bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐D‐T‐617‐07: Development of An Independent Audit Device for Remote Verification of 4D Radiotherapy
Authors: Shoales J , Followill D , Ibbott G , Balter P , Tolani N
Published: June 2005

Purpose: To develop a 4D quality assurance device for remote verification of dose delivery at institutions participating in NCI‐sponsored clinical trials that require the use of respiratory motion mitigation techniques. Method and Materials: A plastic reciprocating platform was designed and constructed to simulate respiratory motion in two dimensions and to evaluate the reproducibility of 4D image acquisition and dose delivery. An anthropomorphic lung phantom was used with the platform to assess imaging characteristics, to provide CT data for radiotherapy treatment planning and for dosimetric evaluation. The lung phantom used radiochromic film in three major planes and TLD centered in the GTV. Static, simulated free‐breathing, breath‐hold, 4D phase‐sorted and respiratory‐gated CT image sets were acquired using the programmable moving platform. A volumetric comparison of internal phantom structures assessed imaging reproducibility. Conformal 6 MV photon treatment plans were created for free‐breathing ITV and respiratory‐gated techniques using Pinnacle. The reproducibility of the 4D irradiation techniques was analyzed through comparisons to calculated treatment planning dose data. Criteria for evaluation were derived from TG‐53 with a range of 5%/3mm to 7%/7mm. Results: CT image analysis showed mean(SD) tumor volumes [cm3] of 24.5(0.4), 23.1(1.6), 24.1(1.6) for static, 4D phase‐sorted and free‐breathing techniques, respectively. Initial evaluation of the ITV technique showed that the ratio of TLD/Pinnacle dose was 0.972. Axial film analysis with binary agreement maps showed ranges of 85.5% to 96.4% and 81.0% to 95.4% agreement within the 5%/3mm to 7%/7mm criteria range for gated and ITV techniques, respectively. Axial profile analyses through the tumor center indicated regions of disagreement between the measured dose data and calculated data within the 5% criterion. Conclusion: The 4D phantom QA system can be used as an independent audit device for dosimetric evaluation of 4D radiotherapy techniques. Work supported by PHS grant CA10953 and CA81647 awarded by the NCI.
WE‐D‐T‐617‐08: Cone Beam Optical CT Scanner for 3D Dosimetry
Authors: Miller J , Adamovics J , Dietrich J
Published: June 2005

Purpose: To evaluate the performance of a cone beam optical CT scanner and to evaluate use of the scanner with a 3D solid radiochromic dosimeter. Method and Materials: The operating characteristics of a cone beam optical CT scanner were investigated using phantoms and solid dosimeters. The scanner acquires projection images (12 degree fan angle, 9 degree cone angle) during a single 360 degree rotation of a sample. 3D Images are reconstructed using Feldkamp backprojection with a Hamming filter. Background attenuation coefficients are removed by subtracting reference (pre‐irradiation) images from data (post‐irradiation) images prior to reconstruction. Reconstructed images have isotropic 2 mm, 1 mm, or 0.5 mm voxel dimensions in a 10 cm cube. Spatial resolution and image distortion were evaluated with a wire phantom and holes drilled in a solid dosimeter. Solid dosimeters were irradiated with a rectangular field and a complex Tomotherapy field. Profiles from scanned images were compared to profiles in calculated dose maps. Results: Reconstructed images of the geometry phantoms showed no spatial distortions. Artifacts are similar in appearance to sampling and beam hardening artifacts common in X‐ray CT. Attenuation coefficients in neutral density liquids are linear with respect to the spectrophotometer readings. Line profiles through calculated and measured dosemaps show qualitative agreement. Scanning times varied from 3 to 9 minutes. Reconstruction times varied from 2 to 20 minutes. The total time to scan a dosimeter was less than 1 hour. Conclusion: The optical CT scanner and solid dosimeter form a promising 3D dosimetry tool. Geometric accuracy, spatial resolution and imaging times are within clinical requirements Conflict of Interest: This research is funded by Modus Medical Devices Inc. and Heuris Pharma LLC. The authors have a commercial interest in the scanner and/or the dosimeter.
WE‐D‐T‐6E‐02: A Clinical Planning Tool for Optimization of Intensity Modulated Radiotherapy Parameters
Authors: Das S , Yin F
Published: June 2005

