bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐C‐201C‐02: Physical Validation of PET/CT for Imaging as a Biomarker
Authors: Kinahan P
Published: August 2010

An expanding goal of quantitative medical imaging is it use by clinical investigators, cooperative cancer trial groups, and pharma in clinical trials of new cancer therapies. Quantitative measures of tracer uptake used in positron emission tomography (PET) imaging have been shown to be a predictor of patient outcome including pathologic response, disease‐free survival and overall survival in single institution imaging and therapy trials. There is increasing interest in using PET as a biomarker to evaluate response to therapy and possibly as an endpoint for cancer therapeutic response in multi‐center trials. However, several sources of variance and inherent in quantifying PET tracer uptake should understood and determined in order to ascertain the significance of differences in serial measurements and aid estimation of expected variances during clinical trial design. This has three distinct and linked components; (1) measuring and reducing the bias and variance of multi‐center quantitative PET/CT imaging measurements, (2) devising optimal PET image analysis methods appropriate for quantitative PET/CT imaging in clinical trials, and (3) developing and testing guidelines for incorporating quantitative PET/CT imaging as a biomarker and measure of response in cancer clinical trial design. Underlying themes include optimizing the clinical and biologic data that can be gleaned from imaging in the setting of cancer therapy clinical trials, matching the design of the imaging components to the phase and complexity of the cancer clinical therapy trial, and matching the imaging approach to the type of tumor and the therapeutic agent.
TU‐D‐204B‐03: Lung CBCT Motion Deblurring Using Tumor Tracking in Rotational Cone‐Beam Projections
Authors: Lewis J , Li R , Jia X , Watkins W , Song W , Jiang S
Published: August 2010

Purpose: To develop an algorithm for the removal of motion blurring artifacts from CBCT images of lung tumors using knowledge of a tumor's motion on the day of treatment acquired by tracking the tumor in rotational cone‐beam projections. Method and Materials: DRR templates derived from 4DCT were used to track lung tumors in rotational cone‐beam projections. Tracking results acquired during a CBCT scan were used to estimate a motion pdf. This pdf was incorporated into a deconvolution algorithm which removes motion artifacts from the reconstructed CBCT volume. Deconvolution is performed through iterative minimization of a cost function where i is the original CBCT image, g is the deblurred image, f is the motion pdf, and λ is a weighting parameter. The second term is a total variation norm regularization defined as . The algorithm is tested on physical phantom and patient data. For the phantom, CBCT scans were acquired for moving and stationary phantoms. Deconvolution was performed on the image of the moving phantom, which was then compared to the image of the stationary phantom. For patient data, deconvolution is performed on a CBCT acquired on the day of treatment, then compared to 4DCT acquired during simulation. Results: Images of the physical phantom show a good match between deblurred, and stationary cases. Line profiles show that the correct tumor dimensions are recovered. For the patient case, motion artifacts are significantly suppressed in the deblurred volume, which appears qualitatively similar to the 4DCT. Conclusion: An algorithm has been developed to remove motion blurring artifacts from CBCT tumor images based on a tumor's tracked motion during the CBCT scan. The algorithm successfully recovered motion‐corrected images in a phantom study, and removes some artifacts in the patient case.
TU‐D‐204B‐08: A Setup for Patient Individual KV CBCT Scatter Prediction Using Monte Carlo Simulations
Authors: Poels K , Van den Heuvel F
Published: August 2010

Purpose: To use Monte Carlo simulations for scatter subtraction on cone‐beam CT projection images to improve the Hounsfield Unit constancy. Materials and Methods: To accurately simulate the scatter contribution for the kV detector a detailed modeling of the entire OBI geometry is performed. We calculated the bremsstrahlung spectrum using MCNPX (v2.7b). A patient voxel model was created using CT images. The detector was accurately defined in MCNPX, including filtering, the anti‐scatter grid and other important structures. To separate the primary and scattered photons, we used the tally tagging functionality. In an alternative method we saved the phase space information at the detector after transport through the object of interest. Afterwards we applied energy response functions to better predict the contribution of scatter in the active layer of the detector. Soft tissue modification was used to study the possibility of scatter subtraction after weight loss for a head‐and‐neck patient. Results: Simulations of the bremsstrahlung spectrum were in good agreement with chamber measurements. The patient voxel model was used to determine the patient individual scatter characteristics. After weight loss the scatter increased due to the larger contribution of the scatter originating from the bowtie filter. The scattered photons was dominated by the primary photons and subtraction errors are believed to be small. Scatter estimates corrected for detector response were calculated using the phase space information for a flood field. The flood field simulation included the heel effect and scatter estimate of the flood field increased towards the unfiltered part of the beam. Conclusion: We provided an initial setup for patient individual scatter prediction using Monte Carlo simulations. When acquiring the phase space at the detector, we can apply detector response functions to approximate the scatter response in an physical kV OBI detector. Conflict of Interest: Research supported by a Varian research grant.
TU‐D‐204B‐09: Rapid MR Imaging for Real‐Time Target Tracking Using Temporal Sparsity
Authors: Hong C , Sawant A , Keall P
Published: August 2010

