bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐J‐193: Efficient Dose Extinction Method for Water Equivalent Path Length (WEPL) of Real Tissue Samples for Validation of CT HU to Stopping Power Conversion
Authors: Zhang R , Baer E , Jee K , Sharp G , Flanz J , Lu H 
Published: July 2016

Purpose:For proton therapy, an accurate model of CT HU to relative stopping power (RSP) conversion is essential. In current practice, validation of these models relies solely on measurements of tissue substitutes with standard compositions. Validation based on real tissue samples would be much more direct and can address variations between patients. This study intends to develop an efficient and accurate system based on the concept of dose extinction to measure WEPL and retrieve RSP in biological tissue in large number of types.Methods:A broad AP proton beam delivering a spread out Bragg peak (SOBP) is used to irradiate the samples with a Matrixx detector positioned immediately below. A water tank was placed on top of the samples, with the water level controllable in sub‐millimeter by a remotely controlled dosing pump. While gradually lowering the water level with beam on, the transmission dose was recorded at 1 frame/sec. The WEPL were determined as the difference between the known beam range of the delivered SOBP (80%) and the water level corresponding to 80% of measured dose profiles in time. A Gammex 467 phantom was used to test the system and various types of biological tissue was measured.Results:RSP for all Gammex inserts, expect the one made with lung‐450 material (<2% error), were determined within ±0.5% error. Depends on the WEPL of investigated phantom, a measurement takes around 10 min, which can be accelerated by a faster pump.Conclusion:Based on the concept of dose extinction, a system was explored to measure WEPL efficiently and accurately for a large number of samples. This allows the validation of CT HU to stopping power conversions based on large number of samples and real tissues. It also allows the assessment of beam uncertainties due to variations over patients, which issue has never been sufficiently studied before.
SU‐F‐J‐199: Predictive Models for Cone Beam CT‐Based Online Verification of Pencil Beam Scanning Proton Therapy
Authors: Yin L , Janssens G , Lin A , Ahn P , Solberg T , McDonough J , Teo B 
Published: July 2016

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 and 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.
SU‐F‐J‐205: Effect of Cone Beam Factor On Cone Beam CT Number Accuracy
Authors: Yao W , Hua C , Farr J , Brady S , Merchant T 
Published: July 2016

Purpose:To examine the suitability of a Catphan™ 700 phantom for image quality QA of a cone beam computed tomography (CBCT) system deployed for proton therapy.Methods:Catphan phantoms, particularly Catphan™ 504, are commonly used in image quality QA for CBCT. As a newer product, Catphan™ 700 offers more tissue equivalent inserts which may be useful for generating the electron density – CT number curve for CBCT based treatment planning. The sensitometry‐and‐geometry module used in Catphan™ 700 is located at the end of the phantom and after the resolution line pair module. In Catphan™ 504 the line pair module is located at the end of the phantom and after the sensitometry‐and‐geometry module. To investigate the effect of difference in location on CT number accuracy due to the cone beam factor, we scanned the Catphan™ 700 with the central plane of CBCT at the center of the phantom, line pair and sensitometry‐andgeometry modules of the phantom, respectively. The protocol head and thorax scan modes were used. For each position, scans were repeated 4 times.Results:For the head scan mode, the standard deviation (SD) of the CT numbers of each insert under 4 repeated scans was up to 20 HU, 11 HU, and 11 HU, respectively, for the central plane of CBCT located at the center of the phantom, line pair, and sensitometry‐and‐geometry modules of the phantom. The mean of the SD was 9.9 HU, 5.7 HU, and 5.9 HU, respectively. For the thorax mode, the mean of the SD was 4.5 HU, 4.4 HU, and 4.4 HU, respectively. The assessment of image quality based on resolution and spatial linearity was not affected by imaging location changes.Conclusion:When the Catphan™ 700 was aligned to the center of imaging region, the CT number accuracy test may not meet expectations. We recommend reconfiguration of the modules.
SU‐F‐J‐211: Scatter Correction for Clinical Cone‐Beam CT System Using An Optimized Stationary Beam Blocker with a Single Scan
Authors: Liang X , Gong S , Zhou Q , Zhang Z , Xie Y , Niu T 
Published: July 2016

