bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐J‐20: Evaluation of Image Qualities and Registration of Varian KV‐CBCT Images Reconstructed from the Reduced Number of Projections
Authors: Xu Heping
Published: June 2012

Purpose: To quantitatively investigate image qualities of the kilo‐voltage cone‐beam CT images reconstructed with reduced number of projections on the Varian OBI system. Evaluate the registration accuracy using those CBCT images against the reference CT images. Methods: CBCT images were obtained from Varian OBI system using standard dose head, pelvis and pelvis spotlight modes. CBCT reconstructions were performed with full, 1/2, 1/4, 1/6 and 1/8 of the full set of projections. Catphan® 504 phantom was used to evaluate high‐contrast spatial resolution, low‐contrast visibility and uniformity. Rando phantom was imaged for rigid registration study. Rando was set up on the linac couch deliberately shifted by 1cm in vertical, lateral, and longitudinal (no rotational) directions from the reference position. Automatch followed by manual adjustment was conducted 5 times to obtain the average shifts. The same method of analysis in the Rando study was used for the clinical registration study. One patient was imaged with pelvis mode and two patients were imaged with pelvis spotlight mode. Results: The Catphan study indicates that high‐contrast spatial resolution and uniformity are virtually not affected by the lowest projection‐number (1/8) reconstruction scheme. However low‐contrast visibility degrades when the projection number used for reconstruction is as low as 1/6. Rando study shows that registration accuracy can be achieved with images reconstructed with 1/6 of the full set of projections. Patient study shows similar results exhibited in Rando study. However, noisy images and streak artifacts are more pronounced with fewer projections (approximate 1/6), which decreases viewer's ability to visualize soft tissues in pelvic sites. Conclusions: This study shows that KV‐CBCT reconstructed with fewer number (approximately as low as 1/6) of regular projections can be used for registration against the reference CT. Although the results are encouraging, more clinical cases should be evaluated in the future. None
SU‐E‐J‐23: Prostate Bed Motion Study Using Surgical Clips Based on Daily CBCT
Authors: Song H , Salama J , Yoo D , Oleson J , Wu Q
Published: June 2012

Purpose: To study prostate‐bed motion after prostatectomy using the surgical clips as a surrogate. Methods: On the treatment planning CT, surgical clips within the PTV are identified and contoured. They are also identified and contoured in each daily CBCT. The center of mass (COM) coordinates for each clip within the native reference frame of each image set of CT and CBCT are recorded. Each CBCT (for daily image guidance) is registered to the planning CT based on the pelvic bony structure. The resulted 3D transformation matrix is used to convert the clip coordinates in the CBCT to the planning CT reference frame. Difference between the converted COM coordinates and the one in planning CT is taken as the rigid motion of the prostate bed relative to the pelvic bony structure during the course of radiation therapy. The motion data are then analyzed using statistical error analysis and quantified by the commonly defined M (average over all fractions and all patients), S (stdev of averages per patient, the systematic motion), and s (root mean square of stdev per patient, the random motion). Among a large pool of patients, seven patients were selected for this retrospective study, each with 3 to 11 identifiable clips and 17 to 26 CBCT sets. The total number of clips is 44 and total daily CBCT sets 160. Results: In the (right‐left, anterio‐posterior, foot‐head) directions, the M values are (0.2 mm, 0.4 mm, −0.6 mm), S (0.2, 2.5, 3.2), and s (1.7, 2.6, 2.1). Conclusions: Relative to the bony pelvic structure, the prostate bed motion characteristics are similar to that of intact prostate, as summarized in Table 2 of Rasch et al 2005 (‘Target Definition in Prostate, Head, and Neck.’ Semin Radiat Oncol 15:136–145).
SU‐E‐J‐28: Comparison of IGRT Shift Data Between Prostate Gland and Prostate Bed Obtained from Ct‐On‐Rails
Authors: Gao Z , Wong J , Merrick S , Karim M , Goldberg Y , Li M
Published: June 2012

Purpose: The daily shifts of prostate gland have been intensively reported in literatures. However, few papers reported daily shifts of prostate bed due to several practical difficulties (e.g. limited soft tissue contrast in MVCT and CBCT and significant deformation of prostate cavity). We have routinely performed IGRT for both prostate gland and bed with ct‐on‐rails, and the superior image quality allows us not only to differentiate both bony anatomy and soft tissue contrast of prostate gland and bed. In this study, we investigated if the shift of prostate bed is signifiant difference from that of prostate gland. Methods: we reviewed shift data of 50 prostate gland patients who underwent 43 fractions and 22 patients of prostatectomy underwent 37 fractions. In total 2150 CT scans were reviewed for prostate gland and 814 scans for prostate bed. Results: Of the reviewed 814 CT images from 22 prostate bed patients, the standard deviation of shift was found to be 5.9 mm in AP direction (ranges from −22.4mm to 22mm), 3.2mm in SI direction (ranges from −14mm to 14mm), and 4.1mm in lateral direction (ranges from −15mm to 22mm). Of the 2150 CT images of prostate gland from 50 patients, the standard deviation of the shift was found to be 5.4 mm in AP direction (−20mm to 18 mm), 5.0mm in SI direction (−26mm to 20mm), and 4.3mm in lateral direction (range from‐15 to 30mm). F tests of systematic /random shift distribution in three orthogonal directions between prostate gland and prostate bed were subsequently performed, it was found that the systematic shift in SI direction for prostate bed is smaller than for prostate gland (p=0.003). Conclusions: Our result suggests no significant difference existing in shift between prostate bed and gland. Therefore strategies for daily prostate gland motion can be directly applied to prostate bed.
SU‐E‐J‐31: Direct Point Dose Verification Using IGRT for Actual Beam Delivery
Authors: Matsubara K , Kohno R , Nishioka S , Shibuya T , Ariji T , Akimoto T , Saitoh H
Published: June 2012