Purpose: Real‐time MRI‐guided radiotherapy is an exciting new modality and requires the development of new imaging schemes focused on the role of MRI in radiotherapy guidance rather than diagnosis. In this work, we investigated sparse k‐space sampling schemes in order to reduce scan time for the purpose of real‐time target tracking. Method and Materials: To compare different k‐space sparse sampling schemes, an IRB‐approved human subject examination of MR imaging was performed using a FIESTA sequence in a 1.5 T system (General Electric, Milwaukee, WI). The power spectrum of the difference between adjacent k‐space image frames was calculated over each time series. Sparse sampling schemes were determined by specifying five different threshold levels for the superimposed power spectrum corresponding to all the frames in each time series. A blood vessel in the liver was segmented in the full‐sampled time series and sparse‐sampled time series. The root mean square (RMS) error of each degraded trajectory with respect to the full‐sampled trajectory was computed. Results: For k‐space sampling reduction schemes using temporal sparsity, the RMS error in the superior‐inferior direction was 0.13, 0.27, 0.38, 0.38, and 0.57 mm for the 88%, 76%, 69%, 60%, and 54% sampling fraction, respectively. Conclusions: Sparse k‐space sampling schemes for MR imaging scan time reduction have been investigated. This allows fast MR imaging, which can be applied to real‐time target tracking for management and localization of tumor motion in radiotherapy. Conflict of Interest: This work was supported by the AAPM Research Seed Funding Initiative.
TU‐D‐204C‐01: Some Uses of Neural Networks in Radiation Therapy
Authors: Murphy M , Wu J
Published: August 2010

Artificial Neural Networks (ANN) have become a staple of machine learning applications. They can be used for pattern recognition, data classification, and process control problems, several of which come up in modern radiation therapy. In this presentation we will look at two representative applications of ANNs: (1) the prediction of breathing, to compensate instrumental lag time in systems that automatically compensate for respiratory motion of a tumor; (2) the analysis of patient setup corrections generated automatically via rigid image registration, to recognize poor or failed results as a quality assurance (QA) measure.

All systems that attempt to actively compensate respiratory motion will have intrinsic delays that necessitate predicting the future tumor position by up to several hundred milliseconds. However, every patient breathes differently, which makes the use of analytical breathing models problematic. An ANN is capable of learning the breathing pattern of any given patient directly from incoming data and making an accurate prediction of its future amplitude. We will show examples of this application.

Image‐guided radiation therapy (IGRT) relies on image acquisition and registration to optimally position the patient for treatment. However, rigid image registration algorithms can sometimes fall into local minima that can be far removed from the optimal setup position. If one identifies a set of significant “features” of the registration result, such as the shape of the cost function surface in the neighborhood of the solution at convergence, an ANN can use them to classify a particular registration as good or bad, according to some predetermined criteria. This provides an important QA tool to assess patient setups.

Learning objectives:

1. learn the basic concepts of ANNs as they are used for pattern recognition and classification.

2. learn how to use an ANN in a real‐time tumor tracking process.

3. understand how an ANN can be trained and used to recognize imperfect patient setup shifts for QA purposes.
TU‐D‐204C‐02: Machine Learning in Real‐time Tumor Localization
Authors: Li R , Jiang S
Published: August 2010

Real‐time tumor localization is an essential step to achieve conformai lung cancer radiotherapy. In practice, tumors may be localized either directly (e.g., in fluoroscopy) or indirectly by some type of surrogate. Direct localization with implanted markers poses the risk of pneumothorax to lung cancer patients, while indirect localization is limited by its accuracy. Direct localization in fluoroscopy without implanted markers achieves a reasonable tradeoff between accuracy and risk to the patients. However, due to the poor soft tissue contrast and superposition of different anatomical structures, it is generally very difficult to localize the tumor in fluoroscopy with conventional methods in computer vision and image processing.

Recently, machine learning has gained great popularity in many aspects of radiation therapy. In this lecture, we will demonstrate the applications of various machine learning techniques in the context of real‐time tumor localization in lung cancer radiotherapy. These cover a wide range of well established machine learning techniques, including principal component analysis (PCA), artificial neural networks, and support vector regression, etc.. We will distinguish between two different paradigms when applying these techniques: one in a two‐dimensional (2D) framework and the other in a three‐dimensional (3D) framework. In the 2D framework, a (supervised) regression model is built between a parametric representation of the fluoroscopic images. and the tumor locations of the fluoroscopicimag fluoroscopic images. Because the representation of the fluoroscopic images is implicit in the 2D framework, it is difficult to account for deformational and large translational changes in the tumor. In the 3D framework, by incorporating the prior information in 4DCT or 4DCBCT, a PCA model is constructed to explicitly represent the entire lung motion in a realistic and efficient way. This model allows one to use a single x‐ray projection image to not only derive the 3D tumor location, but also reconstruct the corresponding volumetric image of the patient. With the aid of graphics processing units, this computationally intensive task can be achieved within half a second given one projection.

