Skip to main content

Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects.

Publication ,  Journal Article
Oakes, JM; Mummy, D; Poorbahrami, K; Zha, W; Fain, SB
Published in: IEEE Trans Biomed Eng
October 1, 2018

UNLABELLED: Combined, medical imaging data and respiratory computer simulations may facilitate novel insight into pulmonary disease phenotypes, including the structure/function relationships within the airways. This integration may ultimately enable improved classification and treatment of asthma. Severe asthma (15% of asthmatics) is particularly challenging to treat, as these patients do not respond well to inhaled therapeutics. METHODS: This study combines medical image data with patient-specific computational models to predict gas distributions and airway mechanics in healthy and asthmatic subjects. We achieve this by integrating segmental volume defect percent (SVDP), measured from hyperpolarized 3He MRI and CT images, to create models of patient-specific gas flow within the conducting airways. Predicted and measured SVDP distributions are achieved when the prescribed resistances are increased systematically. RESULTS: Because of differences in airway morphology and regional function, airway resistances and flow structures varied between the asthmatic subjects. Specifically, while mean SVDP was similar between the severe asthmatics (4.30±5.22 versus 3.54±5.98%), one subject exhibited abnormal flow structures, high near wall flow gradients, and enhanced conducting airway resistances (17.3E-3versus 1.1E-3 cmH2O-s/mL) in comparison to the other severe asthmatic subject. CONCLUSION: By coupling medical imaging data with computer simulations, we provide detailed insight into pathological flow characteristics and airway mechanics in asthmatics, beyond what could be inferred independently.

Duke Scholars

Published In

IEEE Trans Biomed Eng

DOI

EISSN

1558-2531

Publication Date

October 1, 2018

Location

United States

Related Subject Headings

  • Biomedical Engineering
  • 4603 Computer vision and multimedia computation
  • 4009 Electronics, sensors and digital hardware
  • 4003 Biomedical engineering
  • 0906 Electrical and Electronic Engineering
  • 0903 Biomedical Engineering
  • 0801 Artificial Intelligence and Image Processing
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Oakes, J. M., Mummy, D., Poorbahrami, K., Zha, W., & Fain, S. B. (2018). Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects. IEEE Trans Biomed Eng. https://doi.org/10.1109/TBME.2018.2872845
Oakes, Jessica M., David Mummy, Kamran Poorbahrami, Wei Zha, and Sean B. Fain. “Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects.IEEE Trans Biomed Eng, October 1, 2018. https://doi.org/10.1109/TBME.2018.2872845.
Oakes JM, Mummy D, Poorbahrami K, Zha W, Fain SB. Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects. IEEE Trans Biomed Eng. 2018 Oct 1;
Oakes, Jessica M., et al. “Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects.IEEE Trans Biomed Eng, Oct. 2018. Pubmed, doi:10.1109/TBME.2018.2872845.
Oakes JM, Mummy D, Poorbahrami K, Zha W, Fain SB. Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects. IEEE Trans Biomed Eng. 2018 Oct 1;

Published In

IEEE Trans Biomed Eng

DOI

EISSN

1558-2531

Publication Date

October 1, 2018

Location

United States

Related Subject Headings

  • Biomedical Engineering
  • 4603 Computer vision and multimedia computation
  • 4009 Electronics, sensors and digital hardware
  • 4003 Biomedical engineering
  • 0906 Electrical and Electronic Engineering
  • 0903 Biomedical Engineering
  • 0801 Artificial Intelligence and Image Processing