Purpose: In radiation therapy, treatment planning for patients is performed using pre‐acquired CT images. However, many patients with head‐and‐neck (H&N) cancer have tumor shrinkage and/or weight loss during their treatment course. Daily positional error of patients also causes unexpected deviations from the planning. Thus, it is essential to evaluate actual delivered dose for accurate clinical dosimetric consequence. In this study, actual delivered dose for an H&N site was determined by direct point dose measurement with metal‐oxide‐semiconductor field‐effect transistor (MOSFET) detectors using IGRT procedure. We experimentally evaluated usefulness of the IGRT procedure for accurate irradiations. Methods: Treatment processes from planning to beam delivery were performed for an H&N site of an anthropomorphic phantom. The MOSFET detectors were fixed inside the phantom in advance. Then, the anthropomorphic phantom was immobilized with a mould and mask and scanned by simulation‐CT. Beam irradiation condition was field size of 12 cm × 12 cm, gantry angle of 0°, 90° and 330°, and 6 MV X‐ray. Dose distribution was calculated with superposition algorithm with 2 mm calculation grid. Before the dose measurement, the anthropomorphic phantom was positioned using a localization system of mega‐voltage cone‐beam CT (MVCBCT). The MOSFET detectors were exposed five times according to a treatment plan. Measured doses with the MOSFET detectors were compared with calculated doses. Results: Using the MVCBCT, the set‐up of the anthropomorphic phantom was achieved within 1 mm in all directions of anterior/posterior, left/right, and superior/inferior. The calculated doses agreed well to the measured doses within ±3% even in evaluated region with high dose gradient. Conclusions: The actual delivered dose for an H&N site of an anthropomorphic phantom was evaluated experimentally with the MOSFET detectors. The IGRT procedure was useful for accurate irradiations.
SU‐E‐J‐42: Motion Adaptive Image Filter for Low Dose X‐Ray Fluoroscopy in the Real‐Time Tumor‐Tracking Radiotherapy System
Authors: Miyamoto N , Ishikawa M , Sutherland K , Suzuki R , Matsuura T , Takao S , Toramatsu C , Nihongi H , Shimizu S , Onimaru R , Umegaki K , Shirato H
Published: June 2012

Purpose: In the real‐time tumor‐tracking radiotherapy system, fiducial markers are detected by X‐ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. Methods: A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. Results: In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. Conclusions: The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy.
SU‐E‐J‐45: Validation of the ExacTrac Virtual Isocenter Based Target Localization Method
Authors: Zhao B , Kim S , Wen N , Kim J , Glide‐Hurst C , Chetty I , Ryu S , Jin J
Published: June 2012

Purpose: With no stable landmarks available for localization, a ‘virtual isocenter’ “‘or surrogate landmark near the target’” can be used for image guidance. However, using a virtual isocenter in ExacTrac has not been thoroughly validated. This study evaluates its target localization accuracy and investigates the impact of two different couch correction sequences.Methods: A CT scan was acquired on an anthropomorphic thoracic phantom with a 2mm‐diameter ball bearing (BB) marker implanted in thelung region. A treatment plan was created with isocenter placed at the BB center, and exported to ExacTrac. In ExacTrac, a virtual isocenter wasplaced on a spine vertebral body where three translational shifts (8.8cm laterally, 1.5cm longitudinally and 6cm vertically) were present. A series ofcouch rotations (+/−3 degrees, 1 degree increment) was intentionally applied to simulate angular setup variations. For each rotation, two stereoscopic x‐rayimages were acquired and fused using the ExacTrac 6D registrationalgorithm. Calculated shifts were applied using two sequences: (1)automatic 5D corrections (three translations/two robotic couch rotations) followed by manual couch rotation; (2) manual couch rotation then automatic 5D corrections. After each ExacTrac localization, orthogonal (anterior‐posterior and right‐lateral) portal images were acquired to quantify BB center deviations from the radiation isocenter as an indicator of residual error. Results: Minimal difference between investigated table correction sequences was observed. Average translational deviations between the BB and radiation isocenter (mean+/−1SD) were 0.3+/−0.3mm and 1.0+/−0.2mm for lateral and vertical axis respectively. Longitudinally, the deviations were 0.8+/−0.4mm from the anterior‐posterior image and 0.1+/−0.3mm from the right‐lateral image. The systematic difference (0.7+/−0.1 mm) between thetwo may have been attributed to gantry sagging during rotation. Conclusions: ExacTrac system successfully corrected angular shifts using the virtual isocenter method in a rigid phantom setup. The sequence ofcouch correction did not influence the localization accuracy. Further patient study is warranted.
SU‐E‐J‐46: Use of Brainlab‐ExacTrac IGRT with Dot‐Decimal Electron Compensator(BolusECT) for Accurate Patient Positioning
Authors: Prabhu A , Saini D , Patadiya B , Shankar R , Garthwaite T
Published: June 2012