This lecture provides an overview of the different machine learning techniques used in real‐time tumor localization. A detailed description of these machine learning techniques is also presented. Finally, extensions to the current framework as well as some future directions are discussed.

Learning Objectives:

1. Understand the benefits and challenges of real‐time tumor localization without implanted markers.

2. Understand the principles of different types of machine learning techniques for real‐time tumor localization.

3. Understand how machine learning techniques are used to achieve accurate real‐time tumor localization.

Conflict of Interest: This work is partially supported by Varian Master Research Agreement.
TU‐D‐201B‐01: Challenges and Experience in CT Dose Assessment & Dose Reduction ‐ an International Perspective
Authors: Rehani M
Published: August 2010

Radiation doses in computed tomography (CT) is a matter of global interest. In developing countries, there is a lack of upgrading of technology in many facilities, such as tube current modulation, and a lack of skilled manpower (medical physicists) for dosimetry. There are apprehensions that patients may be getting much higher radiation doses than necessary. The International Atomic Energy Agency (IAEA) launched studies few years ago covering a large number of developing countries to access the situation, create awareness and implement dose management. The studies have covered adults and children in more than 200 facilities in over 30 countries in Africa, Asia, Eastern Europe and Latin America. In view of the lack of medical physicists in diagnostic radiology, staff working in universities, regulatory bodies and even radiographers were utilized to collect information and then imparted dosimetry skills. Standardized data collection forms were developed. As anticipated, significant variations in radiation levels and in the frequency of CT scans were observed. Corrective actions were suggested to those where the values were exceeding diagnostic reference levels and in situations where adult exposure factors were used by pediatric patients. Improvements were assessed. The major challenge comes not from lack of technology, but from lack of skilled manpower. However, it was heartening to achieve the cooperation of participants from so many countries and to document improvement.

Learning Objectives:

1. To become familiar with the situation of radiation doses in CT in developing countries.

2. To understand how dose management projects launched by the IAEA have been pursued despite lack of skilled manpower.

3. To become familiar with actions taken and results obtained to improve the situation in a number of developing countries.
TU‐D‐201C‐01: Physics in the Evolution of Contrast Agents in Ultrasound
Authors: Burns P
Published: August 2010

The acoustic bubble has graduated from an intriguing curiosity in physics to the center stage of ultrasound imaging in clinical medicine. This is principally a consequence of the development of a new generation of bubble constructs ‐ heavy gases stabilized by a shell of lipid or other biocompatible material ‐ that have been approved as intravenous contrast agents for diagnostic medicine. The bubbles are smaller than a red blood cell and so pass freely around the circulation. By a serendipity, they happen to resonate at frequencies within the diagnostic range, and so can be driven easily into nonlinear oscillation by a typical ultrasound imaging pulse. This has spawned a mass of nonlinear echo detection strategies that are now sufficiently sensitive to detect an individual 3 micron bubble flowing in a capillary more than 10 cm below the skin surface, while rejecting echoes from tissue. The resulting real time perfusion images have redefined what is possible to diagnose from a medical ultrasound image. This talk will explore the bubbles and their acoustic behavior, the nonlinear imaging methods to detect them and their applications in medicine. Foremost among these is the ability to detect the microvessels that accompany the growth of a cancer ‐ malignant angiogenesis ‐ and, by disrupting the bubbles remotely using the ultrasound beam, to measure blood flow at the tissue level, an important indicator of response to therapy. In their current form, the bubbles flow in the vascular system without interacting with it, but it is easy to modify their surface so that they bind to specific cellular or molecular targets on the endothelial cells lining blood vessels. Such biomarkers assure ultrasound a place in the effort to create an imaging method of the future that provides functional information about the patient at a molecular, as well as a macroscopic level.
TU‐D‐201C‐02: Subharmonic Imaging and Pressure Estimation
Authors: Forsberg F
Published: August 2010

The use of gas filled microbubbles as contrast agents for ultrasound imaging (US) is well established by now. Such contrast agents are used world‐wide to improve the diagnostic capabilities of US especially when employed in combination with novel nonlinear contrast imaging modes such pulse inversion second harmonic and subharmonic imaging (SHI).

