bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐D‐204‐03: Comparison of Patient Positioning Methods Through Modeling of Acute Rectal Toxicity in Intensity Modulated Radiation Therapy for Prostate Cancer. Does Quality of Data Matter More Than the Quantity?
Authors: Liu X , Fatyga M , Herman M , Vora S , Wong W , Schild S , Schild M , Li J , Wu T
Published: July 2016

Purpose:

To determine if differences in patient positioning methods have an impact on the incidence and modeling of grade >=2 acute rectal toxicity in prostate cancer patients who were treated with Intensity Modulated Radiation Therapy (IMRT).

Methods:

We compared two databases of patients treated with radiation therapy for prostate cancer: a database of 79 patients who were treated with 7 field IMRT and daily image guided positioning based on implanted gold markers (IGRTdb), and a database of 302 patients who were treated with 5 field IMRT and daily positioning using a trans‐abdominal ultrasound system (USdb). Complete planning dosimetry was available for IGRTdb patients while limited planning dosimetry, recorded at the time of planning, was available for USdb patients. We fit Lyman‐Kutcher‐Burman (LKB) model to IGRTdb only, and Univariate Logistic Regression (ULR) NTCP model to both databases. We perform Receiver Operating Characteristics analysis to determine the predictive power of NTCP models.

Results:

The incidence of grade >= 2 acute rectal toxicity in IGRTdb was 20%, while the incidence in USdb was 54%. Fits of both LKB and ULR models yielded predictive NTCP models for IGRTdb patients with Area Under the Curve (AUC) in the 0.63 – 0.67 range. Extrapolation of the ULR model from IGRTdb to planning dosimetry in USdb predicts that the incidence of acute rectal toxicity in USdb should not exceed 40%. Fits of the ULR model to the USdb do not yield predictive NTCP models and their AUC is consistent with AUC = 0.5.

Conclusion:

Accuracy of a patient positioning system affects clinically observed toxicity rates and the quality of NTCP models that can be derived from toxicity data. Poor correlation between planned and clinically delivered dosimetry may lead to erroneous or poorly performing NTCP models, even if the number of patients in a database is large.
SU‐D‐BRC‐01: An Automatic Beam Model Commissioning Method for Monte Carlo Simulations in Pencil‐Beam Scanning Proton Therapy
Authors: Qin N , Shen C , Tian Z , Jiang S , Jia X
Published: July 2016

Purpose:

Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam‐model commissioning method for pencil‐beam scanning proton therapy via an optimization approach.

Methods:

We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy, and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero‐size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies.

Results:

We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%.

Conclusion:

The developed automatic MC beam‐model commissioning method for pencil‐beam scanning proton therapy can determine beam model parameters with satisfactory accuracy.
SU‐D‐BRC‐06: Experimental and Monte Carlo Studies of Fluence Corrections for Graphite Calorimetry in Proton Therapy
Authors: Lourenco A , Thomas R , Bouchard H , Kacperek A , Vondracek V , Royle G , Palmans H
Published: July 2016

Purpose:

For photon and electron beams, the standard device used to measure absorbed dose is a calorimeter. Standards laboratories are currently working on the establishment of graphite calorimeters as a primary standard for proton beams. To provide a practical method for graphite calorimetry, it is necessary to convert dose to graphite to dose to water, requiring knowledge of the water‐to‐graphite stopping‐power ratio and the fluence correction factor. This study aims to present a novel method to determine fluence corrections experimentally, and to apply this methodology to low‐ and high‐energy proton beams.

Methods:

Measurements were performed in 60 MeV and 180 MeV proton beams. Experimental information was obtained from depth‐dose ionization chamber measurements performed in a water phantom. This was repeated with different thicknesses of graphite plates in front of the water phantom. One distinct advantage of this method is that only ionization chamber perturbation factors for water are required. Fluence corrections were also obtained through Monte Carlo simulations for comparison with the experiments.

Results:

The experimental observations made in this study confirm the Monte Carlo results. Overall, fluence corrections between water and graphite increased with depth, with a maximum correction of 1% for the low‐energy beam and 4% for the high‐energy beam. The results also showed that a fraction of the secondary particles generated in proton therapy beams do not have enough energy to cross the ionization chamber wall; thus, their contribution is not accounted for in the measured fluence corrections. This effect shows up as a discrepancy in fluence corrections of 1% and has been confirmed by simulations of the experimental setup.

