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Title: SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning

Abstract

Purpose: The aim of this study is to evaluate the feasibility of using a dual-energy CBCT (DECBCT) in proton therapy treatment planning to allow for accurate electron density estimation. Methods: For direct comparison, two scenarios were selected: a dual-energy fan-beam CT (high: 140 kVp, low: 80 kVp) and a DECBCT (high: 125 kVp, low: 80 kVp). A Gammex 467 tissue characterization phantom was used, including the rods of air, water, bone (B2–30% mineral), cortical bone (SB3), lung (LN-300), brain, liver and adipose. For the CBCT, Hounsfield Unit (HU) numbers were first obtained from the reconstructed images after a calibration was made based on water (=0) and air materials (=−1000). For each tissue surrogate, region-of-interest (ROI) analyses were made to derive high-energy and low-energy HU values (HUhigh and HUlow), which were subsequently used to estimate electron density based on the algorithm as previously described by Hunemohr N., et al. Parameters k1 and k2 are energy dependent and can be derived from calibration materials. Results: While for the dual-energy FBCT, the electron density is found be within +/−3% error relative to the values provided by the phantom vendor: −1.8% (water), 0.03% (lung), 1.1% (brain), −2.82% (adipose), −0.49% (liver) and −1.89% (cortical bones).more » While for the DECBCT, the estimation of electron density exhibits a relatively larger variation: −1.76% (water), −36.7% (lung), −1.92% (brain), −3.43% (adipose), 8.1% (liver) and 9.5% (cortical bones). Conclusion: For DECBCT, the accuracy of electron density estimation is inferior to that of a FBCT, especially for materials of either low-density (lung) or high density (cortical bone) compared to water. Such limitation arises from inaccurate HU number derivation in a CBCT. Advanced scatter-correction and HU calibration routines, as well as the deployment of photon counting CT detectors need be investigated to minimize the difference between FBCT and CBCT.« less

Authors:
;  [1]; ; ; ;  [2];  [3]
  1. Stanford University, School of Medicine, Stanford, CA (United States)
  2. Department of Radiation Oncology, Graduate School of Medicine, Sapporo, Hokkaido (Japan)
  3. Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido (Japan)
Publication Date:
OSTI Identifier:
22642241
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; ANIMAL TISSUES; BRAIN; CALIBRATION; COMPUTERIZED TOMOGRAPHY; FEASIBILITY STUDIES; LIVER; LUNGS; PHANTOMS; PROTON BEAMS; RADIOTHERAPY; SKELETON

