A gate evaluation of the sources of error in quantitative90 Y PET

PURPOSE

Accurate reconstruction of the dose delivered by ⁹⁰ Y microspheres using a postembolization PET scan would permit the establishment of more accurate dose-response relationships for treatment of hepatocellular carcinoma with ⁹⁰ Y. However, the quality of the PET data obtained is compromised by several factors, including poor count statistics and a very high random fraction. This work uses Monte Carlo simulations to investigate what impact factors other than low count statistics have on the quantification of⁹⁰ Y PET.

METHODS

PET acquisitions of two phantoms-a NEMA PET phantom and the NEMA IEC PET body phantom-containing either ⁹⁰ Y or ¹⁸ F were simulated using gate. Simulated projections were created with subsets of the simulation data allowing the contributions of random, scatter, and LSO background to be independently evaluated. The simulated projections were reconstructed using the commercial software for the simulated scanner, and the quantitative accuracy of the reconstruction and the contrast recovery of the reconstructed images were evaluated.

RESULTS

The quantitative accuracy of the ⁹⁰ Y reconstructions were not strongly influenced by the high random fraction present in the projection data, and the activity concentration was recovered to within 5% of the known value. The contrast recovery measured for simulated ⁹⁰ Y data was slightly poorer than that for simulated ¹⁸ F data with similar count statistics. However, the degradation was not strongly linked to any particular factor. Using a more restricted energy range to reduce the random fraction in the projections had no significant effect.

CONCLUSIONS

Simulations of ⁹⁰ Y PET confirm that quantitative ⁹⁰ Y is achievable with the same approach as that used for ¹⁸ F, and that there is likely very little margin for improvement by attempting to model aspects unique to ⁹⁰ Y, such as the much higher random fraction or the presence of bremsstrahlung in the singles data.

SU-E-J-21: An Intercomparison of Imaging Performance of Two Linac-Mounted Imaging Systems Used in Radiation Therapy: TrueBeam and Trilogy

PURPOSE

To evaluate and compare the performance of the imaging systems of two linear accelerators, used in radiation therapy. The study includes the following imaging components: electronic portal imaging device (EPID), kilovoltage projection imaging and kilovoltage cone-beam CT.

METHOD AND MATERIALS

The imaging systems mounted on the Varian Trilogy (Varian Medical Systems) and Varian TrueBeam, were evaluated. Image quality of two EPID systems (ASI-1000) and the two kV flat panel imagers (PaxScan 4030CB) was evaluated in terms of spatial resolution and contrast-to-noise ratio (CNR) using the QC-3 and QCkV-1 phantoms (Standard Imaging, Inc.). Cone-beam CT image sets of the CatPhan phantom (The Phantom Lab.) were obtained for standard dose head (100kVp, 0.4mAs per projection) and body (125kVp, 1.04mAs) protocols. Imaging parameters of the default clinical settings were used. The end points of the comparison were spatial resolution, CT number linearity, low contrast detectability and image uniformity. Analysis of all types of images was performed by the PIPSpro software (Standard Imaging).

RESULTS

The critical frequency (f50 in units of lp/mm) of 0.446 and 0.403 were obtained for TrueBeam and Trilogy MV detectors, respectively. The CNR was found double for Trilogy. For kilo-voltage detectors the f50 was 1.337 and 1.363, while the CNR was better by 6% in Trilogy machine. The CBCT comparison showed a 30% higher uniformity index for the TrueBeam system for pelvis protocol and 50% higher head. No significant difference was found in low contrast detectability and CT number linearity and resolution, 5 lp/mm. The Trilogy image was noisier by 35% and 30% for pelvis and standard head protocol, respectively.

CONCLUSIONS

The critical frequencies of both kV and MV detectors were found better in TrueBeam, while CNRs were found better in Trilogy. TrueBeam preformed superiorly in CBCT in terms of image uniformity and noise level.

WE-C-217BCD-04: Multimodality Imaging of Breast Cancer Experimental Lung Metastasis

PURPOSE

Metastatic breast cancer (MBC) is incurable. The clinical gold standard for assessing tumor microvessel density (MVD), an independent prognostic marker in MBC, is CD 105 staining. The goal of this study is to develop a positron emission tomography (PET)/near-infrared fluorescent (NIRF) probe for imaging of CD105 expression in MBC (i.e. non-invasive measurement of MVD), as well as other applications such as early detection of metastasis, intraoperative guidance, etc.