Conclusion:

Fluence corrections derived by experiment do not account for low‐energy secondary particles that are stopped in the ion chamber wall. This work will contribute to a practical graphite calorimetry technique for determining absolute dose to water in proton beams.
SU‐D‐BRB‐03: Full Pre‐Clinical Validation of Comprehensive Knowledge‐Based Planning for Stereotactic Radiosurgery
Authors: Ziemer B , Shiraishi S , Hattangadi‐Gluth J , Sanghvi P , Moore K
Published: July 2016

Purpose:

As knowledge‐based planning (KBP) would augment and potentially supplant manual human‐driven treatment planning, it is imperative to ensure that the KBP system maintains or improves overall plan quality in the aggregate. The purpose of this study was to: (I) demonstrate non‐inferiority of KBP‐driven automated stereotactic radiosurgery (SRS) planning with blinded physician review and (II) determine what factors, if any, contributed to the preference of manual plans over KBP in the blinded review.

Methods:

Automated KBP routines in non‐coplanar VMAT were developed for three clinical SRS scenarios: isolated brain lesions (ISOLATED), lesions closely abutting (<3cm) non‐brain OARs (INVOLVED), and single‐isocenter multiple metastases (MULTIMET). Two SRS‐specializing physicians were given the patient's history/diagnosis/prescription and then presented with the candidate plans with the identities (manual or KBP) obscured. The preferred plan was then selected by the physician reviewer. If two plans were judged to be clinically indistinguishable, this was scored as a KBP selection as the automated plan had thus achieved the same quality as the manual plan. Multiple parameters were explored as possible correlates to manual preference (i.e. KBP failure): planning date, planner, attending physician, reviewing physicist, PTV volume, nearest OAR‐to‐PTV distance and prescription dose. Correlation coefficients were calculated using the Kendall‐Tau statistical test with significance threshold p<0.05.

Results:

For the ISOLATED, INVOLVED and MULTIMET scenarios, the KBP plans were chosen 86% (90/105), 77% (20/26) and 76% (13/17) of the time, respectively. Across the groups, no factors proved to be even moderately correlated or predictive. The only correlation coefficient approaching significance was 0.126 (p=0.052) for PTV volume, implying that KBP plans were selected at a slightly lower rate in the case of smaller PTVs.

Conclusion:

The clinically‐deliverable KBP automated SRS plans were equivalent or superior to manual SRS plans for a clear majority of the cases in all three clinical scenarios.

J.A. Hattangadi: Research Grant; Varian Medical Systems; K.L. Moore: Research Grant; Varian Medical Systems
SU‐D‐BRB‐04: Nomogram for Prediction, Comparison, and Evaluation of Dose to Normal Tissue in SRS Planning
Authors: Templeton A , Liao Y , Diaz A , Turian J
Published: July 2016

Purpose:

Radiosurgery of brain metastases is a unique treatment planning subset in which the treatment approach, high conformality and steep dose gradients are relatively invariant with varying location, size and shape of the target. Prescription doses are generally limited by the size of tumor or amount of surrounding normal brain receiving intermediate doses. We tabulated our treatment plans to establish a nomogram which provides planning expectations, useful for patient scheduling, planning efficiency, and training purposes.

Methods:

The clinical treatment plans of 247 individual metastases (0.3–100cc, 1–5 fractions) were processed, after exclusion of targets qualitatively close to a sensitive brain structure. Plans were designed with 3–5 dynamic conformal arcs using BrainLab‐Iplan or 1–2 VMAT arcs using Eclipse. The effective prescription (D95) was calculated for each plan, and the total volumes of tissue receiving 10%, 20%, 30%, etc. of that dose were calculated (V10, V20, V30 etc.). These data were fitted against the target equivalent diameter with a 3rd degree polynomial minimizing the least‐squares difference, from which the upper and lower quartile fits were generated. Plans were then separated by qualitative concavity of the target, and by MLC type; 0.5cm central leaves versus 0.25cm for Millenium and HD MLCs, respectively.

Results:

The polynomial fitting all data predicted the treated V50 with an r2 value of 0.97 and a mean error of 3.0 cc. The lower‐to‐upper‐quartile V50 range in cc was 12.2–16.2, 14.6–18.1, and 17.2–20.8 for convex, intermediate, and concave targets. The 0.5cm leaves exhibited 1.5cc higher V50 for the smallest targets over 0.25cm leaves.

Conclusion:

Planning performance based on institutional knowledge data offers insights into the attainable results before the planning process begins, and provides support during plan evaluation. Our compiled database will be used to compare treatment approaches and to triage patients.
SU‐D‐BRB‐06: Toward Big‐Data Driven Treatment Planning: VMAT/IMRT Inverse Planning Autopiloted by Population‐Based Prior Data
Authors: Wang H , Xing L
Published: July 2016

Purpose:

Current treatment planning remains a costly and labor intensive procedure and requires multiple trial‐and‐error adjustments of system parameters such as weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning technique with effective use of population‐based prior knowledge.

