bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐J‐29: Automatic Image Registration Performance of Three IGRT Systems for Prostate Radiotherapy
Authors: Barber J , Sykes J , Holloway L , Thwaites D
Published: June 2015

Purpose:

To compare the performance of an automatic image registration algorithm on image sets collected on three commercial image guidance systems, and explore its relationship with imaging parameters such as dose and sharpness.

Methods:

Images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on the CBCT systems of Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings; and MVCT on a Tomotherapy Hi‐ART accelerator with a range of pitch. Using the 6D correlation ratio algorithm of XVI, each image was registered to a mask of the prostate volume with a 5 mm expansion. Registrations were repeated 100 times, with random initial offsets introduced to simulate daily matching. Residual registration errors were calculated by correcting for the initial phantom set‐up error. Automatic registration was also repeated after reconstructing images with different sharpness filters.

Results:

All three systems showed good registration performance, with residual translations <0.5mm (1σ) for typical clinical dose and reconstruction settings. Residual rotational error had larger range, with 0.8°, 1.2° and 1.9° for 1σ in XVI, OBI and Tomotherapy respectively. The registration accuracy of XVI images showed a strong dependence on imaging dose, particularly below 4mGy. No evidence of reduced performance was observed at the lowest dose settings for OBI and Tomotherapy, but these were above 4mGy. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 10% of registrations. Changing the sharpness of image reconstruction had no significant effect on registration performance.

Conclusions:

Using the present automatic image registration algorithm, all IGRT systems tested provided satisfactory registrations for clinical use, within a normal range of acquisition settings.
SU‐E‐J‐30: The Effect of Planning CT Slice Thickness On Evaluation of SRS Target Localization Accuracy
Authors: Briceno J , Li H , Huang Y , Wen N , Chetty I
Published: June 2015

Purpose:

To evaluate the effect of planning CT slice thickness on SRS target localization accuracy on Varian Edge SRS treatment platform.

Methods:

A metal BB of diameter 5 mm was inserted in a Rando head phantom. Planning CTs were scanned with 0.8, 2 and 3 mm slice thickness respectively. The center of BB was setup as isocenter and tattoos were marked on phantom surface. The phantom was initially aligned using laser and tattoos, then a CBCT was acquired and 6‐degree of freedom (DOF) image registration was performed based on bony anatomy. The 6D couch correction was applied. A verification CBCT was taken to evaluate couch corrections. Three orthogonal pairs of images (MV‐MV, KV‐KV and MVKV), were also taken to verify the position of the phantom using a 2D‐3D registration algorithm. Winston‐Lutz tests were taken at 12 combinations of gantry, collimator and couch angles using 1×1cm MLC aperture and 10mm circular cone.

Results:

The vector lengths of the residual error measured with verification CBCT were 0.3, 0.2 and 0.2 mm for the planning CT of 0.8, 2 and 3 mm slice thicknesses respectively. Residual setup error vector lengths for 0.8, 2, and 3 mm CT measured by orthogonal pair were as following: a) MV‐MV: 0.2, 0.5, 0.5mm; b) KV‐KV: 0.2, 0.3, 0.3mm; c)MV‐KV: 0.1, 0.6, 0.3mm respectively. The vector lengths for the Winston‐Lutz tests were: a) MLC: 0.55, 0.32, and 0.2mm; b) CONE: 0.16, 0.17, and 0.29mm for slice thickness of 0.8, 2, and 3mm respectively.

Conclusion:

The residual setup error in this study measured by the 2D‐3D algorithm was comparable to that of the 3D‐3D algorithm. The planning CT slice thickness in the range of 0.8 to 2 mm has no significant impact on the evaluation of the residual setup error and the Result of Winston‐Lutz test.
SU‐E‐J‐33: Comparison Between Soft Tissue Alignment and Bony Alignment for Pancreatic Cancer Radiotherapy
Authors: Suh Y , Crane C , Krishnan S , Das P , Koay E , Beddar S
Published: June 2015

Purpose

An IGRT modality for pancreatic cancer treatment with dose escalation at our institution is in‐room daily CT imaging. The purpose of this study is to assess the difference between soft tissue alignment and bony alignment for pancreatic tumor localization.

Methods

Eighteen patients with pancreatic tumors who underwent IMRT treatment with an inspiration breath‐hold technique between July 2012 and February 2015 are included in this study. Prior to each treatment, a CT scan was acquired. The CT image guidance started with auto‐alignment to either the bony anatomy (vertebral bodies) or fiducials (for the six patients with the stent in/near the tumor) and then, when necessary, manual adjustments were made based on soft tissue alignment using clinical software (CT‐Assisted Targeting system). The difference between soft tissue alignment and bony/fiducial alignment was evaluated.

