X Tang

Visual Analysis of the Daily QA Results of Photon and Electron Beams of a Trilogy Linac over a Five-Year Period

Data visualization technique was applied to analyze the daily QA results of photon and electron beams. Special attention was paid to any trend the beams might display. A Varian Trilogy Linac equipped with dual photon energies and five electron energies was commissioned in early 2010. Daily Linac QA tests including the output constancy, beam flatness and symmetry (radial and transverse directions) were performed with an ionization chamber array device (QA BeamChecker Plus, Standard Imaging). The data of five years were collected and analyzed. For each energy, the measured data were exported and processed for visual trending using an in-house Matlab program. These daily data were cross-correlated with the monthly QA and annual QA results, as well as the preventive maintenance records. Majority of the output were within 1% of variation, with a consistent positive/upward drift for all seven energies (~+0.25% per month). The baseline of daily device is reset annually right after the TG-51 calibration. This results in a sudden drop of the output. On the other hand, the large amount of data using the same baseline exhibits a sinusoidal behavior (cycle = 12 months; amplitude = 0.8%, 0.5% for photons, electrons, respectively) on symmetry and flatness when normalization of baselines is accounted for. The well known phenomenon of new Linac output drift was clearly displayed. This output drift was a result of the air leakage of the over-pressurized sealed monitor chambers for the specific vendor. Data visualization is a new trend in the era of big data in radiation oncology research. It allows the data to be displayed visually and therefore more intuitive. Based on the visual display from the past, the physicist might predict the trend of the Linac and take actions proactively. It also makes comparisons, alerts failures, and potentially identifies causalities.

A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis

Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs-the bladder and the rectum-in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patients collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13u2009mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearsons correlation coefficient, R pu2009u2009=u2009u20090.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R pu2009u2009=u2009u20090.51; 0.68) than the correlation with the TE (bladder: R pu2009u2009=u2009u20090.46; rectum: R pu2009u2009=u2009u20090.47), or the ICE (bladder: R pu2009u2009=u2009u20090.34; rectum: R pu2009u2009=u2009u20090.37). There was a negative correlation between DSC and DDMmean of both the bladder (R pu2009u2009=u2009u2009-0.23) and the rectum (R pu2009u2009=u2009u2009-0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and structures. Our results show a stronger correlation with volume ratios and with the DSC using DDM compared to using ICE and TE. The DDM has the potential to quantitatively identify regions of large DIR uncertainties and consequently identify anatomical/scan outliers. The DDM can, thus, be applied to improve the adaptive RT process for tumor sites subject to motion.

WE‐D‐ValB‐07: Patient Setup Based On Lung Tumor Mass for Gated Radiotherapy

Purpose: To develop a lungcancer patient setup technique for gated radiotherapy based on the direct image registration of lungtumor mass. Method and Materials: We develop a tumor mass based patient setup technique for gated radiotherapy that matches the lungtumor of the radiographicimage to the DRRimage. For each patient, AP and lateral DRRs at exhale are generated from the corresponding 4DCT data with the projected GTV outer contour. During patient setup, AP and lateral radiographs are acquired at exhale using an on‐board x‐ray imaging system. First, an image registration algorithm is applied to match the regions of interest around the tumor mass in both radiographic and DRRimage. Second, an interactive registration procedure, which uses a computer mouse to drag the GTV contour in the radiographicimage to its correct position, is applied to verify and/or correct the automatic registration results. Results: We tested the various existing image registration algorithms and found that maximizing mutual information performs best for lungtumor registrations. Excellent matches can generally be made, and if nuanced adjustments are needed for a particular patient, they can be accomplished through interactive registration. Conclusion: Automatic registration of lungtumor mass in radiographicimage to DRR is feasible for most of patients to provide precise patient setup based on tumor mass, rather than skin markers or bony structures. Interactive registration is needed to provide human verification and correction. Conflict of Interest: Research is partially sponsored by an NCI grant (1 R21 CA110177 A 01A1).

