bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐FF‐T‐442: Comparing Geant4 and MCNPX for Joint Research to Minimize Uncertainties in Proton Therapy
Authors: Titt U , Paganetti H , Mohan R
Published: April 2010

Purpose: To “cross validate” the Monte Carlo codes (MCNPX and GEANT4) used at two different institutions for dose calculation and basic research in proton therapy. Methods and Materials: Geant4 and MCNPX are being used at the MGH (Massachusetts General Hospital) and at the MDACC (MD Andersen cancer Center), respectively, as Monte Carlo systems to provide simulations for research and clinical purposes in proton therapy. A current collaboration between the two institutions concerning the minimization of uncertainties necessitates a synchronization of the systems in order to produce consistent results. Simple validation geometries, consisting of a square brass aperture, half beam blocks, comprising lung and bone material, and a water phantom were used for initial synchronization of dose deposition from monoenergetic proton sources. More complex phantoms and source models were employed to solidify confidence in the validation. Finally, a CT volume of a human head, irradiated with spread out Bragg peaks was used to verify the validity of both Monte Carlo systems. The results of the simulations, lateral and longitudinal dose profiles were compared using absolute differences, the distance to agreement as well as the gamma analysis method. Results: All profiles agreed within 2 mm in the high dose gradient regions of the Bragg peaks, while the gamma analysis for a 2% and 2mm criterion resulted in 97.5% of all points in lateral depth doses and 95% of all points in depth dose profiles passing the test. Conclusions: With the proper choice of physics parameters, the two Monte Carlo systems produce results that agree very well. The use of different Monte Carlo systems at different institutions is, therefore, no source of additional systematic uncertainties in the ongoing research of minimizing uncertainties associated with proton therapy.
SU‐FF‐T‐450: Verification of the GEANT4 Monte Carlo Code in Low Energy Photon Transport
Authors: Jiang H
Published: April 2010

Purpose: GEANT4 is a powerful and versatile general‐purpose Monte Carlo code. The reliability of GEANT4 in high energy photon transport has been largely confirmed. On the other hand, the discrepancy to other Monte Carlo codes in low energy range has also been reported in the past years. The purpose of this investigation is to explore the performance of GEANT4 at low photon energies (< 50 KeV), and to verify the recent improvements of GEANT4 in photon physics. Method and Materials: The MCNP Monte Carlo code will be used as the reference in this study. The physics of dominant photon interactions in low energy range (Photoelectric effect, Compton scattering, and Rayleigh scattering) implemented in the two codes and the corresponding cross section/attenuation coefficient data will be compared. The production of fluorescent photons, which play an important role in dose deposition of KV photons, will be especially addressed. Simplified cases involving 125I/103Pd or KV X‐ray beam will be modeled and simulated with both MCNP and the latest version of GEANT4 to exemplify the extent of influence under various situations. Results: Detailed physics descriptions are required for modeling low energy photon transport in Monte Carlo codes. Differences in physics implementation between MCNP and GEANT4 are known. These differences could induce noticeable differences in radiation dose and particle flux. Conclusion: GEANT4 has been gradually accepted to be a very useful Monte Carlo simulation tool to tackle many problems in radiation therapy. A comprehensive study of KV photon transport provides verification of the reliability of the code in the low energy range, and will potentially boost the applications of GEANT4 in radiotherapy modalities such as eye plaque therapy, prostate seed implant brachytherapy, and intraoperative radiotherapy (IORT).
SU‐FF‐T‐457: Second Cancer Risk From Secondary Neutrons for a Boy Who Received Proton Craniospinal Irradiation
Authors: Taddei PJ , Mirkovic D , Fontenot JD , Giebeler A , Zheng Y , Kornguth D , Mohan R , Newhauser WD
Published: April 2010