Purpose: To develop a clinical tool that incorporates novel strategies to optimize all involved parameters in IMRT treatment planning: (a) the number of beams, (b) beam orientations, and (c) fluence maps. Method and Materials: An IMRT planning tool was developed in the MATLAB (The MathWorks, Natick, Ma.) environment with the capability of interfacing to a commercial treatment planning system. It consists of three components: image segmentation, parameter optimization, and isodose and dose‐volume histogram (DVH) display. The parameter optimization tool starts with a large number of user input feasible beam orientations and sequentially eliminates beams. Beam elimination is terminated when unacceptable deterioration of the critical structure DVH is encountered. The algorithm uses the novel strategy of forcing the sequential dose distributions to imitate, as best as possible, the dose distribution with all beam orientations. This not only ensures a clinically acceptable final dose distribution but also greatly speeds up the computation time by pre‐knowledge of the expected dose at every point in the patient body. This process is illustrated in a typical prostate cancer IMRT plan with prescription doses to prostate and seminal vesicles expanded by 1cm, and more stringent than usual constraints to rectum, bladder, and femoral heads. Results: For the case illustrated, the parameter optimization tool sequentially reduced the number of selected beams from a user input 36 to 7 beams. Reducing the number of selected beams below 7 resulted in abrupt deterioration of the critical structure DVHs. In the tested cases, the resulting dose distributions are clinically excellent owing to the novel strategy of imitating the dose distribution with all beams. Conclusions: The clinical tool presented here serves an important purpose by promoting the extraction of the full benefit of IMRT by optimizing all involved parameters. It can interface with commercial treatment planning systems to enhance their functionality.
WE‐D‐T‐6E‐03: Development of a Fast Algorithm for Classifying Data Points as Inside Or Outside a Polygon
Authors: Fox C , Dempsey J
Published: June 2005

Purpose: Adaptive IMRT with image guidance requires rapid computation of dose for frequent re‐optimization. As patient geometry changes throughout treatment, millions of voxels must be continually associated with the various radiotherapy structures that are delineated for the patient. In beamlet dose models it is advantageous to identify only those voxels which can receive significant dose. Both of these tasks rely on a rapid point‐in‐polygon classification algorithm, which has not been improved since Siddon's work in the 1980s. We present a new algorithm that significantly outperforms the standard algorithm. Method and Materials: A point‐in‐polygon classification algorithm was developed. Current algorithms spend substantial computational time calculating cross products between polygon vertices and grid points to establish intersection points. We present a method where entire rows of dose points are classified together using a single ray. Further, we avoid computing cross products by translating the structure polygons so that rays are cast along the +X axis (assuming polygons lie in X‐Y planes). Crossings are observed where vertices display a change in Y coordinate sign. This algorithm was compared to the Siddon algorithm, with our in‐house treatment‐planning system for both associating voxels with radiotherapy structures and targets and for voxel down sampling using stereographic projection. Results: Our new point‐in‐polygon technique shows considerable decrease in calculation times. 1.7 million voxels classified in 14 structure polygons produced a 100 fold decrease (2.1 vs. 213 s on a 3.6 GHz p4 PC) in computational time. Voxel down sampling using stereographic projection in the computation of 1,466 beamlets produced a 1.8 fold decrease (185.2 vs. 334.5 s) in computational time. Conclusion: Significant improvement in performance over the existing cross‐product method for polygons has been observed with the new algorithm. However, parallel computation is still currently required to produce a typical IMRT treatment plan in less than one minute.
WE‐D‐T‐6E‐06: Implementation of a Fast Incremental Algorithm for Voxel Radiological Path Determination
Authors: Fox C , Dempsey J
Published: June 2005

Purpose: Performing adaptive image‐guided IMRT will require rapid computation of dose for frequent IMRT fluence map optimization (FMO). Patients should not have to tolerate waiting more than a few minutes for a new IMRT treatment plan. Most beamlet dose models in IMRT FMO expend considerable time performing voxel based ray‐tracing computations. Improvements in voxel based ray‐tracing algorithms have not been presented in the radiation therapy literature since the seminal work of Siddon in the 1980s. We present an algorithm that significantly outperforms the voxel ray‐tracing algorithm of Siddon when applied to density scaled radiological path length calculations in patient voxel space for beamlet dose computation. Method and Materials: An incremental voxel ray tracing algorithm that simultaneously computes voxel indices and ray‐voxel intersections was developed. The majority of the computational time required by the standard Siddon algorithm was found to be in the concatenation of the intersection parameters (α's) into a single unique set and the conversion of the calculations of the voxel indices from floating point to integer values. This algorithm was compared, as components of our in‐house IMRT planning system, to the standard Siddon technique. The test case had 1.7 million total voxels on a 2.5 mm isotropic dose grid and the 1,466 beamlets in the IMRT plan intersected an average of ∼15,000 voxels per beamlet. Results: Use of the new algorithm for the test case demonstrated a 2.7 fold increase in computational speed on average over the Siddon algorithm. Conclusion: The new algorithm provides a significant improvement in voxel ray‐tracing performance over the standard Siddon algorithm. However, parallel computation is still currently required to perform the computation of a typical IMRT treatment planning rapidly enough for adaptive IMRT FMO.
WE‐D‐T‐6E‐08: Iterative Regularization of the IMRT Optimization Problem
Authors: Carlsson F , Forsgren A
Published: June 2005