Methods:

Our autopiloted planning tool consists of three major components: (i) a commercial treatment planning system (TPS) (EclipseTM, Varian Medical Systems, CA); (ii) a statistical formulation of prior knowledge, which takes an assemble of prior treatment plans similar to the patient under planning and provides a priori variation range of final solution with an assigned preference level; and (iii) a decision‐making or outer‐loop optimization that assesses plan generated by Eclipse and drives the search toward a solution consistent with population‐based prior knowledge. To query and interact with TPS, Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. These subroutines are called back in the autopilot program written in C# to navigate through the solution space with an iterative algorithm. The utility of the approach is demonstrated by using a prostate IMRT case and three head and neck VMAT case.

Results:

An autonomous inverse planning formalism of using population‐based prior knowledge for autopiloting the VMAT/IMRT treatment planning process is implemented successfully in platform of a commercial TPS. The process mimics the decision‐making process of autopiloted automobile and provides a clinically sensible treatment plan automatically, thus effectively eliminating the tedious manual trial‐and‐errors process of treatment planning. It is found that the prostate and head and neck treatment plans compare favorably with that used for patients’ actual treatments.

Conclusion:

Clinical inverse treatment planning process can be autopiloted effectively with the use of population‐based prior knowledge. The strategy lays foundation for future development of big data‐driven inverse planning of various disease sites.

Research grant and speak honoraria from Varian Medical Systems
SU‐D‐BRA‐01: Feasibility Study for Swallowing Prediction Using Pressure Sensors
Authors: Cho M , Kim S , Kim T , Kim D , Kang S , Kim K , Shin D , Noh Y , Suh T
Published: July 2016

Purpose:

To develop a swallowing prediction system (SPS) using force sensing sensors and evaluate its feasibility.

Methods:

The SPS developed consists of force sensing sensor units, a thermoplastic mask, a signal transport device and a control PC installed with an in‐house software. The SPS is designed to predict the pharyngeal stage of swallowing because it is known that internal organ movement occurs in pharyngeal stage. To detect prediction signal in the SPS, the force sensing sensor units were attached on both the submental muscle region and thyroid cartilage region of the thermoplastic mask. While the signal from the thyroid cartilage region informs the action of swallowing, the signal from the submental muscle region is utilized as a precursor for swallowing. Since the duration of swallowing is relatively short, using such precursor (or warning) signals for machine control is considered more beneficial. A volunteer study was conducted to evaluate the feasibility of the system. In this volunteer study, we intended to verify that the system could predict the pharyngeal stage of the swallowing. We measured time gaps between obtaining the warning signals in the SPS and starting points of the pharyngeal stage of swallowing.

Results:

The measured data was examined whether the time gaps were in reasonable order to be easily utilized. The mean and standard deviation values of these time gaps were 0.550 s ± 0.183 s. in 8 volunteers.

Conclusion:

The proposed method was able to predict the on‐set of swallowing of human subjects inside the thermoplastic mask, which has never been possible with other monitoring systems such as camera‐based monitoring system. With the prediction ability of swallowing incorporated into the machine control mechanism (in the future), beam delivery can be controlled to skip swallowing periods and significant dosimetric gain is expected in head & neck cancer treatments.

This work was supported by the Radiation Technology R&D program (No. 2015M2A2A7038291) and by the Mid‐career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.
SU‐D‐BRA‐04: Computerized Framework for Marker‐Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image‐Guided Radiation Therapy
Authors: Soufi M , Arimura H , Nakamura K , Hirose T , Umezu Y , Shioyama Y , Toyofuku F
Published: July 2016

Purpose:

To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared‐ray based range images by using differential geometry (curvature) features.

Methods:

The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non‐uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray‐based time‐of‐flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus).

Results:

The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001).

Conclusion:

Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature‐based image registration in range‐image guided radiation therapy.
SU‐D‐BRA‐07: Applications of Combined KV/MV CBCT Imaging with a High‐DQE MV Detector
Authors: Bazalova‐Carter M , Wang A , Wu M , Newson M , Xing L , Ansbacher W , Fahrig R , Star‐Lack J
Published: July 2016

Purpose:

To investigate whether a high detection quantum efficiency (DQE) MV detector makes combined kV/MV CBCT clinically practical.

Methods:

Combined kV/MV CBCT was studied for scan time reduction (STR) and metal artifact reduction (MAR). 6MV CBCT data (dose rate = 0.017 MU/degree) were collected using 1) a novel focused pixelated cadmium tungstate (CWO) scintillator (15mm thickness, DQE(0) = 22%, 0.784mm pixel pitch) coupled to a flat panel imager, and 2) a commercial portal imager with a 133mg/cm2 gadolinium oxysulfide (GOS) screen (DQE(0) = 1.2%). The 100kVp data were acquired using a commercial imager employing a columnar cesium iodide scintillator (DQE(0) = 70%) with a dose rate of 0.0016 cGy/degree. For STR, MV and kV projections spanning 105° were combined to constitute a complete CBCT scan. Total dose was ∼2cGy and acquisition time was 18s. For MAR, only the metalcorrupted pixels in the kV projections were replaced with MV data resulting in a total dose of less than 1cGy for a 360° scan. Image quality was assessed using an 18‐cm diameter electron density phantom with nine tissue inserts, some of which were replaced with steel rods for MAR studies.

