAS  PubMed  Google Scholar 

  4. Kimoff RJ, Hamid Q, Divangahi M et al (2011) Increased upper airway cytokines and oxidative stress in severe obstructive sleep apnoea. Eur Respir J 38(1):89–97. https://doi.org/10.1183/09031936.00048610

    Article  CAS  PubMed  Google Scholar 

  5. Vicente E, Marin JM, Carrizo SJ et al (2016) Upper airway and systemic inflammation in obstructive sleep apnoea. Eur Respir J 48(4):1108–1117. https://doi.org/10.1183/13993003.00234-2016

    Article  CAS  PubMed  Google Scholar 

  6. Paulsen FP, Steven P, Tsokos M et al (2002) Upper airway epithelial structural changes in obstructive sleep-disordered breathing. Am J Respir Crit Care Med 166(4):501–509. https://doi.org/10.1164/rccm.2109099

    Article  PubMed  Google Scholar 

  7. Boyd JH, Petrof BJ, Hamid Q, Fraser R, Kimoff RJ (2004) Upper airway muscle inflammation and denervation changes in obstructive sleep apnea. Am J Respir Crit Care Med 170(5):541–546. https://doi.org/10.1164/rccm.200308-1100OC

    Article  PubMed  Google Scholar 

  8. Vogl TJ, Harth M, Siebenhandl P (2010) Different imaging techniques in the head and neck: assets and drawbacks. World J Radiol 2(6):224–229. https://doi.org/10.4329/wjr.v2.i6.224

    Article  PubMed  PubMed Central  Google Scholar 

  9. Ehman EC, Johnson GB, Villanueva-Meyer JE et al (2017) PET/MRI: where might it replace PET/CT? J Magn Reson Imaging 46(5):1247–1262. https://doi.org/10.1002/jmri.25711

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ciscar MA, Juan G, Martinez V et al (2001) Magnetic resonance imaging of the pharynx in OSA patients and healthy subjects. Eur Respir J 17(1):79–86. https://doi.org/10.1183/09031936.01.17100790

    Article  CAS  PubMed  Google Scholar 

  11. Welch KC, Foster GD, Ritter CT et al (2002) A novel volumetric magnetic resonance imaging paradigm to study upper airway anatomy. Sleep 25(5):532–542

    Article  Google Scholar 

  12. Schwab RJ, Pasirstein M, Pierson R et al (2003) Identification of upper airway anatomic risk factors for obstructive sleep apnea with volumetric magnetic resonance imaging. Am J Respir Crit Care Med 168(5):522–530. https://doi.org/10.1164/rccm.200208-866OC

    Article  PubMed  Google Scholar 

  13. Malhotra A, Huang Y, Fogel R et al (2006) Aging influences on pharyngeal anatomy and physiology: the predisposition to pharyngeal collapse. Am J Med 119(1):72.e9. https://doi.org/10.1016/J.AMJMED.2005.01.077

    Article  Google Scholar 

  14. Moon IJ, Han DH, Kim J-W et al (2010) Sleep magnetic resonance imaging as a new diagnostic method in obstructive sleep apnea syndrome. Laryngoscope 120(12):2546–2554. https://doi.org/10.1002/lary.21112

    Article  PubMed  Google Scholar 

  15. Chi L, Comyn F-L, Mitra N et al (2011) Identification of craniofacial risk factors for obstructive sleep apnoea using three-dimensional MRI. Eur Respir J 38(2):348–358. https://doi.org/10.1183/09031936.00119210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Barrera JE (2011) Sleep magnetic resonance imaging: dynamic characteristics of the airway during sleep in obstructive sleep apnea syndrome. Laryngoscope 121(6):1327–1335. https://doi.org/10.1002/lary.21810

    Article  PubMed  Google Scholar 

  17. Kavcic P, Koren A, Koritnik B, Fajdiga I, Groselj LD (2015) Sleep magnetic resonance imaging with electroencephalogram in obstructive sleep apnea syndrome. Laryngoscope 125(6):1485–1490. https://doi.org/10.1002/lary.25085

    Article  PubMed  Google Scholar 

  18. Chiffer RC, Schwab RJ, Keenan BT, Borek RC, Thaler ER (2015) Volumetric MRI analysis pre- and post-transoral robotic surgery for obstructive sleep apnea. Laryngoscope 125(8):1988–1995. https://doi.org/10.1002/lary.25270

    Article  PubMed  Google Scholar 

  19. Feng Y, Keenan BT, Wang S et al (2018) Dynamic upper airway imaging during wakefulness in obese subjects with and without sleep apnea. Am J Respir Crit Care Med 198(11):1435–1443. https://doi.org/10.1164/rccm.201711-2171OC

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kubota R, Yamada S, Kubota K, Ishiwata K, Tamahashi N, Ido T (1992) Intratumoral distribution of fluorine-18-fluorodeoxyglucose in vivo: high accumulation in macrophages and granulation tissues studied by microautoradiography. J Nucl Med 33(11):1972–1980