Purpose: Proton fields used in radiotherapy expose healthy tissue to secondary neutrons emanating from the treatment unit (or “external neutrons”) and produced within the patient (or “internal neutrons”), which provide no known benefit to the patient and may increase a patient's risk of developing a second cancer. The objectives of this study were to calculate equivalent doses to organs and tissues and to estimate second cancer risk from secondary neutrons for a boy who received craniospinal irradiation (CSI) with proton beams. Method and Materials: Using Monte Carlo simulations, equivalent dose from secondary neutrons was calculated in organs and tissues for the 10‐year‐old boy. In order to maximize the accuracy and realism of the simulations, the geometric model comprised a detailed passive‐scattering proton treatment unit and a voxelized phantom that was created from the actual CT images of the patient. All treatment fields were included. The proton treatment included CSI at 30.6 Gy plus a boost of 23.4 Gy to the clinical target volume in the brain. Based on the equivalent dose values, effective dose and second cancer risk from secondary neutrons were predicted. Results: The effective dose from secondary neutrons was 418 mSv, of which 344 mSv was from external neutrons and 74 mSv was from internal neutrons. The lifetime attributable risks of second cancer incidence and mortality were 6.2% and 3.4%, respectively. The cancer sites that carried the highest risks were the lungs, colon, and thyroid. The risks were predominated by the two spinal fields; very little risk was associated with the boost fields. Conclusion: The results of this study provide an estimate of the secondary neutron dose and corresponding risk for a pediatric patient undergoing proton CSI and support the suitability of passively‐scattered proton beams for the treatment of tumors of the central nervous system in children.
SU‐FF‐T‐460: Comparison of Dose Distributions for Proton Machines with In‐Room Energy Degradation with Variable Energy Machines
Authors: Wang S , Gordon J , Langenegger A , Siebers J
Published: April 2010

Purpose: To compare entrance and out‐of‐target dose values obtainable for single energy proton therapy treatment device with in‐room energy degradation with a device that has variable energy selection. Method and Materials: MCNPX Monte Carlo simulations are utilized to create a hypothetical dual‐scattering proton treatment delivery device in which a 250 MeV proton beam is delivered to the treatment room, independent of the desired treatment depth. Energy degradation is achieved in‐line using a carbon range shifter located 1.2 m upstream of the isocenter location. Calculations of in‐phantom depth‐dose and in‐air lateral and distance scans are performed for numerous range‐shifter and range‐modulator wheel settings to provide sufficient input data for a proton dose calculation algorithm. In‐phantom and patient dose distributions for this device are compared with those for a delivery device capable of variable room entrance energies from 70–210 MeV. Results: For a 6×6×4 cm3 target located at 10 cm and 5 cm depth in a water phantom, entrance doses for a single energy device are 69% and 73.8%, respectively, while the variable energy entrance doses are 61% and 64.4%. For a one‐field head‐and‐neck treatment plan, the single energy out‐of‐target doses are 5.7% higher than the variable energy device. Conclusions: The proton machine with in‐room energy degradation shows higher entrance dose than the machine with continuous entrance energy due to increased energy straggling in the beam. Further investigations are warranted to establish the potential clinical significance of such deviations.

Conflict of Interest: This work was funded in part by Varian Medical Systems.
SU‐FF‐T‐467: A New Patient Scheduling Approach for Proton Therapy Treatment Delivery
Authors: Salari E , Men C , Li Z , Mendenhall N , Palta J , Romeijn H
Published: April 2010

Purpose: To develop a patient scheduling system for treatment delivery at the University of Florida Proton Therapy Institute (UFPTI) such that patients' time preferences are satisfied to the largest extent possible, operational and technical restrictions are met, and at the same time efficient utilization of the facility is guaranteed. Method and Materials: A new modeling approach has been proposed in which so‐called restricted and desired time windows are defined for each patient based on the operational restrictions and his/her time preferences, respectively. A treatment schedule is decomposed into two components; (i) sequence and (ii) timing, so that given a certain sequence of patients an associated optimal timing can be determined with respect to the restricted and desired time windows. In order to maintain stability in the treatment schedule, a common order in which patients are treated, a so‐called union sequence is defined for the entire planning horizon. On the solution side, an exact algorithm, the so‐called timing optimizer, is proposed to find the optimal timing given the sequence. Furthermore, a local search heuristic, which employs the timing optimizer to evaluate the quality of a sequence, is developed to obtain high‐quality sequences with respect to three evaluation criteria defined to measure the desirability of a schedule. Results: The patient scheduling approach has been implemented and it is currently under clinical testing at the UFPTI. The experiments show that the proposed system can find high‐quality schedules within a minute. Conclusion: This work presents a new heuristic approach to patients scheduling for treatment delivery. Patient scheduling at the UFPTI was formerly done manually in a time‐consuming process; with the help of the new developed algorithm it is now possible to produce high‐quality schedules in real time.
SU‐FF‐T‐473: Time Response Study of Calypso Localization and Tracking System for Moving Tumors
Authors: Kassaee A , Lin L , Ingram M , Bieda M , Vapiwala N , Metz J
Published: April 2010

