bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐117: Verification Method for the Detection Accuracy of Automatic Winston Lutz Test
Authors: Tang A , Chan K , Fee F , Chau R 
Published: July 2014

Purpose:Winston Lutz test (WLT) has been a standard QA procedure performed prior to SRS treatment, to verify the mechanical iso‐center setup accuracy upon different Gantry/Couch movements. Several detection algorithms exist,for analyzing the ball‐radiation field alignment automatically. However, the accuracy of these algorithms have not been fully addressed. Here, we reveal the possible errors arise from each step in WLT, and verify the software detection accuracy with the Rectilinear Phantom Pointer (RLPP), a tool commonly used for aligning treatment plan coordinate with mechanical iso‐center.Methods:WLT was performed with the radio‐opaque ball mounted on a MIS and irradiated onto EDR2 films. The films were scanned and processed with an in‐house Matlab program for automatic iso‐center detection. Tests were also performed to identify the errors arise from setup, film development and scanning process. The radioopaque ball was then mounted onto the RLPP, and offset laterally and longitudinally in 7 known positions (0, ±0.2, ±0.5, ±0.8 mm) manually for irradiations. The gantry and couch was set to zero degree for all irradiation. The same scanned images were processed repeatly to check the repeatability of the software.Results:Miminal discrepancies (mean=0.05mm) were detected with 2 films overlapped and irradiated but developed seperately. This reveals the error arise from film processer and scanner alone. Maximum setup errors were found to be around 0.2mm, by analyzing data collected from 10 irradiations over 2 months. For the known shift introduced using the RLPP, the results agree with the manual offset, and fit linearly (R2>0.99) when plotted relative to the first ball with zero shift.Conclusion:We systematically reveal the possible errors arise from each step in WLT, and introduce a simple method to verify the detection accuracy of our in‐house software using a clinically available tool.
SU‐E‐J‐119: What Effect Have the Volume Defined in the Alignment Clipbox for Cervical Cancer Using Automatic Registration Methods for Cone‐ Beam CT Verification?
Authors: Wang W , Yang H , Wang Y , Jia H , Xie Y 
Published: July 2014

Purpose:To investigate the impact of different clipbox volumes with automated registration techniques using commercially available software with on board volumetric imaging(OBI) for treatment verification in cervical cancer patients.Methods:Fifty cervical cancer patients received daily CBCT scans(on‐board imaging v1.5 system, Varian Medical Systems) during the first treatment week and weekly thereafter were included this analysis. A total of 450 CBCT scans were registered to the planning CTscan using pelvic clipbox(clipbox‐Pelvic) and around PTV clip box(clipbox‐ PTV). The translations(anterior‐posterior, left‐right, superior‐inferior) and the rotations(yaw, pitch and roll) errors for each matches were recorded. The setup errors and the systematic and random errors for both of the clip‐boxes were calculated. Paired Samples t test was used to analysis the differences between clipbox‐Pelvic and clipbox‐PTV.Results:. The SD of systematic error(σ) was 1.0mm, 2.0mm,3.2mm and 1.9mm,2.3mm, 3.0mm in the AP, LR and SI directions for clipbox‐Pelvic and clipbox‐PTV, respectively. The average random error(Σ)was 1.7mm, 2.0mm,4.2mm and 1.7mm,3.4mm, 4.4mm in the AP, LR and SI directions for clipbox‐Pelvic and clipbox‐PTV, respectively. But, only the SI direction was acquired significantly differences between two image registration volumes(p=0.002,p=0.01 for mean and SD). For rotations, the yaw mean/SD and the pitch SD were acquired significantly differences between clipbox‐Pelvic and clipbox‐PTV.Conclusion:The defined volume for Image registration is important for cervical cancer when 3D/3D match was used. The alignment clipbox can effect the setup errors obtained. Further analysis is need to determine the optimal defined volume to use the image registration in cervical cancer. Conflict of interest: none.
SU‐E‐J‐121: Measuring Prompt Gamma Emission Profiles with a Multi‐Stage Compton Camera During Proton Beam Irradiaition: Initial Studies
Authors: Polf J , Brown S , Mann J , Mackin D , Zheng Y , McCleskey M , Beddar S , He Z 
Published: July 2014

