bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐146: Spatial Accuracy QA of An MR System
Authors: Hwang K , Illerstam F , Torfeh T , Maier J , Shave S , Hoang M 
Published: July 2014

Purpose:To develop a phantom and measurement protocol for quantifying spatial accuracy of an MR imaging system over its entire imaging volume.Methods:The measurement protocol is comprised of a phantom, a set of MR sequence parameters for imaging the phantom, and analysis software for calculating spatial errors in the acquired phantom images. The phantom covers the entire imaging volume of the scanner above the patient table, and consists of layers of foam embedded with a matrix of spherical markers. To account for possible spatial errors in the construction of the phantom, the phantom may be imaged with CT to create a gold standard data set. On MR scanners, the phantom is acquired with a 3D FGRE sequence that covers the full imaging volume. Error measurements are performed by detecting markers in the image sets and identifying them based on their known locations on the phantom. The spatial error of a marker is defined as the difference between its locations on the MR and CT image sets. The phantom, protocol, and analysis program may also be adapted to different applications by allowing for differences in phantom size and region of analysis within the scanner.Results:Three copies of the phantom were constructed and the measurement protocol was successfully executed on several MR scanners at multiple sites. Submillimeter precision and repeatability of the marker detection was also confirmed with manual measurements and repeated acquisitions on a single scanner.Conclusion:The proposed phantom and protocol can be an effective tool for verifying the spatial accuracy of an MR system, which in turn can improve the accuracy and confidence of MR guided therapies. Data from this protocol may also serve as a basis for a specification for spatial accuracy or be used in the development of advanced distortion correction algorithms.Hwang, Illerstam, Maier, and Hoang are employees of GE Healthcare.
SU‐E‐J‐149: Establishing the Relationship Between Pre‐Treatment Lung Ventilation, Dose, and Toxicity Outcome
Authors: Mistry N , D' Souza W , Sornsen de Koste J , Senan S 
Published: July 2014

Purpose:Recently, there has been an interest in incorporating functional information in treatment planning especially in thoracic tumors. The rationale is that healthy lung regions need to be spared from radiation if possible to help achieve better control on toxicity. However, it is still unclear whether high functioning regions need to be spared or have more capacity to deal with the excessive radiation as compared to the compromised regions of the lung. Our goal with this work is to establish the tools by which we can establish a relationship between pre‐treatment lung function, dose, and radiographic outcomes of lung toxicity.Methods:Treatment planning was performed using a single phase of a 4DCT scan, and follow‐up anatomical CT scans were performed every 3 months for most patients. In this study, we developed the pipeline of tools needed to analyze such a large dataset, while trying to establish a relationship between function, dose, and outcome. Pre‐treatment lung function was evaluated using a recently published technique that evaluates Fractional Regional Ventilation (FRV). All images including the FRV map and the individual follow‐up anatomical CT images were all spatially matched to the planning CT using a diffusion based Demons image registration algorithm. Change in HU value was used as a metric to capture the effects of lung toxicity. To validate the findings, a radiologist evaluated the follow‐up anatomical CT images and scored lung toxicity.Results:Initial experience in 1 patient shows a relationship between the pre‐treatment lung function, dose and toxicity outcome. The results are also correlated to the findings by the radiologist who was blinded to the analysis or dose.Conclusion:The pipeline we have established to study this enables future studies in large retrospective studies. However, the tools are dependent on the fidelity of 4DCT reconstruction for accurate evaluation of regional ventilation.Patent Pending for the technique presented in this work to evaluate FRV incorporating mass correction.
SU‐E‐J‐152: Evaluation of TrueBeam OBI V. 1.5 CBCT Performance in An Adaptive RT Environment
Authors: Gardner S , Studenski M , Giaddui T , Cui Y , Galvin J , Yu Y , Xiao Y 
Published: July 2014