METHODS

TRC105, a chimeric anti-CD105 mAb, was dual-labeled with a NIRF dye and ⁸⁹ Zr to yield ^{8 9} Zr-Df-TRC105-800CW. Luciferase-transfected 4T1 murine breast cancer cells were injected intravenously into female BALB/c mice to establish a lung MBC model. Bio luminescence imaging (BLI) was carried out to non- invasively monitor the lung tumor burden. Comprehensive in vivo/ex vivo studies were performed to investigate ^{8 9} Zr-Df-TRC105-800CW in this MBC model. Cetuximab was used as an isotype-matched control.

RESULTS

Radiolabeled TRC105 has high tumor uptake in many tumor types in addition to MBC (e.g. pancreatic/prostate cancer and brain tumor), revealing broad clinical potential for TRC105-based agents. FACS analysis of HUVECs showed no difference in CD 105 binding between TRC105 and Df- TRC105-800CW. PET imaging revealed that 4T1 lung tumor uptake of ⁸⁹ Zr-Df-TRC105-800CW was 8.7±1.4,10.9±0.5, and 9.7±1.1 %ID/g at 4, 24, and 48 h post-injection (n = 4), with excellent tumor contrast. Bio distribution studies, blocking, control studies with ^{8 9} Zr-Df-cetuximab- 800CW, ex vivo BLI/PET/NIRF imaging, and histology all confirmed CD 105 specificity of the tracer. NIRF imaging-guided removal of 4T1 tumors with Df-TRC105-800CW in a subcutaneous model was also straightforward.

CONCLUSIONS

We report the first PET/NIRF imaging of CD105 expression in a MBC model. Broad clinical potential of TRC105- based agents was shown in many tumor types, which also enabled early detection of small metastases and provided intraoperative guidance for tumor removal.

SU-E-I-53: Optimal KVp for Image Quality and Noise in Iodine Contrast in Head CTA

PURPOSE

For brain CT perfusion it is well established that 80 kVp is optimal. Although neuro-CT angiography is somewhat similar, emphasis is on the detection of aneurysms and related vascular pathologies throughout the brain. Thus it is necessary to visualize small and large blood vessels with contrast material, as well as form multi-planar views and 3D images, so image quality and noise in addition to contrast are important for thin slices. A study was initiated to determine the optimal kVp for neuro-CTA.

METHODS

A customized version of a commercial head phantom (CIRS 007TE-27 medium adult head CT dose phantom) was purchased to facilitate quantitative measurements with iodinated contrast material, contrast for white and gray matter, and to maintain the ability to perform dosimetry. The customization consisted of adding four 25 mm holes, 35 mm from the center arranged at 45 degree angles from the center, with solid rods equivalent with brain, white, and gray matter, as well as four fillable vials were included for study of contrast agents. Dosimetry measurements were carried out with standard pencil chamber and with 0.6 cc ionization chamber. For study of the optimal kVp for a head CTA, the vials were filled with four different concentrations of contrast, approximating low to medium concentrations that would be expected in such a study. The standard CTA protocol was followed, 64 × 0.625, pitch 0.53, rotation speed 0.5 second, and CTDIvol was kept constant for each kVp.

RESULTS

The best contrast was observed at 80 kVp; however, in order to achieve noise in CTA low enough to be clinically useful there may be issues with tube current capability for a clinical technique. Clinical investigation is underway.

CONCLUSIONS

The best balance of contrast and noise currently possible will be achieved at 100 kVp in a clinical scan.

SU-D-217BCD-03: Impact of Jaw Width on the Megavoltage Computed Tomography Image Quality and Imaging Dose with Helical Tomotherapy

PURPOSE

On-treatment megavoltage computed tomography on Helical Tomotherapy (Accuray Inc., Sunnyvale, CA) is critical for image guided radiotherapy. A strategy was developed to assess the impact of various jaw widths on image quality and imaging dose with Tomotherapy.

