bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐G‐BRA‐06: Quantification of Tracking Performance of a Multi‐Layer Electronic Portal Imaging Device
Authors: Hu Y , Rottmann J , Myronakis M , Berbeco R 
Published: July 2016

Purpose:The purpose of this study was to quantify the improvement in tumor tracking, with and without fiducial markers, afforded by employing a multi‐layer (MLI) electronic portal imaging device (EPID) over the current state‐of‐the‐art, single‐layer, digital megavolt imager (DMI) architecture.Methods:An ideal observer signal‐to‐noise ratio (d’) approach was used to quantify the ability of an MLI EPID and a current, state‐of‐the‐art DMI EPID to track lung tumors from the treatment beam's‐eye‐view. Using each detector modulation transfer function (MTF) and noise power spectrum (NPS) as inputs, a detection task was employed with object functions describing simple three‐dimensional Cartesian shapes (spheres and cylinders). Marker‐less tumor tracking algorithms often use texture discrimination to differentiate benign and malignant tissue. The performance of such algorithms is simulated by employing a discrimination task for the ideal observer, which measures the ability of a system to differentiate two image quantities. These were defined as the measured textures for benign and malignant lung tissue.Results:The NNPS of the MLI ∼25% of that of the DMI at the expense of decreased MTF at intermediate frequencies (0.25≤<f≤<0.5 cycles/mm). Lung tissue textures were found to follow a power‐law trend in the frequency domain. It was found that for both fiducial marker tracking and lung tissue texture differentiation, the signal power of each task is retained at low frequencies. Thus, little difference may be observed in signal power when DMI and MLI are compared. In all cases, improvements in tracking were greater than a factor of 2.Conclusion:MLI performance in tumor tracking is greatly improved by the additional imager layers. This implies that further improvements in tracking may be gained through increasing the thickness of each MLI layer. For tracking, the MLI performance is limited by noise response. Losses in MTF result in negligible differences in d’.The project was partially supported by a grant from Varian Medical Systems, Inc. and grant No. R01CA188446‐01 from the National Cancer Institute.
SU‐G‐BRA‐10: Marker Free Lung Tumor Motion Tracking by An Active Contour Model On Cone Beam CT Projections for Stereotactic Body Radiation Therapy of Lung Cancer
Authors: Chao M , Wei J , Yuan Y , Lo Y 
Published: July 2016

Purpose:To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an active contour model with interpolated respiration learned from diaphragm motion.Methods:Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered with the CBCT projections on the frame‐by‐frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An active contour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy.Results:The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain.Conclusion:The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.
SU‐G‐BRA‐11: Tumor Tracking in An Iterative Volume of Interest Based 4D CBCT Reconstruction
Authors: Martin R , Ahmad M , Pan T 
Published: July 2016

Purpose:4D CBCT can allow evaluation of tumor motion immediately prior to radiation therapy, but suffers from heavy artifacts that limit its ability to track tumors. Various iterative and compressed sensing reconstructions have been proposed to reduce these artifacts, but are costly time‐wise and can degrade the image quality of bony anatomy for alignment with regularization. We have previously proposed an iterative volume of interest (I4D VOI) method which minimizes reconstruction time and maintains image quality of bony anatomy by focusing a 4D reconstruction within a VOI. The purpose of this study is to test the tumor tracking accuracy of this method compared to existing methods.Methods:Long scan (8–10 mins) CBCT data with corresponding RPM data was collected for 12 lung cancer patients. The full data set was sorted into 8 phases and reconstructed using FDK cone beam reconstruction to serve as a gold standard. The data was reduced in way that maintains a normal breathing pattern and used to reconstruct 4D images using FDK, low and high regularization TV minimization (λ=2,10), and the proposed I4D VOI method with PTVs used for the VOI. Tumor trajectories were found using rigid registration within the VOI for each reconstruction and compared to the gold standard.Results:The root mean square error (RMSE) values were 2.70mm for FDK, 2.50mm for low regularization TV, 1.48mm for high regularization TV, and 2.34mm for I4D VOI. Streak artifacts in I4D VOI were reduced compared to FDK and images were less blurred than TV reconstructed images.Conclusion:I4D VOI performed at least as well as existing methods in tumor tracking, with the exception of high regularization TV minimization. These results along with the reconstruction time and outside VOI image quality advantages suggest I4D VOI to be an improvement over existing methods.Funding support provided by CPRIT grant RP110562‐P2‐01
SU‐G‐BRA‐16: Target Dose Comparison for Dynamic MLC Tracking and Mid‐ Ventilation Planning in Lung Radiotherapy Subject to Intrafractional Baseline Drifts
Authors: Menten MJ , Fast MF , Nill S , Oelfke U 
Published: July 2016