Citation Formats

Peng, H, Xing, L, Kanehira, T, Takao, S, Matsuura, T, Shirato, H, and Umegaki, K. SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning. United States: N. p., 2016. Web. doi:10.1118/1.4956121.
Peng, H, Xing, L, Kanehira, T, Takao, S, Matsuura, T, Shirato, H, & Umegaki, K. SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning. United States. doi:10.1118/1.4956121.
Peng, H, Xing, L, Kanehira, T, Takao, S, Matsuura, T, Shirato, H, and Umegaki, K. Wed . "SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning". United States. doi:10.1118/1.4956121.
@article{osti_22642241,
title = {SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning},
author = {Peng, H and Xing, L and Kanehira, T and Takao, S and Matsuura, T and Shirato, H and Umegaki, K},
abstractNote = {Purpose: The aim of this study is to evaluate the feasibility of using a dual-energy CBCT (DECBCT) in proton therapy treatment planning to allow for accurate electron density estimation. Methods: For direct comparison, two scenarios were selected: a dual-energy fan-beam CT (high: 140 kVp, low: 80 kVp) and a DECBCT (high: 125 kVp, low: 80 kVp). A Gammex 467 tissue characterization phantom was used, including the rods of air, water, bone (B2–30% mineral), cortical bone (SB3), lung (LN-300), brain, liver and adipose. For the CBCT, Hounsfield Unit (HU) numbers were first obtained from the reconstructed images after a calibration was made based on water (=0) and air materials (=−1000). For each tissue surrogate, region-of-interest (ROI) analyses were made to derive high-energy and low-energy HU values (HUhigh and HUlow), which were subsequently used to estimate electron density based on the algorithm as previously described by Hunemohr N., et al. Parameters k1 and k2 are energy dependent and can be derived from calibration materials. Results: While for the dual-energy FBCT, the electron density is found be within +/−3% error relative to the values provided by the phantom vendor: −1.8% (water), 0.03% (lung), 1.1% (brain), −2.82% (adipose), −0.49% (liver) and −1.89% (cortical bones). While for the DECBCT, the estimation of electron density exhibits a relatively larger variation: −1.76% (water), −36.7% (lung), −1.92% (brain), −3.43% (adipose), 8.1% (liver) and 9.5% (cortical bones). Conclusion: For DECBCT, the accuracy of electron density estimation is inferior to that of a FBCT, especially for materials of either low-density (lung) or high density (cortical bone) compared to water. Such limitation arises from inaccurate HU number derivation in a CBCT. Advanced scatter-correction and HU calibration routines, as well as the deployment of photon counting CT detectors need be investigated to minimize the difference between FBCT and CBCT.},
doi = {10.1118/1.4956121},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: To investigate the feasibility of using scatter corrected cone beam CT (CBCT) for proton adaptive planning. Methods: Phantom study was used to evaluate the CT number difference between the planning CT (pCT), quantitative CBCT (qCBCT) with scatter correction and calibrated Hounsfield units using adaptive scatter kernel superposition (ASKS) technique, and raw CBCT (rCBCT). After confirming the CT number accuracy, prostate patients, each with a pCT and several sets of weekly CBCT, were investigated for this study. Spot scanning proton treatment plans were independently generated on pCT, qCBCT and rCBCT. The treatment plans were then recalculated on all images. Dose-volume-histogrammore » (DVH) parameters and gamma analysis were used to compare between dose distributions. Results: Phantom study suggested that Hounsfield unit accuracy for different materials are within 20 HU for qCBCT and over 250 HU for rCBCT. For prostate patients, proton dose could be calculated accurately on qCBCT but not on rCBCT. When the original plan was recalculated on qCBCT, tumor coverage was maintained when anatomy was consistent with pCT. However, large dose variance was observed when patient anatomy change. Adaptive plan using qCBCT was able to recover tumor coverage and reduce dose to normal tissue. Conclusion: It is feasible to use qu antitative CBCT (qCBCT) with scatter correction and calibrated Hounsfield units for proton dose calculation and adaptive planning in proton therapy. Partly supported by Varian Medical Systems.« less