Artificial intelligence will reduce the need for clinical medical physicists

In 2011, IBM’s supercomputer Watson defeated the former human winners and won the first prize on Jeopardy! game. It has created an overly publicized attention on machine learning and Artificial Intelligence (AI). Early this year, Google AlphaGo has marked a major breakthrough in AI by winning the first game against the world’s best champion human player in the world’s most complex game, the ancient Chinese Go game. With no doubt, the interests in AI and its related products had reached a global frenzy. As scientists advance in technology, a concern of job security has risen up: will robots take our jobs? IBM Watson has evolved from a “question answering machine” to a highly intelligent “cognitive diagnostic engine” or a “decision support system” over the past 6 yr. Based on Carl Frey and his collaborators, future family health centers may transition to a team of nurse practitioners with the support of Watson Health and overseen by one single doctor. Will AI technology also marginalize medical physicists in the near future? In this series, we have Dr. Xiaoli Tang arguing for the proposition that “AI will reduce the need for clinical medical physicists” and Dr. Brian Wang arguing against it. Dr. Xiaoli Tang received a Ph.D in Electrical Engineering from the Rensselaer Polytechnic Institute. She then did her postdoctoral training in Medical Physics at the Massachusetts General Hospital and the University of California at San Diego. She previously worked at the University of North Carolina and now is working as an Assistant Attending and chief physicist at the Memorial Sloan Kettering Cancer Center Westchester regional site. She is an expert in motion management, Deep Inspiration Breath Hold (DIBH) for left-sided breast cancer, and machine learning algorithms on medical physic applications. She is interested in developing related clinical trials, and bringing new technology to the clinic. She is a member of the American Association of Physicists in Medicine (AAPM), and the American Society for Radiation Oncology. Dr. Brian Wang received his PhD in nuclear engineering from Rensselaer Polytechnic Institute in Troy, NY in 2005. He currently works at University of Louisville as the chief of physics and medical physics residency director. Dr. Wang is an associate editor for the JACMP. His research interests include motion management, image guidance, and SRS/SBRT. Dr. Wang has been involved with the AAPM Spring Clinical Meeting and its predecessor ACMP annual meeting as a program director or the subcommittee chair for 8 yr. Dr. Wang serves on several committees at ASTRO, RSS, and ABR.

SU-F-T-173: One-Scan Protocol: Verifying the Delivery of Spot-Scanning Proton Beam

PURPOSEnRadiochromic film for spot-scanning QA provides high spatial resolution and efficiency gains from one-shot irradiation for multiple depths. However, calibration can be a tedious procedure which may limit widespread use. Moreover, since there may be an energy dependence, which manifests as a depth dependence, this may require additional measurements for each patient. We present a one-scan protocol to simplify the procedure.nnnMETHODSnWe performed the calibration using an EBT3 film at depths of 18, 20, 24cm of Plastic Water exposed by a 6-level step-wedge plan on a Proteus Plus proton system (IBA, Belgium). The calibration doses ranged 65-250 cGy(RBE) for proton energies of 170-200MeV. A clinical prostate+nodes plan was used for validation. The planar doses at selected depths were measured with EBT3 films and analyzed using one-scan protocol (one-scan digitization of QA film and at least one film exposed to known dose). The Gamma passing rates, dose-difference maps, and profiles of 2D planar doses measured with EBT3 film, IBA MatriXX PT, versus TPS calculations were analyzed and compared.nnnRESULTSnThe EBT3 film measurement results matched well with the TPS calculation data with an average passing rate of ∼95% for 2%/2mm and slightly lower passing rates were obtained from an ion chamber array detector. We were able to demonstrate that the use of a proton step-wedge provided clinically acceptable results and minimized variations between film-scanner orientation, inter-scan, and scanning conditions. Furthermore, it could be derived from no more than two films exposed to known doses (one could be zero) for rescaling the master calibration curve at each depth.nnnCONCLUSIONnThe use of a proton step-wedge for calibration of EBT3 film increases efficiency. The sensitivity of the calibration to depth variations has been explored. One-scan protocol results appear to be comparable to that of the ion chamber array detector. One author has a research grant from Ashland Inc., the manufacturer of the GafChromic film.