Purpose: To study the time response of the Calypso 4D localization and tracking system for prostate and pancreatic tumors Method and Materials: We have implanted Calypso beacon transponders into pancreas of three patients for tumor tracking during the radiation delivery. The system is originally designed for localization and tracking of prostate during radiotherapy. We have observed delay times for localization and delay of start time for tracking longer for pancreatic cases as compared to prostate cases. The system has successfully tracked our pancreatic patients for each treatment. To investigate the delay time as a function of tumor motion, we assembled a moving platform and placed a phantom with imbedded transponders on it. The phantom was moved sinusoidally with various frequencies. The ranges of frequencies included the motion correlated with prostate and pancreas. In the case of pancreas, there is direct correlation with the breathing cycle. Results: The usual delay time for prostate localization and delay time for start of tracking is about 10 to 12 seconds. For pancreatic cases, the time of localization and tracking increases by a factor of 9 to 10. The system delay does not affect its ability to accurately track tumor motion. Conclusion: The Calypso is a robust system that is capable of tracking tumors covering a wide spectrum of motion including respiratory motion. The delay time for localization and tracking modules are well accepted clinically.
SU‐FF‐T‐477: Study On the Modeling of Digital Couch for Proton Treatment Planning System
Authors: Yoon M , Kim J , Ahn S , Cheong M , LIM Y , Kim D , Shin D , Lee S , Park S
Published: April 2010

Purpose: To evaluate the modeling of couch with a commercial proton treatment planning system (TPS, Eclipse, v8.12). Method and Materials: To keep the shape and dimensions of an actual proton treatment couch, it was scanned using CT scanner and inserted into the TPS system by replacing CT couch of all transverse CT slices. Results: The experimental data shows that the range of proton beam is shorten by 0.99 ± 0.01cm and spread‐out Bragg peak (SOBP) varies 0.10 ±0.09cm with insertion of proton couch when the beam direction is perpendicular to proton couch (0° in our configuration). While the average range shift in proton beam increases from 0.99cm to 1.70cm as the angle of the beam increases from 0° to 55°, there were no distinct SOBP changes with beam angle revealing less than 0.1cm variation. Our results suggest that the dosimetic factors such as range, profile, output factor remained almost same with the insertion of proton couch, whereas the beam range is largely dependent on both the insertion of couch and beam angle to couch. Using inserted CT scanned proton couch in TPS, the calculated and measured beam range was cross‐compared and the results show that the range of proton beam is shorten by ∼0.7cm in TPS, which shows ∼0.3cm difference with actual measurement. The difference between computed and measured range was compensated by assigning appropriate densities to the inserted proton couch, which is called digital couch. Measured and computed PDD with the digital couch show that the beam range and SOBP are well matched for various beam angles revealing the difference of 0.01±0.02cm and 0.12±0.03cm, respetively. Conclusion: These results suggest that the digital couch with relevant density assignment may be a good solution for proton couch modeling, which can be used for commercial proton TPS.
SU‐FF‐T‐478: Radiation Oncology Failure Mode Effect Analysis (ROFMEA) Development and Application
Authors: Wasserman S , Gironda V , Forster K
Published: April 2010

