bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐I‐82: Imaging of Gamma Emission Near and Above the Operational Limit of a SPECT Scanner
Authors: Pelletier C , Jung J
Published: July 2013

Purpose: To investigate the imaging of gamma emissions near the operational limit of a clinical SPECT scanner and determine whether higher energy gamma imaging is possible using a clinical scanner with no modifications. Methods: :A Philips BrightView SPECT scanner is used for this investigation. The system acquisition software imposes a maximum energy level of 960 keV. In order to investigate system response near this limit both simulations and clinical scans are performed. Gate 6.1 is used to simulate the system response to Europium‐152 (Eu‐152), a readily available gamma source with several high‐energy gamma emissions. Simulations are validated using clinical scans of a Eu‐152 source with a 700 keV to 960 keV window. In this energy range two major gamma emissions, 779 keV and 867 keV, are present. In addition, simulations of a high‐energy (1.575 MeV) gamma emitter, Prasodymium‐142 (Pr‐142) are performed to determine if the NaI crystal is sufficient to image gamma emissions at this energy. Results: Clinical measurements of Eu‐152 show a FWHM of 14.0mm in this energy range. Simulated spectra of Eu‐152 matches the measured spectra well, with a FWHM of 16.1mm. In addition, simulation of Pr‐142 shows a clear photopeak in the detected spectrum at 1.575 MeV. This indicates the NaI crystal is sufficient for full absorption at this energy level. Conclusion: This work indicates that the BrightView SPECT scanner has the potential to image high energy gamma. Simulations and clinical scans show the system is sufficient up to the maximum allowed acquisition energy. Simulation of Pr‐142 shows the scanner is capable of imaging gamma up above 1.575 MeV, though acquisition software does not currently allow clinical validation. Additional research needs to be done to determine if there is the potential to overcome the software imposed maximum energy level, and if so, validation of the imaging of Pr‐142 will be performed.
SU‐E‐I‐84: Comparing the Accuracy of the Bilateral Filter and Gaussian Filter for PET Image Post‐Processing Through a Phantom Study
Authors: Wu X , Jani S , Dahlbom M , Low D , Lamb J
Published: July 2013

Purpose: To compare the accuracy of an edge‐preserving filter to the standard Gaussian filter for PET image post‐processing through a phantom study. Methods: A phantom was used, consisting of four different spheres (diameter 1–4 cm, filled with a solution of 11‐C) that were mounted inside an acrylic cylinder (filled with a solution of 18‐FDG) to generate a time‐varying signal to background ratio (SBR). To mimic lung and liver lesions, SBRs were chosen to range from 2 to 30 and 2 to 5, respectively. The edge‐preserving filter used was the bilateral filter, which weights pixels based on both spatial distance and intensity difference. Reconstructed 3D‐PET images were separately smoothed with the bilateral filter and Gaussian filter. A commercially available gradient‐based technique was used to segment images and measure sphere volumes. Results were evaluated by the ratio of measured to true volume (RMT) of spheres. Paired two‐tailed t‐tests were applied to test for statistical significance. Results: In the lung case, RMT differences were not statistically significant across all sphere sizes. In the liver case, statistically significant differences were obtained for the 3 cm and 4 cm spheres, with average RMTs of 1.14 (bilateral) and 1.11 (Gaussian). However, these differences did not amount to a clinically significant level. For the 2 cm sphere, the differences were not statistically significant; for the 1 cm sphere, RMT differences were statistically, and potentially clinically, significant: 0.66 (bilateral) vs. 1.31 (Gaussian). However, it should be noted that volume segmentation of the 1 cm sphere was not fully reproducible on a case‐by‐case basis. Conclusion: This work indicates that the bilateral filter has a comparable accuracy to the Gaussian filter in volume measurements of 3D‐PET images. The commercially available gradient‐based segmentation algorithm is reasonably correct for spheres greater than 2 cm, but further studies are needed for smaller spheres. NIH R01 CA096679
SU‐E‐I‐91: The Role of Diagnostic Reference Levels in the Optimization of Patient Protection
Authors: Le Heron J , Borras C
Published: July 2013

Purpose: The concept of Diagnostic Reference Levels (DRLs) has been around for over 20 years and is part of the regulatory framework of many countries. The International Basic Safety Standards (BSS) requires both the establishment and the use of DRLs for imaging procedures. However, the level of implementation around the world varies considerably, with many countries yet to establish DRLs for common procedures. This paper discusses the current experiences with DRLs and their strengths and limitations.Method and Materials: The published experiences of several countries are analyzed and discussed. Points considered include whether there is a need for strict criteria for patient selection or not, whether clinical purpose must be considered or whether body habitus is sufficient, whether DRLs should be set according to the technology used or not, and whether there is a role for international DRLs. Results: Countries that have had several cycles of DRLs have clearly demonstrated their effectiveness in optimization of protection. The initially held belief that the weight of patients included in samples needed to be carefully controlled may not be strictly necessary. DRL values should be based on the then current practice in a given country, and a priori, encompass all technologies and techniques in use. While clinical purpose ultimately determines the signal to noise ratio needed for imaging, for the purposes of DRLs as a blunt tool for identifying outliers, perhaps body habitus based DRLs are sufficient. Impediments to the establishment and use of DRLs include lack of resources, e.g. personnel, dosimeters, and custodians for a national patient dose database. Conclusion: DRLs are an important tool for optimization of protection, and the level of implementation around the world needs to improve. However they are not the only tool for optimization and parallel initiatives need to take place.
SU‐E‐I‐98: Novel Method for Proton Radiography Using Plastic Scintillation Plate and Beam Energy Modulation Water Phantom
Authors: Park S , Jeong C , Kang D , Cho S , Shin J , Jeong J , Shin D , Lim Y
Published: July 2013

