bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐C‐BRB‐05: Determining the Adequacy of Auto‐Contouring Via Probabilistic Assessment of Ensuing Treatment Plan Metrics in Comparison with Manual Contours
Authors: Nourzadeh H , Watkins W , Siebers J , Ahmad M 
Published: July 2016

Purpose:To determine if auto‐contour and manual‐contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT.Methods:Manual and auto‐contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto‐contouring was completed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7‐beam IMRT plans are created; PD with drawn ROIs, PAS with auto‐contoured ROIs, and PM with auto‐contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampled systematic errors for each simulation and a different sampled random error for each fraction were performed using our in‐house GPU‐accelerated robustness analyzer tool which reports the statistical probability of achieving dose‐volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto‐contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross‐evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose‐volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D‐PD).Results:We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV's D95 and Dmin objectives are small for AS‐PM, AS‐PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS‐PM, AS‐PD sustain variations up to %6 compared to other evaluated pairs.Conclusion:No significant probabilistic differences are observed in the metrics when auto‐contoured OARs are used. The prostate auto‐contour needs improvement to achieve clinically equivalent plans.
SU‐C‐BRA‐02: A Lung Tumor Autocontouring Algorithm Based On Particle Filter for Dynamic Magnetic Resonance
Authors: Bourque A , Bedwani S , Filion E , Carrier J 
Published: July 2016

Purpose:This study proposes a novel autocontouring algorithm for lung tumors based on particle filter. It is developed in the context of MR‐linac treatments and is validated on in‐vivo dynamic magnetic resonance images.Methods:A sequential Monte Carlo method called particle filter is combined with Otsu's thresholding technique to contour lung tumors on dynamic MR images. Four non‐small cell lung cancer (NSCLC) patients were imaged with a 1.5 T MR (MAGNETOM Aera, Siemens Healthcare, Erlangen, Germany) for one minute at a rate of 4 images per second. A pretreatment image‐processing step includes a manual contour of the tumor, the tumor's displacement, and its descriptive statistics. During treatment, the contours are automatically generated by thresholding the image in a window surrounding the center of mass of the particles. The Dice similarity coefficient (DSC), the precision, the recall, the Hausdorff distance (HD) and the difference in centroid positions (Δd) are calculated to compare with the expert's contours.Results:This autocontouring algorithm presents continuous adaptability and is independent of pre‐treatment training. The number of particles is proportional to the area of the tumor and increases the computational time at a rate of 2 ms for every 500 particles, whereas the contouring step adds a constant 14 ms. The contours’ comparison is obtained with a mean DSC of 0.89 to 0.91, mean precision of 0.88 to 0.92, mean recall of 0.88 to 0.95 and mean Δd of 0.6 to 2.3 mm.Conclusion:This work presents a new autocontouring algorithm for NSCLC patients on dynamic MR images. Combining the autocontours with a motion prediction algorithm presents a promising method for lung tumor online tracking treatments.
SU‐C‐202‐02: A Comprehensive Evaluation of Adaptive Daily Planning for Cervical Cancer HDR Brachytherapy
Authors: Meerschaert R , Nalichowski A , Burmeister J , Paul A , Miller A , Zhuang L 
Published: July 2016