Results

Of all 380 treatments, manual adjustment was made in 225 treatments, ranging from 11% (3 treatments out of 28) to 96% (27 treatments out of 28) per patient. The mean of the difference between soft tissue alignment and bony/fiducial alignment per patient ranged from −3.6 to 0.3 mm, −1.5 to 2.8 mm, and −3.3 to 3.4 mm in the AP, SI, and RL directions, respectively. The maximum difference over all treatments was −9.5, −14.6, and −14.6 mm in the AP, SI, and RL directions, respectively.

Conclusion

About 60% of the time, manual adjustment based on soft tissue alignment was required. The extent of manual adjustment was usually small but varied significantly from patient to patient. The ultimate goal of the IGRT modality using daily CT imaging is not to fully cover the target but to spare organs‐at‐risk as much as possible to avoid them moving into higher dose gradients than accepted in the treatment plan. To this end, manual adjustment based on soft tissue alignment is critically important.
SU‐E‐J‐36: Comparison of CBCT Image Quality for Manufacturer Default Imaging Modes
Authors: Nelson G
Published: June 2015

Purpose

CBCT is being increasingly used in patient setup for radiotherapy. Often the manufacturer default scan modes are used for performing these CBCT scans with the assumption that they are the best options. To quantitatively assess the image quality of these scan modes, all of the scan modes were tested as well as options with the reconstruction algorithm.

Methods

A CatPhan 504 phantom was scanned on a TrueBeam Linear Accelerator using the manufacturer scan modes (FSRT Head, Head, Image Gently, Pelvis, Pelvis Obese, Spotlight, & Thorax). The Head mode scan was then reconstructed multiple times with all filter options (Smooth, Standard, Sharp, & Ultra Sharp) and all Ring Suppression options (Disabled, Weak, Medium, & Strong). An open source ImageJ tool was created for analyzing the CatPhan 504 images.

Results

The MTF curve was primarily dictated by the voxel size and the filter used in the reconstruction algorithm. The filters also impact the image noise. The CNR was worst for the Image Gently mode, followed by FSRT Head and Head. The sharper the filter, the worse the CNR. HU varied significantly between scan modes. Pelvis Obese had lower than expected HU values than most while the Image Gently mode had higher than expected HU values. If a therapist tried to use preset window and level settings, they would not show the desired tissue for some scan modes.

Conclusion

Knowing the image quality of the set scan modes, will enable users to better optimize their setup CBCT. Evaluation of the scan mode image quality could improve setup efficiency and lead to better treatment outcomes.
SU‐E‐J‐38: Improved DRR Image Quality Using Polyetheretherketone (PEEK) Fiducial in Image Guided Radiotherapy (IGRT)
Authors: Shen S , Jacob R , Popple R , Duan J , Wu X , Cardan R , Brezovich I
Published: June 2015

Purpose

Fiducial‐based imaging is often used in IGRT. Traditional gold fiducial marker often has substantial reconstruction artifacts. These artifacts Result in poor image quality of DRR for online kV‐to‐DRR matching. This study evaluated the image quality of PEEK in DRR in static and moving phantom.

Methods

CT scan of the Gold and PEEK fiducial (both 1×3 mm) was acquired in a 22 cm cylindrical phantom filled with water. Image artifacts was evaluated with maximum CT value deviated from water due to artifacts; volume of artifacts in 10×10 cm in the center slice; maximum length of streak artifacts from the fiducial. DRR resolution were measured using FWHM and FWTM. 4DCT of PEEK fiducial was acquired with the phantom moving sinusoidally in superior‐inferior direction. Motion artifacts were assessed for various 4D phase angles.

Results

The maximum CT value deviation was −174 for Gold and −24 for PEEK. The volume of artifacts in a 10x10 cm 3 mm slice was 0.369 for Gold and 0.074 cm3 for PEEK. The maximum length of streak artifact was 80mm for Gold and 7 mm for PEEK. PEEK in DRR, FWHM was close to actual (1.0 mm for Gold and 1.1 mm for PEEK). FWTM was 1.8 mm for Gold and 1.3 mm for PEEK in DRR. Barrel motion artifact of PEEK fiducial was noticeable for free‐breathing scan. The apparent PEEK length due to residual motion was in close agreement with the calculated length (13 mm for 30–70 phase, 10 mm in 40–60 phase).

Conclusion

Streak artifacts on planning CT associated with use of gold fiducial can be significantly reduced by PEEK fiducial, while having adequate kV image contrast. DRR image resolution at FWTM was improved from 1.8 mm to 1.3 mm. Because of this improvement, we have been routinely use PEEK for liver IGRT.
SU‐E‐J‐40: Improving Uncertainty of Prostate Positioning by Using Implanted Fiducial Marker‐Based Hybrid Evaluation Combined with KV Portal Imaging and CBCT for Prostate IMRT
Authors: Hirose K , Sato M , Aoki M , Kawaguchi H , Akimoto H , Hatayama Y , Komai F , Sohma M , Obara H , Suzuki M , Takai Y
Published: June 2015

Purpose

The aim of this work was to present our single‐institution experience with fiducial marker‐based hybrid evaluation of prostate positioning combined with orthogonal kV portal image which inform the central position of prostate and CBCT which provides the information on localization of the peripheral structures.