Purpose:Recent studies have suggested that the characteristics of prompt gammas (PG) emitted during proton beam irradiation are advantageous for determining beam range during treatment delivery. The purpose of this work was to determine the feasibility of determining the proton beam range from PG data measured with a prototype Compton camera (CC) during proton beam irradiation.Methods:Using a prototype multi‐stage CC the PG emission from a water phantom was measured during irradiation with clinical proton therapy beams. The measured PG emission data was used to reconstruct an image of the PG emission using a backprojection reconstruction algorithm. One dimensional (1D) profiles extracted from the PG images were compared to: 1) PG emission data measured at fixed depths using collimated high purity Germanium and Lanthanum Bromide detectors, and 2) the measured depth dose profiles of the proton beams.Results:Comparisons showed that the PG emission profiles reconstructed from CC measurements agreed very well with the measurements of PG emission as a function of depth made with the collimated detectors. The distal falloff of the measured PG profile was between 1 mm to 4 mm proximal to the distal edge of the Bragg peak for proton beam ranges from 4 cm to 16 cm in water. Doses of at least 5 Gy were needed for the CC to measure sufficient data to image the PG profile and localize the distal PG falloff.Conclusion:Initial tests of a prototype CC for imaging PG emission during proton beam irradiation indicated that measurement and reconstruction of the PG profile was possible. However, due to limitations of the operational parameters (energy range and count rate) of the current CC prototype, doses of greater than a typical treatment dose (∼2 Gy) were needed to measure adequate PG signal to reconstruct viable images.Funding support for this project provided by a grant from DoD.
SU‐E‐J‐123: Targeting Accuracy of Image‐Guided Radiosurgery for Intracranial Lesions
Authors: Huang Y , Wen N , Zhao B , Kim J , Gordon J , Chetty I 
Published: July 2014

Purpose:To evaluate the setup accuracies of image‐guided intracranial radiosurgery across several different linear accelerator platforms.Methods:A CT scan with a slice thickness of 1.0 mm was acquired of a Rando head phantom (The Phantom Laboratory) in a U‐frame mask (BrainLAB AG). The phantom had three embedded BBs, simulating a central, left, and anterior lesion. The phantom was setup with each BB placed at the radiation isocenter under image guidance. Four different setup procedures were investigated: (1) NTX_ExacTrac: 6 degree‐of‐freedom (6D) correction on a Novalis Tx (BrainLAB AG) with ExacTrac localization (BrainLAB AG); (2) NTX_CBCT: 4D correction on the Novalis Tx with cone‐beam computed tomography (CBCT); (3) TrueBeam_CBCT: 4D correction on a TrueBeam (Varian) with CBCT; (4) Edge_CBCT: 6D correction on an Edge (Varian) with CBCT. The experiment was repeated 5 times with different initial setup error at each BB location on each platform, and the mean (μ) and one standard deviation (σ) of the residual error was compared. The congruence between radiation and imaging isocenters on each platform was evaluated by acquiring Winston Lutz (WL) images of a WL jig followed by imaging using ExacTrac or CBCT. The difference in coordinates of the jig relative to radiation and imaging isocenters was then recorded.Results:Averaged over all three BB locations, the residual vector setup errors (μ±σ) of the phantom in mm were 0.6±0.2, 1.0±0.5, 0.2±0.1, and 0.3±0.1 on NTX_ExacTrac, NTX_CBCT, TrueBeam_CBCT, and Edge_CBCT, with their ranges in mm being 0.4∼1.1, 0.4∼1.9, 0.1∼0.5, and 0.2∼0.6, respectively. And imaging isocenter was found stable relative to radiation isocenter, with the congruence to radiation isocenter in mm being 0.6±0.1, 0.7±0.1, 0.3±0.1, 0.2±0.1, respectively, on the four systems in the same order.Conclusion:Millimeter accuracy can be achieved with image‐guided radiosurgery for intracranial lesions based on this set of experiments.
SU‐E‐J‐124: FDG PET Metrics Analysis in the Context of An Adaptive PET Protocol for Node Positive Gynecologic Cancer Patients
Authors: Nawrocki J , Chino J , Light K , Vergalasova I , Craciunescu O 
Published: July 2014