Purpose: To Validate Brainlab‐ExacTrac IGRT with Dot‐Decimal electron compensator(BolusECT) for accurate patient positioning. Methods: Dot‐Decimal electron compensators(BolusECT) are used to achieve conformal dose distributions and greater sparing to normal structures for cases with varying patient contours and treated with single electron beam.Setup for such patients is difficult to verify due to the small clearance between theelectron‐cone and bolus. Hence additional verification is needed for fast setup to avoid discomfort for the patient. In this study we have explored theuse of Brainlab‐ExacTrac IGRT system for such setups.A Preplan isrequired to construct the BolusECT and a post‐plan is used for verifying the treatment plan. Before the patient is scanned again with BolusECT for post‐plan, tungsten BBs were drilled in the Bolus at different depths and the holeswere filled with wax. Tungsten‐BBs have high density and avoid high cost ofgold seeds.A wax phantom and BolusECT were scanned with BBs and a plan was generated. The plan was send to ExacTrac for DRR‐generation.The Wax phantom with BolusECT was then set slightly off centered on thetreatment couch and the ExactTrac system was used to align the Phantom. The ExacTrac system was also tried on two patients for accurate setup. Results: The ExactTrac system correctly identified the tungsten‐BBs and aligned the phantom within +1mm. The SSD was then verified and checked with the planned SSD.The SSD was found to be within +0.5mm. In both patient setups the ExacTrac system gave Lateral, Longitudinal and Vertical Shifts within +1mm and the SSD was found to be within +0.3mm of the planned SSD. Conclusions: The BrainLab‐ ExacTrac IGRT system isan excellent,fast way of aligning the BolusECT. This avoids discomfort for patients by preventing longer setup times. Use of tungsten‐BBs lowers the cost compared to gold seeds. Phantom verification should be performed before implementing this system for actual patient use. The SSDs must be verified after setup.
SU‐E‐J‐52: Validation of 3D Structure Projection Onto 2D DRR in Commercial Treatment Planning Systems
Authors: Zhang L , Court L , Balter P , Dong L
Published: June 2012

Purpose: The use of structure overlay on setup DRRs can aid the image alignment procedure for daily image‐guided setup procedures. However, the accuracy of a 3D region‐of‐interest (ROI) projected on a 2D digitally reconstructed radiograph (DRR) has rarely been evaluated quantitatively. The goal of this study is to test the accuracy of two commercial treatment planning systems (TPS) in producing overlay structures on setup DRRs. Method and Materials: We designed a novel method to identify landmarks which were on the boundary of the projected ROI on a DRR. The 3D ROIvolume is composed of a stack of 2D curves. We first mathematically project each 2D curve onto a beams‐eye‐view (BEV) plane. Next, we detectthe boundary points of the projected curves. Those boundary points serve aslandmarks. Finally, we project the binary mask of the 3D ROI volume using ray tracing method onto the BEV plane. This projected binary mask is used to exclude the false landmarks. Once those landmarks are detected, wecompute the distance between the landmarks and ROI outlines from the TPS. Results: We applied our validation method to 13 ROIs from a lung patient and 4 simulated ROIs on 2 BEV DRRs for two different TPS (Eclipse and Pinnacle). Average distance between the landmarks and ROIoutlines was 0.5mm for both Eclipse and Pinnacle approaches, which is close to the pixel resolution of the DRR. The maximum distance andaverage maximum distance was 2mm and 1 mm, respectively, for both TPS.The maximum distance occurred at points where the ROI curve has a sharpchange between slices. Conclusion: The accuracy of Eclipse and Pinnacle ROI projection method seems to be acceptable to within 1mm althoughprojection error can be as large as 2mm when structure shape has a sharp variation from one slice to the next.
SU‐E‐J‐58: Patient‐Specific Biomechanical Head and Neck Models for Interfraction Dose Accumulation
Authors: Santhanam A , Ennis D , Low D , Kupelian P
Published: June 2012