Methods

Twenty‐five patients received prostate IMRT with daily localization by use of implanted fiducials. Orthogonal kV portal imaging and CBCT preceded all 977 treatments. After shifts in the AP, SI, and LR dimensions were made from kV imaging, following another shifts were made when more than 2‐mm prostate deviation as total sum of all dimensions were detected by CBCT. Post‐treatment kV imaging and CBCT were also obtained in 203 treatments (21%). Shifts between two techniques were analyzed, and compared by Bland‐Altman limits of agreement. Intrafraction motion and PTV margin were determined from shifts between pre‐ and post‐treatment in each technique.

Results

Pre‐treatment isocenter shift were made based on CBCT in addition to kV imaging in 315 (32%) treatments. Mean differences between kV imaging and CBCT in the AP/SI/LR were −0.10±0.93/− 0.06±0.91/0.15±0.51 mm. The correlation between these techniques was follows: R2 = 0.90, 0.93, 0.94. Bland‐Altman 95% confidence intervals were −1.7 to 1.9/−1.7 to 1.8/−1.2 to 0.8 mm, without significant trends. Intrafraction motion for prostate obtained from pre‐ and post‐CBCT were 0.00±0.15/0.02±1.49/0.15±0.64 mm, which were smaller than the results from kV imaging (0.42±1.90/0.12±1.98/0.26±0.80 mm). PTV margins calculated from the results of CBCT were also smaller than kV imaging (3.95 mm vs 5.15 mm, 4.02 mm vs 5.34 mm, 1.75 mm vs 2.18 mm).

Conclusion

Hybrid evaluation combined with identification of cranial and caudal edge of prostate by using CBCT compensates the uncertainty of prostate positioning originated from independent utilization of kV portal imaging, which enables to set PTV margins that reflect more realistic intrafraction organ motion.
SU‐E‐J‐43: Accuracy and Dynamic Range of Optical‐Surface‐Imaging (OSI)‐Based Spirometry
Authors: Huang H , Wei J , Chen Q , Gaebler C , Zatcky J , Mechalakos J , Li G
Published: June 2015

Purpose

To assess the accuracy of optical‐surface‐imaging (OSI)‐based spirometry for tidal volume (TV) measurement using a conventional spirometer and the usability under different breathing conditions.

Methods

Video‐based OSI with high‐speed image capture (HSIC) and a Bernoullitype spirometer were applied simultaneously to measure dynamic TVs of human subjects. Six healthy volunteers participated in an IRB protocol study. The subjects lied on 7.5°–10° upward‐tilted breast board while breathe through the spirometer. The entire torso was imaged to capture all respiration‐induced external motions. Five breathing exercises were performed, including free breathing (FB), belly breathing (BB), chest breathing (CB), deep breathing (DB), and breath holding (BH) with pseudo‐breathing motions. The HSIC data were acquired at 5Hz and 3D surfaces were reconstructed retrospectively. The volume of interest was manually delineated and applied to all surface images for batch‐mode computation. Dynamic TVs were calculated by subtracting the volume at full exhalation. The thorax and abdomen were separated and the breathing pattern (BPv=ΔVthorax/ΔVtorso) was calculated for each exercise. The spirometer was calibrated before experiments and baseline drifts were corrected by zeroing the background pressure initially and during involuntary breath hold, and resetting the baseline by linear regression of five consecutive fullexhalation points. The two TV datasets were compared.

Results

For FB, the average difference among all subjects is −3.2±6.0%. From BB, CB to DB, the discrepancies increase to −3.8±6.0%, −6.4±4.3%, and −1.1±14.0%, respectively. A near full range of BP (0.1–1.0) was observed. During BH, a constant TV was obtained despite the torso motion, conforming to volume conservation and suggesting diaphragmatic motion at the same TV.

Conclusion

The accuracy and dynamic range of OSI‐based spirometry has been assessed by using conventional spirometry as the reference among six healthy volunteers. The resultant discrepancy is acceptable (except DB), suggesting this new spirometry is of promising utility under common breathing conditions.

This study is in part supported by NIH (U54CA137788 and U54CA132378).
SU‐E‐J‐44: A Novel Approach to Quantify Patient Setup and Target Motion for Real‐Time Image‐Guided Radiotherapy (IGRT)
Authors: Li S , Charpentier P , Sayler E , Micaily B , Miyamoto C , Geng J
Published: June 2015

Purpose

Isocenter shifts and rotations to correct patient setup errors and organ motion cannot remedy some shape changes of large targets. We are investigating new methods in quantification of target deformation for realtime IGRT of breast and chest wall cancer.