Purpose: To generate the optimal deliverable plan resulting from a beamlet‐based IMRT optimization approach followed by conversion into machine parameters. This is achieved by utilizing iterative regularization to create smooth profiles. Method and Materials: Our iterative regularization scheme utilizes a quasi‐Newton method with the identity matrix as initial Hessian estimate. The optimization process is terminated before jagged profiles occur, but it is run long enough to generate a dose distribution close to the optimal one. We discuss the one‐to‐one correspondence between our quasi‐Newton method and a preconditioned conjugate gradient method, and use conjugate gradient theory to predict the behavior of our approach. Results: To verify our theoretical analysis, we study the performance of our method on a five beam prostate case with dose‐volume objectives and bounds on the beamlet weights. The plan is optimized using ORBIT. For this case, the jaggedness of the beam profiles increase with iteration number while the objective value decreases rapidly in the first iterations. The objective value after conversion with 50 segments attains a minimum after 40–50 iterations, indicating that further optimization, apart from increasing the calculation time, deteriorates the plan quality. Conclusion: The optimization method considered has the appealing properties of a conjugate gradient method, with fast decrease in the objective function and smooth profiles during the first iterations. In addition, the quasi‐Newton method is preferable when including constraints. By terminating the optimization after relatively few iterations, we generate smooth fluence profiles that, after conversion, outperform the plan obtained by converting the jagged optimal fluence profiles. Our opinion is that iterative regularization is faster and easier to perform than other regularization techniques, and more rigorous than filtering methods. Further refinement of the treatment plan would require direct optimization of the segments. Conflict of Interest: Authors are stockholders in RaySearch Laboratories.
WE‐D‐T‐6E‐09: Machine Learning for the Geometry/Intensity Relationship in IMRT
Authors: Lu R , Radke R , Hong L , Chui C , Xiong J , Yorke E , Jackson A
Published: June 2005

Purpose: We present a feasibility study for breast IMRT showing that, given enough training examples of patient CT images and corresponding plans, machine learning algorithms can predict a good plan for a new patient's geometry directly, without explicit numerical optimization and dose calculation. Method and Materials: From an expert's clinical plans for 22 patients, the features determining the optimized intensities were identified. We applied four machine learning algorithms (nonlinear regression, support‐vector machines, k‐nearest‐neighbors, and barycentric interpolation) to automatically discover the relationship between the beamlet intensities and the input features on CT images. This was learned on a beamlet‐by‐beamlet basis to decrease the input and output dimensionality. Results were evaluated by comparing the predicted intensity and dose distributions to those from the clinical plan (ground truth). Results: First, the plan for each patient was learned from all remaining patients' plans. The average beamlet error (averaged over all patients) for the best method (support‐vector) was −0.16%, with an average absolute error of 2.07%. D95 and D05 (97.1% and 105.3%, respectively), and V95 (97.6%) values for the support‐vector method differed insignificantly from the expert's plans at the 5% significance level. A second experiment using smaller training sets and larger testing sets yielded an average error of 0.22% and an average absolute error of 2.27%, respectively, indicating that a few well‐selected training datasets are adequate to learn the relationships. Plans could be predicted in <10 seconds. Conclusion: While the breast IMRT problem is relatively simple, this work indicates that machine learning has potential to ease the computational burden of IMRT in more complex sites (e.g. prostate, head and neck), where reducing the time for optimization parameter adjustment would be clinically beneficial. Funded in part by National Cancer Institute grant 5P01CA59017‐13 and the NSF Center for Subsurface Sensing and Imaging Systems, grant EEC‐9986821.
MO‐A‐I‐618‐01: What the Medical Physicist Needs to Know and Do in Stereotactic Breast Biopsy
Authors: High M
Published: June 2005

Both diagnostic and therapeutic applications of stereotactic mammography will be discussed. An overview of the American College of Radiology's Breast Biopsy Accreditation Program will be presented along with the recommendations of the associated ACR Stereotactic Breast Biopsy Quality Control Manual. Patient dose issues will be covered, including manufacturer recommendations for image receptor exposure levels, guidance for establishing a technique chart for 512 and 1024 images, and advice on identification of over‐ and under‐exposed images, and the influence of kVp and mAs on dose and image quality. The application of stereotactic digital imaging to interstitial breast brachytherapy will be discussed.

Educational Objectives:

1. Review ACR Accreditation recommendations for QC testing of stereotactic breast biopsy units.

2. Become familiar with recognizing proper exposure levels and with setting up technique charts for appropriate image quality.

3. Become familiar with the application of stereotactic digital image to interstitial breast brachytherapy.
MO‐A‐I‐617‐02: Image Reconstruction Strategies for Positron Emission Tomography
Authors: Levin CS
Published: June 2005

This presentation gives an overview of image reconstruction strategies for PET. We will discuss two classes of PET reconstruction algorithms: analytical and iterative. Analytic approaches model the acquisition process as an analytic transform operator and treat both the measurement and reconstructed image as continuous functions. Analytical image reconstruction algorithms are based upon direct computation of the inverse transform formula. Iterative techniques consider the above functions as discrete and may incorporate statistical methods and accurate system models to determine the best solution. Iterative approaches may be more appropriate for photon count limited data and for PET systems with non‐standard geometry. The analytic methods are typically more computationally efficient. We will focus only on those techniques implemented in the current state‐of‐the‐art commercial PET systems. Educational Objectives:

1. To understand the problem of image reconstruction in PET.

2. To become acquainted with analytic and iterative image reconstruction strategies for PET.
MO‐A‐I‐611‐01: Recent Advances in CT: MSCT and Highspeed Scanning
Authors: Goldman L
Published: June 2005

This lecture begins the CT refresher course series by reviewing fundamental concepts associated with CT image quality in axial and helical scanning, then focuses on principles of multislice CT. Some concepts associated with single‐slice helical scanning are briefly reviewed as an introduction to MSCT helical scanning concepts. The attendee will be familiarized with:

1. properties of the CT scan process affecting image quality, including sampling and scatter

2. traditional and new methods to improve sampling

3. principles of multislice CT scanning

4. MSCT detectors systems

5. reasons for potentially increased radiation doses in MSCT

6. Concepts associated with helical scanning and pitch in MSCT

7. Benefits of MSCT.

8. Current generations of MSCT systems

9. Improvements in gantry rotational speed and associated x‐ray tube design
MO‐B‐T‐6C‐01: Current Techniques for Image Registation and Data Fusion
Authors: Kessler Marc L
Published: June 2005

Acquisition of anatomic and functional data from magnetic resonance imaging and nuclear medicine studies is becoming increasingly common for patient management in radiation therapy. These data can help improve tumor localization and normal tissue delineation for treatment planning and may provide information about treatment efficacy during or after a course of radiotherapy. Time series data from serial and 4D CT before and during the treatment course, including CT data acquired in the treatment room at the time of treatment, is also helping to estimate motion and shape changes of relevant anatomy. In order to fully realize the benefits of these data, the different imaging studies must be registered to a single coordinate system, typically that of the treatment planning CT. The geometric transformation that is used to register the different image data can range from simple rotate‐translate to account for differences in patient orientation to 3D or 4D deformation models to account for changes in internal anatomy during and over the course of therapy. Once mapped to a common coordinate system, data derived from the various studies such as anatomic outlines and computed dose can be integrated or fused to help construct a more complete and accurate representation of the patient. A variety of interactive and automated techniques exist to carry out these steps. The general strategy for registration algorithms is to minimize a metric that measures the geometric mis‐registration between pairs of datasets. Metrics can be derived from extracted geometric structures or from the image intensities directly. Once registered, computer graphics and algebraic techniques are used to combine data and create integrated displays. This lecture will focus on the mechanics of registering and displaying data from different imaging studies using distinct modalities or a single modality over time. A taxonomy of the methods currently implemented in commercial and research treatment planning systems will be described. Methods for display and interaction with multimodality data will also be presented. The overall goal is to provide the basic knowledge required to understand what is happening “under‐the‐hood” of the different registration systems one might encounter in the clinic.

Educational Objectives:

1. Understand the basic mechanics of image registration and data fusion.

2. Understand the different registration algorithms used in commercial and research treatment planning systems.

3. Understand the different techniques used to combine, display and interact with multimodality image data.
MO‐B‐T‐6B‐01: Quality Assurance of Radiation Treatment Planning Systems: A Significant Challenge?
Authors: Van Dyk J
Published: June 2005

During the last decade there has been a technological revolution in radiation oncology. Enhanced use of imaging combined with computer‐controlled methods of dose delivery provides a capability of escalating tumor doses without increasing morbidity. A pivotal component of this modern technology is the computerized radiation treatment planning system (RTPS) which is used to develop optimal treatment techniques for individual patients. Modern RTPSs make increased use of patient images, possibly from various imaging modalities, enhanced 3‐D displays, more sophisticated dose calculation algorithms, more complex treatment plan evaluation tools, combined with the generation of images which can be used for treatment verification. In addition, the implementation of intensity modulated radiation therapy (IMRT) has added a further complexity to the RTPS and this is combined with automated optimization software which is essential if IMRT is going to be used to its best advantage. In recent years, various national and international organizations have developed reports that have made recommendations regarding the commissioning and quality assurance (QA) of RTPSs. In 1998, AAPM TG53 published guidelines for users and vendors on QA for radiation therapy planning. In 2000, the International Electrotechnical Commission (IEC) produced a report (IEC 62083) specifically on safety requirements for manufacturers of RTPSs. In 2004, both the International Atomic Energy Agency (IAEA) and the European Society of Therapeutic Radiation Oncology (ESTRO) published reports on commissioning and QA of RTPSs. Furthermore, the IAEA is presently in the process of developing a protocol for the acceptance testing of RTPSs. In 2005, the Netherlands Commission of Radiation Dosimetry also produced a report on QA of RTPSs. All of these reports indicate that a thorough commissioning of a modern 3‐D RTPS has become a daunting task. This refresher course will look at some of these reports and review issues associated with the commissioning and quality assurance of a modern RTPS.