Purpose: In this abstract, we discuss a biomechanical head and neck model that will be able to represent patient setup variations as well as physiologic changes and subsequently enable dose calculations on the deformed anatomy. Methods: We selected Multi Pose MRI as the imaging modality to aid in model development and validation. The MRI data allowed us to build a biomechanically predictive model that will enable accurate estimation of tumor position when seeded with CT data alone. The soft tissue contrast and lack of ionizing radiation when using MRI enabled us to acquire extensive imaging datasets with a suitable variety of head pose variations. These poses were selected to encompass the clinical positioning variations so that the resulting model will accurately reflect internal organ motion and deformation. All images were acquired using an 8‐channel, 1.5T research MRI system in radiology. The imaging volume extended from about T3(upper thoracic vertebrae) to the top of the head, thereby covering the entire head and neck. Model components included: muscles, skeletal bones, lymph nodes, fat tissues, and organs such as salivary glands, tendons, andligaments. At first, one MRI image dataset was selected as the reference image. The biometric properties (length, volume, mass, shape), hinge constraints of the bones, and the biomechanical properties of each of the anatomies were estimated using MRIs acquired at different head and neck poses. Results: The model's ability to represent different head and neck postures can be illustrated by observing the internal tissue deformations andthe model's ability to represent different postures. Conclusions: Results show that the biomechanical model was able to simulate different poses that may be exhibited during interfraction patient setup variations and intrafraction patient motion. Future work would focus on integrating dose calculations on the deforming model and validating the model deformations.
SU‐E‐J‐60: Comparison of CT‐On‐Rails and a 3D Surface Imaging System for Image Guided Pelvic Radiation Therapy for Both Supine and Prone Patient Positions
Authors: Zhao H , Wang B , Rassiah‐Szegedi P , Sarkar V , Huang Y , Szegedi M , Gonzalez V , Salter B
Published: June 2012

Purpose: We investigate the feasibility of using AlignRT for pelvic radiation image guidance. The uniqueness of our study is that all patients have multiple CT‐on‐rails (CTOR) scans to compare corresponding AlignRT images to. Methods: Ten patients receiving pelvic radiation were enrolled in this study. Two simulation CT scans were performed in supine and prone positions for each patient. Body surface contours were generated in treatment planning system and exported to AlignRT to serve as reference images. The patient was aligned to treatment isocenter with room lasers, and then scanned with both CTOR and AlignRT in both supine and prone positions. Image guidance shifts were calculated for both modalities by comparison to the simulation CT and the differences between them were analyzed. These procedures were performed for each patient once per week for five weeks. The average and maximum difference of displacement between AlignRT and CTOR were calculated for each patient. Results: For supine position, there are 4 patients who had the average difference of displacement between AlignRT and CTOR along any direction (vertical, longitudinal, and lateral) greater than 0.5cm, and 1 patient greater than 1cm. For prone position, there are 7 patients who had the average difference greater than 0.5cm, and 3 patients greater than 1cm. For supine position, there are 4 patients who had the maximum difference great than 1cm. For prone position, there are 9 patients who had the maximum difference greater than 1 cm. The difference of displacement between AlignRT and CTOR is greater for prone position than for supine position. Conclusions: AlignRT does not appear to be an advisable image guidance approach for pelvic radiation therapy for patients with either supine or prone position. There appears to be a potential for large alignment discrepancies (up to 2.25 cm) between AlignRT and CTOR.
SU‐E‐J‐62: Comparison of Brainlab ExacTrac, AlignRT, and CBCT Positional Accuracy for SRS Set‐Up on a TrueBeam STx
Authors: Pursley J , Sintay B , Terrell J , Wiant D
Published: June 2012

Purpose: To compare the ability of Brainlab ExacTrac (Brainlab AG, Feldkirchen, Germany) x‐ray (XRAY), Brainlab infrared array (IR), cone beam CT (CBCT), and AlignRT (VisionRT Ltd., London, UK) to accurately measure patient displacement during stereotactic radiosurgery (SRS) on a Varian TrueBeam STx (Varian Inc, Palo Alto, CA). Methods and Materials: A CT scan was obtained for a custom skull phantom placed in a Brainlab frameless SRS immobilization system with the Brainlab CT localizer box attached. A generic plan was created in Brainlab iPlan and sent to Brainlab ExacTrac, to AlignRT, and to the TrueBeam. The skull phantom was set‐up on the TrueBeam and positioned to isocenter using XRAY. Next, CBCT and IR were acquired and evaluated to determine baseline positions for these methods. A new AlignRT reference surface was acquired as baseline. The phantom was then displaced 2 mm in the vertical, lateral, and longitudinal dimensions using the TrueBeam couch (the couch tolerance is 0.1 mm in each dimension). New XRAY, IR, CBCT, and AlignRT data was acquired in this position. Results: Initially, all methods found that the phantom was positioned with < 0.3 mm accuracy. After the shiftes, XRAY suggested shifts were 2.0, 2,1, 1.8 mm in the vertical, longitudinal, and lateral dimensions, respectively. The IR shifts were 1.7, 2.6, 2.1 mm. The CBCT shifts were 1.8, 1.8, 2.1 mm. The AlignRT shifts were 2.2, 1.6, 1.4 mm. Conclusion: The internal XRAY and CBCT methods produced slightly better agreement with the table shifts. The external IR and AlignRT methods were less accurate, but still gave agreement of <= 0.6 mm. Note, the AlignRT cameras did not produce a clean surface off of the phantom. Improved accuracy is expected from a skin surface. This is preliminary work, more extensive study is needed to evaluate these methods.
SU‐E‐J‐63: Feasibility Study of Proton Digital Tomosynthesis in Proton Beam Therapy
Authors: Min B , Kwak J , Lee J , Cho S , Park S , Yoo S , Chung K , Cho S , Lim Y , Shin D , Lee S , Kim J
Published: June 2012