Purpose The failure mode effect analysis (FMEA) tool was customized for use in radiation oncology practice. The creation of systematic tables to classify severity, occurrence probability, and detection probability enhances the ability of the FMEA tool to minimize errors and, more importantly, their effect. Changes were made to an existing quality management program based upon an application of the customized radiation oncology FMEA (ROFMEA). Methods An existing quality assurance program included documentation of all treatment variances in a Radiation Oncology department. All variances occurring from 2000 through 2005 were analyzed. Variances were scored in the three categories used in a FMEA; the potential harm that could have been caused if the initial error had not been detected, how often this type of error occurred, and the probability of this type of error occurring and not being detected. Data analysis led to the creation of systematic tables specific to Radiation Oncology for scoring each of these three categories. The tables were applied during an FMEA of the prescription, planning and treatment processes. Results The results of a preliminary application of the FMEA tool in Radiation Oncology were limited due to a lack of terminological and classification precision which led members to score the potential severity of any error high. In contrast, application of the ROFMEA tool identified weaknesses in the planning process which had potential to cause the most harm, and resulted in modifications of the process. Conclusions More so than other medical disciplines, Radiation Oncology lends itself to a logical systematic application of the FMEA process. Application of the customized ROFMEA tables will allow staff to identify those parts of a process which have the greatest probability of causing harm to a patient. Evidence‐based safe practices achieved from ROFMEA ally to target practice quality improvement
SU‐FF‐T‐496: A Simple Kinetic Model with a Mechanistic Basis for Tumor Survival Curves
Authors: Martín‐Landrove R , Martín‐Landrove M , Guillén N
Published: April 2010

Purpose: To develop a simple kinetic model for tumor survival curves which is able to describe their behavior for high and low LET clinical applications and at the same time can provide a relation to the mechanisms for DNA damage and repair. Method and Materials: Analytical and numerical solution of a nonlinear set of equations
urn:x-wiley:00942405:media:mp1994:mp1994-math-0001 where N is the number of clonogenic cells with undamaged DNA, NR is the number of cells with reversible DNA damage and NNR is the number of cells with irreversible DNA damage. At the same time α0 and N∞ are Gompertz model parameters and κREP is the probability per unit time for DNA repair. The probability per unit time for radiation reversible damage of DNA is given by κRAD (t), as well as γκRAD (t) is the probability per unit time for radiation irreversible DNA damage. A study of limit cases for the solution behaviour is made for several cases in order to find the relation between the linear‐quadratic model parameters and those of the proposed kinetic model, which is going to make easier its clinical application. Results: The proposed model is able to describe the proper behavior at low and high LET for V‐79 cells in late S phase. The values obtained for the new set of parameters and clinical applications related to fractionation are discussed. Conclusion: It is possible to develop simple microscopic models based on DNA damage and repair mechanisms in order to describe tumor survival curves. DNA damage has to be considered in two steps, one reversible and another irreversible. Its relation with the linear‐quadratic model can be helpful in order to implement its clinical application.
SU‐FF‐T‐501: The Effect of Monte Carlo‐Based Dose Calculations On Tumor Control Probability Modeling
Authors: Huang E , Lindsay P , Hope A , El Naqa I , Bradley J , Deasy J
Published: April 2010

Purpose: It has not been established whether accurate lung dosimetry really has an impact on metrics and modeling related to outcome prediction. We studied the impact of Monte Carlo‐based dose calculations on TCP modeling of lung cancer tumors. Methods and Materials: All analyzable patients treated for NSCLC between 1991 and 2001 at Washington University in St. Louis (n=56) had TCP modeled using water equivalent dosimetry and Monte‐Carlo corrected dosimetry in turn. Clinical factors in the modeling included age, gender, chemotherapy, performance status, weight loss, and smoking. Dosimetric variables included Vx, Dx, maximum dose, mean dose and minimum dose covering the primary GTV. The best multivariate logistic models for both treatment planning system dose (homogeneous, uncorrected for tissue heterogeneities) and Monte‐Carlo corrected dose were obtained. Results: The best multivariate model for homogeneous dose calculations is a six‐parameter model (Spearman's rank correlation coefficient, R=0.62) including V75_TCPgtvPlan, V80_TCPgtvPlan, Mindose_TCPgtvPlan, age, PreTxChemo and gtvVol. However, there was not a strong preference for specific dose‐volume terms, and many models had a similar predictive power. The best multivariate model for Monte‐Carlo corrected dose is a two‐parameter model (R=0.527) including V75_TCPgtvMC and gtvVol, and the modeling strongly indicated that only two terms were necessary to explain the data. Interestingly, the Monte Carlo model has the superior ‘face validity” while the water‐based model resulted in a higher overall predictive power. The reasons for this are currently unknown. Conclusions: Monte‐Carlo corrected dose significantly impacts resulting TCP modeling, which demonstrates the need accurate modeling. Differences in the resulting models between water‐based and Monte Carlo based dosimetry remain poorly understood and will require further research.