    CAS  PubMed  Google Scholar 

  21. Gotthardt M, Bleeker-Rovers CP, Boerman OC, Oyen WJG (2010) Imaging of inflammation by PET, conventional scintigraphy, and other imaging techniques. J Nucl Med 51(12):1937–1949. https://doi.org/10.2967/jnumed.110.076232

    Article  PubMed  Google Scholar 

  22. Torigian DA, Zaidi H, Kwee TC et al (2013) PET/MR imaging: technical aspects and potential clinical applications. Radiology 267(1):26–44. https://doi.org/10.1148/radiol.13121038

    Article  PubMed  Google Scholar 

  23. Shih I-L, Wei S-C, Yen R-F et al (2018) PET/MRI for evaluating subclinical inflammation of ulcerative colitis. J Magn Reson Imaging 47(3):737–745. https://doi.org/10.1002/jmri.25795

    Article  PubMed  Google Scholar 

  24. Nensa F, Beiderwellen K, Heusch P, Wetter A (2014) Clinical applications of PET/MRI: current status and future perspectives. Diagnostic Interv Radiol 20(5):438–447. https://doi.org/10.5152/dir.2014.14008

    Article  Google Scholar 

  25. Kuhn FP, Hüllner M, Mader CE et al (2014) Contrast-enhanced PET/MR imaging versus contrast-enhanced PET/CT in head and neck cancer: how much MR information is needed? J Nucl Med 55(4):551–558. https://doi.org/10.2967/jnumed.113.125443

    Article  CAS  PubMed  Google Scholar 

  26. Cavaliere C, Romeo V, Aiello M et al (2017) Multiparametric evaluation by simultaneous PET-MRI examination in patients with histologically proven laryngeal cancer. Eur J Radiol 88:47–55. https://doi.org/10.1016/j.ejrad.2016.12.034

    Article  PubMed  Google Scholar 

  27. Kim AM, Keenan BT, Jackson N et al (2014) Metabolic activity of the tongue in obstructive sleep apnea. A novel application of FDG positron emission tomography imaging. Am J Respir Crit Care Med 189(11):1416–1425

    Article  Google Scholar 

  28. Kundel V, Trivieri MG, Karakatsanis NA et al (2018) Assessment of atherosclerotic plaque activity in patients with sleep apnea using hybrid positron emission tomography/magnetic resonance imaging (PET/MRI): a feasibility study. Sleep Breath 22(4):1125–1135. https://doi.org/10.1007/s11325-018-1646-2

    Article  PubMed  PubMed Central  Google Scholar 

  29. Johns MW (1991) A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14(6):540–545

    Article  CAS  Google Scholar 

  30. Yalamanchali S, Farajian V, Hamilton C, Pott TR, Samuelson CG, Friedman M (2013) Diagnosis of obstructive sleep apnea by peripheral arterial tonometry. JAMA Otolaryngol Neck Surg 139(12):1343. https://doi.org/10.1001/jamaoto.2013.5338

    Article  Google Scholar 

  31. Ng S, Chan T, To K et al (2010) Validation of Embletta portable diagnostic system for identifying patients with suspected obstructive sleep apnoea syndrome (OSAS). Respirology 15(2):336–342. https://doi.org/10.1111/j.1440-1843.2009.01697

    Article  PubMed  Google Scholar 

  32. Pittman SD, Ayas NT, MacDonald MM, Malhotra A, Fogel RB, White DP (2004) Using a wrist-worn device based on peripheral arterial tonometry to diagnose obstructive sleep apnea: in-laboratory and ambulatory validation. Sleep 27(5):923–933. https://doi.org/10.1093/sleep/27.5.923

    Article  PubMed  Google Scholar 

  33. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet (London, England) 1(8476):307–310

    Article  CAS  Google Scholar 

  34. Nakamoto Y, Tatsumi M, Hammoud D, Cohade C, Osman MM, Wahl RL (2005) Normal FDG distribution patterns in the head and neck: PET/CT evaluation. Radiology 234(3):879–885. https://doi.org/10.1148/radiol.2343030301

    Article  PubMed  Google Scholar 

  35. Wang Y, Chiu E, Rosenberg J, Gambhir SS (2007) Standardized uptake value atlas: characterization of physiological 2-deoxy-2-[18F]fluoro-d-glucose uptake in normal tissues. Mol Imaging Biol 9(2):83–90. https://doi.org/10.1007/s11307-006-0075-y

    Article  PubMed  Google Scholar 

  36. Schwarz EI, Puhan MA, Schlatzer C, Stradling JR, Kohler M (2015) Effect of CPAP therapy on endothelial function in obstructive sleep apnoea: a systematic review and meta-analysis. Respirology 20(6):889–895. https://doi.org/10.1111/resp.12573

    Article  PubMed  Google Scholar 

  37. Mehra R, Benjamin EJ, Shahar E et al (2006) Association of nocturnal arrhythmias with sleep-disordered breathing. Am J Respir Crit Care Med 173(8):910–916. https://doi.org/10.1164/rccm.200509-1442OC