Results:

The CWO contrast‐to‐noise ratio (CNR) was ∼4.0x higher than the GOS CNR and was ∼4.8x lower than the kV CNR when normalized for dose. When CWO MV data were combined with kV data for STR, all contrast inserts were visible, but only two were detectable in the composite kV/GOS image. Metal artifacts were greatly reduced using the kV/MV MAR technique with all contrast inserts clearly visible in the composite kV/CWO image but only two inserts visible in the composite kV/GOS image.

Conclusion:

We have demonstrated that a high DQE MV detector significantly improves kV/MV CBCT image quality thus enabling scan time reduction and metal artifact reduction without a severe dose penalty.

AW and JS‐L are employees of Varian, RF is an employee of Siemens.
SU‐D‐202‐01: Functional Lung Avoidance and Response‐Adaptive Escalation (FLARE) RT: Feasibility of a Precision Radiation Oncology Strategy
Authors: Bowen S , Lee E , Miyaoka R , Saini J , Kinahan P , Sandison G , Wong T , Vesselle H , Rengan R , Zeng J
Published: July 2016

Purpose:

NSCLC patient RT is planned without consideration of spatial heterogeneity in lung function or tumor response, which may have contributed to failed uniform dose escalation in a randomized trial. The feasibility of functional lung avoidance and response‐adaptive escalation (FLARE) RT to reduce dose to [9 9mTc]MAA‐SPECT/CT perfused lung while redistributing 74Gy within [1 8F]FDG‐PET/CT biological target volumes was assessed.

Methods:

Eight Stage IIB–IIIB NSCLC patients underwent FDG‐PET/CT and MAA‐SPECT/CT treatment planning scans. Perfused lung objectives were derived from scatter/collimator/attenuation‐corrected MAA‐SPECT uptake relative to ITV‐subtracted lung to maintain <20Gy mean lung dose (MLD). Prescriptions included 60Gy to PTV and concomitant boost of 74Gy mean to biological target volumes (BTV=GTV+PET margin) scaled to each BTV voxel by relative FDG‐PET SUV. Dose‐painting‐by‐numbers prescriptions were integrated into commercial TPS via previously reported ROI discretization. Dose constraints for lung, heart, cord, and esophagus were defined. FLARE RT plans were optimized with VMAT, proton pencil beam scanning (PBS) with 3%‐3mm robust optimization, and combination PBS (avoidance) plus VMAT (escalation). Dosimetric differences were evaluated by Friedman non‐parametric paired test with multiple sampling correction.

Results:

PTV and normal tissue objectives were not violated in 24 FLARE RT plans. Population median of mean BTV dose was 73.7Gy (68.5–75.5Gy), mean FDG‐PET peak dose was 89.7Gy (73.5–103Gy), MLD was 12.3Gy (7.5–19.6Gy), and perfused MLD was 4.8Gy (0.9–12.1Gy). VMAT achieved higher dose to the FDG‐PET peak subvolume (p=0.01), while PBS delivered lower dose to lung (p<0.001). Voxelwise linear correlation between BTV dose and FDG‐PET uptake was higher for VMAT (R=0.93) and PBS+VMAT (R=0.94) compared to PBS alone (R=0.89).

Conclusion:

FLARE RT is feasible with VMAT and PBS. A combination of PBS for functional lung avoidance and VMAT for FDG‐PET dose escalation balances target/normal tissue objective tradeoffs. These results support future testing of FLARE RT safety and efficacy within a precision radiation oncology trial. This work was supported by a Research Scholar grant from the Radiological Society of North American Research & Education Foundation.
SU‐D‐207A‐01: Female Pelvic Synthetic CT Generation Based On Joint Shape and Intensity Analysis
Authors: Liu L , Jolly S , Cao Y , Vineberg K , Fessler J , Balter J
Published: July 2016

Purpose:

To develop a method for generating female pelvic synthetic CT (MRCT) images from a single MR scan and evaluate its utility in radiotherapy.

Methods:

Under IRB‐approval, an imaging sequence (T1_VIBE_Dixon) was acquired for 10 patients. This sequence yields 3 useful image volumes of different contrast (“in‐phase” T1‐weighted, fat and water). A previously published pelvic bone shape model was used to generate a rough bone mask for each patient. A modified fuzzy c‐means classification was performed on the multi spectral MR data, with a regularization term that utilizes the prior knowledge provided by the bone mask and addresses the intensity overlap between different tissue types. A weighted sum of classification probabilities with attenuation values yielded MRCT volumes. The mean absolute error (MAE) between MRCT and real CT on various regions was calculated following deformable alignment (Velocity). Intensity modulated Treatment plans based on actual CT and MRCT were made and compared.