Purpose:To evaluate the image quality and imaging dose of the Varian TrueBeam OBIv.1.5 CBCT system in a clinical adaptive radiation therapy environment, simulated by changing phantom thickness.Methods:Various OBI CBCT protocols(Head, Pelvis, Thorax, Spotlight) were used to acquire images of Catphan504 phantom(nominal phantom thickness and 10 cm additional phantom thickness). The images were analyzed for low contrast detectability(CNR), uniformity(UI), and HU sensitivity. These results were compared to the same image sets for planning CT(pCT)(GE LightSpeed 16‐ slice). Imaging dose measurements were performed with Gafchromic XRQA2 film for various OBI protocols (Pelvis, Thorax, Spotlight) in a pelvic‐sized phantom(nominal thickness and 4cm additional thickness). Dose measurements were acquired in the interior and at the surface of the phantom.Results:The nominal CNR[additional thickness CNR] for OBI was—Pelvis:1.45[0.81],Thorax:0.86[0.48], Spotlight:0.67[0.39],Head:0.28 [0.10]. The nominal CNR[additional thickness CNR] for pCT was— Pelvis:0.87[0.41],Head:0.60[0.22]. The nominal UI[additional thickness UI] for OBI was—Pelvis:11.5[24.1],Thorax:17.0[20.6], Spotlight:23.2[23.2], Head:15.6[59.9]. The nominal UI[additional thickness UI] for pCT was— Pelvis:9.2[8.6],Head:2.1[2.9]. The HU difference(averaged over all material inserts) between nominal and additional thickness scans for OBI: 8.26HU(Pelvis), 33.39HU(Thorax), 178.98HU(Head), 108.20HU (Spotlight); for pCT: 16.00HU(Pelvis), 19.85HU(Head). Uncertainties in electron density were calculated based on HU values with varying phantom thickness. Average electron‐density deviations (ρ(water)=1)for GE‐Pelvis, GE‐Head, OBI‐Pelvis, OBI‐Thorax, OBI‐Spotlight, and OBI‐Head were: 0.0182, 0.0180, 0.0058, 0.0478, 0.2750, and 0.3115, respectively. The average phantom interior dose was(OBI‐nominal):2.35cGy(Pelvis), 0.60cGy(Thorax), 1.87cGy(Spotlight); OBI‐increased thickness: 1.77cGy(Pelvis), 0.43cGy(Thorax), 1.53cGy (Spotlight). Average surface dose(OBI‐nominal): 2.29cGy(Pelvis), 0.56cGy(Thorax), 1.79cGy (Spotlight); OBI‐increased thickness: 1.94cGy(Pelvis), 0.48cGy(Thorax), 1.47cGy (Spotlight).Conclusion:The OBI‐Pelvis protocol offered comparable CNR and HU constancy to pCT for each geometry; other protocols, particularly Spotlight and Head, exhibited lower HU constancy and CNR. The uniformity of pCT was superior to OBI for all protocols. CNR and UI were degraded for both systems/scan types with increased thickness. The OBI interior dose decreased by approximately 30% with additional thickness.This work was funded, in part, under a grant with the Pennsylvania Department of Health. The Department of Health specifically declaims responsibility for any analyses, interpretations, or conclusions.
SU‐E‐J‐153: MRI Based, Daily Adaptive Radiotherapy for Rectal Cancer: Contour Adaptation
Authors: Kleijnen J , Burbach M , Verbraeken T , Weggers R , Zoetelief A , Reerink O , Lagendijk J , Raaymakers B , Asselen B 
Published: July 2014

Purpose:A major hurdle in adaptive radiotherapy is the adaptation of the planning MRI's delineations to the daily anatomy. We therefore investigate the accuracy and time needed for online clinical target volume (CTV) adaptation by radiation therapists (RTT), to be used in MRI‐guided adaptive treatments on a MRI‐Linac (MRL).Methods:Sixteen patients, diagnosed with early stage rectal cancer, underwent a T2‐weighted MRI prior to each fraction of short‐course radiotherapy, resulting in 4–5 scans per patient. On these scans, the CTV was delineated according to guidelines by an experienced radiation oncologist (RO) and considered to be the gold standard. For each patient, the first MRI was considered as the planning MRI and matched on bony anatomy to the 3–4 daily MRIs. The planning MRI's CTV delineation was rigidly propagated to the daily MRI scans as a proposal for adaptation. Three RTTs in training started the adaptation of the CTV conform guidelines, after a two hour training lecture and a two patient (n=7) training set. To assess the inter‐therapist variation, all three RTTs altered delineations of 3 patients (n=12). One RTT altered the CTV delineations (n=53) of the remaining 11 patients. Time needed for adaptation of the CTV to guidelines was registered.As a measure of agreement, the conformity index (CI) was determined between the RTTs' delineations as a group. Dice similarity coefficients were determined between delineations of the RTT and the RO.Results:We found good agreement between RTTs' and RO's delineations (average Dice=0.91, SD=0.03). Furthermore, the inter‐observer agreement between the RTTs was high (average CI=0.94, SD=0.02). Adaptation time reduced from 10:33 min (SD= 3:46) to 2:56 min (SD=1:06) between the first and last ten delineations, respectively.Conclusion:Daily CTV adaptation by RTTs, seems a feasible and safe way to introduce daily, online MRI‐based plan adaptation for a MRL.
SU‐E‐J‐156: Preclinical Inverstigation of Dynamic Tumor Tracking Using Vero SBRT Linear Accelerator: Motion Phantom Dosimetry Study
Authors: Mamalui‐Hunter M , Wu J , Li Z , Su Z 
Published: July 2014

