bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐GG‐AUD‐09: On the Impact of Functional Imaging Accuracy (Sensitivity and Specificity) On Selective Boosting IMRT
Authors: Kim Y , Tome W
Published: July 2007

Purpose: To quantify the impact of loss in functional imaging sensitivity and specificity on tumor control and normal tissue toxicity for selective boosting IMRT. Methods and materials: Four selective boosting scenarios were designed: SB91‐81 (EUD=91Gy for the high risk tumor subvolume (nodule) and EUD=81Gy for a remaining low risk PTV (rPTV)), SB80‐74, SB90‐70, and risk‐adaptive optimization. For each sensitivity loss level, the loss in tumor control probability (ΔTCP) was calculated. For each specificity loss level, the increase in rectal and the bladder toxicity was quantified using the radiobiological indices (equivalent uniform dose (EUD) and normal tissue complication probability (NTCP)) and physical indices (%‐volumes). Results: The impact of loss in sensitivity on local tumor control was maximized as the dose level for rPTV had a lower value. The SB90‐70 plan had a ΔTCP= 93.8 %, for the SB91‐81 plan ΔTCP = 26.8 %, while for risk‐adaptive optimization ΔTCP= 8.0 %. Independent of planning technique, loss in functional imaging specificity appears to have a minimal impact on the expected normal tissue toxicity since an increase in rectal or bladder toxicity as a function of loss in specificity was not observed. Additionally, all plans fulfilled the rectum and the bladder sparing criteria found in the literature for late rectal bleeding and genitourinary complications. Conclusions: Our study shows that the choice of a low‐risk classification for the rPTV in selective boosting IMRT may lead to a significant loss in TCP. Furthermore, it appears that in order to improve the therapeutic ratio a functional imaging technique with a high sensitivity, rather than specificity, is needed.
MO‐SAMS‐AUD‐01: Daily Localization — I: Kilovolt Imaging
Authors: Yin F , Yoo S , Moseley D , Sharpe M , Siewerdsen J
Published: July 2007

As high‐precision 3‐D conformal radiation therapy and intensity‐modulated radiation therapy have become standard practice, radiographic imaging using kilovoltage (kV) x‐ray sources has been rapidly implemented for in‐room target localization and patient positioning to ensure conformal dose delivery. Various types of imaging devices are commercially available for clinical applications and their typical imaging functionalities include 2‐D radiographic and fluoroscopic imaging as well as 3‐D cone beam CT. There are substantial demands for fundamental understanding of what kind of systems can be used for clinical practice, when and what imaging systems should be used, how they can be properly used for daily target localization for different anatomical sites, and what kind of quality assurance programs are needed.

In this session, we will briefly introduce the latest commercially available imaging systems using kV imaging for in‐room target localization and their imaging principles. Clinical applications and imaging protocols using these systems for accurate target localization and patient positioning will then be discussed. Finally, systematic quality assurance procedures will be presented.

Objectives:

1. Understand the latest commercially available technologies for in‐room kV radiography, fluoroscopy, and cone‐beam CT and their basic imaging principles.

2. Understand the basic clinical imaging applications for daily localization.

3. Understand the basic system limitations and QA components of a comprehensive QA program.
MO‐B‐BRA‐01: Practical Examples, Including IMRT, TBI, SRS
Authors: Rodgers J
Published: July 2007

NCRP Report No. 151(December 2005), titled “Structural Shielding Design and Evaluation for Megavoltage X‐ and Gamma‐Ray Radiotherapy Facilities”, presents updated methods and data for radiation therapy room shielding design. These calculation methods are applied in examples representing the more common shielding design situations. A radiation therapy vault with a maze barrier and intended for use with IMRT and TBI procedures is the principal example. Detailed calculations of the barriers and door shielding structures are presented. Procedures for evaluating compliance with the NRC licensing constraint on dose equivalent in‐any‐one‐hour are presented. An example of a high‐energy room where photoneutron production is of concern is presented with focus on assessing the dose equivalent at the entrance and the maze door design.

Objectives: Learn by worked examples (1) how to apply the methods and data presented in NCRP 151 for designing high energy therapy vault barriers; (2) how to determine prospectively if the barrier design is adequate to satisfy the public areas “2 mrem in‐any‐one‐hour” constraint when it is applicable.
MO‐D‐L100J‐05: A Semi‐Manual Contouring Method in TCS Views
Authors: Chen Q , Lu W , Chen M , Ruchala K , Olivera G
Published: July 2007