Validation of the Calypso Surface Beacon Transponder

Calypso L-shaped Surface Beacon transponder has recently become available for clinical applications. We herein conduct studies to validate the Surface Beacon transponder in terms of stability, reproducibility, orientation sensitivity, cycle rate dependence, and respiratory waveform tracking accuracy. The Surface Beacon was placed on a Quasar respiratory phantom and positioned at the isocenter with its two arms aligned with the lasers. Breathing waveforms were simulated, and the motion of the transponder was tracked. Stability and drift analysis: sinusoidal waveforms (200 cycles) were produced, and the amplitudes of phases 0% (inhale) and 50% (exhale) were recorded at each breathing cycle. The mean and standard deviation (SD) of the amplitudes were calculated. Linear least-squares fitting was performed to access the possible amplitude drift over the breathing cycles. Reproducibility: similar setting to stability and drift analysis, and the phantom generated 100 cycles of the sinusoidal waveform per run. The Calypso systems was re-setup for each run. Recorded amplitude and SD of 0% and 50% phase were compared between runs to assess contribution of Calypso electromagnetic array setup variation. Beacon orientation sensitivity: the Calypso tracks sinusoidal phantom motion with a defined angular offset of the beacon to assess its effect on SD and peak-to-peak amplitude. Rate dependence: sinusoidal motion was generated at cycle rates of 1 Hz, .33 Hz, and .2 Hz. Peak-to-peak displacement and SDs were assessed. Respiratory waveform tracking accuracy: the phantom reproduced recorded breathing cycles (by volunteers and patients) were tracked by the Calypso system. Deviation in tracking position from produced waveform was used to calculate SD throughout entire breathing cycle. Stability and drift analysis: Mean amplitude ± SD of phase 0% or 50% were 20.01±0.04u2009mm and -19.65±0.08u2009mm, respectively. No clinically significant drift was detected with drift measured as 5.1×10-5u2009mm/s at phase 0% and -6.0×10-5u2009mm/s at phase 50%. Reproducibility: The SD of the setup was 0.06 mm and 0.02 mm for phases 0% and 50%, respectively. The combined SDs, including both setup and intrarun error of all runs at phases 0% and 50%, were 0.07 mm and 0.11 mm, respectively. Beacon orientation: SD ranged from 0.032 mm to 0.039 mm at phase 0% and from 0.084 mm to 0.096 mm at phase 50%. The SD was found not to vary linearly with Beacon angle in the range of 0° and 15°. A positive systematic error was observed with amplitude 0.07 mm/degree at phase 0% and 0.05 mm/degree at phase 50%. Rate dependence: SD and displacement amplitudes did not vary significantly between 0.2 Hz and 0.33 Hz. At 1 Hz, both 0% and 50% amplitude measurements shifted up appreciably, by 0.72 mm and 0.78 mm, respectively. As compared with the 0.33 Hz data, SD at phase 0% was 1.6 times higher and 5.4 times higher at phase 50%. Respiratory waveform tracking accuracy: SD of 0.233 mm with approximately normal distribution in over 134 min of tracking (201468 data points). The Surface Beacon transponder appears to be stable, accurate, and reproducible. Submillimeter resolution is achieved throughout breathing and sinusoidal waveforms. PACS number(s): 87.50.ct, 87.50.st, 87.50.ux, 87.50.wp, 87.50.yt.Calypso L‐shaped Surface Beacon transponder has recently become available for clinical applications. We herein conduct studies to validate the Surface Beacon transponder in terms of stability, reproducibility, orientation sensitivity, cycle rate dependence, and respiratory waveform tracking accuracy. The Surface Beacon was placed on a Quasar respiratory phantom and positioned at the isocenter with its two arms aligned with the lasers. Breathing waveforms were simulated, and the motion of the transponder was tracked. Stability and drift analysis: sinusoidal waveforms (200 cycles) were produced, and the amplitudes of phases 0% (inhale) and 50% (exhale) were recorded at each breathing cycle. The mean and standard deviation (SD) of the amplitudes were calculated. Linear least‐squares fitting was performed to access the possible amplitude drift over the breathing cycles. Reproducibility: similar setting to stability and drift analysis, and the phantom generated 100 cycles of the sinusoidal waveform per run. The Calypso systems was re‐setup for each run. Recorded amplitude and SD of 0% and 50% phase were compared between runs to assess contribution of Calypso electromagnetic array setup variation. Beacon orientation sensitivity: the Calypso tracks sinusoidal phantom motion with a defined angular offset of the beacon to assess its effect on SD and peak‐to‐peak amplitude. Rate dependence: sinusoidal motion was generated at cycle rates of 1 Hz, .33 Hz, and .2 Hz. Peak‐to‐peak displacement and SDs were assessed. Respiratory waveform tracking accuracy: the phantom reproduced recorded breathing cycles (by volunteers and patients) were tracked by the Calypso system. Deviation in tracking position from produced waveform was used to calculate SD throughout entire breathing cycle. Stability and drift analysis: Mean amplitude ± SD of phase 0% or 50% were 20.01±0.04u2009mm and ‐19.65±0.08u2009mm, respectively. No clinically significant drift was detected with drift measured as 5.1×10‐5u2009mm/s at phase 0% and ‐6.0×10‐5u2009mm/s at phase 50%. Reproducibility: The SD of the setup was 0.06 mm and 0.02 mm for phases 0% and 50%, respectively. The combined SDs, including both setup and intrarun error of all runs at phases 0% and 50%, were 0.07 mm and 0.11 mm, respectively. Beacon orientation: SD ranged from 0.032 mm to 0.039 mm at phase 0% and from 0.084 mm to 0.096 mm at phase 50%. The SD was found not to vary linearly with Beacon angle in the range of 0° and 15°. A positive systematic error was observed with amplitude 0.07 mm/degree at phase 0% and 0.05 mm/degree at phase 50%. Rate dependence: SD and displacement amplitudes did not vary significantly between 0.2 Hz and 0.33 Hz. At 1 Hz, both 0% and 50% amplitude measurements shifted up appreciably, by 0.72 mm and 0.78 mm, respectively. As compared with the 0.33 Hz data, SD at phase 0% was 1.6 times higher and 5.4 times higher at phase 50%. Respiratory waveform tracking accuracy: SD of 0.233 mm with approximately normal distribution in over 134 min of tracking (201468 data points). The Surface Beacon transponder appears to be stable, accurate, and reproducible. Submillimeter resolution is achieved throughout breathing and sinusoidal waveforms. PACS number(s): 87.50.ct, 87.50.st, 87.50.ux, 87.50.wp, 87.50.yt

