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Title: SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET

Abstract

Purpose: The aim of this work is to evaluate the accuracy and sensitivity of a respiratory-triggered MR-PET protocol in detecting four different sized lesions at two different magnitudes of motion, with two different TR values, using a novel PET-MR-CT compatible respiratory motion phantom. Methods: The eight-compartment torso phantom was setup adjacent to the motion stage, which moved four spherical compartments (28, 22, 17, 10 mm diameter) in two separate (1 and 2 cm) linear motion profiles, simulating a 3.5 second respiratory cycle. Scans were acquired on a 3T MR-PET system (Biograph mMR; Siemens Medical Solutions, Germany). MR measurements were taken with: 1) Respiratory-triggered T2-weighted turbo spin echo (BLADE) sequence in coronal orientation, and 2) Real-time balanced steady-state gradient echo sequence (TrueFISP) in coronal and sagittal planes. PET was acquired simultaneously with MR. Sphere geometries and motion profiles were measured and compared with ground truths for T2 BLADE-TSE acquisitions and real time TrueFISP images. PET quantification and geometry measurements were taken using standardized uptake values, voxel intensity plots and were compared with known values, and examined alongside MR-based attenuation maps. Contrast and signal-to-noise ratios were also compared for each of the acquisitions as functions of motion range and TR. Results: Comparisonmore » of lesion diameters indicate the respiratory triggered T2 BLADE-TSE was able to maintain geometry within −2 mm for 1 cm motion for both TR values, and within −3.1 mm for TR = 2000 ms at 2 cm motion. Sphere measurements in respiratory triggered PET images were accurate within +/− 5 mm for both ranges of motion for 28, 22, and 17 mm diameter spheres. Conclusion: Hybrid MR-PET systems show promise in imaging lung cancer in non-compliant patients, with their ability to acquire both modalities simultaneously. However, MR-based attenuation maps are still susceptible to motion derived artifacts and pose the potential to affect PET accuracy.« less

Authors:
;  [1]; ;  [2];  [3];  [4]
  1. Lawson Health Research Institute, London, Ontario (Canada)
  2. Robarts Research Institute, London, Canada, London, Ontario (Canada)
  3. Western University, Canada, London, Ontario (Canada)
  4. London Regional Cancer Program, London, Ontario (Canada)
Publication Date:
OSTI Identifier:
22632123
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; ATTENUATION; BIOMEDICAL RADIOGRAPHY; IMAGES; LUNGS; NEOPLASMS; PHANTOMS; SIGNAL-TO-NOISE RATIO; SPIN ECHO; STEADY-STATE CONDITIONS