Educational Objectives:

1. To demonstrate the importance of QA of RTPSs by reviewing significant treatment errors associated with their use.

2. To review the major functionality of a modern RTPS.

3. To highlight and summarize various reports that have made recommendations regarding commissioning and QA of RTPSs.

4. To discuss accuracy requirements and criteria of acceptability of the modern RTPS.

5. To summarize acceptance testing procedures as proposed by the IAEA for a modern RTPS.

6. To provide an overview of commissioning a modern RTPS.

7. To provide an overview of the QA associated with a modern TPS.

Conflict of Interest: One of the QA tools described in this presentation was developed by the author and is marketed by Modus Medical Devices Inc.
MO‐E‐T‐6E‐03: Dose‐Volume Modeling of Treatment Outcome
Authors: Jackson A
Published: June 2005

Since the landmark compilation of estimates of normal tissue partial volume tolerance doses and LKB model parameters by Emami et al. [1] and Burman et al. [2] in 1991, phase I dose escalation studies utilizing 3D conformal and IMRT techniques carried out in the last 10‐15 years have provided quantitative data on dose volume dependencies of complication probabilities. For some organs the use of local and global function tests have provided data from objective endpoints which have been used to assess functional damage arising from irradiation of normal tissue. In concert with these developments, more rigorous statistical methods of model fitting and data analysis have been adopted. Improvements in our understanding of the dependence of complication probabilities on partial volumes of normal tissues irradiated will be described, including models for lung, liver, parotid, and rectal complications. Recent data from studies of radiation pneumonitis, including data suggesting variation in sensitivity of upper versus lower lung will be presented. Several limitations of current clinical data will be discussed: numbers for severe complications in single institution trials are usually small, and surrogate (lower priority) endpoints are often used, these have higher incidence and allow modeling with greater confidence, but are of less clinical relevance; use of fixed treatment techniques leads to correlations in values of dose‐volume variables in the patient population, making discrimination between models difficult; effects of organ motion are difficult to remove post‐facto and methods for accounting for them in outcome data in their infancy. To overcome poor statistics, merging of data from different institutions will be required. The difficulties of carrying out this task will be outlined.

Educational Objectives:

1. To understand the advances made in our knowledge of dose‐volume dependencies of normal tissue complication probabilities (NTCP) in the past 10–15 years.

2. To understand the limitations of our current knowledge of NTCP, and future work necessary to overcome these limitations.
TU‐B‐T‐6C‐01: MRI and MRSI in Radiation Therapy Treatment Planning
Authors: Xing L
Published: June 2005

Radiation therapy is an image‐guided procedure whose success depends strongly on the image modality used for treatment planning and the level of integration of the available imaging information. Advancement in intensity modulated radiation therapy (IMRT) has provided an unprecedented means to produce highly conformable dose distribution while sparing sensitive structures, which calls for better imaging tools for tumor target definition and for the management of inter‐ and intra‐fractional organ motion. Clinically, MRI imaging is an important anatomical imaging modality and posses superior soft tissue contrast. It has played a pivotal role in radiation oncology practice and made significant impact in cancer diagnosis, staging, treatment planning, and monitoring of therapeutic response. In the last decade, much progress has been made in high field MRI and in the development of new MRI contrast agents. MR spectroscopic imaging (MRSI) has also emerged as a powerful noninvasive tool for providing the type of metabolic and physiology information needed to identify biologically conformal dose distributions for biologically conformal radiation therapy (BCRT). This presentation will provide an overview of the fundamental principles of MRI and MRSI imaging and inform the audience with some of the new developments in the field and their practical implications to radiation therapy. Examples of these applications in a few disease sites will be presented. Finally, issues related to the quality assurance of MRI/MRSI and BCRT will also be addressed.

Educational Objectives:

1. Review MRI and MRSI physics.

2. Illustrate the steps involved in integrating MRI and MRSI into treatment planning process.

3. Introduce MRI/MRSI image fusion techniques (including deformable image registration).

4. Provide an overview on recent advances in high field MRI and MRSI.

5. Update on the new development of MRI contrast media, including nanoparticles‐based contrast agents.

This work was supported in part by NCI 5R01 CA98523‐01. Therapy Continuing Education Course Room 6B.
TU‐B‐T‐6B‐01: Transition to Heterogeneity Corrections
Authors: Klein E , Stevens C
Published: June 2005