Methods

Ninety‐five patients of breast or chest wall cancer were accrued in an IRB‐approved clinical trial of IGRT using 3D surface images acquired at daily setup and beam‐on time via an in‐room camera. Shifts and rotations relating to the planned reference surface were determined using iterative‐closest‐point alignment. Local surface displacements and target deformation are measured via a ray‐surface intersection and principal component analysis (PCA) of external surface, respectively. Isocenter shift, upper‐abdominal displacement, and vectors of the surface projected onto the two principal components, PC1 and PC2, were evaluated for sensitivity and accuracy in detection of target deformation. Setup errors for some deformed targets were estimated by superlatively registering target volume, inner surface, or external surface in weekly CBCT or these outlines on weekly EPI.

Results

Setup difference according to the inner‐surface, external surface, or target volume could be 1.5 cm. Video surface‐guided setup agreed with EPI results to within < 0.5 cm while CBCT results were sometimes (∼20%) different from that of EPI (>0.5 cm) due to target deformation for some large breasts and some chest walls undergoing deep‐breath‐hold irradiation. Square root of PC1 and PC2 is very sensitive to external surface deformation and irregular breathing.

Conclusion

PCA of external surfaces is quick and simple way to detect target deformation in IGRT of breast and chest wall cancer. Setup corrections based on the target volume, inner surface, and external surface could be significant different. Thus, checking of target shape changes is essential for accurate image‐guided patient setup and motion tracking of large deformable targets.

NIH grant for the first author as cionsultant and the last author as the PI
SU‐E‐J‐52: Decreasing Frequency of Performing TG‐142 Imaging QA – 5 Year Experience
Authors: Lin T , Ma C
Published: June 2015

Purpose

This study is an update to check if the frequency of imaging QA suggested by AAPM Task Group Report 142 (TG142) is necessary with our 5 year experience. TG142 presents recommendations for QA criteria of IGRT treatment. ACR has adopted it to be the requirements for any radiatiotherapy practices; however, we propose to reduce the frequency on image quality QA according to this 5 year study.Method and Materials: This study uses VarianIX2100 and Siemens Artiste Linacs to perform QAs on KV, MV, CBCT modalities. The QA was designed following under the recommendations of TG142. This study reports the daily imaging positioning/repositioning and imaging and treatment coordinate coincidence. QA results on kV, MV and CBCT from 4/7/2010∼3/11/15 are analyzed. KV, MV, CBCT images are taken with the Varian isocube localized at the isocenter. Digital graticule is used in the software to verify the isocenter position. CBCT images are taken with the cube placed at 1cm superior, lateral and anterior of the isocenter. In‐line fusion software is used to verify the contrived shift. Digital ruler provided at the on‐board‐imaging software or adaptive‐targeting software was used to measure the position differences. The position differences were recorded at AP,LR,SI directions.

Results

5 year records on kV, MV, CBCT show the shifts in all three directions are within the tolerance of 1mm suggested in TG142 for stereotactic radiation treatment(SRS/SRT). There is no occasion where shifts are outside 1mm tolerance.

Conclusions

The daily imaging QA suggested in TG142 is useful in ensuring the accuracy needed for SRS/SRT in IGRT. 5 year measurements presented suggest that decreasing the frequency of imaging QA may be acceptable, in particular for institutions reporting no violation of tolerance over periods of few years.
SU‐E‐J‐53: A Phantom Design to Assist Patient Position Verification System in Daily Image‐Guided RT and Comprehensive QA Measurements
Authors: Syh J , Wu H
Published: June 2015

Purpose

This study is to implement a homemade novel device with surface locking couch index to check daily radiograph (DR) function of adaPTInsight™, stereoscopic image guided system (SIGS), for proton therapy. The comprehensive daily QA checks of proton pencil beam output, field size, flatness and symmetry of spots and energy layers will be followed by using MatriXX dosimetry device.

Methods

The iBa MatriXX device was used to perform daily dosimetry which is also used to perform SIGS checks. A set of markers were attached to surface of MatriXX device in alignment of DRR of reconstructed CT images and daily DR. The novel device allows MatriXX to be fit into the cradle which was locked by couch index bars on couch surface. This will keep the MatriXX at same XY plane daily with exact coordinates. Couch height Z will be adjusted according to imaging to check isocenter‐laser coincidence accuracy.

Results

adaPTInsight™ provides robotic couch to move in 6‐degree coordinate system to align the dosimetry device to be within 1.0 mm / 1.0°. The daily constancy was tightened to be ± 0.5 mm / 0.3° compared to 1.0 mm / 1.0° before. For gantry at 0° and couch all 0° angles (@ Rt ARM 0 setting), offsets measured of the couch systems were ≤ 0.5° in roll, yaw and pitch dimensions.