Purpose:Lung tumor motion during radiotherapy can be accounted for by expanded treatment margins, for example using a mid‐ventilation planning approach, or by localizing the tumor in real‐time and adapting the treatment beam with multileaf collimator (MLC) tracking. This study evaluates the effect of intrafractional changes in the average tumor position (baseline drifts) on these two treatment techniques.Methods:Lung stereotactic treatment plans (9‐beam IMRT, 54Gy/3 fractions, mean treatment time: 9.63min) were generated for three patients: either for delivery with MLC tracking (isotropic GTV‐to‐PTV margin: 2.6mm) or planned with a mid‐ventilation approach and delivered without online motion compensation (GTV‐to‐PTV margin: 4.4‐6.3mm). Delivery to a breathing patient was simulated using DynaTrack, our in‐house tracking and delivery software. Baseline drifts in cranial and posterior direction were simulated at a rate of 0.5, 1.0 or 1.5mm/min. For dose reconstruction, the corresponding 4DCT phase was selected for each time point of the delivery. Baseline drifts were accounted for by rigidly shifting the CT to ensure correct relative beam‐to‐target positioning. Afterwards, the doses delivered to each 4DCT phase were accumulated deformably on the mid‐ventilation phase using research RayStation v4.6 and dose coverage of the GTV was evaluated.Results:When using the mid‐ventilation planning approach, dose coverage of the tumor deteriorated substantially in the presence of baseline drifts. The reduction in D98% coverage of the GTV in a single fraction ranged from 0.4‐1.2, 0.6‐3.3 and 4.5‐6.2Gy, respectively, for the different drift rates. With MLC tracking the GTV D98% coverage remained unchanged (+/− 0.1Gy) regardless of drift.Conclusion:Intrafractional baseline drifts reduce the tumor dose in treatments based on mid‐ventilation planning. In rare, large target baseline drifts tumor dose coverage may drop below the prescription, potentially affecting clinical outcome in hypofractionated treatment protocols. Dynamic MLC tracking preserves tumor dose coverage even in the presence of extreme baseline drifts.We acknowledge financial and technical support of the MLC tracking research from Elekta AB. Research at ICR is supported by CRUK under Programme C33589/A19727 and NHS funding to the NIHR Biomedical Research Centre at RMH and ICR. MFF is supported by CRUK under Programme C33589/A19908.
SU‐G‐IeP1‐02: Automated SNR Analysis of MR Images Using Model‐Based Noise Determination
Authors: Krugh K 
Published: July 2016

Purpose:To develop a robust automated method of signal‐to‐noise (SNR) analysis from MR images using a single image acquisition approach and model‐based noise determination.Methods:Three consecutive MRI phantom scans were performed according to the SNR test procedures in the 2015 ACR MRI Quality Control Manual. This was repeated for several different RF coils and on MRI scanners from two different vendors. The three images from each RF coil were analyzed by the single‐image (SNR‐ACR1) and two‐image (SNR‐ACR2) SNR analysis methods also described in the ACR QC Manual. In addition the images were analyzed by the automated method (SNR‐AUTO). The SNR‐AUTO method utilizes an ImageJ macro file that was developed to 1) segment the phantom from the background region by means of a simple histogram‐based thresholding algorithm, 2) measure the signal from a ROI encompassing 80% of the phantom area, and 3) determine noise by fitting the histogram of the background region (devoid of the phase encode direction) to a noise distribution model established in the literature.Results:The accuracy of the SNR‐AUTO analysis method is demonstrated by it yielding SNR results that on average were −0.8% ± 6.7% of the SNR‐ACR1 method and 7.5% ± 8.6% of the SNR‐ACR2 method. The SNR‐AUTO method demonstrated a higher level of reproducibility (average COV = 0.32%) than that of the other two methods (average COV = 1.01% and 1.69% for SNR‐ACR1 and SNRACR2 respectively) both of which require manual placement of ROIs. An additional finding is that the model‐based noise determination is relatively insensitive to the presence of minor artifacts in the background region.Conclusion:The SNR‐AUTO method proved to be an accurate, highly reproducible, time‐efficient method for analysis of SNR in MR images and is insensitive to minor artifacts in the noise‐measuring region.
SU‐G‐IeP1‐04: Comparison of Cerebral Blood Volume Estimated by DSC‐ and DCEMRI
Authors: Aryal M , Cao Y 
Published: July 2016