With the publication of the AAPM's TG‐65 report on inhomogeneity corrections for photon beams, physicians and physicists must clearly understand how implementation of such corrections impact dose prescriptions. The TG report details the physics of the heterogeneity algorithms, methods to evaluate these prescriptions, limitations, and most importantly, how to implement. The report gives clear recommendations as to the dialogue needed before implementation takes place. A clinic should perform simultaneous plans by planning and treating the patient with no corrections applied. A simultaneous plan is generated that applies the correction ‘after the fact’, thereby leaving the homogeneous (and therefore given doses) intact. This will educate the staff as how prescriptions may (or may not) be altered according to the differences observed. In addition, planning volume margins may be affected according the algorithms' ability to calculate penumbra in the presence of inhomogeneous media, particularly lung. In addition, classic beam arrangements may need to be scrutinized due to the impact of increased exit dosing observed with corrections applied. MDAH found that implementation of inhomogeneity corrections was fairly easy to accomplish, even in a busy clinic. Accounting for heterogeneity resulted in better PTV coverage by changing beam weighting, without significantly changing isocenter dose. The distance from PTV to block edge also increased in some situations. Failure to account for tissue heterogeneity could lead to dose calculation errors, particularly to the PTV, which often results in significant underdosing. Accounting for tissue heterogeneity using many commercially available algorithms changes the dose to the PTV much more than will the future use of Monte‐Carlo‐based dose calculation algorithms. Heterogeneity corrections are particularly important when using IMRT, particularly in lung cancer treatment. They concluded that the benefits of accounting for tissue inhomogeneity vastly outweigh the minor difficulties with its implementation, will result in more accurate calculation of dose distributions, and hopefully in better outcomes for patients. The use of heterogeneity corrections also allowed the use of higher energy photon beams in 3D planning, because of greater confidence in dose calculation accuracy. This course will give direction along with caveats in applying inhomogeneity corrections from the perspective of physics and physicians. In addition, there will be a review of current algorithms commercially available, along with a historical perspective on how various stages of algorithms impacted the radiotherapy community on evaluating and using inhomogeneity corrections.

Educational Objectives: The physicist will learn ‐

1. the details of TG‐65

2. details on commercially available algorithms including limitations

3. the MDAH approach to implementing corrections

4. a historical perspective of studies on evaluating corrections

5. TG‐65's recommendation plan for a clinic's implementation.
TU‐C‐T‐617‐04: Beam Configuration of Photon‐Based Stereotactic Radiosurgery
Authors: Wu X , Dooley J , Yang J , Persaud V , Bossart E , Shao H , Both J , de la Zerda A , Schwade J , Markoe A
Published: June 2005

Purpose: Unequivocally, the experience of Gamma knife has set a solid notion pertaining to the definition and the dosimetric requirement of radiosurgery. Any newer, post‐Gamma knife, radiosurgery system has to demonstrate comparable targeting precision and sharp dose gradient characteristics. Statistics shows that the total of number of beams used in Cyberknife treatment is often less than 200. Herein, we present a study to evaluate the dose distribution characteristics comparing with that of the traditional photon‐based radiosurgery. Material and Method: An experimental beam path with beam positions (notes) distributed in 2Π solid angle was created to compare the dose distribution of

a. Single isocenter plan with different collimator sizes and with the total number of beams ranging from 30 to 205.

b. Multiple isocenter conformal plan and non‐isocentric inverse conformal plan.

c. Multiple non‐coplanar beam arrangement and Multiple coplanar beam arrangement

Results and Discussion: For single isocenter plans, no significant differences were observed in isodose levels ranging from 90% to 10%, with number of beams ranging from 55 to 205, distributed over 2Π solid angle. With beam number reduced to 50, the noticeable differences fall in the dose levels under 10%. The conformal planning using multiple isocenters increases the number of beams geometrically, while no‐isocentric inverse planning can achieve excellent conformity with much less number of beams. However, close attention is needed to assure the dose fall‐off is well controlled in all directions. Although the reduction of beam number may not affect significantly the dose gradient in the median‐high dose region, to deliver all beams in a single plane does result in a much inferior dose distribution. The attempt to use a single co‐planar delivery for radiosurgery is thus to be avoided.
TU‐C‐W‐608‐01: Ultrasound QC Workshop
Authors: Kruger R , Lu Z , Miller H , Moore W , Goddu S
Published: June 2005

This workshop will provide attendees an opportunity to observe ultrasound scanner operations and quality assurance procedures. A portable ultrasound unit and various ultrasound QC phantoms will be provided and used to demonstrate the QC procedures. A set of QC test procedures described in AAPM Ultrasound Task Group 1 Report (Medical Physics 1998;Vol 25: 1385–1406) will be presented, including display monitor fidelity, image uniformity, depth of visualization, horizontal and vertical distance accuracy, axial and lateral resolution, slice thickness, dead zone measurement. Demonstrations of test procedures and equipment will be performed by the instructors and industry representatives.

Educational Objectives:

1. To learn the effect of parameter settings on various aspects of ultrasound imaging.

2. To observe the ultrasound quality control test procedures for real‐time B‐mode units.

3. To become acquainted with various ultrasound QC phantoms.
TU‐D‐I‐609‐02: What to Expect When CAD Is Implemented Clinically
Authors: Nishikawa R
Published: June 2005