METHODS

A cheese phantom (Gammex RMI, Middleton, WI) made of water equivalent materials was employed in this study. Three sets of measurements were independently carried out. Firstly, in the imaging dose measurement, the phantom was placed on the couch and aligned with a stationary green laser and beam isocenter. The measurement point was 10 mm up from the cente of the phantom. Three slices on either side of the middle slice were selected. Secondly, two inserts with different rows of holes of various sizes were placed inside the phantom for image contrast and resolution investigation. Lastly, twelve density inserts were placed into the outer holes in the phantom for measurement of the image value to density table (IVDT). A comparison of imaging dose, image resolution and contrast, IVDT table between different jaw configurations was performed to evaluate the imaging system.

RESULTS

Imaging dose was 2.93 cGy with a jaw size of one mm as opposed to 1.62 cGy with a four mm jaw, both of which are below the vendor's requirement: 3 cGy. However, image quality is improved significantly with the smaller jaw. Four lines of holes can be readily identified on images using smaller jaw while only three lines visible with the larger jaw. Image contrast is similarly enhanced when reducing the jaw size. On average CT numbers are 6% higher with the smaller jaw than those obtained with the larger one.

CONCLUSIONS

Significant improvement in image quality is achieved with the smaller jaw field in Tomotherapy while the imaging dose is kept at a clinically acceptable level.

SU-E-J-58: Patient-Specific Biomechanical Head and Neck Models for Interfraction Dose Accumulation

PURPOSE

In this abstract, we discuss a biomechanical head and neck model that will be able to represent patient setup variations as well as physiologic changes and subsequently enable dose calculations on the deformed anatomy.

METHODS

We selected Multi Pose MRI as the imaging modality to aid in model development and validation. The MRI data allowed us to build a biomechanically predictive model that will enable accurate estimation of tumor position when seeded with CT data alone. The soft tissue contrast and lack of ionizing radiation when using MRI enabled us to acquire extensive imaging datasets with a suitable variety of head pose variations. These poses were selected to encompass the clinical positioning variations so that the resulting model will accurately reflect internal organ motion and deformation. All images were acquired using an 8-channel, 1.5T research MRI system in radiology. The imaging volume extended from about T3(upper thoracic vertebrae) to the top of the head, thereby covering the entire head and neck. Model components included: muscles, skeletal bones, lymph nodes, fat tissues, and organs such as salivary glands, tendons, andligaments. At first, one MRI image dataset was selected as the reference image. The biometric properties (length, volume, mass, shape), hinge constraints of the bones, and the biomechanical properties of each of the anatomies were estimated using MRIs acquired at different head and neck poses.

RESULTS

The model's ability to represent different head and neck postures can be illustrated by observing the internal tissue deformations andthe model's ability to represent different postures.

CONCLUSIONS

Results show that the biomechanical model was able to simulate different poses that may be exhibited during interfraction patient setup variations and intrafraction patient motion. Future work would focus on integrating dose calculations on the deforming model and validating the model deformations.

SU-E-I-54: Evaluation of High Contrast Resolution for Model Based Iterative Reconstruction of Sinus Examinations

PURPOSE

To evaluate high contrast resolution of Model Based Iterative Reconstruction used with typical sinus examination acquisition parameters.

METHODS

MBIR has recently become available as a recon option on a clinical scanner (Discovery HD750, GE Healthcare). In this work, we evaluate high contrast resolution for scan and reconstruction options that are available for sinus examinations. For this study we used our adult sinus CT protocol reconstructed with filtered back projection, and two alternative scans reconstructed with IR. Our conventional adult sinus CT protocol utilizes a high resolution scan mode which is not compatible with the scanner's IR recon option. The two additional scans are with high resolution option off, one with the head SFOV, and one with the body SFOV. Using IR and the head SFOV, reconstructed images have a 1024 × 1024 pixel matrix. Using IR and the body SFOV, reconstructed images have a 512 × 512 pixel matrix. Three evaluations of high contrast resolution are made for these images. A wire phantom is scanned for assessment of image modulation transfer function. The bar patterns of the ACR phantom are visually assessed for quality in both axial and coronal reformats.