Citation Formats

Patrick, J, Thompson, R, Tavallaei, M, Drangova, M, Stodilka, R, and Gaede, S. SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET. United States: N. p., 2016. Web. doi:10.1118/1.4955886.
Patrick, J, Thompson, R, Tavallaei, M, Drangova, M, Stodilka, R, & Gaede, S. SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET. United States. doi:10.1118/1.4955886.
Patrick, J, Thompson, R, Tavallaei, M, Drangova, M, Stodilka, R, and Gaede, S. 2016. "SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET". United States. doi:10.1118/1.4955886.
@article{osti_22632123,
title = {SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET},
author = {Patrick, J and Thompson, R and Tavallaei, M and Drangova, M and Stodilka, R and Gaede, S},
abstractNote = {Purpose: The aim of this work is to evaluate the accuracy and sensitivity of a respiratory-triggered MR-PET protocol in detecting four different sized lesions at two different magnitudes of motion, with two different TR values, using a novel PET-MR-CT compatible respiratory motion phantom. Methods: The eight-compartment torso phantom was setup adjacent to the motion stage, which moved four spherical compartments (28, 22, 17, 10 mm diameter) in two separate (1 and 2 cm) linear motion profiles, simulating a 3.5 second respiratory cycle. Scans were acquired on a 3T MR-PET system (Biograph mMR; Siemens Medical Solutions, Germany). MR measurements were taken with: 1) Respiratory-triggered T2-weighted turbo spin echo (BLADE) sequence in coronal orientation, and 2) Real-time balanced steady-state gradient echo sequence (TrueFISP) in coronal and sagittal planes. PET was acquired simultaneously with MR. Sphere geometries and motion profiles were measured and compared with ground truths for T2 BLADE-TSE acquisitions and real time TrueFISP images. PET quantification and geometry measurements were taken using standardized uptake values, voxel intensity plots and were compared with known values, and examined alongside MR-based attenuation maps. Contrast and signal-to-noise ratios were also compared for each of the acquisitions as functions of motion range and TR. Results: Comparison of lesion diameters indicate the respiratory triggered T2 BLADE-TSE was able to maintain geometry within −2 mm for 1 cm motion for both TR values, and within −3.1 mm for TR = 2000 ms at 2 cm motion. Sphere measurements in respiratory triggered PET images were accurate within +/− 5 mm for both ranges of motion for 28, 22, and 17 mm diameter spheres. Conclusion: Hybrid MR-PET systems show promise in imaging lung cancer in non-compliant patients, with their ability to acquire both modalities simultaneously. However, MR-based attenuation maps are still susceptible to motion derived artifacts and pose the potential to affect PET accuracy.},
doi = {10.1118/1.4955886},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Radiographs of phantoms were produced using E-speed film and various rare earth X-ray beam filters. The rare earth filters considerably reduced the amount of radiation needed to produce diagnostic quality images and, in many cases, improved image quality. These filters can be implemented easily and inexpensively in a clinical setting, resulting in radiation exposure reductions of up to 71%.
  • Purpose: To compare and quantify respiratory motion artifacts in images from free breathing 4D-CT-on-Rails(CTOR) and those from MV-Cone-beam-CT(MVCB) and facilitate respiratory motion guided radiation therapy. Methods: 4D-CTOR: Siemens Somatom CT-on-Rails system with Anzai belt loaded with pressure sensor load cells. 4D scans were performed in helical mode, pitch 0.1, gantry rotation time 0.5s, 1.5mm slice thickness, 120kVp, 400 mAs. Normal and fast breathing (>12rpm) scanning protocols were investigated. Helical scan, AIP(average intensity projection) and MIP(maximum intensity projection) were generated from 4D-CTOR scans with amplitude sorting into 10 phases.MVCB: Siemens Artiste diamond view(1MV)MVCB was performed with 5MU thorax protocol with 60more » second of full rotation.Phantom: Anzai AZ-733V respiratory phantom. The settings were set to normal and resp. modes with repetition rates at 15 rpm and 10 rpm. Surgical clips, acrylic, wooden, rubber and lung density, total six mock-ups were scanned and compared in this study.Signal-to-noise ratio(SNR), contrast-to-noise ratio(CNR) and reconstructed motion volume were compared to different respiratory setups for the mock-ups. Results: Reconstructed motion volume was compared to the real object volume for the six test mock-ups. It shows that free breathing helical in all instances underestimates the object excursions largest to −67.4% and least −6.3%. Under normal breathing settings, MIP can predict very precise motion volume with minimum 0.4% and largest −13.9%. MVCB shows underestimate of the motion volume with −1.11% minimum and −18.0% maximum. With fast breathing, AIP provides bad representation of the object motion; however, the MIP can predict the motion volume with −2.0% to −11.4% underestimate. Conclusion: Respiratory motion guided radiation therapy requires good motion recording. This study shows that regular CTOR helical scans provides bad guidance, 4D CTOR AIP cannot represent the fast breathing pattern, MIP can represent the best motion volume, MVCBCT can only be used for normal breathing with acceptable uncertainties.« less