I have developed a simple model to study the effects of computer‐aided detection (CADe) on screening mammography. The model incorporates tumor growth rate, the sensitivity of radiologists and the CADe scheme, how effectively the radiologist uses the CADe output, and the interval cancer rate. The model shows that the additional cancers detected when the radiologists uses CADe depends on how many cancers the radiologist misses without the computer aid, how many of the missed cancers the computer can detect, and what fraction of the computer detected missed cancers the radiologist will correctly recognize as a missed cancer. I also modeled the effect of CADe on radiologist false‐detection rate. Unless the computer can preferentially detect cancers over benign lesions, the increase in the number of cancers detected when using CADe will be the same as the increase in the number of women recalled (the vast majority of which will be false positives). This does not imply that CADe has no net affect. On the contrary, an equal increase in the cancer detection rate and the recall rate is consistent with radiologists operating on a higher ROC curve implying that CADe is improving the radiologists' performance. However, even if CADe was able to help radiologists reduce their miss rate by 50%, there will be only a 10% increase in the cancer detection rate before and after implementation of CADe. This increased is difficult to detect in practice because of the variable growth rate of tumors. The number of cancers present in a screened population will change year by year so that this variation can mask the actual increase in the cancer rate when CADe is implemented. However, the size of the cancers detected when using CADe is smaller than those detected by the radiologist when not using CADe.

Educational Objectives:

1. Understand the factors affecting the clinical effectiveness of computer‐aided detection

2. Understand some of the difficulties of measuring the clinical effectiveness of computer‐aided detection

Financial Disclosure: RM Nishikawa is a shareholder in R2 Technology, Inc. (Sunnyvale, CA). He also receives research funding and royalties from R2 Technology.
TU‐D‐J‐6B‐02: Optical Tomographic Imaging of Small Animals
Authors: Hielscher A
Published: June 2005

Diffuse optical tomography (DOT) is emerging as a viable new biomedical imaging modality. Using visible and near‐infrared light, in the range of 500 to 900 nm, this technique can probe absorption as well as scattering properties of biological tissues. The main applications are currently in brain, breast, limb, and join imaging; however, the area of optical tomographic imaging of small animals is attracting increasing attention. This interest is mainly fueled by recent advances in transgenic manipulation of small animals that has led to many models of human diseases. Using these models it is possible to link specific genes, proteins, and enzymes to molecular, and cellular processes that underlie various disorders. In addition, the advent of novel biochemical markers that are sensitive to molecular processes, defect genes, and cell receptors, makes it for the first time possible to detect diseases on a molecular level long before actual phenotypical symptoms appear. Small animal optical tomography has several advantages over other, more traditional, imaging modalities. For example, optical markers emit low‐energy near‐infrared photons that are less harmful than more energetic gamma rays emitted from radioactive markers (used in SPECT and PET, for instance). This simplifies synthesis procedures and experimental designs and will be of particular importance for future applications in humans. Furthermore, optical methods typically offer higher sensitivity (as compared to MRI and SPECT) and are relatively inexpensive (as compared to PET, SPECT, and MRI). In this paper we will review underlying principles in optical tomographic imaging as they apply to studies involving small animals. We will describe the basic contrast mechanism involved in imaging of endogenous as well exogenous contrast agents. In addition we will discuss specific features and advantages of different types of optical instrumentation currently available, such as steady‐state, frequency‐domain, and time‐resolved imaging systems. Furthermore we will describe in detail the structure of commonly used image reconstruction schemes and algorithms and point to still existing challenges. Finally, we will provide an overview of the most recent literature in optical small animal imaging, specifically in the areas of blood oximetry, fluorescence and bioluminescence imaging.

Educational Objectives:

1. To understand significance, potential, and limits of optical tomographic small animal imaging.

2. To understand the contrast mechanisms that underlie optical tomographic imaging.

3. To understand the basic measurement instrumentation used in optical tomographic imaging.

4. To understand the fundamental concepts and problems involving optical tomographic image reconstruction algorithms.

5. To learn about the major applications of this novel technology.
TU‐EE‐A4‐01: Clinical Experience with a 3‐D Ultrasound Prostate Localization System
Authors: Orton N , Jaradat H , Tomé W
Published: June 2005

Purpose: 3‐D ultrasound localization has been performed for external beam prostate treatments at our institution since September 2001. This poster presents an analysis of the daily shifts for 198 patients and 4855 fractions, and the results of tests performed to assess the system's performance and capabilities under clinical conditions. Method and Materials: All patients were treated supine, using a rectal balloon. Each day patients are initially aligned to skin marks placed by comparison of portal images with digitally reconstructed radiographs. An ultrasound image set is acquired using a 3‐D ultrasound localization system (Sonarray, Varian Medical Systems), and the patient may be shifted to account for variations in prostate position. Ultrasound images and shifts were stored for every fraction. Additionally, three tests are presented:

• To assess the accuracy of the shifts, 7 patients treated on a helical tomotherapy machine were localized daily using both ultrasound and a megavoltage CT scan.

• To assess the extent of intra‐fraction motion, ultrasound localization was repeated after treatment for 6 patients and a total of 29 fractions.

• To assess the inter‐user variation in shifts, four experienced operators independently localized 5 patients for 5 consecutive fractions.