Purpose: Contouring plays an important role in radiation therapy. The traditional slice‐by‐slice manual contouring method is very time‐consuming. There have been several automatic and semi‐automatic segmentation methods proposed to make contouring easier. However, those methods are limited by the image quality and image features. In particular, all those methods fail in the prostate region where both prostate and rectum are difficult to segment. Methods:The contouring method we propose here only requires a few manual contours drawn in TCS (transversal, coronal, and sagittal) views. Our algorithm will then generate a 3D surface based on those manual contours. This method consists of two steps. The first step is a surface‐fitting process (the same principle as curve‐fitting). It determines a surface that approximates the manually drawn contour/control points. Different model is used for different organ (prostate, rectum) to create fit surface. The second step is a surface deformation process. A smooth deformation field is created automatically to deform the surface so that it passes through the manual contour points. This makes sure that the resulting surface conforms to the given contours. Results: This algorithm is very fast and user interactions can be easily incorporated. The algorithm was tested on 39 prostate and rectum cases and the results match manual contour results very well. Five manual contours are used. The false‐negative rate is around 0.07–0.08 and the speed‐up is around 3–5. Conclusions: We have presented a semi‐automatic method that only require human operator to draw a few manual contours to delineate a 3D structure. This method will produce a smooth contour and it is very robust.
MO‐D‐L100J‐07: Improved Deformable Image Registration Using Hybrid Models: An Application to Solitary Pulmonary Nodule
Authors: Xia J , Samant S
Published: July 2007

Purpose: To present a fast and robust hybrid deformable image registration algorithm (Juggler) for target motion estimation, automated segmentation and internal target volume (ITV) generation in 4DCT lung imaging. Method and Materials: The Juggler algorithm utilizes two alternating separately optimized diffusion models: one for low gradient features (soft tissues), the other for high gradient features (bony anatomy). Clinical lung imaging, acquired from 4DCT, consisted of free breathing CT and 10 phased CT sets. Comparison with three other conventional algorithms (demons, accelerated demons, and free‐form deformation method) was carried out using both simulated data and clinical 4DCT. Algorithm validation was carried out using comparison of 1) displacement vectors (for simulated data), 2) correlation coefficient, 3) difference imaging, and 4) vector streamlines. Clinical efficacy of Juggler was evaluated by visual inspection of anatomical structures mapped from the reference onto target imaging using the deformation map. Tumor motion/ deformation was determined using image moments. Results: For simulated data, Juggler achieved the highest correlation coefficient and minimum error. Its unique alternating mechanism greatly improved the convergence rate, resulting in at least 40% reduction in iterations. For 256×256×80 imaging, Juggler required <3 min for 50 iterations using Pentium‐4 3.2 GHz PC. For clinical 4DCT, Juggler performed best based on correlation coefficient and visual inspection. We used Juggler for generating ITV, and autosegmenting normal structures onto the phased CTs based on the initial segmentation on the reference CT. Conclusion: Juggler demonstrated the benefits of utilizing multiple diffusion models into a single unified model. Initial experiments indicated Juggler achieved the fastest rate of convergence per iteration, and overall superior registration based on correlation coefficient, difference imaging and error analysis. Its success in autosegmentation and ITV generation make this highly promising in implementation of adaptive radiation therapy. With new computer hardware, <30sec computation times are expected.
MO‐D‐L100J‐08: Construction of 4D‐CT Motion Model Using Deformable Registration: Comparison of Eulerian and Lagrangian Approaches
Authors: Boldea V , Sharp G , Jiang S , Sarrut D
Published: July 2007

Purpose: To analyze and compare two motion models constructed from 4D‐CT using deformable registration using two different computation approaches: Eulerian and Lagrangian. Method and Material: Accurate motion modeling within the lung is an important consideration in different clinical applications. We consider 4D‐CT scans for three patients treated in radiotherapy for lung cancer. 4D‐CTs were acquired using a 4‐slice fan‐beam CT scanner (GE Lightspeed QX/i; GE Heathcare Technologies, Waukesha, WI), and a respiratory surrogate (Real‐time Position Management; Varian Medical Systems, Palo Alto, CA). Two motion models were constructed from vector fields computed with demons algorithm with Gaussian regularization. We used also a image pre‐treatment method, a priori lung density modification, to handle this limitation of the demons algorithm. The first model, obtained with the Eulerian approach, uses small deformation estimations between successive phases of the 4D‐CT. The second model, obtained with the Lagrangian approach, was generated by estimation of larger deformations between the end‐exhale phase and all other states. The models were validated and compared using consistency (symmetry and transitivity) and accuracy (based on landmark points) metrics. Results: Mean values of accuracy were on the order of the image resolution and comparable to inter‐observer variability (1.9 mm), with slightly better results for the Lagrangian approach: 2.3 mm vs. 2.6 mm. The differences were not statistically significant for consistency.Conclusions: The results of this study suggest that the Lagrangian approach is more appropriate to use for generating a 4D‐CT motion model with deformable registration. In ongoing works, lung and GTV contours are used in order to conclude on the superiority of one motion model over the other for an automatic contour propagation tool, and for lung physiological information computation and analysis.
MO‐D‐L100J‐09: A Multi‐Resolution, Multi‐Scale, Mutual Information Technique for Registration of High‐ and Low‐KVp Projections in Dual‐Energy Imaging
Authors: Dhanantwari A , Siewerdsen J , Shkumat N , Williams D , Moseley D , Paul N , Yorkston J , Van Metter R
Published: July 2007

