Semiautomated Ventilation Defect Quantification in Exercise-induced Bronchoconstriction Using Hyperpolarized Helium-3 Magnetic Resonance Imaging: A Repeatability Study

Wei Zha; David J Niles; Stanley J Kruger; Bernard J Dardzinski; Robert V Cadman; David G Mummy; Scott K Nagle; Sean B Fain

doi:10.1016/j.acra.2016.04.005

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Semiautomated Ventilation Defect Quantification in Exercise-induced Bronchoconstriction Using Hyperpolarized Helium-3 Magnetic Resonance Imaging: A Repeatability Study

Journal article

Peer reviewed

Semiautomated Ventilation Defect Quantification in Exercise-induced Bronchoconstriction Using Hyperpolarized Helium-3 Magnetic Resonance Imaging: A Repeatability Study

Wei Zha, David J Niles, Stanley J Kruger, Bernard J Dardzinski, Robert V Cadman, David G Mummy, Scott K Nagle and Sean B Fain

Academic radiology, Vol.23(9), pp.1104-1114

09/2016

DOI: 10.1016/j.acra.2016.04.005

PMCID: PMC9436394

PMID: 27263987

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https://www.ncbi.nlm.nih.gov/pmc/articles/9436394View

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Abstract

This study aimed to compare the performance of a semiautomated ventilation defect segmentation approach, adaptive K-means, with manual segmentation of hyperpolarized helium-3 magnetic resonance imaging in subjects with exercise-induced bronchoconstriction (EIB). Six subjects with EIB underwent hyperpolarized helium-3 magnetic resonance imaging and spirometry tests at baseline, post exercise, and recovery over two separate visits. Ventilation defects were analyzed by two methods. First, two independent readers manually segmented ventilation defects. Second, defects were quantified by an adaptive K-means method that corrected for coil sensitivity, applied a vesselness filter to estimate pulmonary vasculature, and segmented defects adaptively based on the overall low-intensity signals in the lungs. These two methods were then compared in four aspects: (1) ventilation defect percent (VDP) measurements, (2) correlation between spirometric measures and measured VDP, (3) regional VDP variations pre- and post exercise challenge, and (4) Dice coefficient for spatial agreement. The adaptive K-means method was ~5 times faster, and the measured VDP bias was under 2%. The correlation between predicted forced expiratory volume in 1 second over forced vital capacity and VDP measured by adaptive K-means (ρ = -0.64, P <0.0001) and by the manual method (ρ = -0.63, P <0.0001) yielded almost identical 95% confidence intervals. Neither method of measuring VDP indicated apical/basal or anterior dependence in this small study cohort. Compared to the manual method, the adaptive K-means method provided faster, reproducible, comparable measures of VDP in EIB and may be applied to a variety of lung diseases.

Bronchoconstriction - physiology

Spirometry

Reproducibility of Results

Humans

Respiratory Function Tests - methods

Magnetic Resonance Imaging - methods

Male

Lung - diagnostic imaging

Lung - physiopathology

Helium

Forced Expiratory Volume

Young Adult

Exercise

Adult

Female

Isotopes

Details

Title: Subtitle: Semiautomated Ventilation Defect Quantification in Exercise-induced Bronchoconstriction Using Hyperpolarized Helium-3 Magnetic Resonance Imaging: A Repeatability Study
Creators: Wei Zha - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI
David J Niles - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI
Stanley J Kruger - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI
Bernard J Dardzinski - Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Radiology and Radiological Sciences, Uniformed Services University of the Health Sciences, Bethesda, Maryland
Robert V Cadman - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI
David G Mummy - Department of Biomedical Engineering, University of Wisconsin-Madison, 1550 Engineering Drive, Madison, WI
Scott K Nagle - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI; Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI; Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin
Sean B Fain - Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI; Department of Biomedical Engineering, University of Wisconsin-Madison, 1550 Engineering Drive, Madison, WI; Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI. Electronic address: sfain@wisc.edu
Resource Type: Journal article
Publication Details: Academic radiology, Vol.23(9), pp.1104-1114
DOI: 10.1016/j.acra.2016.04.005
PMID: 27263987
PMCID: PMC9436394
NLM abbreviation: Acad Radiol
ISSN: 1076-6332
eISSN: 1878-4046
Publisher: United States
Grant note: KL2 TR000428 / NCATS NIH HHS UL1 TR000427 / NCATS NIH HHS
Language: English
Date published: 09/2016
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Health, Sport, and Human Physiology
Record Identifier: 9984051797802771

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