ABSTRACT
PURPOSE: To describe the commissioning of AIRO mobile CT system (AIRO) for adaptive proton therapy on a compact double scattering proton therapy system. METHODS: A Gammex phantom was scanned with varying plug patterns, table heights, and mAs on a CT simulator (CT Sim) and on the AIRO. AIRO-specific CT-stopping power ratio (SPR) curves were created with a commonly used stoichiometric method using the Gammex phantom. A RANDO anthropomorphic thorax, pelvis, and head phantom, and a CIRS thorax and head phantom were scanned on the CT Sim and AIRO. Clinically realistic treatment plans and nonclinical plans were generated on the CT Sim images and subsequently copied onto the AIRO CT scans for dose recalculation and comparison for various AIRO SPR curves. Gamma analysis was used to evaluate dosimetric deviation between both plans. RESULTS: AIRO CT values skewed toward solid water when plugs were scanned surrounded by other plugs in phantom. Low-density materials demonstrated largest differences. Dose calculated on AIRO CT scans with stoichiometric-based SPR curves produced over-ranged proton beams when large volumes of low-density material were in the path of the beam. To create equivalent dose distributions on both data sets, the AIRO SPR curve's low-density data points were iteratively adjusted to yield better proton beam range agreement based on isodose lines. Comparison of the stoichiometric-based AIRO SPR curve and the "dose-adjusted" SPR curve showed slight improvement on gamma analysis between the treatment plan and the AIRO plan for single-field plans at the 1%, 1 mm level, but did not affect clinical plans indicating that HU number differences between the CT Sim and AIRO did not affect dose calculations for robust clinical beam arrangements. CONCLUSION: Based on this study, we believe the AIRO can be used offline for adaptive proton therapy on a compact double scattering proton therapy system.
Subject(s)
Algorithms , Head/diagnostic imaging , Phantoms, Imaging , Proton Therapy , Radiotherapy Planning, Computer-Assisted/methods , Tomography, X-Ray Computed/instrumentation , Humans , Image Processing, Computer-Assisted/methods , Organs at Risk/radiation effects , Radiotherapy Dosage , Radiotherapy, Intensity-Modulated/methods , Tomography, X-Ray Computed/methodsABSTRACT
PURPOSE: To characterize the accuracy of noncoplanar image guided radiation therapy with the Varian Edge radiosurgery system for intracranial stereotactic radiosurgery (SRS) treatments by assessing the accuracy of kV/kV orthogonal pair registration with Optical Surface Monitoring System (OSMS) monitoring relative to cone beam computed tomography (CT). METHODS AND MATERIALS: A Computerized Imaging Reference System head phantom and Encompass SRS Immobilization System were used to determine collision-free space for orthogonal image pairs (kV/kV) for couch rotations (CRs) of 45°, 30°, 15°, 345°, 330°, and 315°. Couch-induced shifts were measured using kV/kV orthogonal image pairs, OSMS, and cone beam CT. The kV/kV image pairs and OSMS localization accuracy was also assessed with respect to cone beam CT. RESULTS: Mean orthogonal image pair differences for 315°, 330°, 345°, 15°, 30°, and 45° CRs were ≤±0.60 mm and ±0.37°. OSMS localization accuracy was ≤±0.25 mm and ±0.20°. Correspondingly, kV/kV localization accuracy was ≤±0.30 mm and ±0.5°. Shift differences for various image pairs at all CRs were ≤±1.10 mm and ±0.7°. Cone beam CT deviation was 0.10 mm and 0.00° without patient motion or CR. CONCLUSION: Based on our study, CR-induced shifts with the Varian Edge radiosurgery system will not produce noticeable dosimetric effects for SRS treatments. Thus, replacing cone beam CT with orthogonal kV/kV pairs coupled with OSMS at the treatment couch angle could reduce the number of cone beam CT scans that are acquired during a standard SRS treatment while providing an accurate and safe treatment with negligible dosimetric effects on the treatment plan.
ABSTRACT
BACKGROUND AND AIMS: The role of three-dimensional positron emission tomography/computed tomography (3âD PET/CT) in esophageal tumors that move with respiration and have potential for significant mucosal inflammation is unclear. The aim of this study was to determine the correlation between gross tumor volumes derived from 3âD PET/CT and endoscopically placed fiducial markers. METHODS: This was a retrospective, IRB approved analysis of 40 patients with esophageal cancer with fiducials implanted and PET/CT. The centroid of each fiducial was identified on PET/CT images. Distance between tumor volume and fiducials was measured using axial slices. Image features were extracted and tested for pathologic response predictability. RESULTS: The median adaptively calculated threshold value of the standardized uptake value (SUV) to define the metabolic tumor volume (MTV) border was 2.50, which corresponded to a median 23â% of the maximum SUV. The median distance between the inferior fiducial centroid and MTV was -â0.60âcm (-â3.9 to 2.7âcm). The median distance between the superior fiducial centroid and MTV was 1.25âcm (-â4.2 to 6.9âcm). There was no correlation between MTV-to-fiducial distances greater than 2âcm and the gastroenterologist who performed the fiducial implantation. Eccentricity demonstrated statistically significant correlations with pathologic response. CONCLUSIONS: There was a stronger correlation between inferior fiducial location and MTV border compared to the superior extent. The etiology of the discordance superiorly is unclear, potentially representing benign secondary esophagitis, presence of malignant nodes, inflammation caused by technical aspects of the fiducial placement itself, or potential submucosal disease. Given the concordance inferiorly and the ability to more precisely set up the patient with daily image guidance matching to fiducials, it may be possible to minimize the planning tumor volume (PTV) margin in select patients, thereby, limiting dose to normal structures.