Purpose: We investigated the feasibility of proton tomosynthesis as daily positioning of patients and compared the results with photon tomosynthesis as an alternative to conventional portal imaging or on‐board cone‐beam computed tomography. Methods: Dedicated photon‐like proton beam using the passively scattered proton beams by the cyclotron was generated for proton imaging. The eleven projections were acquired over 30 degree with 3 degree increment in order to investigate the performance of proton tomosynthesis. The cylinder blocks and resolution phantom were used to evaluate imaging performance. Resolution phantom of a cylinder of diameter 12 cm was used to investigate the reconstructed imaging characteristics. Electron density cylinder blocks with diameter of 28 mm and height of 70 mm were employed to assess the imaging quality. The solid water, breast, bone, adipose, lung, muscle, and liver, which were tissue equivalent inserts, were positioned around the resolution phantom. The images were reconstructed by projection onto convex sets (POCS) algorithm and total variation minimization (TVM) methods. The Gafchromic EBT films were utilized for measuring the photon‐like proton beams as a proton detector. In addition, the photon tomosynthesis images were obtained for a comparison with proton tomosynthesis images. The same angular sampling data were acquired for both proton and photon tomosynthesis. Results: In the resolution phantom image obtained proton tomosynthesis, down to 1.6 mm diameter rods were resolved visually, although the separation between adjacent rods was less distinct. In contrast, down to 1.2 mm diameter rods were resolved visually in the reconstructed image obtained photon tomosynthesis. Both proton and photon tomosynthesis images were similar in intensities of different density blocks. Conclusions: Our results demonstrated that proton tomosynthesis could make it possible to provide comparable tomography imaging to photon tomosynthesis for positioning as determined by manual registration of high density materials.
SU‐E‐J‐66: Evaluation of Proton Induced X‐Ray Fluorescence from Gold Fiducial Markers for In‐Vivo Determination of Proton Range and Energy
Authors: Tonner Brian , Li Zuofeng , Tishler Derek
Published: June 2012

Purpose: To evaluate a method for in‐vivo determination of proton range and post‐Bragg peak straggling by detection of proton induced x‐ray fluorescence of markers placed at known locations. Methods: Therapeutic beams from the UF Proton Therapy Institute were used to excite proton‐induced x‐ray fluorescence emission (PIXE) from cylindrical pure gold fiducial markers. The markers were embedded in a homogeneous water phantom and PIXE was measured using NaI photodetectors with energy dispersive spectral analysis. The geometry of the phantom and marker placement was chosen to model parallel‐opposed beam treatment of prostate cancer by proton therapy. The fluorescence yield from these markers was further modeled using the GEANT4 Monte‐Carlo package with low‐energy corrections. Gold K and L shell fluorescence yield as determined by the GEANT4 simulations was verified quantitatively by comparison to measured Au yield at energies from 1 MeV to 68 MeV, and to semiempirical model calculations covering the energy range from 1 MeV to 15 MeV. Results: The Au K‐shell fluorescence cross section is significantly smaller thanthat of the L‐shell, but the higher yield of the L‐shell fluorescence isoffset by the larger absorption as the x‐ray exits the phantom. The overallrelative detection efficiency of K and L shell fluorescence depends on thedetails of the shape of the phantom and location of the marker. Acharacteristic shape of fluorescence yield as it depends on proton range isfound, which can be used to extract an in‐vivo PDD profile of a spread‐outBragg peak (SOBP). Conclusions: A combination of a specific protocol for delivering a SOBP, geometriclocation of fiducial markers from CT, and simultaneous detection of protoninduced x‐ray fluorescence, can determine the depth range of a primary protonbeam in‐vivo. The fluorescence yield as measured at the Proton Therapy Institute is easily distinguished from background radiation.
SU‐E‐J‐67: A Potential New Technique to Measure Respiratory Tidal Volume Using Optical Surface Imaging: A Geometric and Deformable Phantom Study
Authors: Li G , Li D , Cohen P , Ballangrud A , Rimner A , Yorke E , Mechalakos J , Amols H
Published: June 2012

Purpose: To develop a new method for accurate measurement of dynamic respiratory tidal volume, we investigate the feasibility of measuring torso volume change using optical surface imaging (OSI). Methods: Based on a validated volume conservation theory, the tidal volume is equal to the volume change of the torso during quiet respiration (Li et al, PMB, 54:1693, 2009). A clinical OSI system was employed to acquire surface images of seven geometric phantoms and two ‘deformable’ torso phantoms. The mesh surface images were converted into contours for volume calculation using a treatment planning system. For geometric phantoms, their volumes under the incomplete surface images were calculated with aid of their symmetry. The results were compared with theoretical calculation and water containment experiments. For deformable torso phantoms, we created volume‐controlled deformation stages by placing deformable PlayDoh (DPD) materials on top of rigid Rando/Thorax phantoms, mimicking respiration‐induced torso surface elevation and volume change. The volume difference under the surfaces with and without the DPD padding was calculated with aid of a common posterior line to enclose the region of interest. Three different volumes of DPD padding (>500cc) were mounted on the torso phantoms and CT scanned for volume measurements. Results: For geometric phantoms, the OSI measured volume had accuracy (±1s) of 0.0%±1.6% (vs. geometric volume calculation) and 0.6%±3.8% (vs. water containment experiment). For deformable torso phantoms, the volume change was measured using OSI with an accuracy of 1.5%±2.5% against the measured volume using CT imaging. Linear regression showed a one‐to‐one relationship between the OSI volumes and CT volumes with a slope of 1.003 (r2=0.999). Conclusions: The optical surface imaging system can accurately measure the volume of geometric phantoms and the volume change of deformable torso phantoms. The accuracy is about 3% against standard volume measurement methods. Further study on human subjects is under investigation. Memorial Sloan‐Kettering Cancer Center has a reserach agreement with Vision RT, Inc.
SU‐E‐J‐69: Development of an Ambiguity‐Free Optical Tracking System for SBRT
Authors: Yan G , Lu B , Mittauer K , Liu C , Li J
Published: June 2012