Purpose:Following the ‘end‐to‐end testing’ paradigm of Dynamic Target Tracking option in our Image‐Guided dedicated SBRT VeroTM linac, we verify the capability of the system to deliver planned dose to moving targets in the heterogeneous thorax phantom (CIRSTM). The system includes gimbaled C‐band linac head, robotic 6 degree of freedom couch and a tumor tracking method based on predictive modeling of target position using fluoroscopically tracked implanted markers and optically tracked infrared reflecting external markers.Methods:4DCT scan of the motion phantom with the VisicoilTM implanted marker in the close vicinity of the target was acquired, the ‘exhale’=most prevalent phase was used for planning (iPlan by BrainLabTM). Typical 3D conformal SBRT treatment plans aimed to deliver 6‐8Gy/fx to two types of targets: a)solid water‐equivalent target 3cm in diameter; b)single VisicoilTM marker inserted within lung equivalent material. The planning GTV/CTV‐to‐PTV margins were 2mm, the block margins were 3 mm. The dose calculated by MonteCarlo algorithm with 1% variance using option Dose‐to‐water was compared to the ion chamber (CC01 by IBA Dosimetry) measurements in case (a) and GafchromicTM EBT3 film measurements in case (b). During delivery, the target 6 motion patterns available as a standard on CIRSTM motion phantom were investigated: in case (a), the target was moving along the designated sine or cosine4 3D trajectory; in case (b), the inserted marker was moving sinusoidally in 1D.Results:The ion chamber measurements have shown the agreement with the planned dose within 1% under all the studied motion conditions. The film measurements show 98.1% agreement with the planar calculated dose (gamma criteria: 3%/3mm).Conclusion:We successfully verified the capability of the SBRT VeroTM linac to perform real‐time tumor tracking and accurate dose delivery to the target, based on predictive modeling of the correlation between implanted marker motion and external surrogate of breathing motion.
SU‐E‐J‐160: Comparing the Setup Accuracy of Non‐Ionizing Patient Localization Systems with CBCT to Reduce Imaging Dose in Prone Breast Treatments
Authors: Chung E , Yamamoto T , Mayadev J , Dieterich S 
Published: July 2014

Purpose:CBCT is the current gold standard to verify prone breast patient setup. We investigated in a phantom if non‐ionizing localization systems can replace ionizing localization systems for prone breast treatments.Methods:An anthropomorphic phantom was positioned on a prone breast board. Electromagnetic transponders were attached on the left chest surface. The CT images of the phantom were imported to the treatment planning system. The isocenter was set to the center of the transponders. The positions of the isocenter and transponders transferred to the transponder tracking system. The posterior phantom surface was contoured and exported to the optical surface tracking system. A CBCT was taken for the initial setup alignment on the treatment machine. Using the electromagnetic and optical localization systems, the deviation of the phantom setup from the original CT images was measured. This was compared with the difference between the original CT and kV‐CBCT images.Results:For the electromagnetic localization system, the phantom position deviated from the original CT in 1.5 mm, 0.0 mm and 0.5 mm in the anterior‐posterior (AP), superior‐inferior (SI) and left‐right (LR) directions. For the optical localization system, the phantom position deviated from the original CT in 2.0 mm, −2.0 mm and 0.1 mm in the AP, SI and LR directions. For the CBCT, the phantom position deviated from the original CT in 4.0 mm, 1.0 mm and −1.0 mm in the AP, SI and LR directions. The measured values from the non‐ionizing localization systems differed from those with the CBCT less than 3.0 mm in all directions.Conclusions:This phantom study showed the feasibility of using a combination of non‐ionizing localization systems to achieve a similar setup accuracy as CBCT for prone breast patients. This could potentially eliminate imaging dose. As a next step, we are expanding this study to actual patients.This work has been in part supported by Departmental Research Award RODEPT1‐JS001, Department of Radiation Oncology, UC Davis Medical Center.
SU‐E‐J‐162: Quality Assurance Procedures for MR Guided Focused Ultrasound Treatment of Bone Metastasis
Authors: Chen L , Chen X , Wang B , Gupta R , Ma C 
Published: July 2014