Purpose:To evaluate adaptive daily planning for cervical cancer patients who underwent high‐dose‐rate intra‐cavitary brachytherapy (HDR‐ICBT).Methods:This study included 22 cervical cancer patients who underwent 5 fractions of HDR ICBT. Regions of interest (ROIs) including high‐risk clinical tumor volume (HR‐CTV) and organs‐at‐risk (OARs) were manually contoured on daily CT images. All patients were treated with adaptive daily plans, which involved ROI delineation and dose optimization at each treatment fraction. Single treatment plans were retrospectively generated by applying the first treatment fraction's dwell times adjusted for decay and dwell positions of the applicator to subsequent treatment fractions. Various existing similarity metrics were calculated for the ROIs to quantify interfractional organ variations. A novel similarity score (JRARM) was established, which combined both volumetric overlap metrics (DSC, JSC, and RVD) and distance metrics (ASD, MSD, and RMSD). Linear regression was performed to determine a relationship between inter‐fractional organ variations of various similarity metrics and D2cc variations from both plans. Wilcoxon Signed Rank Tests were used to assess adaptive daily plans and single plans by comparing EQD2 D2cc (α/β=3) for OARs.Results:For inter‐fractional organ variations, the sigmoid demonstrated the greatest variations based on the JRARM and DSC similarity metrics. Comparisons between paired ROIs showed differences in JRARM scores and DSCs at each treatment fraction. RVD, MSD, and RMSD were found to be significantly correlated to D2cc variations for bladder and sigmoid. The comparison between plans found that adaptive daily planning provided lower EQD2 D2cc of OARs than single planning, specifically for the sigmoid (p=0.015).Conclusion:Substantial inter‐fractional organ motion can occur during HDR‐BT, which may significantly affect D2cc of OARs. Adaptive daily planning provides improved dose sparing for OARs compared to single planning.
SU‐C‐202‐03: A Tool for Automatic Calculation of Delivered Dose Variation for Off‐Line Adaptive Therapy Using Cone Beam CT
Authors: Zhang B , Lee S , Chen S , Zhou J , Prado K , D'Souza W , Yi B 
Published: July 2016

Purpose:Monitoring the delivered dose is an important task for the adaptive radiotherapy (ART) and for determining time to re‐plan. A software tool which enables automatic delivered dose calculation using cone‐beam CT (CBCT) has been developed and tested.Methods:The tool consists of four components: a CBCT Colleting Module (CCM), a Plan Registration Moduel (PRM), a Dose Calculation Module (DCM), and an Evaluation and Action Module (EAM). The CCM is triggered periodically (e.g. every 1:00 AM) to search for newly acquired CBCTs of patients of interest and then export the DICOM files of the images and related registrations defined in ARIA followed by triggering the PRM. The PRM imports the DICOM images and registrations, links the CBCTs to the related treatment plan of the patient in the planning system (RayStation V4.5, RaySearch, Stockholm, Sweden). A pre‐determined CT‐to‐density table is automatically generated for dose calculation. Current version of the DCM uses a rigid registration which regards the treatment isocenter of the CBCT to be the isocenter of the treatment plan. Then it starts the dose calculation automatically. The AEM evaluates the plan using pre‐determined plan evaluation parameters: PTV dose‐volume metrics and critical organ doses. The tool has been tested for 10 patients.Results:Automatic plans are generated and saved in the order of the treatment dates of the Adaptive Planning module of the RayStation planning system, without any manual intervention. Once the CTV dose deviates more than 3%, both email and page alerts are sent to the physician and the physicist of the patient so that one can look the case closely.Conclusion:The tool is capable to perform automatic dose tracking and to alert clinicians when an action is needed. It is clinically useful for off‐line adaptive therapy to catch any gross error. Practical way of determining alarming level for OAR is under development.
SU‐C‐202‐05: Pilot Study of Online Treatment Evaluation and Adaptive Re‐Planning for Laryngeal SBRT
Authors: Mao W , Liu C , Zhong H , Rozario T , Lu W , Gu X , Yan Y , Jia X , Sumer B , Schwartz D 
Published: July 2016