Purpose: The purpose of this study is to present the experimental evaluation and quantification of proton radiography using plastic scintillation plate and beam energy modulation (BEM) water phantom. Methods: Using the newly designed water phantom, proton beam energy was modulated by controlling water depth horizontally. Modulated proton beam which passed through water phantom was measured by dose‐measurement system which consists of a plastic scintillation plate, a mirror and a CCD camera in a dark box. A range compensator (RC) was positioned between BEM water phantom and scintillation plate for proton radiography. While a proton beam which has 15 cm range in water was being irradiated on RC, water depth is controlled from 71 to 170 mm in 1 mm increment and radiographs of RC on a scintillation plate were saved in every 1 mm increment using a dose‐measurement system. One hundred images were stacked and the position of Bragg peak was found along the stack order. The same radiograph procedure was performed without RC in order to calculate the depth of RC by subtracting the position index of Bragg peak between radiograph of RC and background. This difference was divided by water equivalent thickness value of RC material and then measured depth of RC was compared to plan data, quantifying the precision with the mean absolute depth difference (MADD) and the standard deviation (SD). Results: The MADD and the SD over the entire areas of RC was calculated as 0.62 mm and 0.67 mm respectively. MADD and SD precisions over chosen flat regions were less than 0.54 mm and 0.25 mm. Conclusion: Good image quality with high precision of depth measurement was observed by our proton radiography system. These system can also be used as a 3D dosimetry tool. This study was supported by funds from research projects of the National Cancer Center of Korea (nos. NCC 1210210) and National Research Foundation of Korea (K1A3A1A21 2010 0026071).
SU‐E‐J‐22: Implementation and Validation of a 2D‐3D Rigid Registration Algorithm for Proton Gantry and Stereotactic Radiosurgery Systems
Authors: Zhu M , Warmerdam G , Steininger P , Neuner M , Sharp G , Shih H , Winey B
Published: July 2013

Purpose: To implement and validate the accuracy of an intensity‐based 2D to 3D rigid registration algorithm for proton treatment systems. Methods: A 2D‐3D rigid registration algorithm (REG23) was previously validated for linac machines. We adapted REG23 for use in both gantry‐based and Stereotactic Alignment in Radiosurgery (STAR) proton treatment systems. REG23 registration was run on NVIDIA Quadra600 GPU card using NCC metrics and AMOEBA optimizer and validated using dual orthogonal kV images acquired during cranial target treatments: 66 fractions to 7 patients in gantry system and 135 fractions to 9 patients in STAR. Rectangle ROIs covering the whole region superior to the base‐of‐skull were used for REG23 registration and the accuracy was evaluated using clinical utilized fiducial‐based 2D‐3D ray back‐projection rigid registration as the baseline. Results: For the gantry system, the differences between REG23 and baseline were ‐ 0.01±0.63 mm, 0.43±0.61 mm, 0.12±0.60 mm in the left‐right, superior‐inferior, and anterior‐posterior directions; 0.15±0.44°, 0.11±0.23°, and 0.19±0.37° in pitch, roll, and yaw, respectively. The vector difference was 1.04±0.48 mm. For STAR system, the REG23 results were − 0.34±0.45 mm, −0.10±0.36 mm, −0.38±0.75 mm, −0.14±0.54°, 0.04±0.18°, and 0.03±0.35° different than the baseline in the left‐right, superior‐inferior, and anterior‐posterior directions, pitch, roll, and yaw. The vector difference was 0.93±0.53 mm. The time for REG23 automatic registration was 29.7±9.5 seconds. Conclusion: We demonstrated that the intensity based 2D‐3D rigid registration algorithm REG23 provided sub‐millimeter accuracy and better than 0.5° for both gantry‐based and STAR proton treatment systems for cranial patients. This accuracy is within patient setup tolerance for current fractionated proton treatment systems. Given its accuracy and efficiency, we believe REG23 has great potential for clinical utilization in proton radiation therapy by replacing the implanted fiducial or anatomic feature based patient setup method.

The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center.
SU‐E‐J‐26: Intra‐Fraction Motion Management for Radiosurgical Treatments of Trigeminal Neuralgia: Clinical Experience and Motion Analysis
Authors: Agazaryan N , Sharma A , Low D
Published: July 2013