RESULTS

MTF curves show 50% values of 6.8, 7.5, and 7.7 lp/cm for Body IR 512 × 512, Head IR 1024 × 1024, and filtered back projection with HD Bone kernel. The 10% MFT curves for these reconstructions are 11.2, 11.9, and 12.1 lp/cm. Visual evaluation of the ACR phantom at 15 cm display field of view demonstrates resolution of the 10 lp/cm bar patterns for all reconstructions with better visualization of the axial versus coronal recons.

CONCLUSIONS

MBIR reconstruction demonstrates high contrast resolution that is comparable with our conventional sinus examination.

SU-E-I-100: Feasibility Study of Gamma-Ray Medical Radiography

PURPOSE

The purpose of this research is to study an alternative technique to conventional x-ray radiography that requires less patient radiation dose, less cost, portable, requires less maintenance, and less power consumption. This research explores the feasibility of using gamma-ray radiography in medical imaging. Gamma-ray medical radiography has the potential to provide alternative diagnostic medical information to X-ray radiography.

METHODS

Approximately one Ci of Am-241 radioactive source which emits monoenergetic 59.5 KeV gamma rays was used in this study. Several factors that influence this feasibility were studied. These were the radiation source uniformity, image uniformity, image quality parameters such as contrast, noise, and spatial resolution. In addition, visual assessment of several human phantom gamma-ray and x-ray images were conducted. The images were recorded on computed radiography image receptors and displayed on a standard monitor.

RESULTS

The radioactive source provided a relatively uniform radiation exposure and uniform images. Image noise was mainly dependent on the exposure time and the source size. Although the contrast depended on the window and level setting, it was also dependent on the exposure time and the source size. Spatial resolution was dependent on the source size and the magnification. The generated gamma-ray images were of lower quality than the X-ray images which was mainly due to the low radioactivity used. However, the gamma-ray images displayed most of the main structures contained in the humanoid phantoms.

CONCLUSIONS

Thisresearch explored the feasibility of using gamma-ray radiography in medical imaging and showed that gamma-ray medical radiography has the potential to provide alternative diagnostic medical information to X-ray radiography. Finally, this research also paves the way for the usage and production of high radioactive Am-241 source that will show high quality medical gamma-ray radiography is feasible.

SU-E-J-207: Compensation of Target Distortion of Pancreatic Tumor in Free-Breathing CT Using 4D Contour Propagation

PURPOSE

Due to lack of soft-tissue contrast, target distortion for the upper-abdomen targets such as pancreatic tumors is complicated and requiring sufficient remedy. By applying automatic contour propagation, the authors use the information obtained from 4D CT to test if the deformable image registration compensates the respiration-induced distortion of pancreatic tumor in free breathing (FB) CT images.

METHODS

Ten patients with unresected pancreatic cancer treated with either preoperative or definitive chemoradiation were studied. Pancreas GTVs were delineated on the FB CT. Using deformable image registration, the FB GTV contours were propagated to each phase of the 4D CT images taken right after the FB CT, and were compared with the FB GTV to see difference in tumor volume and tumor size along individual dimensions. A one-dimensional tumor motion in proportion to cos4(ωt) was simulated to calculate the probability distribution function for different magnitude of distortions during FB CT scans, and a binary classification test was conducted to analyze the observed results.

RESULTS

The probability distribution function predicted that four out of the ten cases would have substantial target distortion given the variation in target motion amplitudes. Three of these four cases show substantial difference in the superior-inferior size of FB GTV compared to the average 4D GTV, taking into account the uncertainties caused by motions perpendicular to the scanning axis and resolution of the CT scanner. The binary classification test yielded a precision of 75% and an accuracy of 90%.

CONCLUSIONS

Pancreatic GTV distorted due to respiration-induced tumor motion is effectively compensated by contour propagation from free-breathing CT to 4D CT using DIR. Union of GTVs of all breathing phases or IGTV can be genreated from 4D set of GTVs propagated from that of free breathing. This study is partially supported by NIH grant 1R01CA133539-01A2. I do not have conflict of interest.

SU-E-I-16: Automated Liver Segmentation Method for CBCT Dataset by Probabilistic Atlas Construction

PURPOSE

The aiming is getting accurate liver contour structures automatically for following adaptive radiation therapy in daily CBCT images which is very low-contrast comparing the planning CT.