Purpose: In dual‐energy (DE) imaging, double‐shot acquisition provides superior DQE and detectability index compared to sandwiched detectors, but introduces the potential for misregistration artifacts (e.g., respiratory, cardiac, and bulk motion). This paper reports a projection registration scheme operating at various levels of scale and resolution to resolve misregistration errors prior to DE decomposition. Method and Materials: The method is based on joint histograms of the high‐ and low‐kVp images (or ROIs therein), with optimal image transformations computed to maximize the mutual information between the images. The image is subdivided into a series of ROIs, with an optimal transformation computed for each ROI. Large ROIs are downsampled to reduce the computational complexity of the optimization. The ROI transformations are smoothed and interpolated to determine a pixel‐wise transformation for the entire image. This is repeated with progressively smaller ROIs. Results: The results demonstrate that large scale ROIs (400×400 pixel) are effective in correcting bulk patient motion such as drift or relaxation. A second pass with a smaller ROI (200×200 pixel) corrects breathing and cardiac motion. A final pass with yet smaller ROIs (100×100 pixels) is effective at correcting the motion of fine bronchio‐vascular structure. The combination of these in an iterative multi‐resolution, multi‐scale method effectively registers the high‐ and low‐kVp projections such that DE images exhibit significantly reduced motion artifacts — particularly in the scapulae, aorta, heart, liver, and bronchioles. Expert radiologist readings suggest a significant improvement in image quality and diagnostic performance. Conclusion: The iterative, multi‐resolution, multi‐scale registration corrects misregistration progressively at scales ranging from bulk anatomical drift down to smaller scale motion such as that of fine pulmonary vasculature. The approach is a vital part of the DE image processing chain that has been implemented for a clinical DE imaging trial with 200 patients.

Research partly supported by Eastman Kodak Co.
MO‐D‐AUD‐05: Characterization of Dose in Heterogeneous Situations: A Comparison of Treatment Planning System and Computer Aided Second Check Dosimetry QA Software Dose Evaluations
Authors: Dzintars E , Watts R , Bice W
Published: July 2007

Purpose: To quantify and compare the dosimetric predictions calculated by a treatment planning system, second check dosimetric computer QA software, and ion chamber measurements in heterogeneous situations for 6 and 18 MV photon beams. Method and Materials: An assortment of plastic tissue equivalent materials was used to compare the calculated dose predictions between the Pinnacle3 treatment planning system, the RadCalc® QA computer software, and ion chamber measurements. The dosimetric accuracy of the plastic water, lung, and bone equivalent slab materials was assessed and validated through the use of simple geometries. After planning, doses for each slab arrangement were measured on a Varian 21EX accelerator with a second check performed by the RadCalc® computer software. Percentage differences between the computed and measured doses were then compared and quantified, providing information on the accuracy of the dose predictions. Results: Evaluation and comparison between the calculated dose values from the Pinnacle3, RadCalc®, and measured data indicate that discrepancies exist, even for simple geometric setups. Looking at percentage differences, the Pinnacle3 system (−3.82% – 4.33%) more accurately calculates the dose in the heterogeneous locations than does the RadCalc® software (−8.30% – 4.15%). Examination of all measured point locations show only about 4% of the Pinnacle3 system dose calculations, and almost 18% of the RadCalc® software dose calculations, have a percentage difference greater than ±3%. Conclusion: This work explores the clinical application and accuracy of using RadCalc® for dosimetric second checks. Even with the use of heterogeneity corrections, it is still not guaranteed that an accurate dose calculation will result when heterogeneous material is present. The CIRS Inc. IMRT Thorax and Pelvic 3D phantoms will be utilized for the continuing investigation of the accuracy of dose calculations performed by Pinnacle3 and RadCalc® involving additional complex geometries in a more anatomical construct.
MO‐D‐AUD‐06: Dependence of Total Scatter Factors of Small Beams On the Radial Distribution of the Electron Beam Incident On the Target: A Multi‐Detector and Monte Carlo Study
Authors: Francescon P , Cora S , Cavedon C , Santangelo V , Scalchi P
Published: July 2007

Purpose: To investigate dependence of total scatter factors (sc,p) of small beams used in radiosurgery on the radial distribution of the electron beam incident on the target. The study was performed in order to clarify discrepancies observed in sc,p measurements performed by means of different detectors at the Cyberknife radiosurgery system and was aimed at obtaining a means to infer the electron radial distribution of a specific Cyberknife unit. Method and Materials: PTW PinPoint31014 and Exradin #a16 microchambers, PTW30012 diode and TM60003 diamond were used to measure sc,p. The same detectors were simulated by means of the Monte Carlo code BEAMnrc to calculate correction factors for sc,p. BEAMnrc was also used to calculate theoretical values of sc,p. Accuracy of Monte Carlo simulation depends on the choice of energy, divergence and radial distribution of the electron beam incident on the target. The energy was determined by comparison to experimental TMRs. Radial distribution of the electron beam (expressed as FWHM, gaussian shape) was chosen to be optimal when correction factors of the 4 detectors were such that corrected sc,p converged to the same value within +/−1%. Results: measured sc,p of the 5mm collimator averaged 0.638 −4%+11% with the 4 detectors. E=7.2MeV best matched calculated to experimental TMRs. Optimal FWHM=2.3mm gave sc,p=0.673 −0.7%+0.3%. Correction factors decreased with increasing FWHM, while Monte Carlo‐calculated sc,p increased. Measured (corrected) and calculated sc,p matched at 0.673 only for FWHM=2.3mm. Conclusion: Variations of electron beam focussing can explain significant variations of sc,p. If one of the investigated detectors is used, it is possible to infer actual FWHM values and thus appropriate correction factors by comparison to pure Monte Carlo‐calculated sc,p values as a function of FWHM. This fact could be exploited by centres who do not have access to Monte Carlo codes to simulate their own system.
MO‐D‐AUD‐09: Validation of Response Function‐Based Dose Reconstruction
Authors: Yeo I , Chew M , Wang B , Kim J
Published: July 2007