Purpose: To evaluate the patient positioning and intra‐fraction motion management performance of an image‐guidance protocol established for radiosurgical treatments of trigeminal neuralgia patients. Specifically, to analyze patient data for the evaluation of current motion tolerance levels utilized for repositioning. Methods: NovalisTx equipped with Exactrac is used for stereoscopically positioning and treatments. Treatments are delivered with 4mm collimator using 7 equally spaced arcs that are 20 degrees apart and span 100 arc degrees each. Following initial Exactrac positioning, CBCT is obtained for independent confirmation of patient position. Patient is then stereoscopically imaged prior to the delivery of each arc and repositioned when 0.5mm translational tolerance in any direction is exceeded. Data from 48 patients with 607 image pairs has been analyzed. Results: The mean magnitude of 3D deviation was 0.64mm±0.12mm (range 0.07–2.74mm). With the current 0.50mm tolerance level for repositioning, patients exceeded the tolerance 51.4% of the time considering only images following an arc delivery. For those instances, patients were repositioned with a mean magnitude of 0.85mm±0.15mm. With 0.75mm and 1.00mm tolerance limits, the tolerance would have been exceeded only 21.5% and 6.6% of the time, with a mean magnitude of 1.08mm±0.21mm and 1.34mm±0.24mm respectively. Conclusion: Current 0.50mm tolerance level results in a significant number of patient repositions that Result from actual patient motion convolved with the accuracy and precision of the image analysis. Relaxing the re‐positioning tolerance could more selectively correct for actual patient motion at the expense of more variations in patient position. A 0.75mm would decrease the repositioning rate by approximately a factor of two; however, the permissible magnitude of motion will increase, leading to possible dosimetric consequences. Once treatment begins, there was no trend as to when patients exceeded the tolerance. Future analysis will include quantitative dosimetric consequences due to intra‐fraction motion.
SU‐E‐J‐27: Residual Interfraction Errors for Prostate SBRT with 6 Dimensional Couch Shifts Using Stereoscopic X‐Ray and Cone Beam CT
Authors: Li W , Stockham A , Stephans K , Xia P , Djemil T
Published: July 2013

Purpose: To evaluate residual interfraction alignment errors following prostate SBRT patient setup with stereoscopic kV‐X‐ray (Exactrac), kV‐CBCT, and a 6‐D robotic treatment couch (RTC). Methods: Data was reviewed from seven prostate cancer patients undergoing five‐fraction SBRT with pre‐and daily‐treatment endorectal balloon placement. Setup protocol, using stereoscopic X‐ray images, consisted of an initial RTC displacement based on bony registration (3 shifts, 3 rotations) followed by a RTC displacement based on implanted gold seeds (3 shifts only). Final image verification of the prostate position was performed with kV‐CBCT, upon which additional shifts prior to treatment delivery were permitted. The prostate (CTV), rectum wall and bladder were delineated on each daily CBCT and planning CT by the same physician. Shifts recorded at the time of treatment (X‐ray and X‐ray plus CBCT) were applied. Planning CT and CBCT contours were then superimposed and evaluated with dice similarity coefficient (DSC). Daily CTVs were also compared with the PTV (simulation CTV + 3mm). Paired student t test was used for statistical comparison. ResultsThe average of 96 stereoscopic X‐ray shifts were 0.96±4.08cm, 0.72±3.42cm and 0.58±3.64cm in the lateral, vertical and longitudinal directions, and 0.78±2.42°, 0.55±1.60° and 0.21±1.09° for the pitch, roll and yaw angles, respectively. CBCT‐guided shifts were performed in 25.7% of the fractions, with an average of 0.01±0.03cm, 0.23±0.21cm, and 0.14±0.26cm in the lateral, vertical, and longitudinal directions, respectively. With X‐ray only and X‐ray plus CBCT shifts, 95.1±3.7% and 96.2±3.2% (p=0.01) of daily CTVs were covered by PTV, respectively. The DSC were 77.1±5.8% and 79.2±4.6% for CTV (p<0.01), 40.1±12.8% and 42.1±12.7% for rectal wall (p=0.03), and 65.2±17.5% and 64.5±18.0% for bladder (p=0.34), respectively. Conclusion Interfraction error following Exactrac‐guided RTC shifts was <3mm, resulting in protocol‐appropriate CTV coverage at treatment based on a 3mm PTV margin. Further CBCT‐based shifts improve prostate alignment, but not significantly.
SU‐E‐J‐34: A Multi‐Modality Image Atlas for Transforming An MR Image Into a Pseudo CT Image for MRI‐Based IGRT Application
Authors: Zhang L , Michel K , Yang J , Rubinstein A , Kingsley C , Delacerda J , Balter P , Court L
Published: July 2013

Purpose: IGRT tools are most useful when registering similar datasets. In particular it is difficult to automatically register reference MR images with treatment CT or CBCT images. We proposed to create a pseudo CT from the reference MR images and to register the pseudo CT to the treatment CT. Methods: Two mice were sacrificed and immobilized on a rigid platform, and then imaged with small animal T1 and T2 weighted MRI and CBCT. Data from the first mouse was to develop an atlas and data from the 2nd mouse was to validate the system. To create a pseudo CT from an MRI, we first established the intensity conversion curve between the atlas CBCT and mouse MRI. This intensity conversion curve maps the intensity of fat tissue and soft tissue of the MRI onto the atlas CBCT intensity of the same tissue type. We used this conversion curve to create an intensity‐corrected MRI. Next, using global affine registration, local (bone‐by‐bone) affine registration, and deformable registration, we calculated the deformation field linking bony regions in the atlas MRI and the validation MRI. This deformation field was used to deform the CBCT image inside the atlas bone contour and to replace that section of the image in the validation mouse MRI. Results: The pseudo CT and validation CBCT are visually similar. Soft tissue in the pseudo CT is more recognizable and differentiable than in the validation CBCT. Contouring the bone structure on both images, the Dice index of the two bone structures was found to be 75%. The cross correlation of the image contents inside the fat‐soft tissue region between the pseudo CT and validation CBCT was 0.85. Conclusion: A novel approach was developed to create pseudo CT images from MR images that has potential applications in both small animal and human IGRT.
SU‐E‐J‐45: Verification of Beam‐Line Geometry of Truebeam Using MV‐EPID
Authors: Goddu S , Yaddanapudi S , Sun B , Mutic S
Published: July 2013