Results:

The average/standard deviation of MAE across 10 patients was 10.1/6.7 HU for muscle, 6.7/4.6 HU for fat, 136.9/53.5 HU for bony tissues under 850 HU (97% of total bone volume), 188.9/119.3 HU for bony tissues above 850 HU and 17.3/13.3 HU for intrapelvic soft tissues. Calculated doses were comparable for plans generated on CT and calculated using MRCT densities or vice versa, with differences in PTV D99% (mean/σ) of (–0.1/0.2 Gy) and (0.3/0.2 Gy), PTV D0.5cc of (–0.3/0.2 Gy) and (–0.4/1.7 Gy). OAR differences were similarly small for comparable structures, with differences in bowel V50Gy of (–0.3/0.2%) and (0.0/0.2%), femur V30Gy of (0.7/1.2%) and (0.2/1.2%), sacrum V20GY of (0.0/0.1%) and (–0.1/1.1%) and mean pelvic V20Gy of (0.0/0.1%) and (0.6/1.8%).

Conclusion:

MRCT based on a single imaging sequence in the female pelvis is feasible, with acceptably small variations in attenuation estimates and calculated doses to target and critical organs.

Work supported by NIHR01EB016079
SU‐D‐206‐03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone‐Beam CT
Authors: Wu P , Mao T , Gong S , Wang J , Sheng K , Xie Y , Niu T
Published: July 2016

Purpose:

Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low‐dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone‐beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimization trajectory.

Methods:

Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first‐pass low‐quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process.

Results:

The proposed method is evaluated on the Shepp‐Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value.

Conclusion:

We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction.

This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High‐tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).
SU‐D‐206‐07: CBCT Scatter Correction Based On Rotating Collimator
Authors: Yu G , Yin Y , Qiang L , Li B , Feng Z , Huang P , Li D
Published: July 2016

Purpose:

Scatter correction in cone‐beam computed tomography (CBCT) has obvious effect on the removal of image noise, the cup artifact and the increase of image contrast. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, the inconvenience of mechanics and propensity to residual artifacts limited the further evolution of basic and clinical research. Here, we propose a rotating collimator‐based approach, in conjunction with reconstruction based on a discrete Radon transform and Tchebichef moments algorithm, to correct scatter‐induced artifacts.

Methods:

A rotating‐collimator, comprising round tungsten alloy strips, was mounted on a linear actuator. The rotating‐collimator is divided into 6 portions equally. The round strips space is evenly spaced on each portion but staggered between different portions. A step motor connected to the rotating collimator drove the blocker to around x‐ray source during the CBCT acquisition. The CBCT reconstruction based on a discrete Radon transform and Tchebichef moments algorithm is performed. Experimental studies using water phantom and Catphan504 were carried out to evaluate the performance of the proposed scheme.

Results:

The proposed algorithm was tested on both the Monte Carlo simulation and actual experiments with the Catphan504 phantom. From the simulation result, the mean square error of the reconstruction error decreases from 16% to 1.18%, the cupping (τcup) from 14.005% to 0.66%, and the peak signal‐to‐noise ratio increase from 16.9594 to 31.45. From the actual experiments, the induced visual artifacts are significantly reduced.

Conclusion:

We conducted an experiment on CBCT imaging system with a rotating collimator to develop and optimize x‐ray scatter control and reduction technique. The proposed method is attractive in applications where a high CBCT image quality is critical, for example, dose calculation in adaptive radiation therapy.

We want to thank Dr. Lei Xing and Dr. Yong Yang in the Stanford University School of Medicine for this work. This work was jointly supported by NSFC (61471226), Natural Science Foundation for Distinguished Young Scholars of Shandong Province (JQ201516), and China Postdoctoral Science Foundation (2015T80739, 2014M551949).
SU‐D‐209‐01: Can Fluoroscopic Air‐Kerma Rates Be Reliably Measured with Solid‐State Meters?
Authors: Feng C , Ozus B , Thai L , Wagner L
Published: July 2016

Purpose:

Ionization chambers remain the standard for calibration of air‐kerma rate measuring devices. Despite their strong energy‐dependent response, solid state radiation detectors are increasingly used, primarily due to their efficiency in making standardized measurements. To test the reliability of these devices in measuring air‐kerma rates, we compared ion chambers measurements with solid‐state measurements for various mobile fluoroscopes operated at different beam qualities and air‐kerma rates.

Methods:

Six mobile fluoroscopes (GE OEC models 9800 and 9900) were used to generate test beams. Using various field sizes and dose rate controls, copper attenuators and a lead attenuator were placed at the image receptor in varying combinations to generate a range of air‐kerma rates. Air‐kerma rates at 30 centimeters from the image receptors were measured using two 6‐cm3 ion chambers with electrometers (Radcal, models 1015 and 9015) and two with solid state detectors (Unfors Xi and Raysafe X2). No error messages occurred during measurements. However, about two months later, one solid‐state device stopped working and was replaced by the manufacturer. Two out of six mobile fluoroscopic units were retested with the replacement unit.