Conclusion

Simplicity of novel device made daily image guided QA consistent with accuracy. The offset of the MatriXX isocenter‐laser coincident was reproducible. Such easy task not only speeds up the setup, but it increases confidence level in detailed daily comprehensive measurements. The total SIGS alignment time has been shortened with less setup error. This device will enhance our experiences for the future QA when cone beam CT imaging modality becomes available at proton therapy center.
SU‐E‐J‐113: Effects of Deformable Registration On First‐Order Texture Maps Calculated From Thoracic Lung CT Scans
Authors: Smith C , Cunliffe A , Al‐Hallaq H , Armato S
Published: June 2015

Purpose:

To determine the stability of eight first‐order texture features following the deformable registration of serial computed tomography (CT) scans.

Methods:

CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in‐house program, texture maps were calculated from 32×32‐pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lung were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow‐up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow‐up scans. Bland‐Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value.

Results:

Each patient's scans contained between 6.8–15.4 million ROIs. All of the first‐order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low.

Conclusion:

The eight first‐order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal‐spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient‐by‐patient basis.

SGA and HA receives royalties and licensing fees through the University of Chicago for computer‐aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R25GM109439.
SU‐E‐J‐116: Uncertainties Associated with Dose Summation of High‐Dose Rate Brachytherapy and Intensity Modulated Radiotherapy for Gynecological Cases
Authors: Kauweloa K , Bergamo A , Gutierrez A , Stathakis S , Mavroidis P , Papanikolaou N , Kirby N
Published: June 2015

Purpose:

Determining the cumulative dose distribution (CDD) for gynecological patients treated with both high‐dose rate (HDR) brachytherapy and intensity‐modulated radiotherapy (IMRT) is challenging. The purpose of this work is to study the uncertainty of performing this with a structure‐guided deformable (SGD) approach in Velocity.

Methods:

For SGD, the Hounsfield units inside specified contours are overridden to set uniform values. Deformable image registration (DIR) is the run on these process images, which forces the DIR to focus on these contour boundaries. 18 gynecological cancer patients were used in this study. The original bladder and rectum planning contours for these patients were used to drive the SGD. A second set of contours were made of the bladder by the same person with the intent of carefully making them completely consistent with each other. This second set was utilized to evaluate the spatial accuracy of the SGD. The determined spatial accuracy was then multiplied by the local dose gradient to determine a dose uncertainty associated with the SGD dose warping. The normal tissue complication probability (NTCP) was then calculated for each dose volume histogram (DVH) that included four different probabilistic uncertainties associated with the spatial errors (e.g., 68.3% and 95.4%).

Results:

The NTCPs for each DVH (e.g., NTCP_−95.4%, NTCP_−68.3%, NTCP_68.3%, NTCP_95.4%) differed amongst patients. All patients had an NTCP_−95.4% close to 0%, while NTCP_95.4% ranged from 0.67% to 100%. Nine patients had an NTCP_−95.4% less than 50% while the remaining nine patients had NTCP_95.4% greater than 50%.

Conclusion:

The uncertainty associated with this CDD technique renders a large NTCP uncertainty. Thus, it is currently not practical for clinical use. The two ways to improve this would be to use more precise contours to drive the SGD and to use a more accurate DIR algorithm.
SU‐E‐J‐124: 18F‐FDG PET Imaging to Improve RT Treatment Outcome for Locally Advanced Lung Cancer
Authors: Shusharina N , Khan F , Sharp G , Choi N
Published: June 2015

Purpose:

To investigate spatial correlation between high uptake regions of pre‐ and 10‐days‐post therapy1 8F‐FDG PET in recurrent lung cancer and to evaluate the feasibility of dose escalation boosting only regions with high FDG uptake identified on baseline PET.

Methods:

Nineteen patients with stages II– IV inoperable lung cancer were selected. Volumes of interest (VOI) on pre‐therapy FDG‐PET were defined using an isocontour at ≥50% of SUVmax. VOI of pre‐ and post‐therapy PET images were correlated for the extent of overlap. A highly optimized IMRT plan to 60 Gy prescribed to PTV defined on the planning CT was designed using clinical dose constraints for the organs at risk. A boost of 18 Gy was prescribed to the VOI defined on baseline PET. A composite plan of the total 78 Gy was compared with the base 60 Gy plan. Increases in dose to the lungs, spinal cord and heart were evaluated. IMRT boost plan was compared with proton RT and SBRT boost plans.

Results:

Overlap fraction of baseline PET VOI with the VOI on 10 days‐post therapy PET was 0.8 (95% CI: 0.7 – 0.9). Using baseline VOI as a boosting volume, dose could be escalated to 78 Gy for 15 patients without compromising the dose constraints. For 4 patients, the dose limiting factors were V20Gy and Dmean for the total lung, and Dmax for the spinal cord. An increase of the dose to OARs correlated significantly with the relative size of the boost volume.

