MENU

Click here to

×

Are you sure ?

Yes, do it No, cancel
  1. Home
  2. Meeting Program
  3. All Sessions
  4. All Joint Imaging-Therapy General ePoster Discussion
  5. Development of Digital Thoracic Phantoms Based On Physiological Modeling of Respiratory Motion From Hyperpolarized Gas Tagging MRI Technique

Development of Digital Thoracic Phantoms Based On Physiological Modeling of Respiratory Motion From Hyperpolarized Gas Tagging MRI Technique

I Duarte1*, T Cui2 , W Miller3 , F Yin1 , J Cai1,4 , (1) Duke University Medical Center, Durham, NC, (2) Cleveland Clinic, Cleveland, OH, (3) University of Virginia, Charlottesville, Virginia, (4) The Hong Kong Polytechnic University, Kowloon, Yau Tsim Mong

Presentations

(Tuesday, 7/31/2018) 3:45 PM - 4:15 PM

Room: Exhibit Hall | Forum 2

Purpose: To develop physiologically-plausible digital thoracic phantoms through respiratory motion modelling based on a combination of Hyperpolarized (HP) Gas tagging Magnetic Resonance Imaging (MRI) technique and Deformable Image Registration (DIR) of high-resolution proton MRI (2.5mm x 2.5mm x 2.5mm).

Methods: Lung images for three healthy subjects were acquired at end-of-inhalation (EOI) and end-of-exhalation (EOE) phases using a HP gas tagging MRI and a high-resolution proton MRI technique. The center of mass of the tagged grids was tracked from one phase to the other to obtain the ground-truth displacement vector field (DVF) within the lungs. The resolution of the physiologically-based sparse DVF, of approximately 270 grids, was increased through a cubic interpolation algorithm. A ventilation map was generated by calculating the Jacobian of this ground-truth DVF as a metric of lung function. In order to have a respiratory motion model of the entire thorax, the tagging-based DVF was used to optimize a DVF of the entire thorax obtained through DIR of the proton MRI. The optimization was performed by implementing a cost function that minimized the differences between the DVF from the tagging-MRI and the DVF from the proton-MRI, while preserving the ground-truth ventilation as the lung function metric in this study. To complete the digital phantom, a smoothing function which utilizes a Gaussian filter was applied to the combined DVFs in order to ensure continuity in the lung border regions.

Results: Physiologically-based thoracic digital phantoms were created based on optimization of DIR-based DVFs with ground-truth DVFs from a HP gas tagging MRI technique. The respiratory motion outside the lungs was modeled through DIR, and DVF continuity in the lung borders was successfully addressed through a smoothing algorithm.

Conclusion: The created digital phantoms provide a realistic respiratory motion model that can potentially be used as a validation tool for DIR standardization.

Funding Support, Disclosures, and Conflict of Interest: NIH grant: R21CA195317

Keywords

Phantoms, Deformation, Lung

Taxonomy

IM/TH- Image registration : MRI

Contact Email

Additional Links