  • Purpose: To evaluate the practicality use of ionization chambers with different volumes for delivery quality assurance of CyberKnife plans, Methods: Dosimetric measurements with a spherical solid water phantom and three ionization chambers with volumes of 0.13, 0.04, and 0.01 cm3 (IBA CC13, CC04, and CC01, respectively) were performed for various CyberKnife clinical treatment plans including both isocentric and nonisocentric delivery. For each chamber, the ion recombination correction factors Ks were calculated using the Jaffe plot method and twovoltage method at a 10-cm depth for a 60-mm collimator field in a water phantom. The polarity correction factors Kpol were determined formore » 5–60-mm collimator fields in same experimental setup. The measured doses were compared to the doses for the detectors calculated using a treatment planning system. Results: The differences in the Ks between the Jaffe plot method and two-voltage method were −0.12, −0.02, and 0.89% for CC13, CC04, and CC01, respectively. The changes in Kpol for the different field sizes were 0.2, 0.3, and 0.8% for CC13, CC04, and CC01, respectively. The measured doses for CC04 and CC01 were within 3% of the calculated doses for the clinical treatment plans with isocentric delivery with collimator fields greater than 12.5 mm. Those for CC13 had differences of over 3% for the plans with isocentric delivery with collimator fields less than 15 mm. The differences for the isocentric plans were similar to those for the single beam plans. The measured doses for each chamber were within 3% of the calculated doses for the non-isocentric plans except for that with a PTV volume less than 1.0 cm{sup 3}. Conclusion: Although there are some limitations, the ionization chamber with a smaller volume is a better detector for verification of the CyberKnife plans owing to the high spatial resolution.« less
  • Purpose: To investigate the effectiveness of employing abdominal compression (AC) in reducing motion for the target region and sub-regions of the lung as part of the planning process for radiation therapy. Methods: Fourteen patients with early lung cancer were scanned with 4DCT and it was determined that target motion exceeded our institutional limit of > 8 mm motion and received a repeat 4DCT with AC. For each 4DCT, deformable image registration (DIR) was used to map the max inhale to the max exhale phase to determine the deformation vector fields (DVF). DIR was performed with Morphons and Demons algorithms. Themore » mean DVF was used to represent that sub-region for each patient. The magnitudes of the mean DVF were quantified for the target and 12 sub-regions in the AP, LR SI directions. The sub-regions were contoured on each lung as (add prefix R or L for lung): Upper-Anterior (UA), Upper-Posterior (UP), Mid-Anterior (MA), Mid-Posterior (MP), Lower-Anterior (LA) and Lower-Posterior (LP). Results: The min/max SI motion for the target on the uncompressed 4DCT was 8mm/24.5 mm. The magnitude of decrease in SI was greatest in the RLP region (3.7±4.0mm) followed by target region (3.3±2.2mm) and finally the LLP region (3.0±3.5mm). The magnitude of decrease in 3D vector followed the same trend; RLP (3.5±2.2mm) then GTV (3.5±2.6mm) then LLP (2.7±3.8mm). 79% of the cases had a SI decrease of >12.5%, 43% had a SI decrease of >25% and 21% had a SI decrease of >50% as compared to the motion on the uncompressed 4DCT. Conclusion: AC is useful in reducing motion with the largest decreases observed in the lower posterior regions of the lungs. However, it should be noted that AC will not greatly decrease motion for all cases as 21% of cases did not reduce SI motion more than 12.5% of initial motion.« less
  • Purpose: To study the variability of patient-specific motion models derived from 4-dimensional CT (4DCT) images using different deformable image registration (DIR) algorithms for lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived by 1) applying DIR between each 4DCT image and a reference image, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs, resulting in a motion model (a set of eigenvectors capturing the variations in the DVFs). Three DIR algorithms were used: 1) Demons, 2) Horn-Schunck, and 3) iterative optical flow. The motion models derived weremore » compared using patient 4DCT scans. Results: Motion models were derived and the variations were evaluated according to three criteria: 1) the average root mean square (RMS) difference which measures the absolute difference between the components of the eigenvectors, 2) the dot product between the eigenvectors which measures the angular difference between the eigenvectors in space, and 3) the Euclidean Model Norm (EMN), which is calculated by summing the dot products of an eigenvector with the first three eigenvectors from the reference motion model in quadrature. EMN measures how well an eigenvector can be reconstructed using another motion model derived using a different DIR algorithm. Results showed that comparing to a reference motion model (derived using the Demons algorithm), the eigenvectors of the motion model derived using the iterative optical flow algorithm has smaller RMS, larger dot product, and larger EMN values than those of the motion model derived using Horn-Schunck algorithm. Conclusion: The study showed that motion models vary depending on which DIR algorithms were used to derive them. The choice of a DIR algorithm may affect the accuracy of the resulting model, and it is important to assess the suitability of the algorithm chosen for a particular application. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.« less