Our group has investigated the use of SHI in breast imaging and has produced the first ever human SHI images as well as developed a new contrast imaging mode: dynamic cumulative maximum intensity (CMI) SHI. Fourteen patients with 16 breast lesions, who underwent breast biopsies with histopathological assessment, participated in a pilot study of mammography and contrast US. A Logiq 9 scanner (GE Healthcare, Milwaukee, WI) was modified to perform grayscale SHI (transmitting/receiving at 4.4/2.2 MHz). Of the 16 lesions, 4 were malignant. Mammography had a sensitivity of 100 % and a specificity of 20 %. Baseline grayscale US and PDI both achieved a sensitivity of 50 % and a specificity of 92 %, while contrast‐enhanced PDI produced 75 % and 75 %, respectively. SHI had a sensitivity of 75 % and specificity of 83 %. All the ultrasound modes produced higher specificities than mammography (p<0.04). The area under the ROC curve (Az) for the diagnosis of breast cancer was 0.64 for grayscale and PDI, 0.67 with contrast enhanced PDI, 0.76 for mammography and 0.78 for SHI. For dynamic CMI‐SHI mode the Az increased to 0.90 and this was significantly better (p=0.03) than mammography. More recently, the utility of contrast microbubbles for quantitative measurements of hydrostatic pressure (in mmHg) have been explored. Changes in ambient pressure affect the reflectivity of ultrasound contrast microbubbles leading to an excellent correlation between subharmonic signals and hydrostatic pressure (r2>0.90). We have proposed subharmonic aided pressure estimation (SHAPE; U.S. patent 6,302,845) and provided proof of concept of the feasibility of in vivo SHAPE. The heart and aorta of four dogs were scanned with a Sonix RP scanner (Ultrasonic Medical Corporation, Richmond, BC, Canada) modified to perform SHAPE. Simultaneously, the instantaneous pressures within the aorta were measured using a manometer‐tipped catheter. The instantaneous in vivo pressure measurements and those based on SHAPE were in good accordance over a pressure range of 0 to 70 mmHg (r2 from 0.65–0.85).

In conclusion, a new contrast specific imaging technique, SHI, has been investigated for in vivo breast imaging and for quantitative measurements. SHI appear to improve the diagnosis of breast cancer relative to conventional ultrasound and mammography; albeit based on a very limited patient population. Some encouraging results in pressure estimation have been achieved.

Learning Objectives:

1. Understand the origin of subharmonic bubble signals

2. Understand the pro's and con's of SHI

3. Understand the principle of SHAPE
TU‐E‐204B‐02: Feasibility of Low‐Dose Single‐View Real‐Time 3D Tracking Concurrent with External Beam Delivery
Authors: Wilfley B , Speidel M , Hsu A , Hristov D
Published: August 2010

Purpose: Existing on‐board x‐ray imaging chains orthogonal to the delivery beam cannot recover 3D target trajectories from a single view in real‐time. This limits their utility for real‐time motion management concurrent with beam delivery. We investigate the feasibility of an alternative inverse‐geometry “single‐view” Scanning Beam Digital X‐ray (SBDX, NovaRay Medical, Inc.) system for real‐time 3D intra‐delivery tracking. Method and Materials: A chest phantom (Standard Imaging, WI) comprising a posterior wall, a central lung volume and an anterior wall was used for the investigations. The lung contained a mediastinal volume isodense with the chest. Along the mediastinum, two fiducials were placed: a 1 mm diameter steel sphere superiorly and a gold cylinder (2.6 × 0.9 mm) inferiorly. The phantom was placed on a linear motion stage (Standard Imaging, WI) which moved sinusoidally with peak‐to‐peak displacement of 2 cm, and a period of either 3.5 sec or 5 sec. The stage motion was substantially along the source‐detector (z) axis of the SBDX system. The system operated at 15 frames per second, 100 kVp, providing good apparent conspicuity of the fiducials. With the stage moving, detector data were acquired and subsequently reconstructed using digital tomosynthesis into 15 planes with spacing of 12 mm. Tracking was performed on the plane data for each (temporal) frame to yield the position of each fiducial in 3‐space versus time. Results: Tracking data for the z‐coordinate agreed with the trajectory calculated from the known amplitude and frequency of the motion and with an adjustable phase and z‐offset to within an RMS error of 1.05 mm for the gold cylinder and 0.61 mm for the steel sphere. Conclusion: Tracking with sub‐millimeter accuracy appears to be feasible with “single‐view” SBDX, supporting its use to guide radiotherapy. Conflict of Interest: Brian Wilfley has a financial interest in NovaRay Medical, Inc.
TU‐E‐204B‐04: DMLC Implementation of a Prostate Intrafraction Motion Correction Strategy Based on Failure Detection Concept
Authors: Liu W , Cho B , Keall P , Luxton G , Xing L
Published: August 2010

Purpose: To develop a dynamic MLC‐based real‐time motion tracking system through stereoscopic MV‐kV target localization and to utilize a failure detection concept to reduce kV imaging dose while maintaining high targeting accuracy. Methods and Materials: Continuous MV‐kV target localization, although informative, imposes excessive kV imaging dose. In order to reduce kV usage, we attempted for a first step to only detect potential motion beyond a pre‐defined threshold using MV images and in a second step, through applying as‐needed MV‐kV imaging, to confirm the over‐threshold event and obtain accurate marker position information which could be used to instruct instantaneous MLC adjustment. This technique is particularly useful for slow non‐periodic motion. A Varian Trilogy linac with onboard imaging and a Millennium 120‐leaf MLC was used to examine selected typical prostate trajectories using a 4D motion platform. Geometric and dosimetric tracking performances were evaluated by tracking a moving gold marker during dose delivery from 7 gantry angles. In‐house designed software was used for marker extraction, decision making, and MLC adjustment. Results: Total system latency from occurrence of an over‐threshold motion to the end of MLC repositioning was found to be 0.5 – 0.6 sec. The target was kept within a preset 2.5mm range 99% and 96% of the beam‐on time requiring only 1 and 13 kV‐on for a slow drifting and a high‐frequency motion case, respectively. The MLC repositioning accuracy is ∼0.5mm with system calibration. Dosimetric benefits are seen in reduced failure rate of the gamma‐test applied to dose measurements. Conclusions: Cine MV imaging during therapy delivery provides a valuable tool for detecting non‐negligible intrafraction prostate motion and facilitates intelligent kV use to significantly reduce imaging dose. Successful integration of this monitoring strategy and DMLC motion compensation is demonstrated. The developed system is intriguing for prostate intrafraction motion management with low kV imaging overhead.
WE‐A‐202‐01: Dose and Image Quality in C‐Arm CT Rotational Angiography
Authors: Fahrig R , Girard‐Hughes E , Ganguly A , Tognolini A , Kothary N
Published: August 2010

