Radiation-induced Hounsfield unit change correlates with dynamic CT perfusion better than 4DCT-based ventilation measures in a novel-swine model

Wuschner, Antonia E.; Wallat, Eric M.; Flakus, Mattison J.; Shanmuganayagam, Dhanansayan; Meudt, Jennifer J.; Christensen, Gary E.; Reinhardt, Joseph M.; Miller, Jessica R.; Lawless, Michael J.; Baschnagel, Andrew M.; Bayouth, John E.

doi:10.1038/s41598-021-92609-x

Cited by 9 publications

(24 citation statements)

References 43 publications

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“…These reductions in area under the curve represent an overall reduction in contrast observed in the vessel and a change in the numerator from Equation ( 2 ). This response to radiation has been reported previously in irradiated vasculature [ 24 ], where it was observed that in vasculature irradiated above 25 Gy, there appeared to be a leakage of contrast from the vasculature into the non-vessel parenchyma. The observation of reduced post-RT area under the curve in fed contours but not in not-fed contours suggests an indirect damage effect to the low or unirradiated tissues where there is leakage in the highly irradiated vessel preventing contrast (and more importantly blood) from reaching the branching vessels.…”

Section: Discussionsupporting

confidence: 85%

“…The novelty of the swine model use in this work allows for more direct translation into human studies than previous animal models. Previous work has already established a strong correlation between the WMS and human radiation-induced lung density changes [ 24 ]. The WMS at the size used in this work had lungs that matched human adult lungs.…”

Section: Discussionmentioning

confidence: 99%

“…This work quantifies an anatomical response to radiation dose in an animal model that has been previously established as a surrogate for human response [ 24 ]. Additionally, we used a novel contrast-enhanced CT protocol that allowed for a full kinetic analysis of each vessel.…”

Section: Discussionmentioning

confidence: 99%

“…Our previous work quantified radiation-induced dose–response, correlating 4DCT-derived Hounsfield Unit (HU) changes with changes in contrast from dynamic contrast-enhanced CT [ 24 ]. However, this work focused on direct radiation damage without quantifying observations of indirect damage to regions supplied by damaged vasculature due to irradiation being in the base of the lung.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Wuschner

Flakus

Wallat

et al. 2022

JPM

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“…Computational approaches have the advantages of allowing quantitative, continuous, objective and automated classification of radiological or functional lung damage. One of the most common approaches has been to use Hounsfield Unit (HU) density [ 31 , 32 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ]. Palma et al [ 52 ] performed deformable image registration on the phase of the planning scan with the lung volume most similar to the 3-month follow-up CT images of patients treated with SABR.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Analysis of Radiation-Associated Parenchymal Lung Change

Chandy

Szmul

Stavropoulou

et al. 2022

Cancers

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We present a novel classification system of the parenchymal features of radiation-induced lung damage (RILD). We developed a deep learning network to automate the delineation of five classes of parenchymal textures. We quantify the volumetric change in classes after radiotherapy in order to allow detailed, quantitative descriptions of the evolution of lung parenchyma up to 24 months after RT, and correlate these with radiotherapy dose and respiratory outcomes. Diagnostic CTs were available pre-RT, and at 3, 6, 12 and 24 months post-RT, for 46 subjects enrolled in a clinical trial of chemoradiotherapy for non-small cell lung cancer. All 230 CT scans were segmented using our network. The five parenchymal classes showed distinct temporal patterns. Moderate correlation was seen between change in tissue class volume and clinical and dosimetric parameters, e.g., the Pearson correlation coefficient was ≤0.49 between V30 and change in Class 2, and was 0.39 between change in Class 1 and decline in FVC. The effect of the local dose on tissue class revealed a strong dose-dependent relationship. Respiratory function measured by spirometry and MRC dyspnoea scores after radiotherapy correlated with the measured radiological RILD. We demonstrate the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible.

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