Partially supported by NIH R01 grant CA85181.
SU‐FF‐T‐502: Biological Modeling of the Beam Delivery Line Components for Active Scan Irradiation Technique in Heavy‐Ion Radiotherapy
Authors: Bourhaleb F , Attili A , Russo G , Schmitt E , Cirio R , Giordanengo S , Marchetto F , Monaco V , Peroni C , Sacchi R
Published: April 2010

Purpose/Objective(s): The beam delivery line of the active scanning irradiation system for heavy‐ion radiotherapy requires a series of elements along the beam path before the patient like ripple filters and monitoring system. Usually these elements are optimized only for physical dose profiles. However, it is necessary to consider the biological effect and their impact on the dose distribution, especially in the Bragg peak region for a correct estimation of the peak spread. Materials/Methods: A full beam delivery line of the national center of oncologic hadrontherapy (CNAO) is simulated with the Monte Carlo package GEANT4 to get the actual distribution in the treated volume of particles and fragments and the corresponding energies. The treated volume is simulated as well defining different tissues in the head and neck region. The evaluation of biological effects was studied using a code based on the Local Effect Model (LEM). The computational effort was performed using the distributed INFN Grid computing resources. Results: We estimate the impact on the relative biological effectiveness (RBE) and the biological dose distribution of the passive elements of the beam delivery line. The shape of the physical dose at Bragg peak is different from the corresponding biological dose. Though the transfer functions characterizing each of the element should involve a rigorous evaluation of the biological effects. Conclusions: A full characterization of the beam delivery line considering the biological impact provides a flexible tool in the treatment planning system for modeling the possible variations in the same beam line or modeling a new beam lines.
SU‐GG‐BRC‐06: An Enabling Technology for Very Low Exposure X‐Ray Imaging
Authors: Wronski M , Zhao W , Reznik A , Tanioka K , DeCrescenzo G , Rowlands J
Published: April 2010

Purpose: Medical procedures such as cardiac catheterization, angiography and the deployment of endovascular devices are routinely performed using x‐ray fluoroscopy, in which each image is obtained at very low x‐ray exposures. The imaging performance of current solid‐state flat panel detectors (FPD) is compromised by electronic noise at these low detector exposures (0.1–10 μR/frame). There is thus a clear need to develop an imaging detector with the quantum noise limited operation of an x‐ray image intensifier and the inherent advantages of a compact solid‐state device. Here we propose a technology that takes advantage of avalanche multiplication of charge in an amorphous selenium (a‐Se) photoconductor. Method and Materials: To determine whether this technology holds promise for next‐generation FPDs, we investigate the following: (1) device and material requirements for prevention of electrical breakdown, (2) leakage currents at high electric fields, (3) real‐time imaging capability and linearity, and (4) the compliance of an avalanche a‐Se photoconductor with low‐voltage image readout electronics. Results: Our results show that a distributed resistive layer coupled to the avalanche photoconductor enables breakdown‐free operation. We report, for the first time, avalanche gains exceeding 104 in a solid‐state x‐ray detector, and leakage currents of only ∼10 pA/mm2. The detector has a voltage‐programmable avalanche gain and can be operated in a linear regime at 30 frames per second over a five order of magnitude x‐ray exposure range, including the lowest clinical exposures encountered in fluoroscopy. Furthermore it is compatible with existing thin film transistor technology on which current FPDs are based. Conclusion: This detector technology should enable the development of next‐generation dose‐efficient FPDs for interventional radiology as well as advanced applications such as cone‐beam computed tomography or tomosynthesis. Combined with techniques such as region‐of‐interest fluoroscopy, our detector technology could significantly reduce radiation dose to the patient and physician.
SU‐GG‐BRC‐09: CT Detection of Primary and Metastatic Lesions with a Nano‐Agent in Rabbits: Validation with FDG‐PET
Authors: Zheng J , Allen C , Jaffray D
Published: April 2010