Conebeam CT using C‐arm mounted large area flat panels (FPs) is becoming more commonly used in neuro‐ and body‐interventional suites. The ability to visualize vascular geometry in 3D along with soft tissue during an intervention is providing information that may increase accuracy, shorten procedure time and may even change the course of treatment. However, acquisition of the projection data required for volume imaging requires dose to the patient, and understanding the trade‐offs between acquisition parameters, dose and image quality is critical to the appropriate adoption of this imaging technique.

Unlike conventional CT, the beam length in conebeam CT can cover the entire length of the object to be imaged or can be varied with the use of collimation, and the concept of CTDI is not, therefore, the metric of choice for measurement of dose. In addition, most C‐arm conebeam CT systems use a short‐scan (pi plus fan‐angle) acquisition, and the dose distribution within the object is not cylindrically symmetric. Finally, since FP design has been optimized for fluoroscopy, image quality when used for CT must be carefully evaluated.

This lecture will describe a dose metric that is appropriate for conebeam CT and allows direct comparison with the CTDIw of conventional CT, and will summarize dose‐image quality trade‐offs. A discussion of measured dose metrics and recently published Monte Carlo‐based Effective Dose calculations for head and body applications will be presented. New results from our ongoing clinical study investigating the overall dose impact of 3D C‐arm CT on body interventions will be summarized. Research sponsored by Siemens AG, Healthcare Sector, by NIH grant R01 HL087917 and by the Lucas Foundation.

Learning Objectives:

1. Understand how differences in acquisition geometry between conebeam and conventional CT affect dose measurement and dose distribution.

2. Understand the necessary dose‐image‐quality trade‐offs when using C‐arm CT in the interventional suite
WE‐SAM‐201B‐01: PET/CT Technology Update, Quality Assurance and Applications
Authors: Mawlawi O
Published: August 2010

In the past few years, positron emission tomography/computed tomography (PET/CT) imaging has increasingly been used for the diagnosis, staging, and restaging of malignant diseases. The success of this emerging modality has primarily been due to its ability to combine the advantages of both PET and CT imaging while minimizing their separate weaknesses. One of the main advantages of PET/CT imaging is its ability to generate functional images depicting the biodistribution of radioactive compounds that are correlated with anatomical landmarks thereby increasing the physicians' confidence in image interpretation and improving patient management.

The aim of this lecture is to provide an overview of the basic physics principles of PET/CT imaging as well as the advantages and drawbacks of using CT for attenuation correction of PET data. In addition, the lecture will cover the latest in design specifics of commercially available PET/CT scanners from different manufacturers as well as review PET/CT quality control and assurance techniques.

Learning Objectives:

1. To learn the basic physics principles of PET/CT imaging

2. To understand the advantages and drawbacks of using CT for attenuation correction of PET images.

3. Become familiar with design specifics of commercially available PET/CT scanners.

4. Learn quality control and assurance techniques for PET/CT imaging
WE‐SAM‐201B‐02: SPECT/CT: Basics, Quality Assurance, and Clinical Applications
Authors: Kappadath S C
Published: August 2010

Single‐photon emission computed tomography (SPECT) together with computed tomography (CT), commonly referred to as SPECT/CT, is rapidly becoming a mainstream imaging modality and creating a new paradigm for SPECT imaging. The ability to contemporaneously acquire electro‐mechanically registered dual‐modality SPECT and CT scans improves the SPECT image quality due to CT‐based attenuation correction and enhances the diagnostic confidence of SPECT by providing a CT‐based anatomical overlay. The utilization of SPECT/CT has been mainly in the field of oncology with applications including: tumor localization, differential diagnosis, staging and response to treatment, pre‐surgical planning, radiation therapy treatment planning, and quantitative SPECT/CT‐based internal radionuclide therapy dosimetry/treatment planning. SPECT/CT is also being utilized for cardiac and skeletal imaging and imaging of other non‐malignant diseases.

This lecture will review the physics principles underlying SPECT and SPECT/CT imaging, discuss quality assurance of SPECT/CT systems, and present several examples of the clinical application of SPECT/CT.