SU‐E‐J‐63: Initial Validation of the Surface Beacon Transponder

Purpose: Varian’s L shaped surface beacon transponder for the Calypso system has recently been cleared for real time tracking anywhere on body. We herein conduct initial validation of the surface beacon transponder in preparation for clinical implementations. Methods: The surface beacon transponder was placed on a respiratory phantom to conduct the following three tests. 1) Stability: the phantom was turned on to produce the same breathing cycle repeatedly, and the associated transponder motion was then recorded. The mean and standard deviations of the amplitude were calculated for phase 0% and 50% over all the cycles. We also looked for any possible baseline drift. 2) Reproducibility: the phantom/transponder was setup to the same position multiple times, and motion from each session was recorded. The mean and standard deviation of the amplitude of phase 0% were calculated over all sessions. 3) Transponder placement sensitivity: it is recommended to align two arms of the transponder to the lateral and sagittal lasers. With patient breathing, transponder position might vary during the treatment. We manually introduced 14° yaw to the transponder placement and calculated the amplitude difference compared to when transponder was perfectly aligned (0°). Results: 1) Stability: the means and standard deviations for 0% and 50% were 1.39±0.01 cm and −0.03±0.005 cm. The baseline seemed to drift up: i.e. the amplitude was shifted slightly higher each breathing cycle. 2) Reproducibility: 1.36±0.02 cm. 3) Transponder placement sensitivity: the amplitudes were 1.55 cm at 14° vs. 1.35 cm at 0°. Conclusion: The surface beacon transponder appears to be relatively stable and reproducible. More study is needed to confirm the baseline drift. It is important to align the transponder to the lasers, and users should be cautious about the possible amplitude change due to transponder yaws.