METHODS

Probabilistic atlas is constructed by 50 intravenous contrast planning CT images by iterative affine registration process. The incoming CBCT images are registered with the atlas using deformable registration algorithm which is based on edge preserving scale space, and the liver contour structures are generated automatically by using the deformation map. Incorporating the intensity distribution of candidate liver region into the segmentation processing, we can further remove the irrelative tissue from the original liver region. Our algorithm is capable of segmenting the liver from low-contrast cone beam CT images. In our probabilistic atlas construction process, firstly one training data is arbitrarily chosen as reference image while the rest of training datasets are registered to this reference using the affine transformation. For improving the efficiency of our method, iterative construction method is employed. The resulting atlas which is gained before is used as the reference image for the following atlas construction. This process can be iterated by many loops. However, we used two iterations for efficiency. This iterative atlas construction process can avoid bias toward the specific patient.

RESULTS

The experiments are tested on 10 newly incoming patient data. The volumetric overlap is on an average 87%-94% comparing with manually segmented tumors by oncologists. After evaluation by clinical oncologists, they concluded that the segmentation results are close to the manual results and the liver contours on CBCT which is produced by the deformation field automatically can be used for following adaptive radiation therapy.

CONCLUSIONS

We can conclude that the proposed segmentation method is very effective with low contrast CBCT for adaptive radiation therapy in daily using.

WE-E-213CD-08: A Novel Level Set Active Contour Algorithm Using the Jensen-Renyi Divergence for Tumor Segmentation in PET

PURPOSE

Positron emission tomography (PET) presents a valuable resource for delineating the biological tumor volume (BTV) for image-guided radiotherapy. However, accurate and consistent image segmentation is a significant challenge within the context of PET, owing to its low spatial resolution and high levels of noise. Active contour methods based on the level set methods can be sensitive to noise and susceptible to failing in low contrast regions. Therefore, this work evaluates a novel active contour algorithm applied to the task of PET tumor segmentation.

METHODS

A novel active contour segmentation algorithm based on maximizing the Jensen-Renyi Divergence between regions of interest was applied to the task of segmenting lesions in 7 patients with T3-T4 pharyngolaryngeal squamous cell carcinoma. The algorithm was implemented on an NVidia GEFORCE GTV 560M GPU. The cases were taken from the Louvain database, which includes contours of the macroscopically defined BTV drawn using histology of resected tissue. The images were pre-processed using denoising/deconvolution.

RESULTS

The segmented volumes agreed well with the macroscopic contours, with an average concordance index and classification error of 0.6 ± 0.09 and 55 ± 16.5%, respectively. The algorithm in its present implementation requires approximately 0.5-1.3 sec per iteration and can reach convergence within 10-30 iterations.

CONCLUSIONS

The Jensen-Renyi active contour method was shown to come close to and in terms of concordance, outperforms a variety of PET segmentation methods that have been previously evaluated using the same data. Further evaluation on a larger dataset along with performance optimization is necessary before clinical deployment.

TU-E-217BCD-02: An X-Ray Scatter Correction Method for Dedicated Breast Computed Tomography

PURPOSE

To reduce the impact of x-ray scatter in dedicated breast computed tomography (BCT) images.

METHODS

The inclusion of x-ray scatter in BCT projections results in cupping artifacts, loss of contrast, and quantitative inaccuracies. To correct for this, an additional set of BCT projections is acquired with a tungsten plate placed between the x-ray source and the patient breast. The tungsten plate includes a two-dimensional grid of perforations to generate an array of pencil beams. Due to the limited area illuminated by the x-ray pencil beams, an array of signals of primary x-rays only is obtained. At the pencil beam locations, the difference between the plate projections and the standard projections is an estimate of the scatter present in the latter. These estimates are interpolated to obtain scatter-only estimates of the whole images, which are subtracted from the standard projections, resulting in BCT projections with primary signal only, which are then reconstructed. To reduce the impact of the quantum noise of the scatter signal, the resulting reconstructions are noise filtered. Monte Carlo simulations were performed to estimate the amount of scatter included in the pencil beams and the dose from these additional projections. The algorithm was tested using breast phantoms on a BCT clinical prototype system.