Results:

Generally, solid state and ionization chambers agreed favorably well, with two exceptions. Before replacement of the detector, the Xi meter when set in the “RF High” mode deviated from ion chamber readings by factors of 2 and 10 with no message indicating error in measurement. When set in the “RF Low” mode, readings were within −4% to +3%. The replacement Xi detector displayed messages alerting the user when settings were not compatible with air‐kerma rates.

Conclusion:

Air‐kerma rates can be measured favorably well using solid‐state devices, but users must be aware of the possibility that readings can be grossly in error with no discernible indication for the deviation.
SU‐D‐207B‐02: Early Grade Classification in Meningioma Patients Combining Radiomics and Semantics Data
Authors: Coroller T , Bi W , Abedalthagafi M , Aizer A , Wu W , Greenwald N , Beroukhim R , Al‐Mefty O , Santagata S , Dunn I , Alexander B , Huang R , Aerts H
Published: July 2016

Purpose:

The clinical management of meningioma is guided by its grade and biologic behavior. Currently, diagnosis of tumor grade follows surgical resection and histopathologic review. Reliable techniques for pre‐operative determination of tumor behavior are needed. We investigated the association between imaging features extracted from preoperative gadolinium‐enhanced T1‐weighted MRI and meningioma grade.

Methods:

We retrospectively examined the pre‐operative MRI for 139 patients with de novo WHO grade I (63%) and grade II (37%) meningiomas. We investigated the predictive power of ten semantic radiologic features as determined by a neuroradiologist, fifteen radiomic features, and tumor location. Conventional (volume and diameter) imaging features were added for comparison. AUC was computed for continuous and χ2 for discrete variables. Classification was done using random forest. Performance was evaluated using cross validation (1000 iterations, 75% training and 25% validation). All p‐values were adjusted for multiple testing.

Results:

Significant association was observed between meningioma grade and tumor location (p<0.001) and two semantic features including intra‐tumoral heterogeneity (p<0.001) and overt hemorrhage (p=0.01). Conventional (AUC 0.61–0.67) and eleven radiomic (AUC 0.60–0.70) features were significant from random (p<0.05, Noether test). Median AUC values for classification of tumor grade were 0.57, 0.71, 0.72 and 0.77 respectively for conventional, radiomic, location, and semantic features after using random forest. By combining all imaging data (semantic, radiomic, and location), the median AUC was 0.81, which offers superior predicting power to that of conventional imaging descriptors for meningioma as well as radiomic features alone (p<0.05, permutation test).

Conclusion:

We demonstrate a strong association between radiologic features and meningioma grade. Pre‐operative prediction of tumor behavior based on imaging features offers promise for guiding personalized medicine and improving patient management.
SU‐D‐207B‐03: A PET‐CT Radiomics Comparison to Predict Distant Metastasis in Lung Adenocarcinoma
Authors: Coroller T , Yip S , Kim J , Lee S , Mak R , Aerts H
Published: July 2016

Purpose:

Early prediction of distant metastasis may provide crucial information for adaptive therapy, subsequently improving patient survival. Radiomic features that extracted from PET and CT images have been used for assessing tumor phenotype and predicting clinical outcomes. This study investigates the values of radiomic features in predicting distant metastasis (DM) in non‐small cell lung cancer (NSCLC).

Methods:

A total of 108 patients with stage II–III lung adenocarcinoma were included in this retrospective study. Twenty radiomic features were selected (10 from CT and 10 from PET). Conventional features (metabolic tumor volume, SUV, volume and diameter) were included for comparison. Concordance index (CI) was used to evaluate features prognostic value. Noether test was used to compute p‐value to consider CI significance from random (CI = 0.5) and were adjusted for multiple testing using false rate discovery (FDR).

Results:

A total of 70 patients had DM (64.8%) with a median time to event of 8.8 months. The median delivered dose was 60 Gy (range 33–68 Gy). None of the conventional features from PET (CI ranged from 0.51 to 0.56) or CT (CI ranged from 0.57 to 0.58) were significant from random. Five radiomics features were significantly prognostic from random for DM (p‐values < 0.05). Four were extracted from CT (CI = 0.61 to 0.63, p‐value <0.01) and one from PET which was also the most prognostic (CI = 0.64, p‐value <0.001).

Conclusion:

This study demonstrated significant association between radiomic features and DM for patients with locally advanced lung adenocarcinoma. Moreover, conventional (clinically utilized) metrics were not significantly associated with DM. Radiomics can potentially help classify patients at higher risk of DM, allowing clinicians to individualize treatment, such as intensification of chemotherapy) to reduce the risk of DM and improve survival.