Purpose: Geometrical accuracy of beam‐line components of a linear‐accelerator (LINAC) is indispensible for quality of patient treatments. Positional reproducibility of the flattening filters (FF) may directly affect the beam flatness and symmetry while uncertainties in the imager position may directly impact target localization. In this study we have investigated the positional uncertainties of both of these components. Methods: Images of both flattened and flatness‐filter‐free (FFF) beams of 6 and10 MV were acquired using the megavoltage electronic portal imaging Device (MV‐EPID) over a period of time to investigate the positional uncertainties in the beam‐line geometry. Due to forward peaked nature of the MV beams FFF beams show a cone‐shaped dose distributions that was used determine the center of the X‐ray beams and used as reference points. Central portion of the flattened beams show the image of the FF. These circular objects were used to determine the center of the flatness‐filter with respect to the reference point. Imager reproducibility was also tested against the reference point which is the center of the source. Positional reproducibility of the FF and the imager were tracked over a period of two months. Results: Centers of both 6X and 10X FFs were systematically shifted by 2.2mm in X‐and ‐ 0.7 in Y‐directions. However, the shifts were magnified due to the fact that the FF being close to the MV‐source while the imager is far away (at 108cm) from the source. When corrected for this magnification, the real uncertainty in the FF position is approximately 0.2mm and ‐ 0.06 mm in X‐and Y‐directions. The imager positional reproducibility was found to be within ±1 pixel (<0.5mm). Conclusion: In this study we have shown a new method to detect positional uncertainty of the flatness‐filter and MV‐EPID. This methodology may be useful for QA of the LINACs. This project is supported by Varian Medical Systems
SU‐E‐J‐47: EPID Based Target Tracking During Intensity‐Modulated Radiation Therapy
Authors: Ma C , Xu Q , Tong X , Lin M , Chen X , Fan J , Chen L
Published: July 2013

Purpose: This work investigates the feasibility of using real‐time EPID images of the treatment fields acquired during IMRT for target localization and tracking. Methods: In this study, 35 patients treated with IMRT were retrospectively investigated. These patients were grouped as: prostate with lymph node (n=14), prostate without lymph node (n=17), and lung (n=4). For each patient, two to four fiducial markers were implanted inside the tumor. The DRR, which projects the patient anatomy and the fiducial marker at the EPID location, was reconstructed for each field. The MLC aperture of each control point was overlay on its corresponding DRR to evaluate the fractional time when the fiducial marker was seen on the EPID image. The probability of seeing at least one, two, three, or four fiducial markers during the treatment was recorded. Results: Our results show that for prostate IMRT patients without lymph nodes included in the target volume, the average probability of seeing at least one, two, three, and four fiducial markers during the treatment was 50% (35%–59%), 39% (23%– 51%), 24% (7%–38%), and 12% (4%–29%), respectively. For prostate IMRT patients with lymph nodes, the probability was 41% (24%–51%), 29% (12%– 42%), 15% (3%–24%), and 7% (4%–15%), respectively. For lung IMRT treatment, the average probability of seeing at least one fiducial marker was 34% (20%–52%). Conclusion: The continuous image acquisition from the EPID during IMRT treatment provides sufficient target movement information for real‐time target localization and intrafractional target motion correction for advanced radiotherapy treatments.
SU‐E‐J‐59: Visualizing Target Coverage by Iceball During MRI‐Guided Cryoablation
Authors: Dextraze K , Stafford R , Maier F
Published: July 2013

Purpose: This study sought to investigate a semi‐automated image registration technique for near real‐time visualization of iceball growth compared to planning target volume during MRI‐guided cryoablation of renal tumors. The goal was to accurately project the location of the iceball on the intra‐procedure planning image within 2mm during iceball monitoring. Methods: Development and testing were initiated via retrospective analysis of MRI‐guided renal cryoablations. Given an iceball image and pre‐ablation planning image from the same session, the algorithm performed the following: ‐ User placed seed points (n >= 5) to initialize the segmentation ‐ Segmentation was performed via a Random Walker algorithm and generated binary maps of the kidneys in both images and iceball in the 3D monitoring image (40 sec, 256×256×10 image stack). ‐ The kidney binary maps were resampled to 1mm slices and edge‐filtered prior to registration to improve registration accuracy. ‐ Registration via Fourier‐Mellin invariant matching and Phase‐Only Cross Correlation recovered rotation and translation transformations, which were then applied to the iceball mask. ‐ Registered iceball mask was projected onto the planning image.The algorithm was applied to artificial test objects with known transformations, to test objects with missing information to simulate iceball signal deficit, and to in vivo images of a cryoablation in humans. The Hausdorff distance (edge‐to‐edge distance) was used to quantitatively assess performance. Results: The approach was tested for artificial test objects and in‐vivo data sets. For the test objects, after registration the Hausdorff distance was < 1 pixel and remained accurate while >= 20% of the object was visible in the monitoring image. For the in‐vivo application, the Hausdorff distance was reduced from 14.4 pixels to 2.6 pixels (7.2 sec, 256×256×46 stack). Conclusion: This semi‐automated registration algorithm executed in less than one minute and was robust to missing information, demonstrating potential for clinical use in near real‐time visualization of tumor coverage during cryoablation. This research is supported in part by the MD Anderson Cancer Center Support Grant CA016672.
SU‐E‐J‐64: Landmark and ROI‐Enhancement‐Assisted Inter‐Patient Deformable Registration of 3D Bladder CT Images
Authors: wang Y , Sharp G , Jackson A , Saleh Z , Apte A , Veeraraghavan H , Deasy J
Published: July 2013