RESULTS

The maximum scatter signal in the pencil beams is 2.2% (mean of 0.7%) of the total signal, so the pencil beams are an excellent estimate of the primary-only signal. The additional projections Result in only 0.4% of the glandular dose of the standard projections. The homogeneity of the resulting phantom images, the signal difference between adipose and glandular tissue, reconstruction accuracy, and contrast-to-noise ratios were improved with this algorithm.

CONCLUSIONS

The proposed algorithm has the potential to substantially improve BCT image quality with practically no additional dose to the patient breast.

SU-E-J-127: An Initial Application of Evaluating Lung Tumor Motion Throughout Radiotherapy

PURPOSE

We present a novel method for evaluating lung tumor motion incorporating planning CT scan, imaging for patient localization, and during treatment delivery.

METHODS

Tumor motion is evaluated at three stages of the treatment process. Following the acquisition of 4D CT scans for treatment planning, tumors are contoured at one phase and registered to other phases to obtain tumor motion patterns. Tumor motion prior to each treatment is evaluated by identifying tumors directly on every raw projection of the daily localization CBCT scans. Finally, tumor motion during treatment is evaluated by analyzing MV treatment beam images. Every frame of image is evaluated as three components, each with separate DRRs: all non-moving structures, the tumor, and other moving structures. The locations of three components are determined though a registration process. In order to quantify tumor motion, the cumulated probability, the percentage of time when the tumor motion is equal to or smaller than a given range, is evaluated at every stage.

RESULTS

This methodology has been applied to five lung cancer patients undergoing radiotherapy. More than 5400 frames from MV treatment beam images and 24 CBCT scans were acquired from 12 fractions. Both the average tumor position and the cumulated probability with the range were evaluated. The tumor motion ranges are generally larger than those obtained from 4D CT. Significant variation in motion patterns was observed as well.

CONCLUSIONS

Information obtained from 4DCT is insufficient for motion assessment. In contrast, our novel methodology is capable of accurately characterizing lung tumor motion on a daily basis, without the need for implanted fiducial markers and without additional imaging dose. It provides daily verification that the tumor range is within prior estimates and covered by the treatment planning volume. This research is supported by CPRIT Individual Investigator Award RP110329.

SU-E-J-28: Comparison of IGRT Shift Data Between Prostate Gland and Prostate Bed Obtained from Ct-On-Rails

PURPOSE

The daily shifts of prostate gland have been intensively reported in literatures. However, few papers reported daily shifts of prostate bed due to several practical difficulties (e.g. limited soft tissue contrast in MVCT and CBCT and significant deformation of prostate cavity). We have routinely performed IGRT for both prostate gland and bed with ct-on-rails, and the superior image quality allows us not only to differentiate both bony anatomy and soft tissue contrast of prostate gland and bed. In this study, we investigated if the shift of prostate bed is signifiant difference from that of prostate gland.

METHODS

we reviewed shift data of 50 prostate gland patients who underwent 43 fractions and 22 patients of prostatectomy underwent 37 fractions. In total 2150 CT scans were reviewed for prostate gland and 814 scans for prostate bed.

RESULTS

Of the reviewed 814 CT images from 22 prostate bed patients, the standard deviation of shift was found to be 5.9 mm in AP direction (ranges from -22.4mm to 22mm), 3.2mm in SI direction (ranges from -14mm to 14mm), and 4.1mm in lateral direction (ranges from -15mm to 22mm). Of the 2150 CT images of prostate gland from 50 patients, the standard deviation of the shift was found to be 5.4 mm in AP direction (-20mm to 18 mm), 5.0mm in SI direction (-26mm to 20mm), and 4.3mm in lateral direction (range from-15 to 30mm). F tests of systematic /random shift distribution in three orthogonal directions between prostate gland and prostate bed were subsequently performed, it was found that the systematic shift in SI direction for prostate bed is smaller than for prostate gland (p=0.003).

CONCLUSIONS

Our result suggests no significant difference existing in shift between prostate bed and gland. Therefore strategies for daily prostate gland motion can be directly applied to prostate bed.