Purpose: To evaluate the performance of a recently engineered nano‐sized liposome CT agent to detect primary and metastatic tumor lesions in a VX2‐sarcoma rabbit model as compared to FDG‐PET. Method and Materials: Nine New Zealand White rabbits bearing VX2‐sarcoma in their left lateral quadriceps received a single intravenous injection of 80 nm liposomes co‐encapsulating 185 ± 37 mg/kg iodine in the form of iohexol (Omnipaque®) and 7 ± 1 mg/kg gadolinium in the form of gadoteridol (Prohance®). The CT/PET (GE Discovery ST) imaging session took place twelve days after the tumor inoculation procedure, five days post liposome contrast administration and one hour post‐FDG injection (30.3 ± 5.1 MBq/kg). Following CT/PET imaging, the rabbits were sacrificed and the primary and metastatic lesions were examined by a pathologist. The measurement of tumor size was performed on the CT data set. The registration of the CT and PET images was performed using MIPAV. Results: Liposome‐CT demonstrated the same sensitivity and specificity as FDG‐PET for the detection of the 9 primary tumors (volumes = 25 – 7280 mm3, SUVmax = 1.5 – 10.9, HUmax = 173 – 596). In addition, liposome‐CT detected 13 metastatic muscle lesions (volumes = 14 – 2732 mm3, HUmax = 254 – 493) that were histologically malignant, while FDG‐PET identified 7 (volumes = 54 – 1044 mm3, SUVmax = 2.7 – 7.1). For the 16 lesions detected by both imaging modalities, there was a positive correlation between the PET SUVmax and the CT HUmax. Conclusion: In this investigation, increased contrast of primary and metastatic lesions in CT was achieved with the administration of the liposome nano‐agent. This demonstrates the feasibility of employing the liposome‐CT method for effective tumor detection and localization.
MO‐SAM‐BRB‐01: Biological Aspects of Heavy Charged Particle Radiation Therapy
Authors: Paganetti H
Published: April 2010

The relative biological effectiveness (RBE) is defined as the ratio of the doses required by two radiations to cause the same level of effect. Thus, the RBE depends on the dose and the biological endpoint.

Proton therapy has been based on the use of a generic RBE of 1.1, which is applied to all treatments independent of dose/fraction, position in the irradiated volume, initial beam energy or the particular tissue. The variability of RBE in clinical situations is believed to be within 10% but quantitative dependencies of the RBE on various physical and biological properties are disregarded. The magnitude of RBE values and their variations is significantly larger for Carbon ion therapy. Studies have demonstrated significant RBE values of more than 3 in clinically relevant scenarios for Carbon ions. Further, there might be considerable variations in RBE within the irradiated volume that are being considered in treatment planning and delivery.

Heavy ions have a potential advantage compared to protons when it comes to their therapeutic ratio due to an elevated RBE in the tumor (based on the oxygen enhancement ratio and higher average LET values) compared to the surrounding tissue. However, on the other hand, at present there are still considerable uncertainties in heavy ion RBE values. Elevated RBE values (even for protons) might be expected particularly near the edges of the high‐dose volume because doses may be deposited by high‐LET particles. The increase in RBE as a function of depth in the patient results in an extension of the bio‐effective range of the beam. Further, because RBE values may increase with deceasing dose causing elevated RBE values for organs at risk compared to the target area. In order to incorporate detailed RBE modeling in treatment planning as a function of LET, dose and endpoint, two aspects have to be considered. Firstly, the available information from experimental studies and secondly, our ability to calculate RBE values for a given treatment plan based on parameters extracted from such experiments. RBE values are often based on cell survival data because this is the main endpoint of interest in radiation therapy. However, one migt expect differences in RBE for cell survival compared to cell mutation, the latter being an important endpoint for late effects.

This educational session will focus on summarizing the mechanisms behind RBE variations among treatment modalities. Further, RBE variations as a function of LET, tissue and dose will be presented based on experimental and simulated data for proton and Carbon ion beams. Finally, different approaches for theoretical modeling of RBE values for treatment planning purposes will be discussed briefly.