  • Purpose: To assess dose calculation accuracy of cone-beam CT (CBCT) based treatment plans using a patient-specific stepwise CT-density conversion table in comparison to conventional CT-based treatment plans. Methods: Unlike CT-based treatment planning which use fixed CT-density table, this study used patient-specific CT-density table to minimize the errors in reconstructed mass densities due to the effects of CBCT Hounsfield unit (HU) uncertainties. The patient-specific CT-density table was a stepwise function which maps HUs to only 6 classes of materials with different mass densities: air (0.00121g/cm3), lung (0.26g/cm3), adipose (0.95g/cm3), tissue (1.05 g/cm3), cartilage/bone (1.6g/cm3), and other (3g/cm3). HU thresholds to definemore » different materials were adjusted for each CBCT via best match with the known tissue types in these images. Dose distributions were compared between CT-based plans and CBCT-based plans (IMRT/VMAT) for four types of treatment sites: head and neck (HN), lung, pancreas, and pelvis. For dosimetric comparison, PTV mean dose in both plans were compared. A gamma analysis was also performed to directly compare dosimetry in the two plans. Results: Compared to CT-based plans, the differences for PTV mean dose were 0.1% for pelvis, 1.1% for pancreas, 1.8% for lung, and −2.5% for HN in CBCT-based plans. The gamma passing rate was 99.8% for pelvis, 99.6% for pancreas, and 99.3% for lung with 3%/3mm criteria, and 80.5% for head and neck with 5%/3mm criteria. Different dosimetry accuracy level was observed: 1% for pelvis, 3% for lung and pancreas, and 5% for head and neck. Conclusion: By converting CBCT data to 6 classes of materials for dose calculation, 3% of dose calculation accuracy can be achieved for anatomical sites studied here, except HN which had a 5% accuracy. CBCT-based treatment planning using a patient-specific stepwise CT-density table can facilitate the evaluation of dosimetry changes resulting from variation in patient anatomy.« less
  • Purpose: In searching for a robust, efficient and cost-effective dual energy cone beam CT (DECBCT) solution for various radiation oncology applications, in particularly for improved proton dose planning/replanning accuracy and DE-CBCT guided radiation therapy, we investigate a novel energy modulation scheme using a beam modifier placed between the source and patient and optimize its geometric configuration for routine clinical use. Methods: The study was performed using a Hitachi CBCT scanner and the tube voltage was set at 125 kVp. The higher energy beam was obtained by filtering the incident utilizing a beam modulation layer (material: copper, thickness: 1.8 mm). Tomore » avoid the need for double scans (one with and one without the energy modulator), the modulation layer was configured to cover only the half of the X-ray beam so that two sets of sinograms corresponding low and high energies were collected after a single gantry rotation of 360 deg. The average high energy and low energy HU numbers (HUhigh and HUlow) were derived for pixels in a defined region-of-interest, respectively. Results: The beam modifier increased the threshold of the energy spectrum from ∼20 keV up to ∼50 keV. Two complete sets of images were obtained with good alignment between the high energy and low-energy cases without any artifact observed (Fig. 2). The HUlow/HUhigh is ∼0/0 (water), ∼394/238 (brain), ∼1283/1085 (cortical bone) and ∼3000/1800 (titanium). Conclusion: The feasibility of the proposed DECT implementation using a beam modifier has been demonstrated. Compared to the existing DECT solutions, the proposed scheme is much more cost-effective and requires minimum hardware modification. The work lays foundation for us to study the quantification of HU values to derive material density images and atomic number (and electron density) of substances.« less
  • Purpose: To compare the difference in Hounsfield unit-relative stopping power and evaluate the dosimetric impact of spectral vs. conventional CT on proton therapy treatment plans. Method: The Philips prototype (IQon), a detector-based, spectral CT system (spectral) was used to scan calibration and Rando phantoms. Data were reconstructed with and without energy decomposition to produce monoenergetic 70 keV, 140 keV, and the Zeff images. Relative stopping power (RSP) in the head and lung regions were evaluated as a function of HU in order to compare spectral and conventional CT. Treatment plans for the Rando phantom were also generated and used tomore » produce DVHs of fictitious target volume and organ-at-risk contoured on the head and lung. Results: Agreement of the Zeff of the tissue-substitute materials determined using spectral CT agrees to within 1 to 5% of the Zeff of the known phantom composition. The discrepancy is primarily attributed to non-uniformity in the phantom. Differences between the HU-RSP curves obtained using spectral and conventional CT were small except for in the lung curve at HU>1000. The large difference in planned doses using Spectral vs. conventional CT occurred in a low-dose brain region (1.7mm between the locations of the 100 cGy lines and 3 mm for 50 cGy lines). Conclusion: Conventionally, a single HU-RSP from CT scanner is used in proton treatment planning. Spectral CT allows site-specific HU-RSP for each patient. Spectral and conventional HU-RSP may result in different distributions as shown here. Additional study is required to evaluate the impact of Spectral CT in proton treatment planning. This study is part of a research agreement between Philips and University Hospitals/Case Medical Center.« less
  • Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal andmore » distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.« less