Radiation-induced airway changes and downstream ventilation decline in a swine model

Wallat, Eric M.; Wuschner, Antonia E.; Flakus, Mattison J.; Christensen, Gary E.; Reinhardt, Joseph M.; Shanmuganayagam, Dhanansayan; Bayouth, John E.

doi:10.1088/2057-1976/ac3197

Cited by 11 publications

(17 citation statements)

References 34 publications

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“…We believe this to be indication of an "indirect effect" where regions receiving no or minimal dose experience large functional declines. This effect has been observed previously in several studies (Wallat et al, 2021) (Vicente et al, 2020) (Thomas et al, 2019) (Farr et al, 2018).…”

Section: Figure 11supporting

confidence: 86%

“…To do this, detailed dose response models are required. In recent years, multiple groups have begun developing these models and some have tested their efficacy in clinical trials ( McDonald et al, 1995 ) ( Mah and Dyk, 1988 ) ( Mehta, 2005 ) ( Graves et al, 2010 ) ( Patton et al, 2018 ) ( Koike et al, 2015 ) ( Hopkins et al, 2012 ) ( Zhang et al, 2010 ) ( Vinogradskiy et al, 2013 ) ( Wallat et al, 2020 ) ( Wallat et al, 2021 ) ( Bates et al, 2009 ) ( Hoover et al, 2014 ) ( Ireland et al, 2016 ) ( Vicente et al, 2020 ). To date, the only prospective clinical trials using these techniques have been ventilation-based ( Bayouth et al, 2019 ) and all non-contrast CT-derived methods have been exclusively ventilation based ( Patton et al, 2018 ) ( Vinogradskiy et al, 2013 ) ( Vicente et al, 2020 ) ( Castillo et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have used the Wisconsin Miniature Swine (WMS) and detail their unique characteristics that make them an ideal model as well as show strong correlations between WMS and human response ( Wallat et al, 2021 ) ( Reed et al, 2010 ) ( Wuschner et al, 2021a ). In this work, two groups of five WMS (ten total) each received CT imaging and RT treatment.…”

Section: Methodsmentioning

confidence: 99%

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CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion

et al. 2022

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Vessel segmentation in the lung is an ongoing challenge. While many methods have been able to successfully identify vessels in normal, healthy, lungs, these methods struggle in the presence of abnormalities. Following radiotherapy, these methods tend to identify regions of radiographic change due to post-radiation therapytoxicities as vasculature falsely. By combining texture analysis and existing vasculature and masking techniques, we have developed a novel vasculature segmentation workflow that improves specificity in irradiated lung while preserving the sensitivity of detection in the rest of the lung. Furthermore, radiation dose has been shown to cause vascular injury as well as reduce pulmonary function post-RT. This work shows the improvements our novel vascular segmentation method provides relative to existing methods. Additionally, we use this workflow to show a dose dependent radiation-induced change in vasculature which is correlated with previously measured perfusion changes (R2 = 0.72) in both directly irradiated and indirectly damaged regions of perfusion. These results present an opportunity to extend non-contrast CT-derived models of functional change following radiation therapy.

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Section: Figure 11supporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion

et al. 2022

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“…Additionally, this work was done using SPECT, which has the issue of producing low-resolution images prone to artifacts and attenuation, making the nuances of the indirect effect difficult to localize [ 23 , 25 , 26 , 27 ]. Wallat et al presented the first CT-derived evidence of there being an indirect effect, focusing on post-RT ventilation change due to damage to the airways [ 28 ]. Vicente et al later developed a functional avoidance technique that incorporated this indirect ventilation effect and found that the average predicted ventilation preservation was 14.5% higher than conventional RT techniques and 11.5% higher than functional avoidance algorithms that consider only local damage [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Measuring Indirect Radiation-Induced Perfusion Change in Fed Vasculature Using Dynamic Contrast CT