Purpose:We have instigated a phase I trial of 5‐fraction stereotactic body radiotherapy (SBRT) for advanced‐stage laryngeal cancer. We conducted this pilot dosimetric study to confirm the potential utility of online adaptive re‐planning to preserve treatment quality.Methods:Ten cases of larynx cancer were evaluated. Baseline and daily SBRT treatment plans were generated per trial protocol. Daily volumetric images were acquired prior to every fraction of treatment. Reference simulation CT images were deformably registered to daily volumetric images using Eclipse. Planning contours were then deformably propagated to daily images. Reference SBRT plans were directly copied to calculate delivered dose distributions on deformed reference CT images. In‐house software platform has been developed to calculate cumulative dose over a course of treatment in four steps: 1) deforming delivered dose grid to reference CT images using deformation information exported from Eclipse; 2) generating tetrahedrons using deformed dose grid as vertices; 3) resampling dose to a high resolution within every tetrahedron; 4) calculating dose‐volume histograms. Our inhouse software was benchmarked with a commercial software, Mirada.Results:In all ten cases including 49 fractions of treatments, delivered daily doses were completely evaluated and treatment could be re‐planned within 10 minutes. Prescription dose coverage of PTV was less than intended in 53% of fractions of treatment (mean: 94%, range: 84%–98%) while minimum coverage of CTV and GTV was 94% and 97%, respectively. Maximum bystander point dose limits to arytenoids, parotids, and spinal cord remained respected in all cases, although variances in carotid artery doses were observed in a minority of cases.Conclusion:Although GTV and CTV coverage is preserved by in‐room 3D image guidance of larynx SBRT, PTV coverage can vary significantly from intended plans. Online adaptive treatment evaluation and re‐planning is potentially necessary and our procedure is clinically applicable to fully preserve treatment quality.This project is supported by CPRIT Individual Investigator Research Award RP150386.
SU‐C‐202‐07: Protocol and Hardware for Improved Flood Field Calibration of TrueBeam FFF Cine Imaging
Authors: Adamson J , Faught A , Yin F 
Published: July 2016

Purpose:Flattening filter free photon energies are commonly used for high dose treatments such as SBRT, where localization accuracy is essential. Often, MV cine imaging may be employed to verify correct localization. TrueBeam Electronic Portal Imaging Devices (EPIDs) equipped with the 40×30cm2 Image Detection Unit (IDU) are prone to image saturation at the image center especially for higher dose rates. While saturation often does not occur for cine imaging during treatment because the beam is attenuated by the patient, the flood field calibration is affected when the standard calibration procedure is followed. Here we describe the hardware and protocol to achieve improved image quality for this model of TrueBeam EPID.Methods:A stainless steel filter of uniform thickness was designed to have sufficient attenuation to avoid panel saturation for both 6XFFF and 10XFFF at the maximum dose rates (1400 MU/min & 2400 MU/min, respectively). The cine imaging flood field calibration was then acquired with the filter in place for the FFF energies under the standard calibration geometry (SDD=150cm). Image quality during MV cine was assessed with & without the modified flood field calibration using a low contrast resolution phantom and an anthropomorphic phantom.Results:When the flood field is acquired using the standard procedure (no filter in place), a pixel gain artifact is clearly present in the image center (r=3cm for 10XFFF at 2400 MU/min) which appears similar to and may be mis‐attributed to panel saturation in the subject image. The artifact obscured all low contrast inserts at the image center and was also visible on the anthropomorphic phantom. Using the filter for flood field calibration eliminated the artifact.Conclusion:Use of a modified flood field calibration procedure improves image quality for cine MV imaging with TrueBeams equipped with the 40×30cm2 IDU.
SU‐C‐207A‐06: On‐Line Beam Range Verification with Multiple Scanning Particle Beams: Initial Feasibility Study with Simulations
Authors: Zhong Y , Sun X , Lu W , Jia X , Wang J , Shao Y 
Published: July 2016