Learning Objectives:

1. To understand the physics principles underlying SPECT/CT image acquisition, processing and reconstruction

2. To understand the quality assurance procedures specific to hybrid SPECT/CT system

3. To become familiar with clinical applications of SPECT/CT imaging
WE‐C‐204B‐07: Real‐Time MRI for Soft‐Tissue‐Based IGRT of Moving and Deforming Lung Tumors
Authors: Sawant A , Pauly K Butts , Alley M , Vasanawala S , Loo B , Joshi S , Hinkle J , Keall P
Published: August 2010

Purpose: Integrated MRI+Linacs can potentially provide real‐time soft‐tissue‐based image‐guidance for lung cancer IGRT. Towards this, we investigate guidance strategies using prospective rapid lung MRI coupled with deformable image registration. Method and Materials: All experiments were performed on a 1.5 T MRI scanner, using a 4‐channel cardiac coil, under free‐breathing conditions, without extrinisic contrast. A balanced steady‐state free precession (b‐SSFP) imaging sequence was optimized for prospective imaging and reconstruction. Two lung cancer patients (Pt#l: 4 cm tumor, right lower lobe, Pt#2: 6 cm tumor, left upper lobe) were imaged. A viscous fluid‐flow‐based deformable registration was applied to each MRI time series in order to determine motion trajectories of voxels within the field of view. These trajectories were used to characterize:

(i) motion of the tumor centroid.

(ii) relative trajectories of the tumor centroid and the diaphragmrelative trajectories of different points on the tumor — characterizing tumor rotation/deformation.

Results: The modified b‐SSFP sequence yielded acquisition times of ∼0.16s and ∼1.5s for 2D and 3D acquisition, respectively.

Tumor trajectory analysis:

(i) significant cycle‐to‐cycle variation in tumor motion was observed in both patients

(ii) For Pt#l, the tumor centroid showed good correlation with diaphragmatic motion. For Pt#2, this correlation was relatively poor

(iii) Pt#l did not exhibit significant tumor rotation/deformation. In Pt.#2, the trajectories of two points on the tumor showed maximum deviations of ∼8 mm (superior‐inferior) and 3.4 mm (anterior‐posterior), indicating non‐negligible rotation/deformation likely due to the influence of the adjacent cardiac wall.

Conclusion: To our knowledge, this is the first demonstration of MRI for real‐time imaging of lung cancer. The incorporation of these strategies into MRI+Linacs offers image‐guidance capabilities that are not possible using current techniques: (i) soft‐tissue‐based rather than surrogate‐based monitoring (ii) no fiducial implantation or imaging dose (iii) arbitrary slice selection and (iv) ability to monitor complex motion.
WE‐C‐201C‐01: Perspective on the Developing Modalities for Breast Cancer Imaging
Authors: Karellas A , Vedantham S
Published: August 2010

Perspective on the Developing Modalities for Breast Cancer Imaging Digital mammography has already become the new standard, replacing screen‐film for breast cancer screening, and for diagnostic work‐up of suspicious findings. New digital imaging technologies may use x‐ray beam characteristics such as tungsten target, silver filtration, and higher kVp; in ways that represent a departure from the long established screen‐film techniques. Representing a logical evolution from two‐dimensional to tomographic and 3D imaging of the breast, breast tomosynthesis and dedicated breast CT are currently investigated as potential replacements or adjuncts to mammography. Mammography (screen‐film or digital) is the single most effective tool for the detection of occult breast cancer with an overall sensitivity as high as about 85% for older women and about 60% or lower for women under the age of 50 years (Rosenberg RD et al. Radiology. 1998;209:511–8, Pisano E et al. N. Engl. J. Med. 2005;353: 1773–83). Attempts to increase sensitivity have included the use of intravenously injected (IV) contrast with digital mammography, tomosynthesis or breast CT but these efforts are in the research stage. With improved hardware and image acquisition techniques, the role of IV contrast injected MRI is gradually expanding as a diagnostic tool, and it is also recommended for screening of high risk patients, due to its high sensitivity. Ultrasound, a well established modality for diagnostic work‐up is evolving from the conventional pulse echo‐based approach to elasticity imaging and ultrasound CT of the breast. Breast scintigraphy with a dedicated camera is now in clinical use and it receives much attention as an adjunct to mammography. Other technologies that include diffuse optical tomography as a stand‐alone modality or in conjunction with MRI or with x‐ray imaging are currently under investigation. We are likely to see an increasing use of alternative imaging approaches in conjunction with mammography, ultrasound and MRI, the three essential modalities for breast cancer detection and for diagnostic work‐up of positive findings.

Learning Objectives:

1. Appreciate recent advances in the physics and engineering in x‐ray detector technology that contributed to the development of digital mammography, tomosynthesis and dedicated breast CT.

2. Recognize the potential quantitative applications and important limitations of the x‐ray based breast imaging modalities.

3. Appreciate recent technological developments in current clinical non‐x‐ray modalities such as MRI and ultrasound and their increasingly important role in breast cancer imaging.

