Investigation of Deformable Image Registration Based Lung Ventilation Mapping for Radiation Therapy Using a Hybrid Hyperpolarized Gas MRI Technique
type: CreativeWork
description: Radiation-induced pulmonary toxicity poses a serious challenge and limiting factor in delivering a sufficient amount of dose to eradicate thoracic tumors without compromising lung function. Functional avoidance radiation therapy (RT) using lung ventilation mapping techniques would allow for preferential avoidance of functional lung tissue during radiotherapy and potentially reduce RT-induced lung injuries. Additionally, lung ventilation is also a key metric to assess lung function in patients with pulmonary diseases such as asthma, pulmonary embolism, cystic fibrosis, and chronic obstructive pulmonary disease (COPD). In contrast to global pulmonary function tests such as spirometry, ventilation images provide a regional measure of pulmonary function. Conventional methods for lung ventilation imaging include gamma camera scintigraphy and positron emission tomography scan after inhaling a gaseous radionuclide, as well as hyperpolarized (HP) gas magnetic resonance imaging (MRI) using Helium-3 and Xenon-129 as imaging contrast. Recently, a new method has been proposed in which deformable image registration (DIR) is performed on a pair of anatomical lung images at different respiratory phases to obtain the displacement vector field (DVF) between both phases, and generate a lung ventilation map from the Jacobian Determinant of the DVF. This DIR-based method is advantageous in its high image resolutions and simpler imaging procedures making it a more feasible option for implementation into the clinical workflow. However, current DIR-based lung ventilation methods have been largely hampered due to two major deficiencies: 1) current DIR algorithms are morphologically based, lacking of sufficient physiological realism and thus resulting in erroneous calculations of lung ventilation; and 2) there is a lack of validation of the DIR-based lung ventilation calculation against clinical ground truth, as well as large uncertainties and variations among different DIR algorithms. The …
abstract: Radiation-induced pulmonary toxicity poses a serious challenge and limiting factor in delivering a sufficient amount of dose to eradicate thoracic tumors without compromising lung function. Functional avoidance radiation therapy (RT) using lung ventilation mapping techniques would allow for preferential avoidance of functional lung tissue during radiotherapy and potentially reduce RT-induced lung injuries. Additionally, lung ventilation is also a key metric to assess lung function in patients with pulmonary diseases such as asthma, pulmonary embolism, cystic fibrosis, and chronic obstructive pulmonary disease (COPD). In contrast to global pulmonary function tests such as spirometry, ventilation images provide a regional measure of pulmonary function. Conventional methods for lung ventilation imaging include gamma camera scintigraphy and positron emission tomography scan after inhaling a gaseous radionuclide, as well as hyperpolarized (HP) gas magnetic resonance imaging (MRI) using Helium-3 and Xenon-129 as imaging contrast. Recently, a new method has been proposed in which deformable image registration (DIR) is performed on a pair of anatomical lung images at different respiratory phases to obtain the displacement vector field (DVF) between both phases, and generate a lung ventilation map from the Jacobian Determinant of the DVF. This DIR-based method is advantageous in its high image resolutions and simpler imaging procedures making it a more feasible option for implementation into the clinical workflow. However, current DIR-based lung ventilation methods have been largely hampered due to two major deficiencies: 1) current DIR algorithms are morphologically based, lacking of sufficient physiological realism and thus resulting in erroneous calculations of lung ventilation; and 2) there is a lack of validation of the DIR-based lung ventilation calculation against clinical ground truth, as well as large uncertainties and variations among different DIR algorithms. The …
author: Duarte, Isabella
keywords: Physics, Medical imaging, DIR, Hyperpolarized Gas, Jacobian, Lung Ventilation, Radiation Therapy, Ventilation Mapping
date published: 2020
date modified: 2026-07-24T02:07:17Z
provider: Duke University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Duke University

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10161/21011