Purpose:The cerebral blood volume (CBV) is commonly estimated from T2*/T2‐weighted dynamic susceptibility contrast (DSC) MRI acquired by an EPI sequence. There are several challenges with DSC imaging, including geometric distortion, limited brain spatial coverage, and unreliable arterial input function (AIF) due to the partial volume effect. However, CBV can be estimated from T1‐weighted dynamic contrast enhanced (DCE) MRI. This study aimed to examine whether CBV estimated from DCE‐MRI is comparable to one from DSC‐MRI. Methods and Materials: Of 16 patients with brain metastases, both DCE and DSC series were acquired on a 3T scanner. 3D T1‐weighted DCE images were acquired using a gradient‐echo (GRE) sequence, while 2D multi‐slice DSC (14–19 slices) were obtained using a GRE EPI sequence. CBV maps were generated from DCE images by the modified Toft model and from DSC images by a pharmacokinetic model with leakage correction. After image registration, CBV values estimated by the two methods were compared in two volumes of interest (VOIs) of normal appearing gray matter and white matter (NAGMWM) and in metastatic lesions at both voxel‐level and the VOI‐level.Results:In the two normal tissue VOIs, means (±std) of CBV were 2.04(±0.45)% and 1.86(±0.45)% from DCE imaging and 1.95(±0.46)% and 1.82(±0.44)% from DSC imaging, which were not significantly different in either VOIs. The voxel‐by‐voxel correlations within the two normal tissue VOIs led to averaged R=0.53 and 0.59 across 16 patients, suggesting high correlation between the two methods.Conclusion:The CBV estimated from DCE imaging was highly comparable to one from DSC imaging. The CBV estimated from DCE imaging is less affected by the susceptibility effect, and can cover the whole brain, which could be an alternative approach for the CBV estimation.This research work was supported by NIH grant: U01 CA183848
SU‐G‐IeP1‐06: Estimating Relative Tissue Density From Quantitative MR Images: A Novel Perspective for MRI‐Only Heterogeneity Corrected Dose Calculation
Authors: Soliman A , Hashemi M , Safigholi H , Tchistiakova E , Song W 
Published: July 2016

Purpose:To explore the feasibility of extracting the relative density from quantitative MRI measurements as well as estimate a correlation between the extracted measures and CT Hounsfield units.Methods:MRI has the ability to separate water and fat signals, producing two separate images for each component. By performing appropriate corrections on the separated images, quantitative measurement of water and fat mass density can be estimated. This work aims to test this hypothesis on 1.5T.Peanut oil was used as fat‐representative, while agar as water‐representative. Gadolinium Chloride III and Sodium Chloride were added to the agar solution to adjust the relaxation times and the medium conductivity, respectively. Peanut oil was added to the agar solution with different percentages: 0%, 3%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%. The phantom was scanned on 1.5T GE Optima 450W with the body coil using a multigradient echo sequences. Water/fat separation were performed while correcting for main field (B0) inhomogeneity and T2* relaxation time. B1+ inhomogeneities were ignored. The phantom was subsequently scanned on a Philips Brilliance CT Big Bore. MR‐corrected fat signal from all vials were normalized to 100% fat signal. CT Hounsfield values were then compared to those obtained from the normalized MR‐corrected fat values as well as to the phantom for validation.Results:Good agreement were found between CT HU and the MR‐extracted fat values (R2 = 0.98). CT HU also showed excellent agreement with the prepared fat fractions (R2=0.99). Vials with 70%, 80%, and 90% fat percentages showed inhomogeneous distributions, however their results were included for completion.Conclusion:Quantitative MRI water/fat imaging can be potentially used to extract the relative tissue density. Further in‐vivo validation are required.
SU‐G‐IeP1‐09: MRI Evaluation of a Direction‐Modulated Brachytherapy (DMBT) Tandem Applicator for Cervical Cancer On 3T
Authors: Soliman A , Han D , Elzibak A , Safigholi H , Mashouf S , Owrangi A , Ravi A , Song W 
Published: July 2016