Purpose:The purpose of this work is to develop and verify our quality assurance (QA) procedures to ensure the safety and efficacy of MR‐guided focused ultrasound (MRgFUS) treatment of bone metastases.Methods:A practical QA program was developed. Monthly and daily QA (DQA) procedures were performed. The major QA items included the checks of the machine hardware, software and patient safety features. Briefly, these checks/tests include: 1) the cooling system reservoir and treatment table; 2) power to the treatment table; 3) the MR coil; 4) the transducer position with MRI; 5) image display on the treatment work station; 6) the effective focal spot in 3 directions using MR thermometry; and 7) all the safety devices including a sonication lamp, and the emergency stop‐sonication switches. In order to avoid patient skin burn, it is important to remove gas bubbles in the interfaces between the treatment table and the gel pad, and the gel pad and patients skin during the patient setup. Our QA procedures have been verified and evaluated through patient treatments. Seven patients with scapula, humeral head, sacrum, ilium, pubic ramus and acetabular bone metastases were treated using MRgFUS.Results:Our study showed that all seven patients tolerated the MRgFUS treatment well. No skin toxicity or other complications were observed. The pain score (0–10) using the visual analog scale (VAS) was significantly reduced from 8.0 ± 1.1 before treatment to 4.7 ± 3.0, 3.0 ± 1.5, 3.2 ± 2.8 and 3.4 ± 1.5 at one day, one month, two months and three months after the MRgFUS treatment, respectively.Conclusion:We demonstrated that with the appropriate QA procedures, MRgFUS is a safe, effective and noninvasive treatment modality for palliation of bone metastases.
SU‐E‐J‐182: A Feasibility Study Evaluating Automatic Identification of Gross Tumor Volume for Breast Cancer Radiotherapy Using Dynamic Contrast‐Enhanced MR Imaging
Authors: Wang C , Horton J , Yin F , Blitzblau R , Palta M , Chang Z 
Published: July 2014

Purpose:To develop a computerized pharmacokinetic model‐free Gross Tumor Volume (GTV) segmentation method based on dynamic contrastenhanced MRI (DCE‐MRI) data that can improve physician GTV contouring efficiency.Methods:12 patients with biopsy‐proven early stage breast cancer with post‐contrast enhanced DCE‐MRI images were analyzed in this study. A fuzzy c‐means (FCM) clustering‐based method was applied to segment 3D GTV from pre‐operative DCE‐MRI data. A region of interest (ROI) is selected by a clinician/physicist, and the normalized signal evolution curves were calculated by dividing the signal intensity enhancement value at each voxel by the pre‐contrast signal intensity value at the corresponding voxel. Three semi‐quantitative metrics were analyzed based on normalized signal evolution curves: initial Area Under signal evolution Curve (iAUC), Immediate Enhancement Ratio (IER), and Variance of Enhancement Slope (VES). The FCM algorithm wass applied to partition ROI voxels into GTV voxels and non‐GTV voxels by using three analyzed metrics. The partition map for the smaller cluster is then generated and binarized with an automatically calculated threshold. To reduce spurious structures resulting from background, a labeling operation was performed to keep the largest three‐dimensional connected component as the identified target. Basic morphological operations including hole‐filling and spur removal were useutilized to improve the target smoothness. Each segmented GTV was compared to that drawn by experienced radiation oncologists. An agreement index was proposed to quantify the overlap between the GTVs identified using two approaches and a thershold value of 0.4 is regarded as acceptable.Results:The GTVs identified by the proposed method were overlapped with the ones drawn by radiation oncologists in all cases, and in 10 out of 12 cases, the agreement indices were above the threshold of 0.4.Conclusion:The proposed automatic segmentation method was shown to be promising and might be used to improve physician contouring efficiency.J Horton receives grant from NIH and Varian Medical Systems; F‐F Yin receives grant from Varian Medical Systems
SU‐E‐J‐183: Quantifying the Image Quality and Dose Reduction of Respiratory Triggered 4D Cone‐Beam Computed Tomography with Patient‐ Measured Breathing
Authors: Cooper B , OBrien R , Kipritidis J , Keall P 
Published: July 2014