Purpose: Deformable image registration (DIR) of the pelvis, and in particular, the bladder, is known to be a difficult problem. We tested several pre‐processing strategies to improve the effectiveness of registration. Methods: We studied the use of automatically‐derived landmarks (LMs) and enhanced regions of interest (ROIs) to improve existing DIR algorithms, such as B‐Spline. The three outstanding LMs in the bladder are the two ureteral orifices and the internal urethral orifice.We used 10 pelvic CT image sets with bladders of different shapes (either full or empty). Interpatient registration was performed using four Methods: 1. B‐Spline, standard intensity‐based B‐Spline registration;2. LM B‐Spline, B‐Spline registration with forced matching of corresponding landmarks;3. ROI enhancement (ROI Enh) B‐Spline, signal intensity of the bladder ROI enhanced during pre‐processing to weigh the bladder more when registering; 4. LM + ROI Enh B‐Spline. Results: 1. B‐Spline DIR resulted in poor registration due to the variance of shapes and sizes among the bladders.2. LM B‐Spline achieved the least distance between landmarks, albeit with poor Dice coefficient values and high registration uncertainty. This method is reliant on the number of landmarks. 3. ROI Enh B‐Spline achieved a higher Dice coefficient and lower registration uncertainty but larger LM distance, when compared to LM B‐Spline. This method is most applicable where ROI volume boundary alignment is sufficient. 4. LM + ROI Enh B‐Spline achieved the best Result, when taking into account of all the quantitative and qualitative measurements. In general, we observed a tradeoff between achieving a reliable bladder registration and reliable registration of other parts, such as bones. Conclusion: We developed three methods to improve DIR by combining existing approaches. For DIR of bladders, the application of LMs plus ROI Enh B‐Spline achieved the best overall results, based on quantitative results and physician opinion.
SU‐E‐J‐86: A Deformable Image Registration Method for Dose Accumulation Between IMRT and HDR CT Images
Authors: Zhen X , Yan H , Hu J , Zhou L , Jia X , Jiang S , Cervino L
Published: July 2013

Purpose: To develop and validate a method to improve existing deformable image registration (DIR) algorithms for the registration between the high‐dose‐rate (HDR) brachytherapy CT image and the intensity‐modulated radiation therapy (IMRT) CT image of gynecologic cancer patients for dose accumulation. Methods: Deformable registration of brachytherapy CT images and external beam CT images is challenging due to the presence of the applicator in the brachytherapy image. We have developed a method to adapt DIR algorithms to this situation. A segmentation step is used to remove the applicator, which is imaged in the HDR CT image but not in the IMRT image, leaving an empty virtual cavity. An artificial deformation vector field is then generated in the tissue around the applicator to deflate this cavity toward the center at each slice and restore the vagina to a state without applicator. Different schemes are employed for two different registration tasks, i.e., deforming HDR CT image to IMRT CT image, or vice versa. In both cases, demons algorithm is used as the main DIR method to perform registration. The generated final deformation vector fields are used to deform the dose grid from one CT anatomy to another for dose accumulation. Results: Visual inspection of the DIR results indicates that our proposed method can suppress the interference of the applicator to the DIR algorithm, and successfully and accurately register the HDR and IMRT CT images as well as deforming and adding doses from both treatment modalities. Conclusion: We have developed a novel and robust DIR scheme that can perform registration between IMRT CT image and HDR CT image for dose accumulation, and can yield accurate registration results. This work was supported in part by the National Natural Science Foundation of China (no 30970866), Major Program of Natural Science Foundation of Guangdong Province of China (no 10251051501000007)
SU‐E‐J‐92: Multi‐Atlas Based Prostate Segmentation Guided by Partial Active Shape Model for CT Image with Gold Markers
Authors: Chai X , Xing L
Published: July 2013

Purpose: The gold markers implanted in prostate, which are used for IGRT, yield strong streak artifacts in planning CT image, which often causes a failure of automatic prostate segmentation. Our aim is to develop a novel method to utilize the partial active shape model to enable an automatic prostate segmentation on the CT image with strong streak metal artifacts. Methods: In the training stage, a groupwise surface correspondence was established via B‐spline deformable registration of binary structures. A joint active shape model was built for prostate, bladder and rectum together from 30 training CT images. In the segmentation stage, the gold markers on both atlas and target images were automatically detected. A mask was created to cover the region of gold markers and streak artifacts. By running the active shape model, the initial contours (from contours of atlas) was deformed to obtain the best fit with the edges of three pelvic organs in the target image, however the cost function is determined by matching only the parts of contours outside the mask based on gradient. The parts of contour inside the mask were purely estimated by the shape statistics. The segmentation was refined by a local profile based adjustment. Such segmentation was done 30 times using different training image as patient‐specific atlas, and the final Result was determined by a weighted majority voting algorithm. Results: The performance of the proposed method was evaluated for on independent dataset containing 5 CT images. The mean DSC overlap for prostate, bladder and rectum were 77.1%, 71.2% and 66.7%, respectively. The mean MAD for prostate, bladder and rectum were 3.1mm, 4.8mm and 4.6mm, respectively. Conclusion: The partial active shape model can very well estimate the contour passing the region of gold markers and streak artifacts from the rest part of contour and shape statistics.
SU‐E‐J‐94: Assessment of Dose Accumulation with Different Deformable Image Registration Algorithms for Image‐Guided Radiotherapy of Head and Neck Cancer
Authors: Dogan N , Sleeman W , Asher D , Fatyga M , Schutzer M , Song S
Published: July 2013