Purpose:X‐ray scatter photons result in significant image quality degradation of cone‐beam CT (CBCT). Measurement based algorithms using beam blocker directly acquire the scatter samples and achieve significant improvement on the quality of CBCT image. Within existing algorithms, single‐scan and stationary beam blocker proposed previously is promising due to its simplicity and practicability. Although demonstrated effectively on tabletop system, the blocker fails to estimate the scatter distribution on clinical CBCT system mainly due to the gantry wobble. In addition, the uniform distributed blocker strips in our previous design results in primary data loss in the CBCT system and leads to the image artifacts due to data insufficiency.Methods:We investigate the motion behavior of the beam blocker in each projection and design an optimized non‐uniform blocker strip distribution which accounts for the data insufficiency issue. An accurate scatter estimation is then achieved from the wobble modeling. Blocker wobble curve is estimated using threshold‐based segmentation algorithms in each projection. In the blocker design optimization, the quality of final image is quantified using the number of the primary data loss voxels and the mesh adaptive direct search algorithm is applied to minimize the objective function. Scatter‐corrected CT images are obtained using the optimized blocker.Results:The proposed method is evaluated using Catphan@504 phantom and a head patient. On the Catphan©504, our approach reduces the average CT number error from 115 Hounsfield unit (HU) to 11 HU in the selected regions of interest, and improves the image contrast by a factor of 1.45 in the high‐contrast regions. On the head patient, the CT number error is reduced from 97 HU to 6 HU in the soft tissue region and image spatial non‐uniformity is decreased from 27% to 5% after correction.Conclusion:The proposed optimized blocker design is practical and attractive for CBCT guided radiation therapy.This work is supported by grants from Guangdong Innovative Research Team Program of China (Grant No. 2011S013), National 863 Programs of China (Grant Nos. 2012AA02A604 and 2015AA043203), the National High‐tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917)
SU‐F‐J‐213: Feasibility Study of Using a Dual‐Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning
Authors: Peng H , Kanehira T , Takao S , Matsuura T , Umegaki K , Shirato H , Xing L 
Published: July 2016

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.
SU‐F‐J‐216: MR‐Guided Non‐Thermal Pulsed Focused Ultrasound for Cancer Therapy
Authors: Ma C , Wang B , Cvetkovic D , Chen L 
Published: July 2016

Purpose:High‐intensity focused ultrasound has been investigated for ablative therapy and drug enhancement for gene therapy and chemotherapy. The aim of this work is to explore the feasibility of pulsed focused ultrasound (pFUS) for non‐thermal cancer therapy using an in vivo animal model.Methods:An InSightec ExAblate 2000 with a 1.5T GE MR scanner was used in this study. Suitable ultrasound parameters were investigated to perform non‐thermal sonications. LNCaP human prostate tumor cells (106) were injected orthotopically in the prostates of nude mice (n = 16). When tumors reached the volume of 88 ± 18 mm3 as measured on MRI, the tumor‐bearing mice (n = 10) were treated with pFUS (1 MHz frequency; 25 W acoustic power; 0.1 duty cycle; 60 sec duration) 4 times in 2 weeks. A total of 6–12 sonications were used to cover the entire tumor volume under MR image guidance. The animals were allowed to survive for 4 weeks after the initial treatment. The tumor volume was measured on MRI weekly post treatment and was compared with that of the control group (n = 6).Results:Significant tumor growth delay was observed in the tumor‐bearing mice treated with pFUS. The mean tumor volume for the pFUS treated mice grew from 1 to 1.18 and 1.81 at 1 week and 2 weeks after the initial treatment, respectively, while the mean tumor volume of the control mice grew from 1 to 1.67 and 2.78, respectively, over the same time periods. These results are statistically significant and are consistent with our previous findings.Conclusion:Our results demonstrated that non‐thermal pFUS has a great potential for cancer therapy. Further experiments are needed to understand the cell killing mechanisms of pFUS and to derive optimal ultrasound parameters and fractionation schemes to maximize the therapeutic effect of pFUS.
SU‐F‐J‐218: Predicting Radiation‐Induced Xerostomia by Dosimetrically Accounting for Daily Setup Uncertainty During Head and Neck IMRT
Authors: Park S , Quon H , McNutt T , Plishker W , Shekhar R , Lee J 
Published: July 2016