Purpose:To assess image quality and artifact extent of a novel direction modulated brachytherapy (DMBT) tandem applicator on a 3T MRI using various clinical imaging sequences.Methods:The tandem applicator is composed of a tungsten alloy with 6 peripheral grooves covered with a PEEK tip. An MR‐compatible phantom with similar dimensions to the female pelvis was manufactured. To visually assess the spatial shift of the applicator's tip, a mountable radial‐fiducial with 4 plastic rods, each of 3mm diameter, was designed to tightly fit on the applicator. The rods are separated by 16 mm and mounted at 90‐degree relative to one another. The pelvis phantom was filled with a solution of MnCl2 to mimic T2 relaxation time of the cervix (60‐80 ms at 3T).Imaging was performed on a 3T Philips Achieva using a 16‐channel Torso coil array. Four MR sequences were tested: T2‐weighted fast spin‐echo (T2w‐FSE), proton density weighted FSE (PDw‐FSE), T1‐weighted FSE (T1w‐FSE) and T1 weighted spoiled gradient echo (T1w‐GE). The spatial resolution was kept the same between all sequences: 0.6 × 0.6 × 3 mm3 with no slice gaps. Para‐sagittal images were acquired with the applicator fixed at a 30‐degree angle anterior to the B0‐ field to mimic clinical settings.Results:Minimal artifacts were observed on T2w‐FSE, PDw‐FSE and T1‐FSE, while significant artifacts were seen on T1w‐GE images. Artifacts induced in all 3 FSE sequences did not hinder accurate localisation of the tip and the applicator boundaries. The drift of the applicator's centreline from the radial fiducials was measured and found to be < 1 mm for the 3 FSE sequences.Conclusion:The tungsten–based DMBT applicator can be potentially used on 3T with various clinical sequences without inducing significant artifacts. Further validation on patients as well as the evaluation of relative SNR among the different sequences is required.
SU‐G‐JeP1‐03: Automatic Motion Tracking Reset in Ultrasound Liver Image Sequences
Authors: Xu Kele , W Ruixing , Zhu Li , Liu Chang , Zhao Yi 
Published: July 2016

Purpose:We explore an automatic anatomical landmarks tracking reset method in the ultrasound liver sequences, with the goal to improve the robustness and accuracy of the tracking.Methods:The proposed tracking failure re‐initialization method works as follows: before anatomic landmarks tracking is carried out, the image similarity coefficient is calculated (In our method, the complex wavelet structural similarity is used), between the region of interest (ROI) selected in current frame and the ROI in the first frame. If this similarity coefficient exceeds a set threshold, the positions of anatomical landmarks are reset to those which were input for the first frame. This provides a method to prevent accumulation of errors over long sequences, which can lead to erroneous tracking, and amounts to a sort of “automatic reset” of the tracking starting points based on initial a priori information.Results:The experiments are conducted to track the landmarks in the 5 volunteer B‐mode ultrasound liver sequences. The results were evaluated by comparison with manual annotations of liver feature (vessels) throughout each image sequence which were provided after automated tracking was complete. Tracking accuracy was evaluated using the Euclidean distance between tracked points and manually annotated points which was summarized by the mean. The mean error for all ROIs in different sequences are about 1–1.5 mm with the proposed automatic reset method, while the error is about 2 mm without the automatic reset method.Conclusion:Due to the periodic motion of the anatomical landmarks, the proposed image similarity‐based automatic re‐initialization method can improve the accuracy and robustness of the motion tracking in the ultrasound liver sequences. It may also be applied to other organs’ tracking problem using ultrasound imaging.
SU‐G‐JeP1‐05: Clinical Impact of MLC Tracking for Lung SABR
Authors: Caillet V , Colvill E , Szymura K , Stevens M , Booth J , Keall P 
Published: July 2016