Purpose:To compare PET extracted metrics and investigate the role of a gradient‐based PET segmentation tool, PET Edge (MIM Software Inc., Cleveland, OH), in the context of an adaptive PET protocol for node positive gynecologic cancer patients.Methods:An IRB approved protocol enrolled women with gynecological, PET visible malignancies. A PET‐CT was obtained for treatment planning prescribed to 45–50.4Gy with a 55– 70Gy boost to the PET positive nodes. An intra‐treatment PET‐CT was obtained between 30–36Gy, and all volumes re‐contoured. Standard uptake values (SUVmax, SUVmean, SUVmedian) and GTV volumes were extracted from the clinician contoured GTVs on the pre‐ and intra‐treament PET‐CT for primaries and nodes and compared with a two tailed Wilcoxon signed‐rank test. The differences between primary and node GTV volumes contoured in the treatment planning system and those volumes generated using PET Edge were also investigated. Bland‐Altman plots were used to describe significant differences between the two contouring methods.Results:Thirteen women were enrolled in this study. The median baseline/intra‐treatment primary (SUVmax, mean, median) were (30.5, 9.09, 7.83)/(16.6, 4.35, 3.74), and nodes were (20.1, 4.64, 3.93)/(6.78, 3.13, 3.26). The p values were all < 0.001. The clinical contours were all larger than the PET Edge generated ones, with mean difference of +20.6 ml for primary, and +23.5 ml for nodes. The Bland‐Altman revealed changes between clinician/PET Edge contours to be mostly within the margins of the coefficient of variability. However, there was a proportional trend, i.e. the larger the GTV, the larger the clinical contours as compared to PET Edge contours.Conclusion:Primary and node SUV values taken from the intratreament PET‐CT can be used to assess the disease response and to design an adaptive plan. The PET Edge tool can streamline the contouring process and lead to smaller, less user‐dependent contours.
SU‐E‐J‐126: Respiratory Gating Quality Assurance: A Simple Method to Achieve Millisecond Temporal Resolution
Authors: McCabe B , Wiersma R 
Published: July 2014

Purpose:Low temporal latency between a gating on/off signal and a linac beam on/off during respiratory gating is critical for patient safety. Although, a measurement of temporal lag is recommended by AAPM Task Group 142 for commissioning and annual quality assurance, there currently exists no published method. Here we describe a simple, inexpensive, and reliable method to precisely measure gating lag at millisecond resolutions.Methods:A Varian Real‐time Position Management™ (RPM) gating simulator with rotating disk was modified with a resistive flex sensor (Spectra Symbol) attached to the gating box platform. A photon diode was placed at machine isocenter. Output signals of the flex sensor and diode were monitored with a multichannel oscilloscope (Tektronix™ DPO3014). Qualitative inspection of the gating window/beam on synchronicity were made by setting the linac to beam on/off at end‐expiration, and the oscilloscope's temporal window to 100 ms to visually examine if the on/off timing was within the recommended 100‐ms tolerance. Quantitative measurements were made by saving the signal traces and analyzing in MatLab™. The on and off of the beam signal were located and compared to the expected gating window (e.g. 40% to 60%). Four gating cycles were measured and compared.Results:On a Varian TrueBeam™ STx linac with RPM gating software, the average difference in synchronicity at beam on and off for four cycles was 14 ms (3 to 30 ms) and 11 ms (2 to 32 ms), respectively. For a Varian Clinac™ 21EX the average difference at beam on and off was 127 ms (122 to 133 ms) and 46 ms (42 to 49 ms), respectively. The uncertainty in the synchrony difference was estimated at ±6 ms.Conclusion:This new gating QA method is easy to implement and allows for fast qualitative inspection and quantitative measurements for commissioning and TG‐142 annual QA measurements.
SU‐E‐J‐131: Automatic Detection of Gold Fiducial Markers On MR Images Using the RASOR Technique
Authors: Seevinck P , van den Berg C A T , Moerland M A , Philippens M , Lagendijk J 
Published: July 2014