A method based on dose‐response function was developed in the past, which verifies the beamlet weight of intensity modulated radiation therapy (IMRT) from dose image in electronic portal imaging device (EPID) and reconstructs dose in a patient. The establishment of a linear relationship between beamlets and dose responses in patient and in electronic portal imaging device (EPID) was the key to this methodology. The responses are to be predetermined by a full‐scope Monte Carlo calculation in patient and EPID structures. In this study, the method was validated through measurement using in‐phantom and exit film dosimetry which simulated in‐patient and EPID measurements, respectively. The in‐phantom film was inserted at 100 cm from the target and at 12.5 cm depth within a 25‐cm thick phantom and the exit film was placed at 139.5 cm from the target and at 2 cm depth within a 4‐cm thick EPID phantom. For the validation, a 6MV X‐ray beam with the size of 6 × 6 cm2 was perpendicularly exposed to the phantom. Responses to each beamlet (0.2 × 5 mm2) within a phantom and an EPID phantom were then calculated. Using the calculated responses, the exit film dose was used to inversely reconstruct the in‐phantom dose, which was then compared with the measured in‐phantom dose. In a second study, an IMRT beam intensity reconstruction was investigated computationally. The dose comparison in patient showed a difference of less than 3 %. Some propagated noise was found in the reconstructed intensity distribution, suggesting the need for noise filtration prior to reconstruction. The reconstruction took less than 10 seconds of calculation time and 10 MB of memory. The method is accurate as well as effective for the dose reconstruction of IMRT. A follow‐up study will include detailed modeling of a therapeutic beam and EPID and experiments.
MO‐D‐M100J‐05: Robust Optimization to Accommodate Effects of Systematic Treatment Uncertainties
Authors: Lee E , Cha K , Bortfeld T , Deasy J
Published: July 2007

Uncertainties in the precise locations of tumor voxels are inherent for a variety of reasons. It is therefore desirable to take those uncertainties into account, and further, to derive treatment planning methodologies that directly utilize information (e.g. probability distributions or actual trajectories) about the location of the target, including spatial uncertainties, so that resulting treatment plans exhibit normal tissue dose reduction, and potentially higher tumor doses.

Two novel robust approaches are investigated. 1)Under‐dose probability(UDP) estimates the probability of the tumor receiving a dose less than a user‐defined critical dose. It can be modeled using linear mixed‐integer programming techniques. 2)Probability dose generation(PDG) designs treatment plans in which the probability of a voxel located in a target is factored during the dose generation process. Utilizing 4D‐CT scans of lung/liver cancer patients during different breathing phases(phases 0–9, 0:full‐inhale, 5:full‐exhale), four treatment planning strategies are compared. 1)Standard planning with a static PTV based on a single selected phase (control). 2)The Internal Target Volume (ITV) approach, where ITV is defined as the union of CTVs in all breathing phases. 3)Plans obtained with UDP. 4)Plans obtained via PDG. Sophisticated computational optimization techniques are used to solve each of these models.

Compared to Standard and ITV plans, UDP and PDG plans offer good coverage, comparable min‐PTV‐dose, improved PTV‐conformity, and higher PTV‐dose. In addition, in lung, PDG reduces normal‐lung‐mean‐dose by 13% and heart‐mean‐dose by 20%; and UDP reduces esophagus‐mean‐dose by 70% and heart‐mean‐dose by 49%. In liver, PDG reduces normal‐liver‐ mean‐dose by 8% and other‐normal‐tissue‐mean‐dose by 26%, whereas UDP reduces normal‐liver‐mean‐dose by 10%, both with improved PTV‐conformity of 7%.

Thus, the UDP and PDG approaches can result in treatment plans of increased robustness, they allow a reduction in mean dose to organs‐at‐risk and normal tissue, and in some cases, deliver higher dose to the tumor volume.
MO‐D‐M100J‐06: Reducing Intra‐Fraction Organ Motion Effects Using Segment Size Constraint in Direct Aperture Optimization
Authors: Zhang G , Yi B , Jiang Z , Yu C
Published: July 2007