Purpose:Respiratory triggered four dimensional cone‐beam computed tomography (RT 4D CBCT) is a novel technique that uses a patient's respiratory signal to drive the image acquisition with the goal of imaging dose reduction without degrading image quality. This work investigates image quality and dose using patient‐measured respiratory signals for RT 4D CBCT simulations instead of synthetic sinusoidal signals used in previous work.Methods:Studies were performed that simulate a 4D CBCT image acquisition using both the novel RT 4D CBCT technique and a conventional 4D CBCT technique from a database of oversampled Rando phantom CBCT projections. A database containing 111 free breathing lung cancer patient respiratory signal files was used to create 111 RT 4D CBCT and 111 conventional 4D CBCT image datasets from realistic simulations of a 4D RT CBCT system. Each of these image datasets were compared to a ground truth dataset from which a root mean square error (RMSE) metric was calculated to quantify the degradation of image quality. The number of projections used in each simulation is counted and was assumed as a surrogate for imaging dose.Results:Based on 111 breathing traces, when comparing RT 4D CBCT with conventional 4D CBCT the average image quality was reduced by 7.6%. However, the average imaging dose reduction was 53% based on needing fewer projections (617 on average) than conventional 4D CBCT (1320 projections).Conclusion:The simulation studies using a wide range of patient breathing traces have demonstrated that the RT 4D CBCT method can potentially offer a substantial saving of imaging dose of 53% on average compared to conventional 4D CBCT in simulation studies with a minimal impact on image quality.A patent application (PCT/US2012/048693) has been filed which is related to this work.
SU‐E‐J‐194: Dynamic Tumor Tracking End‐To‐End Testing Using a 4D Thorax Phantom and EBT3 Films
Authors: Su Z , Wu J , Li Z , Mamalui‐Hunter M 
Published: July 2014

Purpose:To quantify the Vero linac dosimetric accuracy of the tumor dynamic tracking treatment using EBT3 film embedded in a 4D thorax phantom.Methods:A dynamic thorax phantom with tissue equivalent materials and a film insert were used in this study. The thorax phantom was scanned in 4DCT mode with a viscoil embedded in its film insert composed of lung equivalent material. Dynamic tracking planning was performed using the 50% phase CT set with 5 conformal beams at gantry angles of 330, 15, 60, 105 and 150 degrees. Each field is a 3cm by 3cm square centered at viscoil since there was no solid mass target. Total 3 different 1–2cos4 motion profiles were used with varied motion magnitude and cycle frequency. Before treatment plan irradiation, a 4D motion model of the target was established using a series of acquired fluoroscopic images and infrared markers motion positions. During irradiation, fluoroscopic image monitoring viscoil motion was performed to verify model validity. The irradiated films were scanned and the dose maps were compared to the planned Monte Carlo dose distributions. Gamma analyses using 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria were performed and presented.Results:For each motion pattern, a 4D motion model was built successfully and the target tracking performance was verified with fluoroscopic monitoring of the viscoil motion and its model predicted locations. The film gamma analysis showed the average pass rates among the 3 motion profiles are 98.14%, 96.2%, 91.3% and 85.61% for 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria.Conclusion:Target dynamic tracking was performed using patient‐like breathing patterns in a 4D thorax phantom with EBT3 film insert and a viscoil. There was excellent agreement between acquired and planned dose distributions for all three target motion patterns. This study performed end‐to‐end testing and verified the treatment accuracy of tumor dynamic tracking.