4. Gain perspective on some emerging modalities such as optical diffuse tomography and their potential role in the detection and diagnosis of breast cancer.
WE‐C‐201C‐02: Advances in Breast MRI: Clinical and Scientific Perspective
Authors: Schnall M
Published: August 2010

Technology for Breast MRI continues to evolve. A major focus of technical development has been to improve the ability to manage the trade‐off between spatial and temporal resolution in the dynamic contrast enhanced series that is central to breast MRI. Improvement of coil technology, more aggressive use of parallel imaging and the application of novel K — space sampling approaches are all being implemented. In addition, there is significant work related to incorporation of diffusion and spectroscopy data into the breast MRI examination. Finally, there are many academic and commercial groups developing methods of analyzing the multidimensional data acquired as part of an MRI exam to predict diagnosis, characterize cancer and predict treatment response.

Research sponsored by Siemens.

Learning Objectives:

1. Understand methods to improve breast MRI techniques

2. Understand the potential role of diffusion and spectroscopy in Breast MRI

3. Understand the clinical roles for breast MRI
WE‐C‐201C‐03: Tissue Discrimination Methods in Mammography and Tomosynthesis
Authors: Maidment A D A
Published: August 2010

Breast imaging is undergoing a revolution towards quantitative tomographic methods. There is active research and development of both dedicated computed tomography, and digital breast tomosynthesis (DBT) or limited‐angle computed tomography. Numerous clinical DBT trials are in progress and two systems are available in Europe. DBT has been shown to have clear value in increasing the conspicuity of lesions by removing overlaying structures present in mammograms.

We have recently installed a Hologic Dimensions DBT prototype that has been modified to allow contrast‐enhanced (CE) imaging. Both dual‐energy and temporal CE‐DBT are under investigation. Current research is focused on the development and validation of precise image‐derived metrics (image‐based biomarkers) with physiologically relevant parameters, including treatment response to interventions and clinical outcomes. Our work continues with technique optimization, reconstruction algorithm development, motion correction, and scatter and other signal dependent corrections.

With appropriate corrections, CE‐DBT can accurately quantify contrast agent uptake. In previous work, we have shown that CE‐DBT can provide results concordant with dynamic contrast‐enhanced MR in a group of 17 women with known or suspected breast cancer. As such, we believe that CE‐DBT has potential in the same roles as MR. These roles include screening high‐risk populations, staging cancer patients through identification of multifocal, multicentric and contralateral cancer, and assessment of tumor response to neoadjuvant chemotherapy.

Finally, there is a revolution in radiographic contrast agents. Taking inspiration from nuclear medicine and optical imaging, we are seeing an increase in research into radiographic contrast agents. These developments are made possible given recent advances in nanoparticles such as designer liposomes, polymersomes and nanospheres. Both blood‐pool and targeted contrast agents are under investigation.

Learning Objectives:

1. Review the state‐of‐the‐art in DBT system design

2. Describe adaptations necessary to perform quantitative CE‐DBT

3. Exemplify the clinical applications of CE‐DBT

Research support for this project has been provide in part by XCounter AB, General Electric Health Care, and Hologic Corp, in addition to the Komen for the Cure Foundation, the Department of Defense and the Radiological Society of North America.
WE‐C‐201C‐04: Breast Ultrasound Tomography: Clinical Results at the Karmanos Cancer Institute
Authors: Duric N
Published: August 2010

Ultrasound is a widely accepted imaging modality that has gained a firm and universal foothold in medical imaging. However, in the case of breast imaging, it serves mainly an adjunctive role. It is not on the front lines of screening and diagnosis because of limitations that include operator dependence, small field of view, and relatively poor image quality compared to other imaging modalities. Research to overcome these limitations began over 30 years ago and has led to the development of ultrasound tomography (UST), an operator independent technique for imaging the breast. Initially, limited computational power and slow data acquisition prevented rapid development of this method. However, in recent years, much progress has been made and UST is now poised to appear on the clinical stage.

We report on the performance of an experimental UST prototype at the Karmanos Cancer Institute (KCI) in Detroit, MI. Clinical data were collected under an IRB‐approved protocol from subjects recruited at KCI's Alexander J. Walt Comprehensive Breast Center. The data were used to generate stacks of cross‐sectional reflection images as well as images of the acoustic parameters of sound speed and attenuation. The combination of these images reveals major breast anatomy, including fat, parenchyma, fibrous stroma and masses. Fusion imaging, utilizing thresholding, is shown to visualize mass characteristics and facilitate differentiation of cancer from benign masses. These initial results indicate that operator‐independent whole‐breast imaging and the detection and characterization of cancerous breast masses are feasible using UST techniques. Clinical applications ranging from risk assessment to detection and treatment monitoring are discussed. This presentation will provide an overview of how UST is applied to breast imaging, ranging from theory to clinical use.