Purpose: Commercial optical tracking system such as BrainLab ExacTrac© suffers from ambiguous markers which can cause significant delay in patient treatment. We developed an ambiguity‐free optical tracking system for high precision SBRT. Methods: The optical tracking system consists of a pair of camera sensors, 4∼8 infra‐red (IR) reflective markers affixed on patient skin and in‐house developed software. We developed an effective algorithm to automatically eliminate ambiguous markers. A recursive backtracking algorithm was developed to build one‐to‐one correspondence between reference markers and optical markers. The algorithm was able to deal with missing, misplaced, or occluded markers by introducing ‘dummy’ markers. Isocenter displacements were calculated in six‐degree of freedom through rigid‐body registration between reference markers and optical markers. The system accuracy was evaluated with a pelvis phantom against cone beam CT (CBCT) and ExacTrac. The impact of number of markers on tracking accuracy was also evaluated. The performance of automatic ambiguity elimination was assessed with synthetic and clinic marker patterns. Results: Difference of isocenter displacement reported by our system and commercial systems (CBCT, ExacTrac) were within 0.5 mm/0.1o. Impact of number of markers on tracking accuracy in our phantom test was negligible with isocenter displacement varying within 0.2 mm/0.2o when number of markers varied from 4 to 8. The system successfully identified and eliminated ambiguous markers in both synthetic and clinic marker patterns. Conclusions: An accurate optical tracking system free of ambiguous markers was developed for patient positioning and monitoring in high precision SBRT. The developed algorithms to eliminate ambiguous markers and to handle missing, misplaced or occluded markers were effective and efficient.
SU‐E‐J‐73: Using Surface‐Based Imaging for Patient Identification
Authors: Sintay B , Wiant D
Published: June 2012

Purpose: A feasibility study to determine if daily surface‐based imaging can be used for patient identification with reliable accuracy. Methods: Three‐dimensional surface images were acquired using AlignRT (VisionRT Ltd., London, UK) prior to daily radiotherapy treatment for 12 breast cancer patients. These were compared retrospectively to body contours generated from computed tomography simulation (CT sim) scans. Two types of comparisons were made. The first compared the surface of each patient for all fractions of treatment. The second compared a random incorrect patient body contour for each patient in the study. The ‘surface statistic’ tool reveals the percentage of surface points within a threshold distance of 3mm. Results: Comparison of the patients' daily AlignRT images to the CT sim body contour showed similarity of the surfaces of 81.0% +/− 6.6% with a total range of 61.5–95.3%. This same comparison of the wrong patient's CT sim body contour to a random fraction of another patient's AlignRT image revealed similarity of the surfaces of 27.9% +/− 10.2% with a range of 6.7‐58.3%. A threshold of approximately 60% separates misidentification from correct identification in our limited study set. There was no overlap between the two groups in our test. However, we recognize that the two groups come close to the threshold value and could overlap in a larger study set. Conclusions: Using daily surface‐based imaging to identify patients is feasible with AlignRT using a surface statistic threshold of approximately 60%. This has the possibility of improving radiotherapy safety using existing image‐guided technology. Further study is needed to better understand the sensitivity and specificity of this tool for a larger patient population.
SU‐E‐J‐82: Improvement in Reproducibility of Lung Expansion Measures with Respiratory Effort Correction
Authors: Du K , Reinhardt J , Christensen G , Ding K , Cao K , Bayouth J
Published: June 2012

