Modeling the impact of out-of-phase ventilation on normal lung tissue response to radiation dose

Eric M Wallat; Mattison J Flakus; Antonia E Wuschner; Wei Shao; Gary E Christensen; Joseph M Reinhardt; Andrew M Baschnagel; John E Bayouth

doi:10.1002/mp.14146

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Modeling the impact of out-of-phase ventilation on normal lung tissue response to radiation dose

Journal article

Peer reviewed

Modeling the impact of out-of-phase ventilation on normal lung tissue response to radiation dose

Eric M Wallat, Mattison J Flakus, Antonia E Wuschner, Wei Shao, Gary E Christensen, Joseph M Reinhardt, Andrew M Baschnagel and John E Bayouth

Medical physics (Lancaster), Vol.47(7), pp.3233-3242

07/2020

DOI: 10.1002/mp.14146

PMCID: PMC9486957

PMID: 32187683

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https://www.ncbi.nlm.nih.gov/pmc/articles/9486957View

Open Access

Abstract

To create a dose-response model that predicts lung ventilation change following radiation therapy, and examine the effects of out-of-phase ventilation. The dose-response model was built using 27 human subjects who underwent radiation therapy (RT) from an IRB-approved trial. For each four-dimensional computed tomography, two ventilation maps were created by calculating the N-phase local expansion ratio (LER ) using most or all breathing phases and the 2-phase LER (LER ) using only the end inspiration and end expiration breathing phases. A polynomial regression model was created using the LER ventilation maps pre-RT and post-RT and dose distributions for each subject, and crossvalidated with a leave-one-out method. Further validation of the model was performed using 15 additional human subjects using common statistical operating characteristics and gamma pass rates. For voxels receiving 20 Gy or greater, there was a significant increase from 52% to 59% (P = 0.03) in the gamma pass rates of the LER model predicted post-RT Jacobian maps to the actual post-RT Jacobian maps, relative to the LER model. Additionally, accuracy significantly increased (P = 0.03) from 68% to 75% using the LER model, relative to the LER model. The LER model was significantly more accurate than the LER model at predicting post-RT ventilation maps. More accurate post-RT ventilation maps will aid in producing a higher quality functional avoidance treatment plan, allowing for potentially better normal tissue sparing.

Four-Dimensional Computed Tomography

Humans

Lung - diagnostic imaging

Lung Neoplasms

Radiation Dosage

Radiotherapy Planning, Computer-Assisted

Respiration

Details

Title: Subtitle: Modeling the impact of out-of-phase ventilation on normal lung tissue response to radiation dose
Creators: Eric M Wallat - University of Wisconsin–Madison
Mattison J Flakus - University of Wisconsin–Madison
Antonia E Wuschner - University of Wisconsin–Madison
Wei Shao - University of Iowa
Gary E Christensen - University of Iowa
Joseph M Reinhardt - University of Iowa
Andrew M Baschnagel - University of Wisconsin–Madison
John E Bayouth - University of Wisconsin–Madison
Resource Type: Journal article
Publication Details: Medical physics (Lancaster), Vol.47(7), pp.3233-3242
DOI: 10.1002/mp.14146
PMID: 32187683
PMCID: PMC9486957
NLM abbreviation: Med Phys
ISSN: 0094-2405
eISSN: 2473-4209
Grant note: R01 CA166703 / NCI NIH HHS The University of Iowa Carver College of Medicine CA166703 / NIH HHS
Language: English
Date published: 07/2020
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Radiation Research Laboratory; The Iowa Institute for Biomedical Imaging; Advanced Pulmonary Physiomic Imaging Laboratory; Holden Comprehensive Cancer Center
Record Identifier: 9984196988502771

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