ABSTRACT
PURPOSE: The purpose of this study was to characterize the Mobius AIRO Mobile CT System for localization and image-guided proton therapy. This is the first known application of the AIRO for proton therapy. METHODS: Five CT images of a Catphan® 504 phantom were acquired on the AIRO Mobile CT System, Varian EDGE radiosurgery system cone beam CT (CBCT), Philips Brilliance Big Bore 16 slice CT simulator, and Siemens SOMATOM Definition AS 20 slice CT simulator. DoseLAB software v.6.6 was utilized for image quality analysis. Modulation transfer function, scaling discrepancy, geometric distortion, spatial resolution, overall uniformity, minimum uniformity, contrast, high CNR, and maximum HU deviation were acquired. Low CNR was acquired manually using the CTP515 module. Localization accuracy and CT Dose Index were measured and compared to reported values on each imaging device. For treatment delivery systems (Edge and Mevion), the localization accuracy of the 3D imaging systems were compared to 2D imaging systems on each system. RESULTS: The AIRO spatial resolution was 0.21 lp mm-1 compared with 0.40 lp mm-1 for the Philips CT Simulator, 0.37 lp mm-1 for the Edge CBCT, and 0.35 lp mm-1 for the Siemens CT Simulator. AIRO/Siemens and AIRO/Philips differences exceeded 100% for scaling discrepancy (191.2% and 145.8%). The AIRO exhibited higher dose (>27 mGy) than the Philips CT Simulator. Localization accuracy (based on the MIMI phantom) was 0.6° and 0.5 mm. Localization accuracy (based on Stereophan) demonstrated maximum AIRO-kV/kV shift differences of 0.1 mm in the x-direction, 0.1 mm in the y-direction, and 0.2 mm in the z-direction. CONCLUSIONS: The localization accuracy of AIRO was determined to be within 0.6° and 0.5 mm despite its slightly lower image quality overall compared to other CT imaging systems at our institution. Based on our study, the Mobile AIRO CT system can be utilized accurately and reliably for image-guided proton therapy.
Subject(s)
Proton Therapy/instrumentation , Radiosurgery/instrumentation , Radiotherapy, Image-Guided/instrumentation , Tomography, X-Ray Computed , Cone-Beam Computed Tomography , Equipment Design , Humans , Phantoms, Imaging , Proton Therapy/methods , Radiosurgery/methods , Radiotherapy, Image-Guided/methodsABSTRACT
The effect of noise on image features has yet to be studied in depth. Our objective was to explore how significantly image features are affected by the addition of uncorrelated noise to an image. The signal-to-noise ratio and noise power spectrum were calculated for a positron emission tomography/computed tomography scanner using a Ge-68 phantom. The conventional and respiratory-gated positron emission tomography/computed tomography images of 31 patients with lung cancer were retrospectively examined. Multiple sets of noise images were created for each original image by adding Gaussian noise of varying standard deviation equal to 2.5%, 4.0%, and 6.0% of the maximum intensity for positron emission tomography images and 10, 20, 50, 80, and 120 Hounsfield units for computed tomography images. Image features were extracted from all images, and percentage differences between the original image and the noise image feature values were calculated. These features were then categorized according to the noise sensitivity. The contour-dependent shape descriptors averaged below 4% difference in positron emission tomography and below 13% difference in computed tomography between noise and original images. Gray level size zone matrix features were the most sensitive to uncorrelated noise exhibiting average differences >200% for conventional and respiratory-gated images in computed tomography and 90% in positron emission tomography. Image feature differences increased as the noise level increased for shape, intensity, and gray-level co-occurrence matrix features in positron emission tomography and for gray-level co-occurrence matrix and gray-level size zone matrix features in conventional computed tomography. Investigators should be aware of the noise effects on image features.
Subject(s)
Image Processing, Computer-Assisted , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/pathology , Positron Emission Tomography Computed Tomography , Aged , Aged, 80 and over , Algorithms , Female , Humans , Image Processing, Computer-Assisted/methods , Male , Middle Aged , Phantoms, Imaging/standards , Positron Emission Tomography Computed Tomography/methods , Positron Emission Tomography Computed Tomography/standards , Sensitivity and Specificity , Signal-To-Noise RatioABSTRACT
Radiomics is being explored for potential applications in radiation therapy. How various imaging protocols affect quantitative image features is currently a highly active area of research. To assess the variability of image features derived from conventional [three-dimensional (3D)] and respiratory-gated (RG) positron emission tomography (PET)/computed tomography (CT) images of lung cancer patients, image features were computed from 23 lung cancer patients. Both protocols for each patient were acquired during the same imaging session. PET tumor volumes were segmented using an adaptive technique which accounted for background. CT tumor volumes were delineated with a commercial segmentation tool. Using RG PET images, the tumor center of mass motion, length, and rotation were calculated. Fifty-six image features were extracted from all images consisting of shape descriptors, first-order features, and second-order texture features. Overall, 26.6% and 26.2% of total features demonstrated less than 5% difference between 3D and RG protocols for CT and PET, respectively. Between 10 RG phases in PET, 53.4% of features demonstrated percent differences less than 5%. The features with least variability for PET were sphericity, spherical disproportion, entropy (first and second order), sum entropy, information measure of correlation 2, Short Run Emphasis (SRE), Long Run Emphasis (LRE), and Run Percentage (RPC); and those for CT were minimum intensity, mean intensity, Root Mean Square (RMS), Short Run Emphasis (SRE), and RPC. Quantitative analysis using a 3D acquisition versus RG acquisition (to reduce the effects of motion) provided notably different image feature values. This study suggests that the variability between 3D and RG features is mainly due to the impact of respiratory motion.