    Article  PubMed  PubMed Central  Google Scholar 

  38. Gottlieb DJ, Yenokyan G, Newman AB et al (2010) Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure. Circulation 122(4):352–360. https://doi.org/10.1161/CIRCULATIONAHA.109.901801

    Article  PubMed  PubMed Central  Google Scholar 

  39. Peker Y, Glantz H, Eulenburg C, Wegscheider K, Herlitz J, Thunström E (2016) Effect of positive airway pressure on cardiovascular outcomes in coronary artery disease patients with nonsleepy obstructive sleep apnea. The RICCADSA Randomized Controlled Trial. Am J Respir Crit Care Med. 194(5):613–620. https://doi.org/10.1164/rccm.201601-0088OC

    Article  CAS  PubMed  Google Scholar 

  40. Young T, Finn L, Peppard PE et al (2008) Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort. Sleep 31(8):1071–1078

    PubMed  PubMed Central  Google Scholar 

  41. Marshall NS, Wong KKH, Cullen SRJ, Knuiman MW, Grunstein RR (2014) Sleep apnea and 20-year follow-up for all-cause mortality, stroke, and cancer incidence and mortality in the Busselton health study cohort. J Clin Sleep Med 10(4):355–362. https://doi.org/10.5664/jcsm.3600

    Article  PubMed  PubMed Central  Google Scholar 

  42. de la Peña Bravo M, Serpero LD, Barceló A, Barbé F, Agustí A, Gozal D (2007) Inflammatory proteins in patients with obstructive sleep apnea with and without daytime sleepiness. Sleep Breath. 11(3):177–185. https://doi.org/10.1007/s11325-007-0100-7

    Article  Google Scholar 

  43. DeMartino T, El GR, Wang L et al (2016) Oxidative stress and inflammation differentially elevated in objective versus habitual subjective reduced sleep duration in obstructive sleep apnea. Sleep 39(7):1361–1369. https://doi.org/10.5665/sleep.5964

    Article  PubMed  PubMed Central  Google Scholar 

  44. Li Y, Vgontzas AN, Fernandez-Mendoza J et al (2017) Objective, but not subjective, sleepiness is associated with inflammation in sleep apnea. Sleep 40(2):zsw033. https://doi.org/10.1093/sleep/zsw033

    Article  Google Scholar 

  45. Heusch P, Buchbender C, Beiderwellen K et al (2013) Standardized uptake values for [18F] FDG in normal organ tissues: comparison of whole-body PET/CT and PET/MRI. Eur J Radiol 82(5):870–876. https://doi.org/10.1016/j.ejrad.2013.01.008

    Article  PubMed  Google Scholar 

  46. Iagaru A, Mittra E, Minamimoto R et al (2015) Simultaneous whole-body time-of-flight 18F-FDG PET/MRI: a pilot study comparing SUVmax with PET/CT and assessment of MR image quality. Clin Nucl Med 40(1):1–8. https://doi.org/10.1097/RLU.0000000000000611

    Article  PubMed  PubMed Central  Google Scholar 

  47. Jadvar H, Colletti PM (2014) Competitive advantage of PET/MRI. Eur J Radiol 83(1):84–94. https://doi.org/10.1016/j.ejrad.2013.05.028

    Article  PubMed  Google Scholar 

  48. Broski SM, Goenka AH, Kemp BJ, Johnson GB (2018) Clinical PET/MRI: 2018 update. Am J Roentgenol 211(2):295–313. https://doi.org/10.2214/AJR.18.20001

    Article  Google Scholar 

  49. Mehranian A, Zaidi H (2015) Impact of time-of-flight pet on quantification errors in MR imaging-based attenuation correction. J Nucl Med 56(4):635–641. https://doi.org/10.2967/jnumed.114.148817

    Article  PubMed  Google Scholar 

  50. Ziai P, Hayeri MR, Salei A et al (2016) Role of optimal quantification of FDG PET imaging in the clinical practice of radiology. Radiographics 36(2):481–496. https://doi.org/10.1148/rg.2016150102

    Article  PubMed  Google Scholar 

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Acknowledgements

Support for this study was provided by the American Academy of Sleep Medicine Foundation through a Focused Project Award (126-FP-15) to Dr. Neomi Shah.

Funding

The study was funded by an American Academy of Sleep Medicine Foundation Focused Project Award (126-FP-15) to Dr. Shah. Dr. Shah also has funding from the National Institute of Health/National Heart, Lung, and Blood Institute (1R01HL143221-01). Dr. Cohen has funding from the American Thoracic Society’s ASPIRE Fellowship.

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All authors contributed meaningfully to this work. All authors have seen and approved this manuscript for publication.

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Correspondence to Oren Cohen or Neomi A. Shah.

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The study was approved by the Institutional Review Board at the Icahn School of Medicine at Mount Sinai.

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Cohen, O., John, M.M., Kaufman, A.E. et al. Novel non-invasive assessment of upper airway inflammation in obstructive sleep apnea using positron emission tomography/magnetic resonance imaging. Sleep Breath 26, 1087–1096 (2022). https://doi.org/10.1007/s11325-021-02480-3

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  • DOI: https://doi.org/10.1007/s11325-021-02480-3

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