Purpose:To determine if the accumulated parotid dosimetry using planning CT to daily CBCT deformation and dose re‐calculation can predict for radiation‐induced xerostomia.Methods:To track and dosimetrically account for the effects of anatomical changes on the parotid glands, we propagated physicians’ contours from planning CT to daily CBCT using a deformable registration with iterative CBCT intensity correction. A surface mesh for each OAR was created with the deformation applied to the mesh to obtain the deformed parotid volumes. Daily dose was computed on the deformed CT and accumulated to the last fraction. For both the accumulated and the planned parotid dosimetry, we tested the prediction power of different dosimetric parameters including D90, D50, D10, mean, standard deviation, min/max dose to the combined parotids and patient age to severe xerostomia (NCI‐CTCAE grade≥2 at 6 mo follow‐up). We also tested the dosimetry to parotid sub‐volumes. Three classification algorithms, random tree, support vector machine, and logistic regression were tested to predict severe xerostomia using a leave‐one‐out validation approach.Results:We tested our prediction model on 35 HN IMRT cases. Parameters from the accumulated dosimetry model demonstrated an 89% accuracy for predicting severe xerostomia. Compared to the planning dosimetry, the accumulated dose consistently demonstrated higher prediction power with all three classification algorithms, including 11%, 5% and 30% higher accuracy, sensitivity and specificity, respectively. Geometric division of the combined parotid glands into superior‐inferior regions demonstrated ∼5% increased accuracy than the whole volume. The most influential ranked features include age, mean accumulated dose of the submandibular glands and the accumulated D90 of the superior parotid glands.Conclusion:We demonstrated that the accumulated parotid dosimetry using CT‐CBCT registration and dose re‐calculation more accurately predicts for severe xerostomia and that the superior portion of the parotid glands may be particularly important in predicting for severe xerostomia.This work was supported in part by NIH/NCI under grant R42CA137886 and in part by Toshiba big data research project funds.
SU‐F‐J‐219: Predicting Ventilation Change Due to Radiation Therapy: Dependency On Pre‐RT Ventilation and Effort Correction
Authors: Patton T , Du K , Christensen G , Reinhardt J , Bayouth J 
Published: July 2016

Purpose:Ventilation change caused by radiation therapy (RT) can be predicted using four‐dimensional computed tomography (4DCT) and image registration. This study tested the dependency of predicted post‐RT ventilation on effort correction and pre‐RT lung function.Methods:Pre‐RT and 3 month post‐RT 4DCT images were obtained for 13 patients. The 4DCT images were used to create ventilation maps using a deformable image registration based Jacobian expansion calculation. The post‐RT ventilation maps were predicted in four different ways using the dose delivered, pre‐RT ventilation, and effort correction. The pre‐RT ventilation and effort correction were toggled to determine dependency. The four different predicted ventilation maps were compared to the post‐RT ventilation map calculated from image registration to establish the best prediction method. Gamma pass rates were used to compare the different maps with the criteria of 2mm distance‐to‐agreement and 6% ventilation difference. Paired t‐tests of gamma pass rates were used to determine significant differences between the maps. Additional gamma pass rates were calculated using only voxels receiving over 20 Gy.Results:The predicted post‐RT ventilation maps were in agreement with the actual post‐RT maps in the following percentage of voxels averaged over all subjects: 71% with pre‐RT ventilation and effort correction, 69% with no pre‐RT ventilation and effort correction, 60% with pre‐RT ventilation and no effort correction, and 58% with no pre‐RT ventilation and no effort correction. When analyzing only voxels receiving over 20 Gy, the gamma pass rates were respectively 74%, 69%, 65%, and 55%. The prediction including both pre‐ RT ventilation and effort correction was the only prediction with significant improvement over using no prediction (p<0.02).Conclusion:Post‐RT ventilation is best predicted using both pre‐RT ventilation and effort correction. This is the only prediction that provided a significant improvement on agreement.Research support from NIH grants CA166119 and CA166703, a gift from Roger Koch, and a Pilot Grant from University of Iowa Carver College of Medicine
SU‐F‐J‐220: Micro‐CT Based Quantification of Mouse Brain Vasculature: The Effects of Acquisition Technique and Contrast Material
Authors: Tipton C , Lamba M , Qi Z , LaSance K , Tipton C 
Published: July 2016

Purpose:Cognitive impairment from radiation therapy to the brain may be linked to the loss of total blood volume in the brain. To account for brain injury, it is crucial to develop an understanding of blood volume loss as a result of radiation therapy. This study investigates µCT based quantification of mouse brain vasculature, focusing on the effect of acquisition technique and contrast material.Methods:Four mice were scanned on a µCT scanner (Siemens Inveon). The reconstructed voxel size was 18µm3 and all protocols were Hounsfield Unit (HU) calibrated. The mice were injected with 40mg of gold nanoparticles (MediLumine) or 100µl of Exitron 12000 (Miltenyi Biotec). Two acquisition techniques were also performed. A single kVp technique scanned the mouse once using an x‐ray beam of 80kVp and segmentation was completed based on a threshold of HU values. The dual kVp technique scanned the mouse twice using 50kVp and 80kVp, this segmentation was based on the ratio of the HU value of the two kVps. After image reconstruction and segmentation, the brain blood volume was determined as a percentage of the total brain volume.Results:For the single kVp acquisition at 80kVp, the brain blood volume had an average of 3.5% for gold and 4.0% for Exitron 12000. Also at 80kVp, the contrast‐noise ratio was significantly better for images acquired with the gold nanoparticles (2.0) than for those acquired with the Exitron 12000 (1.4). The dual kVp acquisition shows improved separation of skull from vasculature, but increased image noise.Conclusion:In summary, the effects of acquisition technique and contrast material for quantification of mouse brain vasculature showed that gold nanoparticles produced more consistent segmentation of brain vasculature than Exitron 12000. Also, dual kVp acquisition may improve the accuracy of brain vasculature quantification, although the effect of noise amplification warrants further study.
SU‐F‐J‐221: Adjusted Dose and Its Relation to Radiation Induced Liver Disease During Hepatocellular Carcinoma Radiotherapy
Authors: Huang P , Li H , Chen J , Ma C , Gang Y , Qin S , Yin Y , Li D 
Published: July 2016