Purpose:To investigate the feasibility and requirement for intra‐fraction on‐line multiple scanning particle beam range verifications (BRVs) with in‐situ PET imaging, which is beyond the current single‐beam BRV with extra factors that will affect the BR measurement accuracy, such as beam diameter, separation between beams, and different image counts at different BRV positions.Methods:We simulated a 110‐MeV proton beam with 5‐mm diameter irradiating a uniform PMMA phantom by GATE simulation, which generated nuclear interaction‐induced positrons. In this preliminary study, we simply duplicated these positrons and placed them next to the initial protons to approximately mimic the two spatially separated positron distributions produced by two beams parallel to each other but with different beam ranges. These positrons were then imaged by a PET (∼2‐mm resolution, 10% sensitivity, 320×320×128 mm^3 FOV) with different acquisition times. We calculated the positron activity ranges (ARs) from reconstructed PET images and compared them with the corresponding ARs of original positron distributions.Results:Without further image data processing and correction, the preliminary study show the errors between the measured and original ARs varied from 0.2 mm to 2.3 mm as center‐to‐center separations and range differences were in the range of 8–12 mm and 2–8 mm respectively, indicating the accuracy of AR measurement strongly depends on the beam separations and range differences. In addition, it is feasible to achieve ≤ 1.0‐mm accuracy for both beams with 1‐min PET acquisition and 12 mm beam separation.Conclusion:This study shows that the overlap between the positron distributions from multiple scanning beams can significantly impact the accuracy of BRVs of distributed particle beams and need to be further addressed beyond the established method of single‐beam BRV, but it also indicates the feasibility to achieve accurate on‐line multi‐beam BRV with further improved method.
SU‐C‐206‐01: Impact of Charge Sharing Effect On Sub‐Pitch Resolution for CZT‐Based Photon Counting CT Systems
Authors: Zheng X , Cheng Z , Deen J , Peng H , Xing L 
Published: July 2016

Purposes:Photon counting CT is a new imaging technology that can provide tissue composition information such as calcium/iodine content quantification. Cadmium zinc telluride CZT is considered a good candidate the photon counting CT due to its relatively high atomic number and band gap. One potential challenge is the degradation of both spatial and energy resolution as the fine electrode pitch is deployed (<50 µm). We investigated the extent of charge sharing effect as functions of gap width, bias voltage and depth‐of‐interaction (DOI).Methods:The initial electron cloud size and diffusion process were modeled analytically. The valid range of charge sharing effect refers to the range over which both signals of adjacent electrodes are above the triggering threshold (10% of the amplitude of 60keV X‐ray photons). The intensity ratios of output in three regions (I1/I2/I3: left pixel, gap area and right pixel) were calculated. With Gaussian white noises modeled (a SNR of 5 based upon the preliminary experiments), the sub‐pitch resolution as a function of the spatial position in‐between two pixels was studied.Results:The valid range of charge sharing increases linearly with depth‐of‐interaction (DOI) but decreases with gap width and bias voltage. For a 1.5mm thickness CZT detector (pitch: 50µm, bias: 400 V), the range increase from ∼90µm up to ∼110µm. Such an increase can be attributed to a longer travel distance and the associated electron cloud broadening. The achievable sub‐pitch resolution is in the range of ∼10–30µm.Conclusion:The preliminary results demonstrate that sub‐pixel spatial resolution can be achieved using the ratio of amplitudes of two neighboring pixels. Such ratio may also be used to correct charge loss and help improve energy resolution of a CZT detector. The impact of characteristic X‐rays hitting adjacent pixels (i.e., multiple interaction) on charge sharing is currently being investigated.
SU‐C‐206‐03: Metal Artifact Reduction in X‐Ray Computed Tomography Based On Local Anatomical Similarity
Authors: Dong X , Yang X , Rosenfield J , Elder E , Dhabaan A 
Published: July 2016

Purpose:Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set‐up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices.Methods:Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact‐free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact‐corrupted CT image. The minimum value in each pixel's gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact‐corrupted pixel. This replacement only occurs if the minimum value in a particular pixel's gamma map is larger than a threshold. The proposed method was evaluated with clinical images.Results:Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non‐uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively.Conclusions:The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.
SU‐C‐206‐05: Pixel‐Wise Calculation of Noise Statistics On Iterative CT Reconstruction from a Single Scan
Authors: Wang T , Zhu L 
Published: July 2016