Purpose: In IMRT delivery, an important issue is intra‐fraction organ motion, which causes significant degradation of the delivered dose. Some simulation researches have showed that organ motion effects could be significantly reduced by increasing the segment size. In this study, a direct aperture optimization based commercial inverse planning system was modified to assess the clinical impact of creating optimized plans with segment size constraints (SSC). Our study seeks to answer what price in static plan quality one has to pay to avoid dose degradation in moving targets? Method and Materials: IMRT plans with and without SSC were optimized for two abdominal cases using static CT images. The MLC travel direction is aligned with the projected motion direction and SSC penalizes all MLC leaf openings smaller than twice the projected motion amplitude. Static plans were recalculated with a sinusoidal target motion with 1cm amplitude and 4second period. Results: In both cases with and without SSC, PTV volume covered by 95% of the prescribed dose (V95) was less than 1%, indicating that SSC had little effect on static plan quality. After incorporating target motion, V95 was improved by applying SSC, with the degree of improvement depending on the particular case. For case 1, V95 improved from 84.5% to 93.3% by adding SSC. Further study shows that dose coverage of peripheral PTV regions improved more significantly with SSC than central regions. In all plans, differences of the doses to the critical structures were within a few percent. By adding SSC, the treatment plan was more tolerant to target motion. Conclusions: Our study showed that when segmental IMRT plans were delivered to a moving target, SSC improves delivered dose conformity (V95) as much as 9% without significantly sacrificing static plan quality. Peripheral PTV shows more improvement in dose coverage with SSC than central regions.
MO‐E‐L100J‐02: Limits On Achievable Performance Levels for Active Matrix Flat Panel Imagers Incorporating Active Pixel Sensor Architectures
Authors: Antonuk L , El‐Mohri Y , Du H , Zhao Q , Behravan M , Wang Y , Street R
Published: July 2007

Purpose: The relatively high level of additive noise in active matrix flat‐panel imagers (AMFPIs) leads to significant loss of DQE under conditions of low exposures per frame and/or high spatial frequencies. One promising method for dealing with such performance loss involves in‐pixel signal amplification through incorporation of additional circuitry to each pixel — a concept generally referred to as an active pixel sensor. In this presentation, an examination of performance levels that can be achieved with active pixel sensors based on thin‐film electronics will be presented. Method and Materials: Calculations of the DQE of various active pixel sensor designs were performed using the cascaded systems formalism. Inputs to the calculations come from empirical measurements, published data, analytic calculations, and results derived from detailed circuit simulations. The calculations were performed for a series of designs, under fluoroscopic irradiation conditions, and using various readout protocols. Results: Our model calculations indicate that, under conditions of low exposure and/or high spatial frequency, substantial DQE restoration can be achieved via a combination of in‐pixel amplification circuitry and correlated double sampling protocols — each specifically selected to eliminate specific noise contributions. In particular, it appears feasible to reduce thermal noise associated with the pixel reset TFT and preamplifier noise to negligible levels and thereby increase DQE. However, the degree of performance improvement that can be practically realized will also depend upon the quality and properties of the thin film transistors used in the pixel circuit as well as selection of circuits that will yield well in manufacture. Conclusion: The degree of performance improvement made possible through array architectures comprising active pixel sensors is critically dependent on many factors including the properties of the transistors, the engineering rules governing pixel and array design, the choice of pixel circuit, and the method of array readout.
MO‐E‐L100J‐03: Development of a Novel Electronic Portal Imaging Device Based On Cherenkov Radiation
Authors: Pang G , Mei X , Rowlands JA
Published: July 2007

Purpose: Most electronic portal imaging devices (EPIDs) developed so far use a Cu plate/phosphor screen to absorb x rays. The main problem with this approach is that the Cu plate/phosphor screen must be thin (∼ 2 mm) in order to obtain a high spatial resolution, resulting in a low quantum efficiency (QE) for megavoltage (MV) x rays (typically 2–4%). In addition, the phosphor screen contains high atomic number (high‐Z) materials, resulting in an over‐response of the detector to low energy x rays in dosimetric verification. Our goal is to develop a new high QE MV x‐ray detector made of a low‐Z material for both geometrical and dosimetric verification in radiotherapy. Method and Materials: Our approach uses radiation‐induced light (Cherenkov radiation) in optical fibers that are made of low‐Z materials. With our approach, a thick (∼ 10–30 cm) fiber‐optic taper consisting of a matrix of optical fibers aligned with the incident x rays is used to replace the thin Cu plate/phosphor screen to dramatically increase the QE. The feasibility of this approach has been investigated using a single optical fiber embedded in a solid material. The spatial resolution expressed by the modulation transfer function (MTF) and the signal‐to‐noise ratio of the proposed detector at low doses (∼ one Linac pulse) have been measured. Results: It is predicted that, using this approach, a detective quantum efficiency (DQE) of an order of magnitude higher at zero frequency can be obtained while maintaining a reasonable MTF, as compared to current EPIDs. Conclusion: This work demonstrated the feasibility of using Cherenkov radiation for portal imaging applications [Work supported by the Individual Discovery Grant Program awarded by National Sciences and Engineering Research Council of Canada (NSERC)].
MO‐E‐BRB‐06: Communicating Radiation Safety Procedures After Patient Death: Beyond Decay in Storage
Authors: Jafari M E
Published: July 2007