SU-E-J-119: Comparative Evaluation of Respiratory Motion-Corrected Cone-Beam CT Images Derived from Treatment-Day Vs. Simulation-Day Respiration-Correlated CT Scans

PURPOSE

Respiration-induced motion artifacts in cone-beam CT (CBCT) can be corrected using a model of patient motion obtained from respiration-correlated CT (RCCT). This approach assumes that respiration-induced organ deformations at simulation, when RCCT scans are normally acquired, are still valid at treatment. The purpose of this study is to compare lung tumor image quality in motion-corrected CBCT images derived from treatment-day RCCT(tx) to simulation-day RCCT(sim) patient images.

METHODS

In an IRB-approved study, lung cancer patients receive an RCCT at simulation, and an RCCT, gated CBCT and 1-minute CBCT at one treatment session. CBCT projections from the 1-minute scan are sorted according to breathing amplitude from an external monitor and reconstructed and warped to obtain a motion-corrected MC-CBCT at end expiration. Motion correction uses a model adapted from either RCCT(tx) or RCCT(sim), thus obtaining MC-CBCT(tx) and MC-CBCT(sim) images respectively. A gated CBCT, in which gantry rotation and projection acquisition occur within a gate at end expiration, serves as ground truth for comparison. Quality of MC-CBCT images is evaluated from tumor-to-background contrast ratio (TBCR) values measured by delineating the tumor and annular volume around it on the gated CBCT then transferring the contours and aligning them to each MC-CBCT.

RESULTS

TBCR is found tobe lower in MC-CBCT(sim) images, relative to MC-CBCT(tx), in four out of five patients with mean 21% reduction in a range 9-39%. In the remaining case, where there was no change in TBCR, tumor motion observed in the RCCT was small (2mm). Tumor motion extent relative to diaphragm is observed to change between RCCT(tx) and RCCT(sim) scans.

CONCLUSIONS

Preliminary results indicate that deformation patterns in lung do change between simulation and treatment. Such variations may reduce the validity of using simulation data for motion-corrected CBCT at treatment. The findings require confirmation with larger numbers of patients. NIH/NCI award R01 CA126993, research grant from Varian Medical Systems.

WE-C-218-01: Ultrasound Contrast Agents

Medical ultrasound has long been used in clinical applications both as a primary modality and as a supplement to other diagnostic procedures. The basis for ultrasound imaging is the transmission of high frequency (megaHertz) sound waves that propagate through tissue. These sound waves backscatter from the interfaces between tissue components with different acoustic properties and are detected by the imaging system, allowing the creation of images based on tissue characteristics and spatial location. Thus, traditional ultrasound has focused primarily on the imaging of anatomical structures and analysis of blood flow in large vessels. Unfortunately, blood is a weak scatterer, which can make vascular diagnostic applications (example: echocardiography) challenging especially with larger patients. Contrast agents help to improve on this shortcoming by enhancing the visualization of blood flow, thus improving the quality of diagnostics. The use of contrast agents for ultrasound was first reported in 1968 when Gramiak and Shah discovered that there was an increased backscatter of ultrasound caused by injected microbubbles. This is because the mismatch in acoustic impedance (a function of an object's density and compressibility) between the microbubble gas core and blood (or tissue) is several orders of magnitude, which results in substantially higher scattering from a bubble than an equivalent volume of tissue or blood. Additionally, microbubbles oscillate in response to an ultrasound field, and respond non-linearly to acoustic pulses even at low energies, unlike tissue. The non-linear property of microbubbles in an ultrasound field allows for the use of various pulsing and signal processing strategies to detect the backscattered signal from contrast agents and segment it from tissue, thus providing a high contrast-to- noise ratio. Due to these unique acoustic properties, a clinical ultrasound system can detect even single microbubble contrast agents, providing exquisite sensitivity and the ability to perform advanced diagnostic procedures. Over the last several decades, ultrasound contrast agents have been improved for enhanced stability and increased persistence times. Although preclinical studies as well as clinical use in Europe and Asia strongly suggest that the use of contrast ultrasound can substantially improve diagnostic capabilities in both cardiology and radiology applications, contrast use in the US is still very limited. Obstacles to the widespread use of microbubbles include safety concerns, the need for optimization of approaches for contrast use, and general understanding of their potential by physicians. This course covers the basic principles of contrast agents used in ultrasound imaging including their stability, shell properties and their behavior within an acoustic field. In addition, we will cover many new techniques that are being evaluated in preclinical studies including: p er fus ion-based techniques, molecular imaging, gene therapy, drug delivery, and acoustic angiography. Finally, basic safety concerns and biological effects will be reviewed.