Purpose:The detection of gold fiducial markers on MR images is important for CT‐MR registration and will be key to upcoming MRI‐only treatment planning. Visualization of gold fiducials with MRI is, however, challenging as seeds lead to small signal voids that are difficult to detect on regular MR scans. Here, we demonstrate that by using a balanced radial SSFP sequence in combination with an off‐resonance reconstruction, gold fiducials can be given a positive contrast facilitating automatic detection.Methods:Three gold fiducials (HA2 Medizintechnik, Germany, 1x 5 mm²) were placed in three orthogonal orientations in an agarose gel phantom. We used a 3D stack of stars transient balanced gradient echo (tbGE) sequence with SPAIR fat suppression (TR/TE = 3.3/1.63ms, 1×1×2 mm³ acquired voxels, BW=1085Hz/vox). To create positive contrast at the seed locations the RASOR technique employs an additional off‐resonance reconstruction at 3000 Hz. Background‐suppression was obtained by subtracting the on‐resonance image twice from the off‐resonance image.Results:The short echo time of the sequence combined with a “balanced” gradient scheme resulted in well localized and sharp signal voids at fiducial locations. By employing RASOR reconstruction the gold fiducials were depicted hyperintense and allowed determination of the locatation and orientation of the fiducials. The radial readout ensures accurate localization as any susceptibility induced geometrical shift for a radial readout line, is balanced by an opposite radial readout. Thus the centre‐of‐gravity of the hyperintensity reflects the true position of the fiducials.Conclusion:A radial balanced sequence in combination with short TR and TR and high spatial resolution, results in accurate depiction of gold fiducials while being standardly available on MR systems. The RASOR reconstruction results in a positive contrast facilitating automatic detection. This enables automatic registration between CT and MRI based on fiducial markers, and in the may warrant an MRI‐only planning approach.
SU‐E‐J‐134: An Augmented‐Reality Optical Imaging System for Accurate Breast Positioning During Radiotherapy
Authors: Nazareth D , Malhotra H , French S , Hoffmann K , Merrow C 
Published: July 2014

Purpose:Breast radiotherapy, particularly electronic compensation, may involve large dose gradients and difficult patient positioning problems. We have developed a simple self‐calibrating augmented‐reality system, which assists in accurately and reproducibly positioning the patient, by displaying her live image from a single camera superimposed on the correct perspective projection of her 3D CT data. Our method requires only a standard digital camera capable of live‐view mode, installed in the treatment suite at an approximately‐known orientation and position (rotation R; translation T).Methods:A 10‐sphere calibration jig was constructed and CT imaged to provide a 3D model. The (R,T) relating the camera to the CT coordinate system were determined by acquiring a photograph of the jig and optimizing an objective function, which compares the true image points to points calculated with a given candidate R and T geometry. Using this geometric information, 3D CT patient data, viewed from the camera's perspective, is plotted using a Matlab routine. This image data is superimposed onto the real‐time patient image, acquired by the camera, and displayed using standard live‐view software. This enables the therapists to view both the patient's current and desired positions, and guide the patient into assuming the correct position. The method was evaluated using an in‐house developed bolus‐like breast phantom, mounted on a supporting platform, which could be tilted at various angles to simulate treatment‐like geometries.Results:Our system allowed breast phantom alignment, with an accuracy of about 0.5 cm and 1 ± 0.5 degree. Better resolution could be possible using a camera with higher‐zoom capabilities.Conclusion:We have developed an augmented‐reality system, which combines a perspective projection of a CT image with a patient's real‐time optical image. This system has the potential to improve patient setup accuracy during breast radiotherapy, and could possibly be used for other disease sites as well.
SU‐E‐J‐139: Fuzzy Clustering Segmentation of Glioblastoma in T1‐MRI Imaging for Clinical Trials
Authors: Cordova J S , Schreibmann Eduard , Hadjipanayis Constantinos G. , Holder Chad A. , Bansal Vivek , Julio Sepulvedad , Hasan Danish , Guo Ying , Fox Tim H. , Crocker Ian R. , Shu Hui‐Kuo G. , Shim Hyunsuk 
Published: July 2014

Purpose:Generating brain tumor volume measurements in a reproducible and efficient manner is a difficult, yet necessary, component of response assessment. The purpose of this study was to adapt and validate a multilevel Fuzzy C‐means clustering algorithms for ROI tumor segmentation to allow consistent volumetric comparisons at multiple sites.Methods:Preoperative contrast‐enhanced T1W images from 37 glioblastoma cases were segmented using Fuzzy C‐means clustering‐based methods and compared to manually contoured volumes created by specialists. The same was done post‐operatively, using subtracted images to eliminate intrinsically T1‐hyperintense material (blood). Volume computations based on the MacDonald criteria were also used for comparison. Agreement and inter‐rater variability between volumes produced with each method was assessed by determining the concordance correlation coefficient (CCC).Results:The MacDonald criteria method had poor agreement (CCC=0.350–0.972) with manual contouring pre‐ and postoperatively, while the proposed semi‐automated methods exhibited very high agreement (CCC=0.839–0.995) with manual contouring before and after resection. Fuzzy C‐means clustering with three classes was the most robust semi‐automated method, showing better inter‐rater agreement than the MacDonald criteria method for both pre‐ (CCC of 0.990 and 0.975, respectively) and post‐operative cases (CCC of 0.983 and 0.576, respectively). Post‐operative inter‐rater agreement was significantly different between these methods (p < 0.001).Conclusion:The proposed semi‐automated segmentation methods allow tumor volume measurements of MR images in a reliable and reproducible fashion necessary for measuring treatment response in glioblastoma patients in multicenter clinical trials.
SU‐E‐J‐148: Evaluating Tumor Response with a Commercially Available Deformable Registration System
Authors: Bowling J , Ramsey C 
Published: July 2014