R.M. has consulting interests with Amgen.
SU‐F‐SPS‐01: Accuracy of the Small Field Dosimetry Using Acuros XB and AAA Dose Calculation Algorithms of Eclipse Treatment Planning System Within and Beyond Heterogeneous Media for Trubeam 2.0 Unit
Authors: Codel G , Serin E , Pacaci P , Sanli E , Cebe M , Mabhouti H , Doyuran M , Kucukmorkoc E , Kucuk N , Altinok A , Canoglu D , Acar H , Caglar Ozkok H
Published: July 2016

Purpose:

In this study, the comparison of dosimetric accuracy of Acuros XB and AAA algorithms were investigated for small radiation fields incident on homogeneous and heterogeneous geometries

Methods:

Small open fields of Truebeam 2.0 unit (1×1, 2×2, 3×3, 4×4 fields) were used for this study. The fields were incident on homogeneous phantom and in house phantom containing lung, air, and bone inhomogeneities. Using the same film batch, the net OD to dose calibration curve was obtaine dusing Trubeam 2.0 for 6 MV, 6 FFF, 10 MV, 10 FFF, 15 MV energies by delivering 0‐ 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. The dosimetric accuracy of Acuros XB and AAA algorithms in the presence of the inhomogeneities was compared against EBT3 film dosimetry

Results:

Open field tests in a homogeneous phantom showed good agreement betweent wo algorithms and measurement. For Acuros XB, minimum gamma analysis passin grates between measured and calculated dose distributions were 99.3% and 98.1% for homogeneousand inhomogeneous fields in thecase of lung and bone respectively. For AAA, minimum gamma analysis passingrates were 99.1% and 96.5% for homogeneous and inhomogeneous fields respectively for all used energies and field sizes.In the case of the air heterogeneity, the differences were larger for both calculations algorithms. Over all, when compared to measurement, theAcuros XB had beter agreement than AAA.

Conclusion:

The Acuros XB calculation algorithm in the TPS is an improvemen tover theexisting AAA algorithm. Dose discrepancies were observed for in the presence of air inhomogeneities.
SU‐F‐SPS‐05: Experimental Validation of Peripheral Dose Distribution of Electron Beams for Eclipse Electron Monte Carlo Algorithm
Authors: Cebe M , Pacaci P , Mabhouti H , Codel G , Sanli E , Serin E , Kucuk N , Kucukmorkoc E , Doyuran M , Canoglu D , Altinok A , Acar H , Caglar Ozkok H
Published: July 2016

Purpose:

In this study, the two available calculation algorithms of the Varian Eclipse treatment planning system(TPS), the electron Monte Carlo(eMC) and General Gaussian Pencil Beam(GGPB) algorithms were used to compare measured and calculated peripheral dose distribution of electron beams.

Methods:

Peripheral dose measurements were carried out for 6, 9, 12, 15, 18 and 22 MeV electron beams of Varian Triology machine using parallel plate ionization chamber and EBT3 films in the slab phantom. Measurements were performed for 6×6, 10×10 and 25×25cm2 cone sizes at dmax of each energy up to 20cm beyond the field edges. Using the same film batch, the net OD to dose calibration curve was obtained for each energy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution measured using parallel plate ionization chamber and EBT3 film and calculated by eMC and GGPB algorithms were compared. The measured and calculated data were then compared to find which algorithm calculates peripheral dose distribution more accurately.

Results:

The agreement between measurement and eMC was better than GGPB. The TPS underestimated the out of field doses. The difference between measured and calculated doses increase with the cone size. The largest deviation between calculated and parallel plate ionization chamber measured dose is less than 4.93% for eMC, but it can increase up to 7.51% for GGPB. For film measurement, the minimum gamma analysis passing rates between measured and calculated dose distributions were 98.2% and 92.7% for eMC and GGPB respectively for all field sizes and energies.

Conclusion:

Our results show that the Monte Carlo algorithm for electron planning in Eclipse is more accurate than previous algorithms for peripheral dose distributions. It must be emphasized that the use of GGPB for planning large field treatments with 6 MeV could lead to inaccuracies of clinical significance.
SU‐F‐E‐07: Web‐Based Training for Radiosurgery: Methods and Metrics for Global Reach
Authors: Schulz R , Thomas E , Popple R , Fiveash J , Jacobsen E
Published: July 2016

Purpose:

Webinars have become an evolving tool with greater or lesser success in reaching health care providers (HCPs). This study seeks to assess best practices and metrics for success in webinar deployment for optimal global reach.