Wuschner

Flakus

Wallat

et al. 2022

JPM

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Recent functional lung imaging studies have presented evidence of an “indirect effect” on perfusion damage, where regions that are unirradiated or lowly irradiated but that are supplied by highly irradiated regions observe perfusion damage post-radiation therapy (RT). The purpose of this work was to investigate this effect using a contrast-enhanced dynamic CT protocol to measure perfusion change in five novel swine subjects. A cohort of five Wisconsin Miniature Swine (WMS) were given a research course of 60 Gy in five fractions delivered locally to a vessel in the lung using an Accuray Radixact tomotherapy system with Synchrony motion tracking to increase delivery accuracy. Imaging was performed prior to delivering RT and 3 months post-RT to yield a 28–36 frame image series showing contrast flowing in and out of the vasculature. Using MIM software, contours were placed in six vessels on each animal to yield a contrast flow curve for each vessel. The contours were placed as follows: one at the point of max dose, one low-irradiated (5–20 Gy) branching from the max dose vessel, one low-irradiated (5–20 Gy) not branching from the max dose vessel, one unirradiated (<5 Gy) branching from the max dose vessel, one unirradiated (<5 Gy) not branching from the max dose vessel, and one in the contralateral lung. Seven measurements (baseline-to-baseline time and difference, slope up and down, max rise and value, and area under the curve) were acquired for each vessel’s contrast flow curve in each subject. Paired Student t-tests showed statistically significant (p<0.05) reductions in the area under the curve in the max dose, and both fed contours indicating an overall reduction in contrast in these regions. Additionally, there were statistically significant reductions observed when comparing pre- and post-RT in slope up and down in the max dose, low-dose fed, and no-dose fed contours but not the low-dose not-fed, no-dose not-fed, or contralateral contours. These findings suggest an indirect damage effect where irradiation of the vasculature causes a reduction in perfusion in irradiated regions as well as regions fed by the irradiated vasculature.

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“…Subject weights ranged from 70 to 100 kg. Our group has previously used WMS for pre-clinical studies ( Wallat et al., 2021 ; Wuschner et al., 2021 ; Wuschner et al., 2022a ; Wuschner et al., 2022b ).…”

Section: Methodsmentioning

confidence: 99%

Quantifying robustness of CT-ventilation biomarkers to image noise

et al. 2023

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Purpose: To quantify the impact of image noise on CT-based lung ventilation biomarkers calculated using Jacobian determinant techniques.Methods: Five mechanically ventilated swine were imaged on a multi-row CT scanner with acquisition parameters of 120 kVp and 0.6 mm slice thickness in static and 4-dimensional CT (4DCT) modes with respective pitches of 1 and 0.09. A range of tube current time product (mAs) values were used to vary image dose. On two dates, subjects received two 4DCTs: one with 10 mAs/rotation (low-dose, high-noise) and one with CT simulation standard of care 100 mAs/rotation (high-dose, low-noise). Additionally, 10 intermediate noise level breath-hold (BHCT) scans were acquired with inspiratory and expiratory lung volumes. Images were reconstructed with and without iterative reconstruction (IR) using 1 mm slice thickness. The Jacobian determinant of an estimated transformation from a B-spline deformable image registration was used to create CT-ventilation biomarkers estimating lung tissue expansion. 24 CT-ventilation maps were generated per subject per scan date: four 4DCT ventilation maps (two noise levels each with and without IR) and 20 BHCT ventilation maps (10 noise levels each with and without IR). Biomarkers derived from reduced dose scans were registered to the reference full dose scan for comparison. Evaluation metrics were gamma pass rate (Γ) with 2 mm distance-to-agreement and 6% intensity criterion, voxel-wise Spearman correlation (ρ) and Jacobian ratio coefficient of variation (CoVJR).Results: Comparing biomarkers derived from low (CTDIvol = 6.07 mGy) and high (CTDIvol = 60.7 mGy) dose 4DCT scans, mean Γ, ρ and CoVJR values were 93% ± 3%, 0.88 ± 0.03 and 0.04 ± 0.009, respectively. With IR applied, those values were 93% ± 4%, 0.90 ± 0.04 and 0.03 ± 0.003. Similarly, comparisons between BHCT-based biomarkers with variable dose (CTDIvol = 1.35–7.95 mGy) had mean Γ, ρ and CoVJR of 93% ± 4%, 0.97 ± 0.02 and 0.03 ± 0.006 without IR and 93% ± 4%, 0.97 ± 0.03 and 0.03 ± 0.007 with IR. Applying IR did not significantly change any metrics (p>0.05).Discussion: This work demonstrated that CT-ventilation, calculated using the Jacobian determinant of an estimated transformation from a B-spline deformable image registration, is invariant to Hounsfield Unit (HU) variation caused by image noise. This advantageous finding may be leveraged clinically with potential applications including dose reduction and/or acquiring repeated low-dose acquisitions for improved ventilation characterization.

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Radiation-induced airway changes and downstream ventilation decline in a swine model

Cited by 11 publications

References 34 publications

CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion

CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion

Measuring Indirect Radiation-Induced Perfusion Change in Fed Vasculature Using Dynamic Contrast CT

Quantifying robustness of CT-ventilation biomarkers to image noise

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