Conclusion:

VOI defined on baseline 18F‐FDG PET by the SUVmax‐≥50% isocontour may be a biological target volume for escalated radiation dose. Dose escalation to this volume may provide improved tumor control without breaching predefined dose constraints for OARs. The best treatment outcome may be achieved with proton RT for large targets and with SBRT for small targets.
SU‐E‐J‐128: Two‐Stage Atlas Selection in Multi‐Atlas‐Based Image Segmentation
Authors: Zhao T , Ruan D
Published: June 2015

Purpose:

In the new era of big data, multi‐atlas‐based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two‐stage atlas selection scheme to achieve computational economy with performance guarantee.

Methods:

We develop a low‐cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full‐fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is first roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full‐fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability.

Results:

The performance and complexity of the proposed two‐stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one‐stage method with full‐fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one‐stage cost‐saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78).

Conclusion:

This work has developed a model‐guided two‐stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit in both complexity and performance is expected to be most pronounced with large‐scale heterogeneous data.
SU‐E‐J‐129: Atlas Development for Cardiac Automatic Contouring Using Multi‐Atlas Segmentation
Authors: Zhou R , Yang J , Pan T , Milgrom S , Pinnix C , Shi A , Yang J , Liu Y , Nguyen Q , Gomez D , Dabaja B , Balter P , Court L , Liao Z
Published: June 2015

Purpose:

To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity.

Methods:

Six thoracic cancer patients with both contrast and non‐contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non‐contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fused using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in‐house multi‐atlas segmentation. Using leave‐one‐out test, we generated auto‐segmented contours for each ROI and each patient. The auto‐segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD).

Results:

Inter‐observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto‐segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm.

Conclusion:

A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need for auto‐segmented contours of indistinguishable small structures.
SU‐E‐J‐130: Automating Liver Segmentation Via Combined Global and Local Optimization
Authors: Li Dengwang , Wang Jie , Kapp Daniel S. , Xing Lei
Published: June 2015

Purpose:

The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor.

Methods:

200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H‐PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate).

Results:

The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%.

Conclusion:

The proposed automatic segmentation method provides a sensible technique for segmentation of CT images.

This work is supported by NIH/NIBIB (1R01‐EB016777), National Natural Science Foundation of China (No.61471226 and No.61201441), Research funding from Shandong Province (No.BS2012DX038 and No.J12LN23), and Research funding from Jinan City (No.201401221 and No.20120109).
SU‐E‐J‐137: Image Registration Tool for Patient Setup in Korea Heavy Ion Medical Accelerator Center
Authors: Kim M , Cho W , Jung W , Suh T
Published: June 2015

Purpose:

A potential validation tool for compensating patient positioning error was developed using 2D/3D and 3D/3D image registration.

Methods:

For 2D/3D registration, digitally reconstructed radiography (DRR) and three‐dimensional computed tomography (3D‐CT) images were applied. The ray‐casting algorithm is the most straightforward method for generating DRR. We adopted the traditional ray‐casting method, which finds the intersections of a ray with all objects, voxels of the 3D‐CT volume in the scene. The similarity between the extracted DRR and orthogonal image was measured by using a normalized mutual information method. Two orthogonal images were acquired from a Cyber‐Knife system from the anterior‐posterior (AP) and right lateral (RL) views. The 3D‐CT and two orthogonal images of an anthropomorphic phantom and head and neck cancer patient were used in this study. For 3D/3D registration, planning CT and in‐room CT image were applied. After registration, the translation and rotation factors were calculated to position a couch to be movable in six dimensions.

Results:

Registration accuracies and average errors of 2.12 mm ± 0.50 mm for transformations and 1.23° ± 0.40° for rotations were acquired by 2D/3D registration using an anthropomorphic Alderson‐Rando phantom. In addition, registration accuracies and average errors of 0.90 mm ± 0.30 mm for transformations and 1.00° ± 0.2° for rotations were acquired using CT image sets.

Conclusion:

We demonstrated that this validation tool could compensate for patient positioning error. In addition, this research could be the fundamental step for compensating patient positioning error at the first Korea heavy‐ion medical accelerator treatment center.
SU‐E‐J‐142: Prompt Gamma Emission Measurements From a Passively Scattered Proton Beam On Targets Containing 16O, 12C and 14N
Authors: Jeyasugiththan J , Peterson S
Published: June 2015

Purpose:

To measure the prompt gamma emission from the important elements found in tissue (1 6O,1 2C and1 4N) in a clinical passive‐scatter treatment environment.