Purpose: Many automated Deformable Image Registration (DIR) validation methods are based on comparisons of deformed and observer contours. However, contour‐based comparisons are not sufficient to assess the dosimetric accuracy of a DIR algorithm. There is also potential for large dosimetric discrepancy when DVH accumulation is performed with different DIR algorithms. In this work, we compare the accumulated doses obtained with two different DIR algorithms in Head and Neck (H&N) cancer. Methods: Eight H&N patients who had weekly FBCT scans were included. Small Deformation Inverse‐Consistent Linear Elastic (SICLE) registration was used was used to estimate the displacement vector fields (DVFs) that simultaneously matched the CT intensity from the source (planning CT) image to weekly FBCT (target) images. In addition to intensity‐based matching (SICLE_I), contour‐based (SICLE_C) and intensity plus contour‐based (SICLE_I+C) matching was also performed. GTV, parotids, larynx and esophagus were used to drive SICLE_C registrations. The SICLE registrations were also compared to ITK Diffeomorphic Demons (ITKDD) registration algorithm. Finally, the accumulated dose was calculated for both adaptive and non‐adaptive scenarios and evaluated using dose‐volume constraints. Results: For non‐adaptive scenario, there was hardly any difference in the accumulated dose for target coverage using SICLE_I, SICLEC, SICLEI+C and ITKDD. Using adaptive replanning, however, PTV1 D98 improved by 1.5% using SICLEI+C. The maximum accumulated dose to the brainstem (D2) was also reduced by 12% by adaptive. On the average, the left parotid D50 also decreased by 32% using adaptive replanning. The maximum dose to the cord did not have a significant change using adaptive replanning‐based dose accumulation using all DIR algorithms. Conclusion: Intensity driven DIR algorithms used in this work produced fairly similar accumulated dose results in H&N cases. Overall, the dose accumulation based on adaptive replanning and utilizing intensity + contour driven registration resulted in better target coverage and critical structure sparing.
SU‐E‐J‐96: Does Combining Lung Ventilation Information to Perfusion Provide Any Additional Value for Treatment Planning?
Authors: Shi X , Diwanji T , Chen S , D' Souza W , Mistry N
Published: July 2013

Purpose: Recently, there have been efforts to incorporate regional lung function during treatment planning to limit radiation toxicity in the lungs. However, most efforts have focused on using either perfusion or ventilation alone in designing a function based treatment plan. There have been no reports whether combining the two metrics of lung function will add value. In this study, we test whether the two modalities provide redundant information by analyzing the distribution of perfusion in areas of low and high ventilation. Methods: Five patients with non‐small cell lung cancer (NSCLC) were recruited in a prospective study. Perfusion imaging was carried out using dynamic contrast enhanced MRI, and ventilation imaging was carried out using 4DCT. Anatomical and functional images were matched using an affine transform. The lung was segmented into regions of high and low ventilation using the threshold as the mean of lung ventilation. For both regions, the average pulmonary blood flow (PBF) value and the histogram of the PBF distribution were obtained and compared. Results: Visual spatial assessment of lung ventilation/perfusion images show areas of general agreement as expected (V/Q match). However, this is not true on a voxel‐by‐voxel assessment. For 4 out of 5 patients, the average PBF value is similar (0.123 vs 0.127; 0.049 vs 0.045; 0.062 vs 0.063; 0.091 vs 0.080) between areas of low and high ventilation. The remaining patient had only one functioning lung showing high correspondence between ventilation and perfusion. Conclusion: The necessity of including the ventilation information into functional treatment planning for patients with thoracic tumors was investigated. Early results suggest that for most cases combining ventilation and perfusion can provide additional insight for function based treatment planning. Further studies are needed to validate the findings from this preliminary study. Supported by Varian Medical Systems
SU‐E‐J‐103: Preliminary Evaluation of the Dosimetric Accuracy of the Cone‐Beam CT for the Cases with the Respiratory Motion
Authors: Kim D , Chung W , Lee Y
Published: July 2013