Learning Objectives:

1. Understand how tissue properties can be measured with UST

2. Understand the differences between UST and other breast imaging modalities

3. Understand the issues related to clinical applications of UST.
WE‐D‐BRB‐04: Evaluation of MatriXX in Peripheral Dose Regions for IMRT and VMAT Dose Verifications
Authors: Han Z , Ng SK , Bhagwat M , Lyatskaya Y , Zygmanski P
Published: August 2010

Purpose: To evaluate MatriXX and to develop a MatriXX correction technique for IMRT and VMAT dose verifications in peripheral (low) dose regions. Method and Materials: We compare a 2D ion chamber array — MatriXX with a reference Exradin A12 ion chamber in solid water phantoms. Comparisons were performed for a number of cases that involve different gantry and MLC dynamics including open beam, sweeping MLC gap mimicking IMRT, oscillating sweeping MLC gap mimicking VMAT, as well as clinical IMRT and RapidArc plans. Results: We have identified four types of error associated with MatriXX dose in peripheral regions: (1) Pixel‐dependent positive bias which is independent of dose level, cumulative over time, and dependent on operation parameters; (2) Over‐response to scattered beams by 2.0% on average for regions 2 – 15 cm from the field edge where patient and collimator scatters dominate; (3) Angular dependence up to 11% and 8% for primary and scattered (peripheral) radiations, respectively; (4) Round‐off error due to insufficient precision in conversion of raw signals to MatriXX software data for very small doses. In order to extend the application of MatriXX to peripheral regions, we have developed a method to correct for these errors. With corrections, MatriXX shows good agreement with A12 in all cases involving different gantry and/or MLC dynamics as well as the clinical plans. For both primary and peripheral doses, MatriXX shows good dose linearity down to about 1 – 2 cGy with an accuracy of within 1% of the local doses. Conclusion: Inherent dose errors of MatriXX were identified and thoroughly studied. A correction method was developed and successfully tested by a series of experimental and clinical plans. Therefore, we have demonstrated that, with proper corrections, MatriXX can be used for accurate 2D peripheral (low) dose measurements.
WE‐D‐BRB‐05: Dose‐Rate Constant Determination of the Xoft Axxent Electronic Brachytherapy Source Using Spectroscopic Methods
Authors: Pike T , Moga J , Davis S , DeWerd L
Published: August 2010

Purpose: To use spectroscopic methods to determine the dose‐rate constant (DRC) of the Xoft Axxent® miniature x‐ray source. Method and Materials: Analytical methods have been used to determine the DRC of brachytherapy sources using spectroscopic methods. The method developed at Yale University (Med. Phys. 28, 86–96, 2001) was used with the Axxent® spectrum to calculate the spectroscopic DRC of the Axxent® source. While this method is useful its limitations are pronounced when applied to sources of considerable diameter, such as the Axxent® source. When source size increases the point‐ and line‐source approximations are insufficient for buildup or attenuation calculations. This investigation modifies the original method to account for source diameter and calculates the DRC with measured and Monte Carlo (MC) generated spectra. The Axxent® spectrum was measured at 1 m in air with a low‐energy germanium detector. The spectrum was corrected for detector response and air attenuation to obtain the emitted spectrum in vacuum. Results: The measured spectrum agreed well with the MC generated spectrum. Slight differences in the spectra can be attributed to the energy resolution of the detector. The spectroscopic DRC calculated with the original method produced DRCs that were up to 23% low when compared to the MC calculated DRC. The modified method corrected the attenuation and buildup calculations to account for source diameter and produced DRC that were within 5% of the MC calculated DRC. Conclusion: It was possible to measure and correct the photon spectrum of the Axxent® source. The original method for analytically determining the spectroscopic DRC works well for sources of very small diameter, but is insufficient when applied to sources of considerable diameter. The method must be modified to correct the attenuation and buildup determination in the monoenergetic DRC determination.

Conflict of Interest: This research was partially sponsored by Xoft, Inc.
WE‐D‐BRB‐07: Wide Field Array Calibration Dependence on Beam Shape Stability
Authors: Simon T , Simon W , Liu C
Published: August 2010

Purpose: To simulate the effects of beam symmetry instabilities on detector array calibrations and explore compensation methods during actual calibration with a linear accelerator (LINAC). Methods: The array calibration method that was investigated is known as wide field (WF) calibration. With this method, a linear array [y‐axis (65 detectors) of the IC PROFILER™; Sun Nuclear Corporation, Melbourne, FL USA] requires three calibration measurements (α, θ, and λ) using a radiation field that is larger than the array. Measurement θ is a 180° rotation from α, and λ is a physical shift by one detector from θ. The relative detector sensitivities are then determined through ratios of detector readings at the same field locations. This method results in error propagation that is proportional to the array size. The WF calibration postulates that the dose distribution is constant for each calibration measurement. Postulate violations were quantified by applying a sine shaped perturbation (of up to 0.1%) to a calibration measurement and determining the error relative to a baseline calibration. Actual postulate violations were limited by using a continuously on beam and mechanized array movement during θ and λ. Symmetry is more stable for a continuously on beam. Results: Simulated perturbations to θ or λ resulted in calibration errors of up to 2%, while α was relatively immune (<0.1% error). Wide field calibration error on a LINAC with similar symmetry instabilities was (±) 1.6%. Using a continuous beam during θ and λ reduced the calibration error to (±) 0.68%. Conclusion: This work increased the reproducibility of WF calibrations by limiting the effect of measurement perturbations due to LINAC symmetry instabilities. The same technique would work for any array using WF calibration. Conflict of Interest: Research sponsored by Sun Nuclear Corporation.