Methods:

The targets (composed of water, Perspex, graphite and liquid nitrogen) were irradiated with a 200 MeV passive‐scatter proton beam and the discrete prompt gamma energy spectra was detected by a high resolution 2′ × 2′ LaBr. detector. In order to reduce the high level of radiation produced by the beam line elements, the detector was surrounded by 10 cm of lead to attenuate the scattered gamma‐rays entering the detector with an extra 5 cm thick layer of lead added along the beam direction. A 10 cm thick collimator with a 5 cm × 10 cm rectangular opening was also used.

Results:

The prompt gamma peaks at 6.13 MeV and 4.44 MeV were clearly identified as a Result of the inelastic nuclear reaction between the protons and the 16O atoms found in the water target. The 6.13 MeV peak was 5% higher than the peak at 4.44 MeV for the water target. The 4.44 MeV peak was the only identified emission in the prompt gamma energy spectra from the graphite target (1 2C). The expected 2.313 MeV peak form the1 4N (liquid nitrogen target) was identified, but the other expected1 4N peaks could not be resolved.

Conclusion:

Prompt gamma measurements with a passive‐scatter proton beam are possible, but the presence of a high amount of background radiation from the patient final collimator presents a challenge at the treatment isocenter. The prominent prompt gamma peaks at 6.13 MeV and 4.44 MeV were identified from the water, Perspex and graphite targets. The prompt gammas from the liquid nitrogen target were difficult to see, but may not be significant in the in‐vivo verification process.
SU‐E‐J‐146: A Research of PET‐CT SUV Range for the Online Dose Verification in Carbon Ion Radiation Therapy
Authors: Sun L , Hu W , Moyers M , Zhao J , Hsi W
Published: June 2015

Purpose:

Positron‐emitting isotope distributions can be used for the image fusion of the carbon ion planning CT and online target verification PETCT, after radiation in the same decay period,the relationship between the same target volume and the SUV value of different every single fraction dose can be found,then the range of SUV for the radiation target could be decided.So this online range also can provide reference for the correlation and consistency in planning target dose verification and evaluation for the clinical trial.

Methods:

The Rando head phantom can be used as real body,the 10cc cube volume target contouring is done,beam ISO Center depth is 7.6cm and the 90 degree fixed carbon ion beams should be delivered in single fraction effective dose of 2.5GyE,5GyE and 8GyE.After irradiation,390 seconds later the 30 minutes PET‐CT scanning is performed,parameters are set to 50Kg virtual weight,0.05mCi activity.MIM Maestro is used for the image processing and fusion,five 16mm diameter SUV spheres have been chosen in the different direction in the target.The average SUV in target for different fraction dose can be found by software.

Results:

For 10cc volume target,390 seconds decay period,the Single fraction effective dose equal to 2.5Gy,Ethe SUV mean value is 3.42,the relative range is 1.72 to 6.83;Equal to 5GyE,SUV mean value is 9.946,the relative range is 7.016 to 12.54;Equal or above to 8GyE,SUV mean value is 20.496,the relative range is 11.16 to 34.73.

Conclusion:

Making an evaluation for accuracy of the dose distribution using the SUV range which is from the planning CT with after treatment online PET‐CT fusion for the normal single fraction carbon ion treatment is available.Even to the plan which single fraction dose is above 2GyE,in the condition of other parameters all the same,the SUV range is linearly dependent with single fraction dose,so this method also can be used in the hyper‐fraction treatment plan.
SU‐E‐J‐147: Monte Carlo Study of the Precision and Accuracy of Proton CT Reconstructed Relative Stopping Power Maps
Authors: Dedes G , Asano Y , Arbor N , Dauvergne D , Letang J , Testa E , Rit S , Parodi K
Published: June 2015

Purpose:

The quantification of the intrinsic performances of proton computed tomography (pCT) as a modality for treatment planning in proton therapy. The performance of an ideal pCT scanner is studied as a function of various parameters.

Methods:

Using GATE/Geant4, we simulated an ideal pCT scanner and scans of several cylindrical phantoms with various tissue equivalent inserts of different sizes. Insert materials were selected in order to be of clinical relevance. Tomographic images were reconstructed using a filtered backprojection algorithm taking into account the scattering of protons into the phantom. To quantify the performance of the ideal pCT scanner, we study the precision and the accuracy with respect to the theoretical relative stopping power ratios (RSP) values for different beam energies, imaging doses, insert sizes and detector positions. The planning range uncertainty resulting from the reconstructed RSP is also assessed by comparison with the range of the protons in the analytically simulated phantoms.

Results:

The results indicate that pCT can intrinsically achieve RSP resolution below 1%, for most examined tissues at beam energies below 300 MeV and for imaging doses around 1 mGy. RSP maps accuracy of less than 0.5 % is observed for most tissue types within the studied dose range (0.2–1.5 mGy). Finally, the uncertainty in the proton range due to the accuracy of the reconstructed RSP map is well below 1%.