Purpose: Cone‐beam computed tomography (CBCT) images are currently used for patient positioning and adaptive dose calculation. However, it is still interesting to know how large the uncertainty of CBCT for the cases of respiratory motion. This study evaluated the uncertainty of the dose calculation based on CBCT for the cases of the respiratory motion. Methods: The geometrical and Hounsfield Unit (HU) differences estimated for CT and CBCT by using the caphan phantom (The Phantom Laboratory, Salem, NY). The ECLIPSE (Varian Medical Systems, Palo Alto, CA) radiation treatment planning system was used the dose calculations both of CT and CBCT image to compare the dose distributions. HU and dose calculation Result are compared between CT and CBCT to evaluate the effect by respiratory motion. Results: A geometrical uncertainties of CT and CBCT image of the catphan phantom were measured less than 0.15 cm. The CBCT gives a relatively large uncertainty, but absolute value of the uncertainty was not significant. The HU difference between CT and CBCT with standard‐dose‐head mode, high‐quality‐head mode, normal pelvis mode and low‐dose‐thorax mode measured as 31, 36, 23 and 33 HU. The dose calculation difference estimated as gamma (3%, 0.3 cm) as less than 1 in 99% of area. The HU difference with motion phantom was ranged from 5 to 450 HU. The dose calculation difference was estimated as gamma as less than 1 in 98% of area. Conclusion: We evaluated the uncertainty of CBCT based dose calculation for cases of the respiratory motion. The dosimetric uncertainty by motion is not significant in the case of the planning CT with 4DCT MIPS for whole phase, because of CBCT gives similar scanning Result of their scan time (about 1minute). On the other hand, it is expected that the CBCT base adaptive planning with respiratory gate treatment will give the relatively large uncertainty.
SU‐E‐J‐110: A Novel Metric to Evaluate Dose Deformation Error for Deformable Image Registration Algorithms
Authors: Surucu M , Roeske J
Published: July 2013

Purpose: To propose a novel metric to estimate the dosimetric error associated with deforming dose cloud using the mapping generated by deformable image registration (DIR). Methods: The increasing use of the DIR techniques in daily clinical practice requires extensive quality assurance. Deforming dose using the deformation map generated by deforming one CT image to the other is controversial. We propose here a novel method that can serve as a quantitative QA metric for DIR. First, various isodoses in the original dose are converted into structures. Then a deformation map is generated by deforming the original CT to new CT scan. The subsequent mapping is then used to deform the isodose level structures and dose into the new CT (Dose/structure/deform set). The same isodose levels in the deformed dose are converted into structures (Dose/deform/structure set). Then, differential dose surface histograms (DDSH) for each contour are generated using the deformed dose. The difference between the full‐width‐half‐maximum (FWHM) of the DDSHs at the corresponding isodose levels in both sets is defined as the dose deformation factor (DDF). For demonstration purposes, DDF was calculated at 14 different isodose levels for a representative head & neck and representative lung cancer patient that were rescanned during treatment. Results: The mean DDF was 0.38 Gy (range: 0.06 to 1.28Gy) for lung case and was 0.14 Gy (range: 0.02 to 0.85Gy) for the HN case. The maximum DDF values occurred at the 50% and 30% isodose levels for lung and HN cases, respectively. Conclusion: The proposed DDF can be used to evaluate the dose deformation error at different dose levels, independent of the deformation algorithm. The unit of the DDF is Gy and is useful in understanding the clinical effect of dose deformation at different isodose levels. This metric can be used to evaluate commercially available DIR software.
SU‐E‐J‐113: Interactive Contour Delineation and Refinement in Treatment Planning of Image Guided Radiation Therapy
Authors: Zhou W , Xie Y
Published: July 2013

Purpose: The accurate contour delineation of the target and/or organs at risk (OAR) is essential in treatment planning for image guided radiation therapy (IGRT). Although lots of automatic contour delineation approaches have been proposed, few of them can fulfill the necessities of applications in terms of accuracy and efficiency. Moreover, doctors would like to analyze the characteristics of regions of interests (ROI) and adjust contours manually during IGRT. The objective of this work is to develop an efficient tool of curve fitting for interactive contour delineation in IGRT. Methods: In this work, a novel approach of curve fitting for interactive contour delineation is proposed. Initially, a region which contains the interesting object is selected by mouse clicks and motion manually, then the program could automatically select important control points from the region, and the fitting method of Hermite cubic curves will be used to fit the control points. Hence, the optimized curve could be revised by moving its control points interactively. Finally, in order to improve the accuracy of contour delineation, the process of the curve refinement based on the maximum gradient magnitude is proposed. Points on the curve are automatically adjusted towards the positions with maximum gradient magnitude. Results: Hermite cubic curves exhibit superior efficiency for interactive segmentation and contour delineation of medical images, and the proposed scheme of the curve refinement greatly improves the final contour delineation to be subpixel level. Experimental results of real images in clinic applications demonstrate the efficiency, accuracy and robustness of the proposed process. Conclusion: We have designed a fast tool for interactive contour delineation in the application of IGRT. Experimental results show that Hermite cubic curves and the curve refinement based on the maximum gradient magnitude possess superior performance on the proposed platform in terms of accuracy, robustness and calculation time. This work is supported in part by grants from National Natural Science Foundation of China (NSFC: 81171402), NSFC Joint Research Fund for Overseas Research Chinese, Hong Kong and Macao Young Scholars (30928030), National Basic Research Program 973 (2010CB732606) from Ministry of Science and Technology of China, and Guangdong Innovative Research Team Program (No. 2011S013) of China.
SU‐E‐J‐114: Automated Processing of Sensitometry Data for Radiation Therapy Treatment Planner and Quality Assurance
Authors: Healy A , Levy J , Fredriksson J , Olafsdottir H , Kristinsson S , Dalbow G , Pawlicki T , Goodenough D
Published: July 2013