Purpose:The purpose of this study is to present a method for evaluating the response to treatment using a commercially available deformable image registration software package (Velocity Medical Systems) and repeat PET/CT imaging. This technique can be used to identify volumes that are risk for tumor recurrence.Methods:Response to treatment was evaluated using PET/CT images acquired prior‐to and post‐treatment for radiation therapy patients treated with concurrent chemotherapy. Velocity (Version 3.0.1) was used to deform the initial PET/CT to the post treatment PET/CT. The post‐treatment PET images were then subtracted from the pre‐treatment PET images. The resulting re‐sampled image is a three‐dimensional SUV difference map that shows pixels with increasing SUV values. SUV values increases greater than 2.5 in the post treatment images were identified for additional follow‐up.Results:A total of 5 Lung patients were analyzed as part of this study. One lung patient in the cohort had an SUV increase of +3.28 that was identified using the SUV difference map. This volume of increased uptake was located outside the treatment field and adjacent to the 35 Gy isodose line. The remaining four patients all had SUV decreases inside the planning target volume, and no unexpected areas of increase outside the irradiated volumes. All five patients were analyzed using standard tools inside the Velocity application.Conclusion:The response to treatment can easily be measured using serial PET/CT images and a commercially available deformable image registration. This provides both the radiation oncologists and medical oncologists with a quantitative assessment of their treatment to use in patient follow‐up.
SU‐E‐J‐154: Deformable Image Registration Based Delivered Dose Estimation for Head and Neck Radiotherapy
Authors: Kumarasiri A , Liu C , Chetvertkov M , Gordon J , Siddiqui F , Chetty I , Kim J 
Published: July 2014

Purpose:To estimate the accumulated dose to targets and organs at risk (OAR) for head and neck (H' N) radiotherapy using 3 deformable image registration (DIR) algorithms.Methods:Five H' N patients, who had daily CBCTs taken during the course of treatment, were retrospectively studied. All plans had 5 mm CTV‐to‐PTV expansions. To overcome the small field of view (FOV) limitations and HU uncertainties of CBCTs, CT images were deformably registered using a parameter‐optimized B‐spline DIR algorithm (Elastix, elastix.isi.uu.nl) and resampled onto each CBCT with a 4 cm uniform FOV expansion. The dose of the day was calculated on these resampled CT images. Calculated daily dose matrices were warped and accumulated to the planning CT using 3 DIR algorithms; SmartAdapt (Eclipse/Varian), Velocity (Velocity Medical Solutions), and Elastix. Dosimetric indices for targets and OARs were determined from the DVHs and compared with corresponding planned quantities.Results:The cumulative dose deviation was less than 2%, on average, for PTVs from the corresponding plan dose, for all algorithms/patients. However, the parotids show as much as a 37% deviation from the intended dose, possibly due to significant patient weight loss during the first 3 weeks of treatment (15.3 lbs in this case). The mean(±SD) cumulative dose deviations of the 5 patients estimated using the 3 algorithms (SmartAdapt, Velocity, and Elastix) were (0.8±0.9%, 0.5±0.9%, 0.6±1.3%) for PTVs, (1.6±1.9%, 1.4±2.0%, 1.7±1.9%) for GTVs, (10.4±12.1%, 10.7±10.6%, 6.5±10.1%) for parotid glands, and (4.5±4.6%, 3.4±5.7%, 3.9±5.7%) for mucosa, respectively. The differences among the three DIR algorithms in the estimated cumulative mean doses (1SD (in Gy)) were: 0.1 for PTVs, 0.1 for GTVs, 1.9 for parotid glands, and 0.4 for mucosa.Conclusion:Results of this study are suggestive that more frequent plan adaptation for organs, such as the parotid glands, might be beneficial during the course of H' N RT.This study was supported in part by a research grant from Varian Medical Systems, Palo Alto, CA