Results: The mean daily shift for all patients was 7.4±3.8mm. Comparison of ultrasound to MVCT showed that ultrasound localization improved alignment: the mean ultrasound‐MVCT vector was 3.0±1.7mm, compared to 4.8±2.4mm between the MVCT and the skin marks. Intra‐fraction motion and inter‐user variation were found to be small in comparison with the daily shifts. The mean intra‐fraction prostate shift was 1.9±1.0mm, and the shift was within the 3mm imaging uncertainty of the system for 25 of 29 fractions. Conclusion: Our experience shows that 3‐D US localization can be a valuable tool for aligning external beam prostate patients, enabling the use of reduced margins and more aggressive fractionation schedules.
WE‐B‐I‐618‐02: Digital Image Displays — Resolution, Brightness, and Grayscale Calibration
Authors: Flynn M
Published: June 2005

Digital radiographs from CR, DR, RF, and XA systems are displayed on monitors when the exam is performed, when a radiologist interprets the examination, and when the referring physician or surgeon review the image. The various monitors used typically vary in image quality. Display resolution is influenced by pixel size and viewing distance. Displayed field of view varies with the monitor array size and image zoom. Image brightness influences low contrast detection, peripheral vision, and may effect observer fatigue. The display grayscale influence contrast and may alter the appearance for different viewers unless matched on all monitors. The requirements for resolution, brightness, and grayscale are considered for various situations including RF and XA exam room displays, technologist QC stations, radiologists reading stations, general clinic review stations, surgical display, and conference case presentation.

Educational Objectives:

1. Understand how pixel size and viewing distance influence resolution in relation to visual limits of the human eye.

2. Understand how image brightness influences observer performance.

3. Learn how the grayscale characteristics of clinical display systems can be calibrated to match diagnostic systems.

4. Learn the performance characteristics of displays now available for various applications.
WE‐C‐J‐6B‐02: Infrastructure for 4D Image Guide Therapy
Authors: McShan D
Published: June 2005

This presentation looks at infrastructure needed for research investigation and for routine clinical use of time resolved volumetric (4D) image guided therapy The 4D imaging data used for IGRT comes from a variety of sources ranging from standard CT scanners, cone‐beam CT from gantry mounted imagers, MR, and PET images. An example of a reconstructed 4‐ D data set for CT would have dimensions (512×512×100×10) (100 slices per volume representing 10 different time intervals. This represents approximately 0.5 gigabytes of data. Daily acquisition of these images therefore represents significant storage demands and increased network speeds needed to communicate this data between various processes (image alignment tools, contouring/segmentation, and treatment planning). While the DICOM imaging standard can be used for storing 4D datasets, the related derive data such as deformable alignment parameters and other associated data such as statistics about anatomical variability and embedded marker positions, are beyond the standard and require establishment of separate bookkeeping to maintain that data. The actual use of 4D data varies. This data provides information about patient alignment and extent of physiological motion. However, 4D data can also provide time dependent functional information which may provide early indicators of tumor and normal tissue responses. Decision based on analysis of these functions can be employed for daily assessment and immediate adjustments to the treatment either before or during delivery. Or analysis of the 4D data may be used to provide statistical support for more deliberate plan adjustment decisions. Often 4D data implies geometrical changes over time such as heart and respiratory motion which require deformable alignment of image volumes to relate and track anatomical regions of interest between different motion states and in reference to the imaging volumes used for planning. To aid in this presentation, a survey of current research and clinical uses of 4D image guided therapy will be presented with answers to questions regarding : the types of 4D imaging data sets used, the sizes of typical data sets, the frequency of acquisition, storage demands (long term and short term) and algorithms used for reconstruction, registration, analysis, and compression. The survey results demonstrate infrastructure needs for 4D image guided therapy that are significantly above and beyond what is typically needed for static volumetric imaging and planning in terms of both the amounts of data acquired and the tools needed for data management and analysis, This survey has included manufacturers and leading researchers in the field. In addition to survey results, examples of the infrastructure implemented by these users will be shown.

Educational Objectives:

1. Identify various sources of 4D data and typical storage requirements

2. Present various use of 4D for IGRT employed to date and associated data display and analysis tools

3. Demonstrate successful infrastructure implementations
Characterization of ultrasound contrast microbubbles usingin vitroexperiments and viscous and viscoelastic interface models for encapsulation
Authors: Sarkar Kausik , Shi William T. , Chatterjee Dhiman , Forsberg Flemming
Published: June 2005

Zero-thickness interface models are developed to describe the encapsulation of microbubble contrast agents. Two different rheological models of the interface, Newtonian (viscous) and viscoelastic, with rheological parameters such as surface tension, surface dilatational viscosity, and surface dilatational elasticity are presented to characterize the encapsulation. The models are applied to characterize a widely used microbubble based ultrasound contrast agent. Attenuation of ultrasound passing through a solution of contrast agent is measured. The model parameters for the contrast agent are determined by matching the linearized model dynamics with measured attenuation data. The models are investigated for its ability to match with other experiments. Specifically, model predictions are compared with scattered fundamental and subharmonic responses. Experiments and model prediction results are discussed along with those obtained using an existing model [Church, J. Acoust. Soc. Am. 97, 1510 (1995) and Hoff et al., J. Acoust. Soc. Am. 107, 2272 (2000)] of contrast agents.