Purpose:The objective of this study was to investigate the dosimetric benefits of multi‐leaf collimator (MLC) tracking for lung SABR treatments in end‐to‐end clinically realistic planning and delivery scenarios.Methods:The clinical benefits of MLC tracking were assessed using previously delivered treatment plans and physical experiments. The 10 most recent single lesion lung SABR patients were re‐planned following a 4D‐GTV‐based real‐time adaptive protocol (PTV defined as the end‐of‐exhalation GTV plus 5.0 mm margins). The plans were delivered on a Trilogy Varian linac. Electromagnetic transponders (Calypso, Varian Medical Systems, USA) were embedded into a programmable moving phantom (HexaMotion platform) tracked with the Varian Calypso system. For each physical experiment, the MLC positions were collected and used as input for dose reconstruction. For both planned and physical experiments, the OAR dose metrics from the conventional and real‐time adaptive SABR plans (Mean Lung Dose (MLD), V20 for lung, and near‐maximum dose (D2%) for spine and heart) were statistically compared. The Wilcoxon test was used to compare plan and physical experiment dose metrics.Results:While maintaining target coverage, percentage reductions in dose metrics to the OARs were observed for both planned and physical experiments. Comparing the two plans showed MLD percentage reduction (MLDr) of 25.4% (absolute differences of 1.41 Gy) and 28.9% (1.29%) for the V20r. D2% percentage reduction for spine and heart were respectively 27.9% (0.3 Gy) and 20.2% (0.3 Gy). For the physical experiments, MLDr was 23.9% (1.3 Gy), and V20r 37.4% (1.6%). D2% reduction for spine and heart were respectively 27.3% (0.3 Gy) and 19.6% (0.3 Gy). For both plans and physical experiments, significant OAR dose differences (p<0.05) were found between the conventional SABR and real‐time adaptive plans.Conclusion:Application of MLC tracking for lung SABR patients has the potential to reduce the dose to OARs during radiation therapy.
SU‐G‐TeP2‐12: IROCHouston and MDAPL SRS Anthropomorphic Phantom Results
Authors: Molineu A , Kry S , Alvarez P , Hernandez N , Nguyen T , Followill D 
Published: July 2016

Purpose:To report the results of SRS phantom irradiationsMethods:Anthropomorphic SRS head phantoms were sent to institutions participating in NCI sponsored SRS clinical trials and institutions interested in verifying SRS treatment delivery. The phantom shell was purchased from Phantom Laboratory and altered to house dosimetry and imaging inserts. The imaging insert has 1.9 cm diameter spherical target. The dosimetry insert holds two TLD capsules and radiochromic film in the coronal and sagittal planes through the center of the target. Institutions were asked to image, plan and treat the phantom as they would an SRS patient. GammaKnife, CyberKnife and c‐arm accelerator institutions were asked to cover the target with 15 Gy, 20 Gy and 25 Gy, respectively. Following these guidelines and typical planning protocols for these three types of machines gives roughly 30 Gy to the center of the target for all units. Submission of the DICOM digital data set was required for analysis. Criteria of 5% for TLD results and 85% of pixels passing 5%/3mm gamma analysis were applied beginning in 2013.Results:The phantom was analyzed 269 times between the beginning of 2013 to present. The pass rate is 81%. Nineteen of the irradiation results failed only the TLD criteria, 19 failed only the film criteria and 12 failed both. Irradiations included 32 CyberKnife 23 GammaKnife, 3 TomoTherapy and 211 c‐arm units. Planning systems included Eclipse, Ergo, GammaPlan, Hi‐Art, iPlan, Monaco, MultiPlan, Pinnacle, RayStation, XiO and XKnife. Irradiations that were not accompanied with DICOM data were not included in this analysis.Conclusion:The phantom is a valuable end‐to‐end test used to independently verify the accuracy of SRS treatment delivery.This investigation was supported by IROC grant CA180803 awarded by the NCI.