Automated Processing of Sensitometry Data for Radiation Therapy Treatment Planning and Quality AssurancePurpose: To investigate the efficacy of the calibration of the Hounsfield unit (HU) number to electron density (ED) for a range of traditional and experimental sensitometry targets and optimize the calibration for different sets of targets using automated image‐processing software. The possibility of calibration including virtualization of calcium‐based targets was studied. Methods: Ninety‐four scans of the Catphan 700 phantom were made on three different scanners using different filters, slice thicknesses, and energies. The phantom has ten sensitometry targets ranging in CT number from about ‐ 1000 to +1000 HU, and includes two calcium based bone analogs. For each scan, contrast scale and effective energy calculations were performed using the Image Owl Catphan QA automated image processing system. Separately, ten different calcium based targets of varying density and composition were manufactured and purchased. Theoretical calculations of linear attenuation coefficients of calcium and non‐calcium based targets were performed. Measured and theoretical CT#s were compared for all materials and HU vs. ED calibrations were performed. Results: Measured CT numbers can vary significantly (+/− 20 HU or more for some materials), depending on the scanner, filtration, slice thickness, and energy of the scan, but this variation in HU is not significant with respect to establishing HU vs. ED calibration within acceptable tolerances for planning purposes. The greatest variation in HU is seen in high density and low density materials. Contrast scale and HU vs. ED calibrations including a wide range of calcium‐based bone analogs proved to be robust. Conclusion: Automated image processing of well‐quantified sensitometry targets provides a potentially powerful tool for both accurate and consistent HU to ED calibration for radiation therapy treatment planning as well as statistical evaluation of scanner performance. This research was supported by Image Owl, Inc., and The Phantom Laboratory, Inc.
SU‐E‐J‐115: A Comparison of Methods for Functional Volume Delineation in PET: Simple Vs. Advanced Ones
Authors: Wang J , Li L , Lu W , Tan S
Published: July 2013

Purpose: To examine the importance of taking into account partial volume effect (PVE) for functional volume delineation in PET. Methods: Five acquisitions with different source‐to‐background ratio (SBR) from a PET phantom were used as test data in this study. The phantom contains six spheres of different diameters. A total of eight methods were used to delineate the spheres from each acquisition. Five among the eight are simple thresholding methods and the other three are advanced methods which were well‐known and widely used in the image processing community. The five thresholding methods are the dynamic thresholding, iterative thresholding, thresholding with 42% and 50% of the maximum uptake and the Otsu method. The three advanced methods are active contours without edges (CV), geodesic active contours (GAC) and max‐flow/min‐cut graph cut. The first two thresholding methods take into account the partial volume effect for the delineation while the other six do not. Robustness of different methods with respect to SBR and object size was evaluated using dice similarity index (DSI), classification error (CE) and volume error (VE). Results: The first two thresholding methods outperformed all the other six methods at all SBR levels and for all object sizes according to DSI, CE and VE. The first two thresholding methods were also less sensitive to the change of object size. Conclusion: It has been widely accepted that advanced methods should outperform simple thresholding ones for functional volume delineation in PET. The results indicated, however, that simple thresholding methods may not be inferior to advance methods once these thresholding methods take into account the PVE. It is thus important to consider the PVE for functional volume image delineation in PET.
SU‐E‐J‐116: Quantitative Study of 18F‐Fluorodeoxyglucose and 18F‐Fluorothymidine PET Characteristics in Esophageal Squamous Cell Carcinoma Staging
Authors: Ma C
Published: July 2013

Purpose: The aim of this study was to quantitatively evaluate the value of diagnostic information provided by both 18F‐FDG and 18F‐FLT PET and quantitatively investigated whether 18F‐FLT PET had a better performance compared with 18F‐FDG PET in esophageal squamous cell carcinoma (ESCC) staging and delineation. Methods: 26 patients with newly diagnosed ESCC and underwent pretreatment 18F‐FDG and 18F‐FLT PET were included in this study. The indices such as the standardized uptake value (SUV), gross tumor length and extracted texture parameters between 18F‐FDG and 18F‐FLT PET were compared, respectively. Tumor delineation length on 18F‐FDG (SUV threshold 2.5) and 18F‐FLT (SUV threshold 1.4) PET were validated by pathologic gross tumor length. Results: 18F‐FDG highly correlated with 18F‐FLT possessing a high correlation coefficient value r approximate 0.8 and p<0.001 in SUVmax or SUVmean. 18F‐FDG uptake was significantly higher than 18F‐FLT with respect to average SUVmax(18F‐FDG: 11.48, 18F‐FLT: 6.07) or average SUVmean (18F‐FDG: 6.09, 18F‐FLT: 3.80), with Paired T‐test Result p<0.001. In terms of texture parameters relationship Entropy and Correlation (two derived texture parameters) showed statistically significant difference. Both of 18F‐FDG and 18F‐FLT PET SUV, some of texture parameters,gross tumor length and shape feature showed statistically significant difference with respect to their feasibility in ESCC staging. The mean±standard deviation pathologic longitudinal tumor length was 5.52±2.56 cm and delineation length for 18F‐FDG and 18F‐FLT were 5.60±2.32 cm and 5.49±2.43 cm, respectively. Conclusion: The 18F‐FDG and 18F‐FLT PET scans have their own advantages in ESCC staging and tumors were well identified as the nonphysiologic distribution of radiotracers intensity typically higher than normal tissues on either PET scans. Those different indices extracted from PET scans can be potentially employed to differentiate AJCC and TNM in ESCC stage.