SU‐FF‐J‐119: Respiratory Gating with Gantry Mounted Fluoroscopic Imaging

Purpose: To perform respiratory‐gated treatment based on the position of implanted markers in fluoroscopy using a gantry mounted x‐ray imaging system. Method and Material: We have designed hardware and software capable of gated treatment using the position of implanted markers. The system tracks the position of the marker in real‐time using fluoroscopic imaging. Tracking can be done in a single image, for 2D position information, or can be done simultaneously in a pair of orthogonal images, for 3D position information. When the marker is in the treatment window, the linear accelerator is signaled to deliver the beam. A live display of the fluoroscopy is used to initiate tracking, and to verify tracking and gating operation. Results: Gated treatment was performed on a moving phantom, with 3 cm peak‐to‐peak motion and a 4 mm gating window for internal motion. Fluoroscopy was acquired at a rate of 7.5 frames per second. The system latency from image acquisition to gating was roughly estimated to be approximately 50 ms. Gating operation was tested by delivering 4×4 cm open fields, and tracking the position of a 2mm steel marker in fluoroscopy. This initial position of the marker was assigned interactively. Treatment was delivered successfully for each field, despite some image degradation due to scatter from the MV treatment beam. The dosimetry of the gated treatment was measured in film, and compares well with the non‐gated treatment of a static phantom. Conflict of Interest: Research sponsored by Varian Medical Systems.

Feasibility study of individualized optimal positioning selection for left‐sided whole breast radiotherapy: DIBH or prone

Abstract The deep inspiration breath hold (DIBH) and prone (P) position are two common heart‐sparing techniques for external‐beam radiation treatment of left‐sided breast cancer patients. Clinicians select the position that is deemed to be better for tissue sparing based on their experience. This approach, however, is not always optimum and consistent. In response to this, we develop a quantitative tool that predicts the optimal positioning for the sake of organs at risk (OAR) sparing. Sixteen left‐sided breast cancer patients were considered in the study, each received CT scans in the supine free breathing, supine DIBH, and prone positions. Treatment plans were generated for all positions. A patient was classified as DIBH or P using two different criteria: if that position yielded (1) lower heart dose, or (2) lower weighted OAR dose. Ten anatomical features were extracted from each patients data, followed by the principal component analysis. Sequential forward feature selection was implemented to identify features that give the best classification performance. Nine statistical models were then applied to predict the optimal positioning and were evaluated using stratified k‐fold cross‐validation, predictive accuracy and receiver operating characteristic (AUROC). For heart toxicity‐based classification, the support vector machine with radial basis function kernel yielded the highest accuracy (0.88) and AUROC (0.80). For OAR overall toxicities‐based classification, the quadratic discriminant analysis achieved the highest accuracy (0.90) and AUROC (0.84). For heart toxicity‐based classification, Breast volume and the distance between Heart and Breast were the most frequently selected features. For OAR overall toxicities‐based classification, Heart volume, Breast volume and the distance between ipsilateral lung and breast were frequently selected. Given the patient data considered in this study, the proposed statistical model is feasible to provide predictions for DIBH and prone position selection as well as indicate important clinical features that affect the position selection.

Effects of Irregular Respiratory Motion on the Positioning Accuracy of Moving Target with Free Breathing Cone-Beam Computerized Tomography

For positioning a moving target, a maximum intensity projection (MIP) or average intensity projection (AIP) image derived from 4DCT is often used as the reference image which is matched to free breathing cone-beam CT (FBCBCT) before treatment. This method can be highly accurate if the respiratory motion of the patient is stable. However, a patient’s breathing pattern is often irregular. The purpose of this study is to investigate the effects of irregular respiration on positioning accuracy for a moving target aligned with FBCBCT. Nine patients’ respiratory motion curves were selected to drive a Quasar motion phantom with one embedded cubic and two spherical targets. A 4DCT of the phantom was acquired on a CT scanner (Philips Brilliance 16) equipped with a Varian RPM system. The phase binned 4DCT images and the corresponding MIP and AIP images were transferred into Eclipse for analysis. FBCBCTs of the phantom driven by the same respiratory curves were also acquired on a Varian TrueBeam and fused such that both CBCT and MIP/AIP images share the same target zero positions. The sphere and cube volumes and centroid differences (alignment error) determined by MIP, AIP and FBCBCT images were calculated, respectively. Compared to the volume determined by MIP, the volumes of the cube, large sphere, and small sphere in AIP and FBCBCT images were smaller. The alignment errors for the cube, large sphere and small sphere with center to center matches between MIP and FBCBCT were 2.5 ± 1.8mm, 2.4±2.1 mm, and 3.8±2.8 mm, and the alignment errors between AIP and FBCBCT were 0.5±1.1mm, 0.3±0.8mm, and 1.8±2.0 mm, respectively. AIP images appear to be superior reference images to MIP images. However, irregular respiratory pattern could compromise the positioning accuracy, especially for smaller targets.