Purpose: Longitudinal measurements of pulmonary function must account for subject variation when assessing radiation‐induced changes. Previously, we reported intra‐subject reproducibility of Jacobian‐based measures of lung tissue expansion using repeat 4DCT scans prior to radiation therapy without correcting for differences in respiratory effort. In this study, we present two normalization schemes that correct ventilation images for variations in respiratory effort. Methods: Two repeat 4DCT image acquisitions were collected before treatment from seven patients. Using a tissue volume preserving deformable image registration algorithm, two Jacobian ventilation maps were computed from separate acquisitions. Two effort normalization strategies were investigated using intermediated inspiration phases upon the principles of equivalent tidal volume (ETV) and equivalent lung volume (ELV). Additional experiments were performed to verify the effectiveness of the ETV method. Scatter plots of two ventilation maps and statistical parameters of Jacobian ratio were compared before and after each effort correction approach. Results: The scatter plots of the ventilation maps show improvement in measurement reproducibility using either the ETV or ELV effort correction for all but one case. The one case that did not show improvement had a very similar lung volumes and tidal volumes in the two studies, so effort correction was unnecessary. The coefficient of variation (CV) of Jacobian ratio improved by 21±11 percent (mean±standard deviation) after ETV, and improved by 20±17 percent after ELV. Our experimental results on ETV show the decrease of tidal volume difference in two acquisitions improves reproducibility of lung expansion measures. Conclusions: ETV and ELV correction methods improve the reproducibility of pulmonary function measurements in subjects that have differences in respiratory effort in the baseline and followup scans. Additional work is needed to investigate whether ETV or ELV is more effective, and to develop alternate regional normalization schemes that can account for difference in lung expansion rates.
SU‐E‐J‐86: Free form Deformable Model Based on Multi‐Resolution B‐Spline Grid for Registration of 4D CT Images of Hepatocellular Carcinoma Patients
Authors: Wang H , Li D , Wang H , Yin Y , Gong G
Published: June 2012

Purpose: The breathing motion has a significant influence to radiation therapy of hepatocellular carcinoma patients, and the motions are irregular. We used deformable registration of four‐dimensional computed tomography (4D CT) data to eliminate breathing motion artifact to truly track the tumors' positions and shapes, and guide medical physicists to delineate the more accurate tumor targets for treatment planning. Methods: We collected 4D CT data of 8 hepatocellular carcinoma patients, 4D‐CT images were segmented into 10 serious CT images according the respiratory phase, and named CT0,CT10'¦CT90, and CT0 was at end inspiration, CT50 was at end expiration. We proposed the free form deformable (FFD) model based on multi‐resolution B‐spline grid registration method to the 4D CT data during a whole breathing cycle, and we used L‐BFGS to optimize system and multi‐resolution to pick up the registration speed and accuracy. In particular we defined the gross target volume of HCC with the help of iodipin on CT images which can verify the registration performance. We chose end‐exhale CT as the reference image. Results: We compared the floating images, the subtractions of floating images and reference image, the iodipin landmarks' positions and the multi‐informations between floatings image and reference image before and after registered to verify the registration performance. From the registered images, we can track the ‘trajectory’ of the tumors during a whole breathing cycle, and the average multi‐information improved 3.5% after registration between the two extreme phases. Conclusions: Wecan use this registration method to register the 4D CT data and use iodipin on CT images to define gross target volume to guide medical physicists delineating the more accurate tumor targets.
SU‐E‐J‐89: Deformable Registration Method Using B‐TPS in Radiotherapy
Authors: Xie Y
Published: June 2012

Purpose: A novel deformable registration method for four‐dimensional computed tomography (4DCT) images is developed in radiation therapy. Methods: The proposed method combines the thin plate spline (TPS) and B‐spline together to achieve high accuracy and high efficiency. The method consists of two steps. First, TPS is used as a global registration method to deform large unfit regions in the moving image to match counterpart in the reference image. Then B‐spline is used for local registration, the previous deformed moving image is further deformed to match the reference image more accurately. Results: Two clinical CT image sets, including one pair of lung and one pair of liver, are simulated using the proposed algorithm, which results in a tremendous improvement in both run‐time and registration quality, compared with the conventional methods solely using either TPS or B‐spline. Conclusions: The proposed method can combine the efficiency of TPS and the accuracy of B‐spline, performing good adaptively and robust in registration of clinical 4DCT image.
SU‐E‐J‐93: Fourier Transform‐Based Medical Image Registration
Authors: Luce J , James G , Hoggarth M , Lin J , Block A , Roeske J
Published: June 2012

Purpose: To evaluate the use of a Fast Fourier Transform (FFT) based pattern‐matching algorithm for two‐dimensional translational and rotational medical image registration. Methods: The FFT pattern matching algorithm is based on the Fourier shift theorem. Briefly, image registration is accomplished by obtaining the Fourier Transform (FT) of two images, taking the normalized cross‐correlation of the two FT, and performing an inverse FT on this correlation matrix. This results in a Dirchlet delta function that has a maximum value at a location corresponding to the translational shift between the two images. Rotational registration can also be achieved by performing this algorithm on the polar transformation of the FT images. The FT registration method was evaluated through the use of clinical images with induced translational and rotational shifts. Results: Over a range of induced shifts of +/−10 mm in both the x and y directions, and induced rotations of +/−10 degrees, all recovered rotations were within 0.1 degree of the induced rotation, and all recovered translations were within 0.5 mm of the induced translation. The computational time of the FT registration on a 1024×1024 image was approximately 2.23 sec. Conclusions: An FFT based image registration algorithm is computationally efficient and provides a high degree of accuracy for two dimensional image registrations. The FFT registration approach provides a distinct analytical solution and does not rely on iterative methods to converge on a solution. In addition, the discrete nature of the FFT means that the accuracy of the solution is directly related to the size of the pixels in the images. The equivalent of sub‐pixel registration can be achieved by simply resizing the image to a larger matrix (i.e. 512×512 to 1024×1024).
SU‐E‐J‐98: 3D Tracking of Interfraction Patient Setup Uncertainties Using Multiple Kinect Sensors
Authors: Santhanam A , Low D , Kupelian P
Published: June 2012