Purpose:Many patients with hepatocellular carcinoma (HCC) had hepatic anatomy variations as a result of inter‐fraction deformation during fractionated radiotherapy, which may result in difference from the planned dose. This study aimed to investigate the relationship between adjusted dose and radiation induced liver disease (RILD) in HCC patients receiving three dimensional conformal radiotherapy (3DCRT).Methods:Twenty‐three HCC patients received conventional fractionated 3DCRT were enrolled in this retrospective investigation. Among them, seven patients had been diagnosed of RILD post‐radiotherapy, including 4 cases of grade 2, 3 cases of grade 3 according to the CTCAE Version 3.0. Daily cone‐beam CT (CBCT) scans were acquired throughout the whole treatment course for each patient. To reconstruct the daily dose to a patient considering the interfraction anatomy variations, the planned beams from each patient's treatment plan were firstly applied to each daily modified CBCT (mCBCT). The daily doses were then summed together with the help of deformable image registration (DIR) to obtain the adjusted dose (Dadjusted) of the patient. Finally, the dose changes in normal liver between planned dose (Dplan) and Dadjusted were evaluated by V20, V30, V40 and the mean dose to normal liver (MDTNL). Univariate analysis was performed to identify the significant dose changes.Results:Among the twenty‐three patients, the adjusted liver V20, V30, V40 and MDTNL showed significant changes from the planned ones (p<0.05) and averagely increased by 4.1%, 4.7%, 4.5% and 3.9Gy, respectively. And the adjusted liver dose in twenty‐one patients (91%) were higher than planned value, the adjusted dose of patients with RILD (6/7) exceeds to the hepatic radiation tolerance.Conclusion:The adjusted dose of all the studied patients significantly differs from planned dose, and mCBCT‐based dose reconstruction can aid in evaluating the robustness of the planning solutions, and adjusted dose has the potential to reduce the risk of RILD.The author would like to express great thanks to Lei Xing, Daniel S Kapp and Yong Yang in the Stanford University School of Medicine for their valuable suggestions to this work.This work is supported by NSFC(61471226),China Postdoctoral Science Foundation (2015T80739, 2014M551949) and research funding from Shandong Province(JQ201516).
SU‐F‐J‐222: Using PET Imaging to Evaluate Proliferation and Blood Flow in Irradiated and Non‐Irradiated Bone Marrow 1 Year After Chemoradiation Therapy
Authors: McGuire S , Ponto L , Menda Y 
Published: July 2016

Purpose:To compare proliferation and blood flow in pelvic and thoracic bone marrow 1 year after pelvic chemoradiation.Methods:Sixteen pelvic cancer patients were enrolled in an IRB‐approved protocol to acquire FLT PET images during radiation therapy simulation (baseline) and 1 year after chemoradiation therapy. Three subjects also had optional O‐15 water PET images acquired 1 year after chemoradiation therapy. Baseline FLT PET images were used to create IMRT plans to spare pelvic bone marrow identified as regions with FLT SUV ≥ 2 without compromising PTV coverage or OAR sparing. Marrow VOIs were defined using a 50% maximum pixel value threshold on baseline FLT PET images (VIEW, PMOD version 3.5) in the sacrum and thoracic spine representing irradiated and non‐irradiated regions, respectively. FLT PET and O‐15 water PET images acquired 1 year after therapy were co‐registered to baseline images (FUSION PMOD) and the same VOIs were used to measure proliferation (FLT SUV) and blood flow (O‐15 water uptake). Separate image‐based input functions were used for blood flow quantitation in each VOI.Results:Mean 1 year FLT SUV in sacral and thoracic VOIs for were 1.1 ± 0.4 and 6.5 ± 1.7, respectively for N = 16 subjects and were 1.2 ± 0.2 and 5.6 ± 1.6, respectively for N = 3 subjects who also underwent O‐15 water imaging. Blood flow measures in equivalent sacral and thoracic marrow regions (N = 3) were 21.3 ± 8.7 and 18.3 ± 4.9 mL/min/100mL respectively.Conclusion:Decreased bone marrow proliferation measured by FLT SUV does not appear to correspond to decreased blood flow as measured by O‐15 water PET imaging. Based on this small sample at a single time point, reduced blood supply does not explain reductions in bone marrow proliferative activity 1 year after chemoradiation therapy.