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Updated: Feb 26, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
Published on: April 12, 2024
Assessing lung function using contrast-enhanced dual-energy computed tomography for potential applications in
Andréanne Lapointe1, Houda Bahig2, Danis Blais2
1Département de physique, Université de Montréal, Pavillon Roger-Gaudry (D-428), 2900 boulevard Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada.
Dual-energy CT (DECT) effectively measures lung function for radiation therapy planning, showing strong agreement with SPECT/CT. This functional imaging helps spare healthy lung tissue during treatment.
Area of Science:
- Medical Imaging
- Radiation Oncology
- Pulmonary Physiology
Background:
- Increasing interest in lung function imaging for radiation therapy.
- Goal to reduce post-radiation toxicities.
- Need for reliable functional data from imaging.
Purpose of the Study:
- Retrieve reliable functional information from contrast-enhanced dual-energy CT (DECT).
- Apply DECT-derived functional data in radiation therapy planning.
- Compare DECT functional data with single-energy CT (SECT) and SPECT/CT.
Main Methods:
- Retrospective analysis of 5 lung cancer patients.
- Acquired contrast-enhanced DECT and SPECT/CT scans.
- Processed DECT into iodine concentration maps to determine perfused blood volume.
- Computed differential lung function per lobe for DECT, SECT, and SPECT/CT.
Main Results:
- Strong correlation (r=0.91) between DECT and SPECT/CT for differential lung function per lobe.
- Moderate correlation (r=0.46) between DECT and SECT.
- DECT showed a 7% mean difference compared to SPECT/CT for left lung function.
- Identified nonfunctional lung areas via iodine concentration drops.
Conclusions:
- Successfully extracted iodine concentration maps from DECT for lung subvolume function calculation.
- DECT shows good agreement with SPECT/CT for functional lung assessment.
- Integrating DECT functional data into radiation therapy planning can optimize dose and spare healthy lung tissue.
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