Purpose: On‐board optical 3D imaging enables measuring daily setup patient uncertainties without involving any additional imaging‐induced radiation dose to critical structures. We hypothesize that the tumor and normal organ deformation caused by routine patient head and neck misalignments can be determined by coupling a quantitative patient‐specific biomechanical model with quantitative skin surface 3D imaging. Methods: A set of 3D cameras are used to track the patient anatomy externally. One of the cameras employed a marker less face recognition and tracking for delineating the region of the patient's face. The location of the face was then shared among the camera controllers in real‐time and the anatomical contour that closely matches the face region is selected and integrated to form a single 3D anatomical representation. Patient surface aligning was performed between the patient's external surface obtained from a reference 3D anatomy (simulation CT, MRI, patient surface map from previous fraction) and the above‐mentioned camera system to quantify the daily patient setup variations. For each of the 3D patient surface, a point feature histogram (PFH) was first generated. Once the PFH descriptors were generated, a non‐rigid iterative closest point registration algorithm that minimizes the difference in the PFH descriptor aligns the patient surface to the reference 3D anatomy. Results: The proposed tracking system was able to track both the patient surface setup uncertainty and the internal anatomy when coupledwith a patient specific biomechanical head and neck model. Conclusions: A 3D head and neck tracking system that monitors the interfraction patient setup uncertainties in the head and neck cancer patient is presented. The aligning process was shown to perform for cases with and without the head immobilization system. The external patient surface manifold and the motion vectors will be coupled to align the biomechanical model using model‐guided techniques.
SU‐E‐J‐103: Characteristics of Bladder Wall Deformation as a Function of Bladder Filling
Authors: Xu H , Siebers J
Published: June 2012

Purpose: ICRU report 83 recommends delineation of the wall for hollow organs such as the bladder. For image guided radiotherapy, there is no guidance as to how to delineate deformed walls as the filling of hollow organs change. This work investigates characteristics of bladder wall deformation as a function of bladder filling in a controlled process. Methods: CT images of a fresh pig bladder are obtained in‐air with different bladder air fillings. A plastic hose inserted into and glued to the bladder neck forms an air‐tight seal for filling with a syringe. At each air‐filling level, a helical CT (90kV, 90mAs) of the bladder is obtained. The pixel size on all CT images is <0.5 mm. Images are imported into a commercial planning system for delineation and statistical evaluation. Bladder walls at each filling status are auto‐contoured, then edited for quality assurance slice by slice. The auto‐contouring threshold is selected to obtain consistent volumes of the resulting region‐of‐interest at each filling status. Results: When the bladder wall interior volume increases by 360 cm3 from injecting air, the wall thickness decreases from 2.9 mm to 1.2 mm. The decrease in wall thickness is accompanied by a decrease in the wall CT number. Conclusions: For a pig bladder, the wall thickness decreases with increased air filling. The CT number (hence apparent density) of the volume decreases as the bladder expands. Further investigation is ongoing to determine if the apparent density decrease is real, due to CT reconstruction, or due to the bladder being in an air, rather than liquid environment. Characterization of hollow organ wall thickness variations may be important for image guided radiation therapy and organ wall dose evaluation. Support: P01CA116602
SU‐E‐J‐105: Evaluating Auto‐Contouring of Prostate KV Conebeam CTs
Authors: Godley A , Olsen L Sheplan , Stephans K
Published: June 2012

Purpose: Auto‐contouring of daily kV conebeam CTs (kVCBCT) is critical for online adaptive radiotherapy. We surveyed a set of geometric and dosimetric measures to determine which best assess the suitability of kVCBCT contouring algorithms for use in prostate region adaptive planning. Methods: Six patients with daily kVCBCT undergoing IMRT of the prostate to 78 Gy were selected. Dose was recalculated with patient density forced to water. Contours were generated on nine kVCBCT for each patient using ABAS (Elekta Ltd.) and also by a physician. The prostate mean dose, D100, D98, where determined and V70 (% and cc) and mean dose for the bladder and rectum for both physician and auto contours. The Dice's Coefficient (DC) was calculated between auto and physician contours, as well as a restricted DC (rDC) which combines geometric and dosimetric information by comparing only the volume within a high dose region. Results: Prostate accuracy can only be discerned with D100, additionally there is no correlation (R2=0.036) between D100 and DC. For all organs, mean dose does not reflect contour suitability. There is large variation in V70 (% and cc) for rectum and bladder, implying V70 is a sensitive indicator of contour suitability. There is however no correlation of V70 with DC. A dose region (>57 Gy) to calculate rDC was chosen to provided optimal correlation (R2>0.81) to V70 (% and cc, rectum and bladder). Conclusions: V70 for rectum and bladder shows the most sensitivity to contour suitability, by concentrating on where accuracy is most vital. Prostate contouring is less critical due to treatment margins, D100 provides the most discerning metric. DC and mean dose are not useable. In lieu of V70, rDC could be used. The rDC can be approximated by limiting to within 2–3 cm of the prostate contour, alleviating the need to calculate dose. A research version of ABAS was provided by Elekta.