Purpose: To discuss radiation safety issues that may arise in the event of death of patients who have received radiopharmaceutical therapy or a radioactive implant and to educate clinical medical physicists in specific procedures performed by pathology personnel, morgue personnel, funeral directors and crematory workers that present radiation safety risks to those workers. Also to provide guidance on lessons learned by the author in communicating appropriate radiation safety procedures to funeral professionals and working with state agencies that regulate funeral homes and crematories. Method and Materials: The author researched pathology, embalming, and cremation procedures and facilities and spent considerable time on‐site in such facilities to gain an understanding of the specific risks presented to personnel and safety precautions that are currently used (or not used). Results: The author prepared instructions to be provided to personnel in the event of the death of radiopharmaceutical therapy or radioactive implant patient to comply with state and federal radiation control regulations and ensure personnel safety. The author also provided education to local funeral directors and spoke on this subject at a state funeral directors conference. Conclusions: It is not a matter of “if” but rather “when” a clinical medical physicist at a facility performing radiopharmaceutical therapy or radioactive implant procedures will receive a call regarding radiation safety procedures for a deceased patient. It is preferable to be prepared with specific instructions and establish a relationship with your pathology laboratory, morgue, and local funeral professionals in advance than to flounder when the event occurs.
MO‐E‐BRB‐07: IAEA Activities in Medical Radiation Physics
Authors: Shortt K , Izewska J , McLean I , Vatnitsky S
Published: July 2007

Purpose: Although well known for its work in dosimetry, the IAEA requires experts in medical radiation physics to assist with projects in developing countries such as commissioning radiotherapy machines and treatment planning systems. Consultants are used also to draft documents and provide advice on divergent topics such as quality assurance for IMRT and PET‐CT, and a methodology for comprehensive auditing in radiotherapy. Method and Materials: Through its publications, the IAEA's attention in developing countries is focused on redressing the dual gaps in access to basic technology using radiation medicine and in advanced technology that attempts to increase the fraction of patients treated with curative intent. Results: DMRP has produced information of relevance to the practice of medical physics in any centre of limited resources irrespective of geographic location. In educating medical physicists, the handbook for teachers and students in Radiation Oncology Physics has been supplemented by a β‐version of a set of 2,500 slides to assist in self‐directed studies, recently posted on the DMRP web site for comments and feedback. A syllabus for medical physics in diagnostic radiology has been prepared and co‐authors are being recruited to write individual chapters. TRS‐430 on QA for treatment planning systems has been supplemented by two additional documents on type tests to be done by the supplier, and acceptance and commissioning tests to be done on‐site. A methodology for comprehensive auditing of radiotherapy centres and a more specific document on physics auditing in radiotherapy have been prepared. A new document describing a basic radiotherapy facility including its human resources component has completed technical editing. Conclusion: New projects and up‐coming opportunities, and the process to become an IAEA consultant will be described in the hope that AAPM members will be encouraged to offer their services to strengthen the practice of medical physics internationally.
MO‐E‐AUD‐06: Ultra‐Fast Gamma Index Calculation for Quality Assurance and Optimization in Radiotherapy
Authors: Chen M , Lu W , Chen Q , Ruchala K , Olivera G
Published: July 2007

Purpose It is clinically essential in IMRT to compare two dose distributions for dose quality assurance (DQA). The gamma index (Low et al, 1998), which combines both dose difference and distance to agreement, provides a quantitative measure of acceptability in DQA. However, its calculations can be time‐consuming and limit its applications to 2‐dimensional dose distributions. In this work, we propose an efficient calculation method. Method By embedding the k‐dimensional reference dose distribution in the (k+1)‐dimensional spatial‐dose space, we then use the Euclidean distance transform to find the distance to the reference dose distribution, regarded as a feature set, for every point in a range of the spatial‐dose space. This leads to a table of gamma indices. And the evaluation of the gamma indices for any dose distribution with respect to the reference dose distribution is simply table‐lookup. Our implementation uses a fast Euclidean distance transform, which was developed in Maurer et al, 2003 and proved to have only linear complexity. Results Using simulated 2‐D dose distributions of size 400×400, the pre‐calculation of the Gamma index table takes 26 sec and the table lookup to evaluate the Gamma index for each test dose distribution takes less than 0.1 sec in a 3GHz PC. On the other hand, it takes about 2400 sec using the exhaustive search on the same PC to evaluate the Gamma index for each test distribution. The speedup for 3D Gamma index calculation is expected to be 104∼105. Conclusion Numerical simulations demonstrate the efficiency of our proposed method. Thus, the clinical usage of 3D Gamma index becomes feasible. In addition, the Gamma index table can be used to determine the derivative of Gamma index over the dose distribution, which facilitates the inclusion of Gamma index in treatment planning and/or machine parameters optimization.
MO‐E‐AUD‐07: Calculating the Air‐Kerma Strength and Dose‐Rate Constant of 125I and 103Pd Low Dose Rate Brachytherapy Sources Using Spectra Measured With a High‐Purity Germanium Spectrometer
Authors: Usher J , DeWerd L , Beach S , Selwyn R
Published: July 2007