Conclusion:

This work explores the intrinsic performance of pCT as an imaging modality for proton treatment planning. The obtained results show that under ideal conditions, 3D RSP maps can be reconstructed with an accuracy better than 1%. Hence, pCT is a promising candidate for reducing the range uncertainties introduced by the use of X‐ray CT alongside with a semiempirical calibration to RSP.Supported by the DFG Cluster of Excellence Munich‐Centre for Advanced Photonics (MAP)
SU‐E‐J‐155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality
Authors: Kiely J Blanco , Olszanski A , Both S , Low D , White B
Published: June 2015

Purpose:

To develop a quantitative decision making metric for automatically detecting irregular breathing using a large patient population that received phase‐sorted 4DCT.

Methods:

This study employed two patient cohorts. Cohort#1 contained 256 patients who received a phasesorted 4DCT. Cohort#2 contained 86 patients who received three weekly phase‐sorted 4DCT scans. A previously published technique used a single abdominal surrogate to calculate the ratio of extreme inhalation tidal volume to normal inhalation tidal volume, referred to as the κ metric. Since a single surrogate is standard for phase‐sorted 4DCT in radiation oncology clinical practice, tidal volume was not quantified. Without tidal volume, the absolute κ metric could not be determined, so a relative κ (κrel) metric was defined based on the measured surrogate amplitude instead of tidal volume. Receiver operator characteristic (ROC) curves were used to quantitatively determine the optimal cutoff value (jk) and efficiency cutoff value (τk) of κrel to automatically identify irregular breathing that would reduce the image quality of phase‐sorted 4DCT. Discriminatory accuracy (area under the ROC curve) of κrel was calculated by a trapezoidal numeric integration technique.

Results:

The discriminatory accuracy of ?rel was found to be 0.746. The key values of jk and tk were calculated to be 1.45 and 1.72 respectively. For values of ?rel such that jk≤κrel≤τk, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of κrel held consistent over 3 weeks for 73% of the patients in cohort#3.

Conclusion:

The decision making metric, ?rel, was shown to be an accurate classifier of irregular breathing patients in a large patient population. This work provided an automatic quantitative decision making metric to quickly and accurately assess the extent to which irregular breathing is occurring during phase‐sorted 4DCT.
SU‐E‐J‐156: Velocity‐Based Reference Scan Selection for Motion‐Model Error Reduction of 5DCT
Authors: Yang Liu (Lisa) , O'Connell Dylan , Dou Tai , Thomas David , Lamb James , Low Daniel A.
Published: June 2015

Purpose:

A recently proposed 5DCT protocol uses fast helical CT scans to model lung tissue motion that requires one of the scans to be used as a reference for deformable image registration. We have found that, while the CT scans are acquired using fast helical acquisition, residual motionartifacts remain for scans acquired during mid inspiration or exhalation. Selecting the scan with minimal motion artifacts as the reference scan will improve image registration and model accuracy.

Methods:

A free‐breathing patient was scanned 25 successive times in alternating directions with a Siemens 64‐slice CT scanner using a low‐mA fast‐helical protocol. Each of the 25 CT scans was successively used as the reference scan with the other 24 images registered to it. Motion‐model parameters were determined using the breathing‐motion model. Voxel specific tissue velocity maps were generated for each of the 25 scan based on the breathing amplitude surrogate and its time derivative. The resulting 24 model error maps were registered to the first CT scan for comparison. The relationships between regional motion‐model error, reference scan motion‐artifacts and tissue‐velocity were analyzed using linear‐regression.

Results:

Motion‐model errors were linearly correlated with reference scan blurring artifacts and doubling artifacts. The effects of blurring‐artifacts on motion model errors were stronger than doubling artifacts due to their impact on registration accuracy. Selecting the lowest tissue motion velocity scan as the reference scan decreased the regional motion model error by 33.67%±43.12%.

Conclusion:

Motion‐artifacts, especially blurring artifacts, that exist in the reference image induce motion model errors in 5DCT. A carefully selected reference scan based on the lowest tissue velocities can minimize the regional motion model error.
SU‐E‐J‐159: Analysis of Total Imaging Uncertainty in Respiratory‐Gated Radiotherapy
Authors: Suzuki J , Okuda T , Sakaino S , Yokota N
Published: June 2015

Purpose:

In respiratory‐gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory‐gated radiotherapy.

Methods:

Two factors of imaging uncertainties related to respiratory‐gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X‐ray image was acquired for image‐guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X‐ray image. The total imaging uncertainty was analyzed from these two factors.

Results:

In the CT image, the uncertainty between the target and cylindrical marker's actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm.

Conclusion:

The total imaging uncertainty in respiratory‐gated radiotherapy was clinically acceptable. However, an internal margin should be added to account for the total imaging uncertainty.