LEARNING OBJECTIVES

1. Understand the basic principles of ultrasound contrast agents a. What are microbubble contrast agents? b. Properties of microbubbles c. Safety concerns and biological effects 2. Understand basic contrast imaging techniques a. Harmonic and suharmonic imaging techniques b. Pulse inversion techniques 3. Understand the use of contrast agents in various vascular applications a. Traditional methods (Cardiovascular, Abdominal) b. Advanced perfusion imaging techniques 4. Understand the role of contrast agents in preclinical applications a. Ultrasound molecular imaging b. Gene therapy c. Drug delivery d. Acoustic angiography.

WE-E-213CD-05: A Non-Rigid Image Registration Algorithm That Accommodates Organ Segmentation Error

PURPOSE

To introduce a new deformable image registration algorithm based on surface matching that accommodates organ delineation error in daily Cone-beam CT images based on a priori knowledge of inter-observer segmentation uncertainty.

METHODS

The dataset includes four prostate cancer patients who underwent primary external beam radiotherapy and had tumors that were confined to the prostate. All imaging was performed without intravenous contrast. Organ surface segmentation errors in a multiple observer-contouring study on the pelvic organs in Fan-beam CT (FBCT) and Cone-beam CT (CBCT) were estimated from the training dataset. A novel deformable image registration algorithm is presented where the organ surface matching is penalized by this error. Portions of the organ surface that are delineated reliably are used to guide the registration whereas the portions that are highly uncertain are ignored. This approach reduces the impact of delineation errors in CBCT. An evaluation experiment compares three algorithms, namely intensity-only registration (INT), equally-weighted surface and image registration (EWSIR) and the proposed uncertainty- weighted surface and image registration.

RESULTS

The surface dissimilarity was reduced from 0.172 to 0.134, 0.043 and 0.044 respectively after registration. The Jacobian of the transformation found by the proposed method was closer to one than that of EWSIR in the prostate.

CONCLUSIONS

In prostate external-beam radiotherapy, slice-by-slice 2D manual contouring has variable spatial accuracy. For deformable image registration methods that match segmented surfaces, regions of high inaccuracy can misguide the registration. In contrast to the image registration methods where the FBCT and CBCT surfaces (or other features) are assumed to be exact, our method takes this uncertainty into account. Preliminary results show an improved registration performance suggesting a potential use in IGRT. This work was supported by National Cancer Institute Grant No. P01 CA 116602.

Sci-Sat AM(1): Imaging-05: Analytical scatter estimation for cone-beam computed tomography

A significant challenge to the implementation of cone-beam computed tomography (CBCT) for high-resolution imaging is the high scatter to primary ratio. Scatter causes cupping and shading artifacts, increased noise and decreased contrast in reconstructed images. Methods to reduce the impact of scatter in CBCT are thus very desirable. We are investigating methods for computational scatter estimation and compensation for CBCT, with the goal of incorporating a scatter estimator within a statistical reconstruction algorithm. We have developed an analytical method for estimating single scatter, based on Klein-Nishina cross-sections. We have compared scatter estimates generated with this method with the results of high-count EGSnrc Monte Carlo simulations. The analytical estimates compare favorably with the Monte Carlo estimates. The paper will discuss our method for analytical estimation of single scatter, including the assumptions and simplifications required to render it computationally tractable, along with the results of the comparison between the analytical method and Monte Carlo simulations. The paper will extend previous results obtained with small (40 × 40 × 40 voxel) homogeneous computational phantoms to include results for larger, more clinically relevant phantoms (128 × 128 × 128 voxels, simulated 50/50 breast tissue with inserts of varying contrast). The paper will also discuss computational acceleration obtained through the use of parallel processing via the WestGrid High-Performance Computing network.