Journal article
Pulmonary CT and MRI phenotypes that help explain chronic pulmonary obstruction disease pathophysiology and outcomes
Journal of magnetic resonance imaging, Vol.43(3), pp.544-557
03/2016
DOI: 10.1002/jmri.25010
PMCID: PMC5207206
PMID: 26199216
Abstract
Pulmonary x-ray computed tomographic (CT) and magnetic resonance imaging (MRI) research and development has been motivated, in part, by the quest to subphenotype common chronic lung diseases such as chronic obstructive pulmonary disease (COPD). For thoracic CT and MRI, the main COPD research tools, disease biomarkers are being validated that go beyond anatomy and structure to include pulmonary functional measurements such as regional ventilation, perfusion, and inflammation. In addition, there has also been a drive to improve spatial and contrast resolution while at the same time reducing or eliminating radiation exposure. Therefore, this review focuses on our evolving understanding of patient-relevant and clinically important COPD endpoints and how current and emerging MRI and CT tools and measurements may be exploited for their identification, quantification, and utilization. Since reviews of the imaging physics of pulmonary CT and MRI and reviews of other COPD imaging methods were previously published and well-summarized, we focus on the current clinical challenges in COPD and the potential of newly emerging MR and CT imaging measurements to address them. Here we summarize MRI and CT imaging methods and their clinical translation for generating reproducible and sensitive measurements of COPD related to pulmonary ventilation and perfusion as well as parenchyma morphology. The key clinical problems in COPD provide an important framework in which pulmonary imaging needs to rapidly move in order to address the staggering burden, costs, as well as the mortality and morbidity associated with COPD.
Details
- Title: Subtitle
- Pulmonary CT and MRI phenotypes that help explain chronic pulmonary obstruction disease pathophysiology and outcomes
- Creators
- Eric A Hoffman - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USADavid A Lynch - Department of Radiology, National Jewish Health Center, Denver, Colorado, USAR Graham Barr - Department of Epidemiology, Columbia University Medical Center, New York, New York, USAEdwin J R van Beek - Clinical Research Imaging Centre, Queen's Medical Research Institute, University of Edinburgh, Scotland, UKGrace Parraga - Department of Medical Biophysics, University of Western Ontario, London, Canada
- Resource Type
- Journal article
- Publication Details
- Journal of magnetic resonance imaging, Vol.43(3), pp.544-557
- DOI
- 10.1002/jmri.25010
- PMID
- 26199216
- PMCID
- PMC5207206
- NLM abbreviation
- J Magn Reson Imaging
- ISSN
- 1053-1807
- eISSN
- 1522-2586
- Publisher
- United States
- Grant note
- P30 ES005605 / NIEHS NIH HHS R01 HL077612 / NHLBI NIH HHS R01 HL126838 / NHLBI NIH HHS R01 HL093081 / NHLBI NIH HHS R01 HL112986 / NHLBI NIH HHS R01 HL121270 / NHLBI NIH HHS P30 DK054759 / NIDDK NIH HHS
- Language
- English
- Date published
- 03/2016
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984051512002771
Metrics
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