Methods:

Webinars have been developed and launched to reach practicing health care providers in the field of radiation oncology and radiosurgery. One such webinar was launched in early February 2016. “Multiple Brain Metastases & Volumetric Modulated Arc Radiosurgery: Refining the Single‐Isocenter Technique to Benefit Surgeons and Patients” presented by Drs. Fiveash and Thomas from UAB was submitted to and accredited by the Institute for Medical Education as qualifying for CME as well as MDCB for educational credit for dosimetrists, in order to encourage participation. MedicalPhysicsWeb was chosen as the platform to inform attendees regarding the webinar. Further IME accredited the activity for 1 AMA PRA Category 1 credit for physicians & medical physicists. The program was qualified by the ABR in meeting the criteria for self‐assessment towards fulfilling MOC requirements. Free SAMs credits were underwritten by an educational grant from Varian Medical Systems.

Results:

The webinar in question attracted 992 pre‐registrants from 66 countries. Outside the US and Canada; 11 were from the Americas; 32 were from Europe; 9 from the Middle East and Africa. Australasia and the Indian subcontinent represented the remaining 14 countries. Pre‐registrants included 423 Medical Physicists, 225 Medical Dosimetrists, 24 Radiation Therapists, 66 Radiation Oncologists & other.

Conclusion:

The effectiveness of CME and SAM‐CME programs such as this can be gauged by the high rate of respondents who state an intention to change practice habits, a primary goal of continuing medical education and self‐assessment. This webinar succeeded in being the most successful webinar on Medical Physics Web as measured by pre‐registration, participation and participation to pre‐registration ratio.

R.A. Schulz is an employee of Varian Medical Systems
SU‐F‐E‐13: Design and Fabrication of Gynacological Brachytherapy Shielding & Non Shielding Applicators Using Indigenously Developed 3D Printing Machine
Authors: Shanmugam S
Published: July 2016

Purpose:

In this innovative work we have developed Gynecological Brachytherapy shielding & Non Shielding Applicators and compared with the commercially available applicators by using the indigenously developed 3D Printing machine.

Methods:

We have successfully indigenously developed the 3D printing machine. Which contain the 3 dimensional motion platform, Heater unit, base plate, ect… To fabricate the Gynecological Brachytherapy shielding & non shielding applicators the 3D design were developed in the computer as virtual design. This virtual design is made in a CAD computer file using a 3D modeling program. Separate programme for the shielding & non shielding applicators. We have also provided the extra catheter insert provision in the applicator for the multiple catheter. The DICOM file of the applicator were then converted to stereo Lithography file for the 3D printer. The shielding & Non Shielding Applicators were printed on a indigenously developed 3D printer material. The same dimensions were used to develop the applicators in the acrylic material also for the comparative study. A CT scan was performed to establish an infill‐density calibration curve as well as characterize the quality of the print such as uniformity and the infill pattern. To commission the process, basic CT and dose properties of the printing materials were measured in photon beams and compared against water and soft tissue. Applicator were then scanned to confirm the placement of multiple catheter position. Finally dose distributions with rescanned CTs were compared with those computer‐generated applicators.

Results:

The doses measured from the ion Chamber and X‐Omat film test were within 2%. The shielded applicator reduce the rectal dose comparatively with the non shielded applicator.

Conclusion:

As of submission 3 unique cylinders have been designed, printed, and tested dosimetrically. A standardizable workflow for commissioning custom 3D printed applicators was codified and will be reported.
SU‐F‐P‐07: Applying Failure Modes and Effects Analysis to Treatment Planning System QA
Authors: Mathew D , Alaei P
Published: July 2016

Purpose:

A small‐scale implementation of Failure Modes and Effects Analysis (FMEA) for treatment planning system QA by utilizing methodology of AAPM TG‐100 report.

Methods:

FMEA requires numerical values for severity (S), occurrence (O) and detectability (D) of each mode of failure. The product of these three values gives a risk priority number (RPN). We have implemented FMEA for the treatment planning system (TPS) QA for two clinics which use Pinnacle and Eclipse TPS. Quantitative monthly QA data dating back to 4 years for Pinnacle and 1 year for Eclipse have been used to determine values for severity (deviations from predetermined doses at points or volumes), and occurrence of such deviations. The TPS QA protocol includes a phantom containing solid water and lung‐ and bone‐equivalent heterogeneities. Photon and electron plans have been evaluated in both systems. The dose values at multiple distinct points of interest (POI) within the solid water, lung, and bone‐equivalent slabs, as well as mean doses to several volumes of interest (VOI), have been re‐calculated monthly using the available algorithms.

Results:

The computed doses vary slightly month‐over‐month. There have been more significant deviations following software upgrades, especially if the upgrade involved re‐modeling of the beams. TG‐100 guidance and the data presented here suggest an occurrence (O) of 2 depending on the frequency of re‐commissioning the beams, severity (S) of 3, and detectability (D) of 2, giving an RPN of 12.

Conclusion:

Computerized treatment planning systems could pose a risk due to dosimetric errors and suboptimal treatment plans. The FMEA analysis presented here suggests that TPS QA should immediately follow software upgrades, but does not need to be performed every month.