Using Hyperpolarized 129Xe MRI to Quantify the Pulmonary Ventilation Distribution.
Journal Article (Journal Article)
RATIONALE AND OBJECTIVES: Ventilation heterogeneity is impossible to detect with spirometry. Alternatively, pulmonary ventilation can be imaged three-dimensionally using inhaled 129Xe magnetic resonance imaging (MRI). To date, such images have been quantified primarily based on ventilation defects. Here, we introduce a robust means to transform 129Xe MRI scans such that the underlying ventilation distribution and its heterogeneity can be quantified. MATERIALS AND METHODS: Quantitative 129Xe ventilation MRI was conducted in 12 younger (24.7 ± 5.2 years) and 10 older (62.2 ± 7.2 years) healthy individuals, as well as in 9 younger (25.9 ± 6.4 yrs) and 10 older (63.2 ± 6.1 years) asthmatics. The younger healthy population was used to establish a reference ventilation distribution and thresholds for six intensity bins. These bins were used to display and quantify the ventilation defect region (VDR), the low ventilation region (LVR), and the high ventilation region (HVR). RESULTS: The ventilation distribution in young subjects was roughly Gaussian with a mean and standard deviation of 0.52 ± 0.18, resulting in VDR = 2.1 ± 1.3%, LVR = 15.6 ± 5.4%, and HVR = 17.4 ± 3.1%. Older healthy volunteers exhibited a significantly right-skewed distribution (0.46 ± 0.20, P = 0.034), resulting in significantly increased VDR (7.0 ± 4.8%, P = 0.008) and LVR (24.5 ± 11.5%, P = 0.025). In the asthmatics, VDR and LVR increased in the older population, and HVR was significantly reduced (13.5 ± 4.6% vs 18.9 ± 4.5%, P = 0.009). Quantitative 129Xe MRI also revealed altered ventilation heterogeneity in response to albuterol in two asthmatics with normal spirometry. CONCLUSIONS: Quantitative 129Xe MRI provides a robust and objective means to display and quantify the pulmonary ventilation distribution, even in subjects who have airway function impairment not appreciated by spirometry.
Full Text
Duke Authors
Cited Authors
- He, M; Driehuys, B; Que, LG; Huang, Y-CT
Published Date
- December 2016
Published In
Volume / Issue
- 23 / 12
Start / End Page
- 1521 - 1531
PubMed ID
- 27617823
Pubmed Central ID
- PMC5411263
Electronic International Standard Serial Number (EISSN)
- 1878-4046
Digital Object Identifier (DOI)
- 10.1016/j.acra.2016.07.014
Language
- eng
Conference Location
- United States