Purpose:As iterative CT reconstruction continues to advance, the spatial distributions of noise standard deviation (STD) and accurate noise power spectrum (NPS) on reconstructed CT images become more important for method evaluation ans algorithm parameters settings. Using data of a single scan, we propose a practical method for pixel‐wise noise statistics calculation on iterative CT reconstruction image, which enables accurate calculation of noise STD for each pixel and NPS without stationary noise assumption.Methods:We first iteratively reconstruct a CT image using existing reconstruction algorithm. Noise perturbation is then simulated on the raw projection data based on the estimated noise statistics, and the iterative reconstruction continues to generate a different CT image. The above process is repeated on the same projection data but with different noise perturbations, until a sufficient number (32 in our implementations) of different noisy reconstruction images are generated. Pixel‐wise calculations of noise STD and NPS are finally performed on the entire stack of noisy images.Results:We have evaluated our method via simulation studies on a clinical head‐and‐neck CT image, using two iterative reconstruction algorithms: penalized weighted least‐square (PWLS) and total‐variation (TV) regularization. 128 sets of simulated noisy sinogram are used to generate ground‐truths of noise STD and NPS. Using only one set noisy sinogram, the proposed method accurately calculates noise STD map, with a correlation of 94% and 95% for PWLS and TV methods, respectively, compared with the ground‐truth. The relative root‐mean‐square error of 1D‐NPS for proposed method are 1.5% and 3.4% for PWLS and TV methods, respectively, while those for conventional method (averaging NPS of sub‐ROIs in ROI of one image) are 9.0% and 12.9%.Conclusion:The proposed method accurately calculates noise STD for each pixel and NPS without stationary noise assumption on iteratively reconstructed CT image, with no requirements of repeated CT scans.Research reported in this abstract was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597.
SU‐C‐209‐01: Validation of the Simulated Detectability Metric (G‐ROD) Using the Experimental Generalized Measured Relative Object Detectability Metric (GM‐ROD)
Authors: Russ M , Ionita C , Bednarek D , Rudin S 
Published: July 2016

Purpose:The Generalized Relative Object Detectability (G‐ROD) family of ideal observer metrics are a well‐characterized set of task‐based metrics used for quantitatively comparing imaging systems that include the detector, focal spot geometry and scatter characteristics on the basis of system abilities in imaging a given simulated object. The G‐ROD metric takes the integral over spatial frequencies of the Fourier transform of a simulated object function weighted with the detector generalized DQE (GDQE), divided by the comparable integral for another detector. When a measured image of an actual object is used, the generalized measured‐ROD (GM‐ROD) metric can compare detector systems without explicitly determining detector MTF. In this work, the results of simulated and measured ROD calculations for the same object are compared for the first time.Methods:G‐ROD calculations were performed to compare a high resolution microangiographic fluoroscopic (MAF) detector to a flat panel detector (FPD) using 5mm segments of simulated copper wires of varying diameter (d=0.05–0.6mm) as the object function for three different focal spot sizes at two magnifications. A GM‐ROD experiment with similar parameters was performed to compare the same detector system using three actual 5mm copper wires (d=0.113mm,0.238mm,0.558mm) imaged under identical but simulated conditions used in G‐ROD calculations to determine the agreement between simulated and experimentally obtained results.Results:The G‐ROD and GM‐ROD calculations examined relative detector system imaging performance. The GM‐ROD results for all three different sized wires imaged with low magnification and a small focal spot size were 2.1, 1.38, and 1.1, respectively, and the G‐ROD results for the same calculation was 1.81, 1.3, and 1.07, corresponding to percent deviations of 13%, 5.8%, and 2.7%.Conclusion:These results indicate experimental validation of the simulated metric results.Partial support from NIH grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp.