To analyze radiation induced changes in Hounsfield units and determine their correlation with changes in perfusion and ventilation. Additionally, to compare the post-RT changes in human subjects to those measured in a swine model used to quantify perfusion changes and validate their use as a preclinical model. A cohort of 5 Wisconsin Miniature Swine (WMS) were studied. Additionally, 19 human subjects were recruited as part of an IRB approved clinical trial studying functional avoidance radiation therapy for lung cancer and were treated with SBRT. Imaging (a contrast enhanced dynamic perfusion CT in the swine and 4DCT in the humans) was performed prior to and post-RT. Jacobian elasticity maps were calculated on all 4DCT images. Contours were created from the isodose lines to discretize analysis into 10 Gy dose bins. B-spline deformable image registration allowed for voxel-by-voxel comparative analysis in these contours between timepoints. The WMS underwent a research course of 60 Gy in 5 fractions delivered locally to a target in the lung using an MRI-LINAC system. In the WMS subjects, the dose-bin contours were copied onto the contralateral lung, which received < 5 Gy for comparison. Changes in HU and changes in Jacobian were analyzed in these contours. Statistically significant (p < 0.05) changes in the mean HU value post-RT compared to pre-RT were observed in both the human and WMS groups at all timepoints analyzed. The HU increased linearly with dose for both groups. Strong linear correlation was observed between the changes seen in the swine and humans (Pearson coefficient > 0.97, p < 0.05) at all timepoints. Changes seen in the swine closely modeled the changes seen in the humans at 12 months post RT (slope = 0.95). Jacobian analysis showed between 30 and 60% of voxels were damaged post-RT. Perfusion analysis in the swine showed a statistically significant (p < 0.05) reduction in contrast inside the vasculature 3 months post-RT compared to pre-RT. The increases in contrast outside the vasculature was strongly correlated (Pearson Correlation 0.88) with the reduction in HU inside the vasculature but were not correlated with the changes in Jacobians. Radiation induces changes in pulmonary anatomy at 3 months post-RT, with a strong linear correlation with dose. The change in HU seen in the non-vessel lung parenchyma suggests this metric is a potential biomarker for change in perfusion. Finally, this work suggests that the WMS swine model is a promising pre-clinical model for analyzing radiation-induced changes in humans and poses several benefits over conventional swine models.
Purpose This work seeks to investigate new methods to determine the absorbed dose to water from kilovoltage x rays. Current methods are based on measurements in air and rely on correction factors in order to account for differences between the photon spectrum in air and at depth in phantom, between the photon spectra of the calibration beam and the beam of interest, or in the radiation absorption properties of air and water. This work aims to determine the absorbed dose to water in the NIST‐matched x‐ray beams at the University of Wisconsin Accredited Dosimetry Calibration Laboratory (UWADCL). This will facilitate the use of detectors in terms of dose to water, which will allow for a simpler determination of dose to water in clinical kilovoltage x‐ray beams. Materials and methods A model of the moderately filtered x‐ray beams at the UWADCL was created using the BEAMnrc user code of the EGSnrc Monte Carlo code system. This model was validated against measurements and the dose to water per unit air kerma was calculated in a custom built water tank. Using this value and the highly precise measurement of the air kerma made by the UWADCL, the dose to water was determined in the water tank for the x‐ray beams of interest. The dose to water was also determined using the formalism defined in the report of AAPM Task Group 61 and using a method that makes use of a 60Co absorbed dose‐to‐water calibration coefficient and a beam quality correction factor to account for differences in beam quality between the 60Co calibration and kilovoltage x‐ray beam of interest. The dose to water values as determined by these different methods was then compared. Results The BEAMnrc models used in this work produced simulations of transverse and depth dose profiles that agreed with measurements with a 2%/2 mm criteria gamma test. The dose to water as determined from the different methods used here agreed within 3.5% at the surface of the water tank and agreed within 1.8% at a depth of 2 cm in phantom. The dose‐to‐water values all agreed within the associated uncertainties of the methods used in this work. Both the Monte Carlo‐based method and the 60Co‐based method had a lower uncertainty than the TG‐61 methodology for all of the x‐ray beams used in this work. Conclusion Two new dose determination methods were used to determine the dose to water in the NIST‐matched x‐ray beams at the UWADCL and they showed good agreement with previously established techniques. Due to the improved Monte Carlo calculation techniques used in this work, both of the methods have lower uncertainties compared to TG‐61. The methods presented in this work compare favorably with calorimetry‐based standards established at other institutions.
The relative response of TLD-100 in mixed fields fell between the relative response in the photon-only and electron-only fields. TLD-100 dosimetry of mixed fields must account for this intermediate response to minimize the estimation errors associated with calibration factors obtained from a single beam quality.
Accurate liver tumor delineation is crucial for radiation therapy, but liver tumor volumes are difficult to visualize with conventional single-energy CT. This work investigates the use of split-filter dual-energy CT (DECT) for liver tumor visibility by quantifying contrast and contrast-to-noise ratio (CNR). Methods: Split-filter DECT contrast-enhanced scans of 20 liver tumors including cholangiocarcinomas, hepatocellular carcinomas, and liver metastases were acquired. Analysis was performed on the arterial and venous phases of mixed 120 kVp-equivalent images and VMIs at 57 keV and 40 keV gross target volume (GTV) contrast and CNR were calculated. Results: For the arterial phase, liver GTV contrast was 12.1 ± 10.0 HU and 43.1 ± 32.3 HU (P < 0.001) for the mixed images and 40 keV VMIs. Image noise increased on average by 116% for the 40 keV VMIs compared to the mixed images. The average CNR did not change significantly (1.6 ± 1.5, 1.7 ± 1.4, 2.4 ± 1.7 for the mixed, 57 keV and 40 keV VMIs (P > 0.141)). For individual cases, however, CNR increases of up to 607% were measured for the 40 keV VMIs compared to the mixed image. Venous phase 40 keV VMIs demonstrated an average increase of 35.4 HU in GTV contrast and 121% increase in image noise. Average CNR values were also not statistically different, but for individual cases CNR increases of up to 554% were measured for the 40 keV VMIs compared to the mixed image. Conclusions: Liver tumor contrast was significantly improved using split-filter DECT 40 keV VMIs compared to mixed images. On average, there was no statistical difference in CNR between the mixed images and VMIs, but for individual cases, CNR was greatly increased for the 57 keV and 40 keV VMIs. Therefore, although not universally successful for our patient cohort, split-filter DECT VMIs may provide substantial gains in tumor visibility of certain liver cases for radiation therapy treatment planning.
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