Purpose: To calculate spectroscopic analogs of the air‐kerma strength and dose‐rate constant using the fully corrected energy spectra of and low dose‐rate (LDR) brachytherapy sources measured with a high‐purity germanium (HPGe) spectrometer. Methods and Materials: A high‐purity germanium spectrometer (CANBERRA, GR2519), driven by CANBERRA Genie2000™ gamma analysis software, was used to measure spectra of Theragenics model 200 and Best Medical model 2301 sources. The thin beryllium entrance window (0.05 cm) allows high transmittance of low energy photons making it ideal for LDR applications. An iterative deconvolution algorithm was used to correct each measured spectrum for detector effects such as efficiency and germanium fluorescence. The deconvolved spectrum represents the photon spectrum incident on the entrance window of the detector. The spectrum was corrected to vacuum to represent the spectrum emitted from the encapsulated source. The spectroscopic air‐kerma strength, SK,Spect, was calculated from the fully corrected emitted spectrum of each source. A spectroscopic dose‐rate constant, ΛSpect, was also calculated for both the models 200 and 2301 using the method developed by Chen and Nath (Med. Phys. 28, 86–96, 2001). Results: SK,Spect for model 200 and model 2301 sources were calculated. The values were compared with standard SK measurements showing an agreement of 3.2–3.4% for most sources, while one source exhibited a 12% difference that is being investigated further. ΛSpect was calculated to be 0.699 cGy h−1U−1 for the model 200 and 1.033 cGy h−1U−1 for the model 2301. These values are within the experimental uncertainty of the consensus dose‐rate constant values, which are 0.686 cGy h−1U−1 and 1.025 cGy h−1U−1, respectively. Conclusions: The spectroscopic method for calculating the air‐kerma strength and dose‐rate constant of LDR sources has proven to be a promising technique that can be extended to additional source models and new designs entering the market.
MO‐E‐BRA‐03: Application of Robust Optimization in Lung Cancer Treatment
Authors: Chan TCY , Trofimov A , Vrancic C , Tsitsiklis JN , Bortfeld T
Published: July 2007

For lung tumors, the presence of motion due to breathing is a key source of uncertainty. Motion essentially blurs the static dose distribution, which can be thought of mathematically as a convolution of the static dose distribution with a probability density function (PDF) describing the motion. The 4D IMRT optimization/inverse planning method tries to undo this blurring effect by taking the motion PDF into account during the optimization of the intensity map. Such an approach is effective as a motion compensation technique, but only when the motion is highly reproducible over the entire treatment course. In terms of the PDF, “reproducibility” corresponds to witnessing the same PDF over the course of treatment that was observed in the treatment planning stage. However, if the realized PDF during treatment differs from the planning PDF, the subsequent convolution of the static dose distribution with the realized PDF may produce undesirable hot and cold spots.

Robust optimization is a concept that has gained prominence in the optimization community for its wide applicability to problems with uncertain data. Real‐world problems are rarely, if ever, accompanied by noiseless data, hence, there is a natural motivation to incorporate this uncertainty into any optimization process. The robust framework we present builds on the 4D approach by explicitly accounting for the uncertain motion represented by uncertainty in the motion PDF. Instead of basing the optimization on one PDF, robust optimization uses a family of PDFs to create a static dose distribution that is less sensitive to variations in the motion.

The robust framework allows us to craft solutions in the entire spectrum between the idealized 4D method, and a conservative, ITV‐like margin approach. A given intensity map that results from the robust optimization method will balance intensity‐modulation with intensity‐homogeneity in order to effectively trade off the sparing of healthy tissues with ensuring sufficient tumor coverage. Accordingly, the robust optimization method implicitly performs multi‐objective optimization on these competing objectives.

Educational Objectives:

1. Understand the concept of robust optimization.

2. Understand the construction of robust treatment plans based on breathing motion PDFs.

3. Understand the mathematical and dosimetric differences between treatment plans of varying levels of robustness.

4. Understand the multi‐objective viewpoint of robust optimization.
TU‐D‐L100J‐02: Noise Stationarity in Spiral CT
Authors: Whiting B , Politte D , Snyder D , O'Sullivan J , Massoumzadeh P , Williamson J
Published: July 2007

Purpose: The properties of noise in CT images are important in system design, algorithm development, and assessment of diagnostic observer performance, as well as for developing accurate dose reduction simulators. Conventional analysis assumes noise stationarity, even though it is well known that elements in a CT scanner, such as bowtie filters or tube‐current modulation, as well as filtered backprojection reconstruction, introduce variation in measurement statistics. In this presentation, two additional contributors to nonstationarity, hardware component variation and data interpolation, are analyzed, and the properties of noise in CT images are characterized. Method and Materials: Raw sinogram data was collected from open gantry scans. Offline reconstruction software, with access to data at individual processing steps, such as linear interpolation, was used for image reconstruction. White noise data was injected at various stages of reconstruction and changes in statistical properties at subsequent processing steps measured. Multiple simulations were used to create data ensembles for analysis. Covariance measures were calculated in the sinogram and image domains. Results: Raw CT data is nonstationary during the acquisition cycle, with covariances as high as 20% in unattenuated signals. Image reconstruction steps, such as linear interpolation and filtered backprojection, introduce variations in noise power on the order of +/− 50% in sinogram data. The variation of noise power can be up to 600% across a uniform image. The off‐diagonal covariance coefficients are on the order of 10% with nearest neighbor pixels. Conclusion: The conventional assumption of noise stationarity in CT images needs to be extended to include additional processes that introduce local variations in image statistics.
TU‐D‐L100J‐05: Assessment of Mesothelioma Tumor Response: Correlation of Tumor Thickness and Tumor Area
Authors: Armato S , Pearson E , Roberts R , Sensakovic W , Caligiuri P
Published: July 2007

Purpose: The quantification of pleural mesothelioma tumor extent is required to evaluate the efficacy of clinical trials. The manual acquisition of up to three linear tumor thickness measurements on each of three sections across a series of computed tomography (CT) scans is the current standard for tumor response assessment. The purpose of this study was to determine the correlation of response based on linear tumor thickness measurements and response based on tumor area. Method/MATERIALS: Two CT scans from each of 22 mesothelioma patients were collected. Using a computer interface, a radiologist acquired linear tumor thickness measurements on three sections of each patient's baseline scan and on the corresponding sections of each patient's follow‐up scan in accordance with our clinical protocol. These linear measurements across 132 CT sections (3 sections per scan, 2 scans per patient, 22 patients) provided the standard for comparison of area measurements. Another radiologist used a computer interface to delineate the tumor border in the same 132 CT sections to obtain tumor area and the changes in tumor area between the baseline and follow‐up scans of each patient. Results: A comparison of the sum of tumor thickness measurements and tumor area yielded a correlation coefficient of 0.59 across the 132 sections. With regard to tumor response, a comparison of change in the sum of tumor thickness measurements and change in the total tumor area between the baseline and follow‐up scans of the 22 patients yielded a correlation coefficient of 0.83. This relatively high correlation, however, does not capture the extent of variability in the data. For example, among patients with RECIST‐based “stable disease,” change in tumor area ranged from a decrease of 58% to an increase of 89%. Conclusions: Although measurements of tumor thickness and tumor area demonstrated moderate correlation, variability in this association requires further investigation.
TU‐D‐L100J‐09: The Effect of Mid‐Scan Changes of Breathing Frequency and Amplitude On 4D CT Quality
Authors: Noel C , Parikh P , Malinowski K
Published: July 2007

Purpose: Commercial 4D CT systems attempt to correlate imaging with the respiratory cycle of the patient. Though it is known that irregular breathing introduces artifacts, this has not been systematically explored. The purpose of this study is to quantitatively investigate the effect of changing the amplitude and frequency of the breathing pattern mid‐scan on image quality. Materials and Methods: The Washington University 4D phantom holding a 2 cm lung tumor object encased in solid water was scanned with the Philips Brilliance 64 slice CT scanner in retrospective helical mode using the “bellows” respiratory surrogate. The breathing cycle was obtained from a lung cancer patient, and the motion during the first half of the scan was produced at a baseline trajectory with a consistent frequency and amplitude. The two parameters were then varied mid‐scan to new frequency and amplitude values, throughout a range of 7.5 to 22.5 breaths/minute and 5 to 15 mm, respectively. Four phases were reconstructed using the commercial scanner software. Image quality was then evaluated by assessing volumetric, centroid, and geometric changes. Results: Changes in amplitude of more than 25%, regardless of change in frequency, caused measurable volumetric and geometric image artifacts. Conversely, changes in frequency alone did not cause a notable change in the presence of artifacts. The largest amount of volume change was present at the 0% phase (peak inhalation) where the change in amplitude was greatest, while the least amount of volume change was present at the 50% phase. Conclusions: These basic breathing statistics of the patient's respiratory wave would be useful in quickly assessing the quality of a helical 4D CT scan prior to image reconstruction. More work is necessary to generalize these results with other scan acquisition techniques and respiratory tagging algorithms. Conflict of Interest: Research funded by Philips Medical Systems.
TU‐D‐AUD‐01: Absolute Dose Reconstruction in Proton Therapy Using PET Imaging Modality: Feasibility Study
Authors: Fourkal E , Fan J , Paskalev K , Ma C , Velchev I
Published: July 2007

Purpose: Radiation treatments using proton beams are accompanied by production of small amounts of positron‐emitting isotopes along the beam paths. These short‐lived radioisotopes, mainly , and , allow imaging of three dimensional in‐vivo activity distribution using positron emission tomography (PET). However, since the correlation between the combined activity distribution and absorbed dose is not linear, one cannot readily ascertain the dose distribution from the measured activity. The purpose of this study is to develop a mathematical model which would allow reconstruction of the absolute dose in a patient based on in‐vivo activity distribution. Method and Materials: Fluka Monte Carlo simulation code was used to generate three dimensional activity kernels for each individual proton energy in the therapeutic range. Subsequently, these kernels can be employed to calculate the unknown energy spectra used in each individual proton beam during patient irradiation. The method is based on a solution of a system of linear inhomogeneous equations using a “random creep” algorithm. The final convolution of the energy spectra with dose kernels will yield the absolute dose. Results: The developed model has been used to reconstruct the dose distribution for a test case of a tissue phantom irradiated by two parallel‐opposed proton beams. Comparison between the known and reconstructed dose distributions shows that the reconstructed dose to the target compares very well (within 2.%) to that initially delivered. This suggests that it should be feasible to use the PET scanning modality to reconstruct in‐vivo absolute dose distribution. Conclusions: Energy delivered by proton beams to the patient in a single fraction generates enough activity that can be used for the inverse problem of dose reconstruction. Our calculations confirmed that by studying a test case of a tissue phantom irradiated by a parallel‐opposed beam arrangement. The reconstructed dose is within 2% of the delivered.