Learning Objectives:

1. Understand the mechanisms behind heavy charged particle RBE values

2. Understand the variations of RBE as a function of physical and biological parameters

3. Understand the clinical implication of RBE values in proton and Carbon ion therapy
MO‐SAM‐304A‐01: Optimizing CT Dose and Image Quality for Different Patient Sizes
Authors: Cody D , McNitt‐Gray M
Published: April 2010

CT technology has improved dramatically over the past decade and its clinical utilization has increased significantly as well. While CT can yield exquisite descriptions of anatomy that were not previously possible (at least not with noninvasive techniques), its increased utilization has led concerns over radiation dose; CT has now been identified as the single largest contributor to medical radiation dose to the population and accounts for approximately 50% of medical exposure. Methods to reduce radiation dose have been the focus of all stakeholders (medical physicists, technologists, radiologists, manufacturers and regulators). Reducing dose while maintaining acceptable image quality can be complex and this is made even more complex when considering patients of different sizes. This talk will first describe methods currently used, and some being developed, to estimate radiation dose in patients. This will include a discussion of measurement techniques as well as Monte Carlo simulation‐based techniques. Specific attention will be paid to the differences in dose to patients of different sizes ranging from pediatric patients to obese adult patients. Tradeoffs in image quality and radiation dose will also be described in this context as well. Radiation dose reduction techniques, including a review of various tube current modulation schemes currently being employed will also be described. The effect of these dose reduction methods on both radiation dose and image quality will be discussed, again with attention to how they can be deployed with patients of different size.

Learning Objectives:

1. Understand how radiation dose for CT studies is currently estimated

2. Understand the trade‐offs of dose and image quality, especially for large (obese) patients and in pediatric patients

3. Review of the manufacturers' dose modulation methods and how these affect dose in different patients
MO‐A‐213A‐01: Harmonic Imaging
Authors: Zagzebski J
Published: April 2010

The purpose of this course is to acquaint participants with recent signal processing techniques and modes on ultrasound instruments. Emphasis is on second harmonic imaging, a processing and display mode implemented on most scanners. Harmonic imaging was originally applied to enhance echo signals due to nonlinear scattering by ultrasound contrast agents. However, the modality is much more commonly used in “native tissue harmonic” mode, where echoes originating from nonlinear components of propagating acoustic beams are detected and displayed. The source of these echo signals and the advantages and disadvantages of harmonic imaging will be described. When applied effectively, harmonic imaging provides significant improvements in image quality compared to that obtained using conventional signal processing. A primary reason for harmonic imaging's improved image quality is reduction of acoustic noise caused by reverberations within overlying tissues. Other contributors to high quality ultrasound images include spatial and frequency compounding and speckle reduction. These techniques also will be described and placed in context with harmonic imaging.

Learning Objectives

After completing this course, participants will:

1. Describe the origin of harmonic echo signals for both conventional and contrast agent imaging modes;

2. Contrast resolution and penetration capabilities for harmonic imaging and linear imaging;

3. Identify clinical situations where harmonic imaging is used advantageously;

4. Describe how harmonic imaging is used to enhance detection of contrast agents;

5. State the benefits of spatial and frequency compounding, and speckle reduction.
MO‐B‐211A‐01: Biological/Clinical Outcomes Models in Radiation Therapy Planning
Authors: Yorke E
Published: April 2010

Radiation therapy must strike a balance between clinically acceptable tumor control probability (TCP) and normal tissue complication probability (NTCP). Typical treatments expose several normal organs to incidental dose with an associated risk of a variety of radiation‐induced complications, each of which may depend differently on the spatial and temporal dose distribution. Dose/volume effects, wherein the ‘iso‐complication dose’ increases if the irradiated volume fraction decreases, are particularly important in designing and evaluating treatment plans. These effects are pronounced for some complications and weak for others. The classic “Emami” paper of 1991 summarized guidelines based on decades of clinical experience derived from the simple beam arrangements of the 2‐dimensional planning era when discrete parts of normal tissues typically received uniform doses at conventional fractionation schedules (partial organ irradiation). More recently, 3‐dimensional planning (including IMRT) has led to more conformal distributions with superior patient‐specific dosimetric information. Three‐dimensionl techniques have also encouraged treatment to higher doses and exposed normal tissues to a more variable and inhomogeneous range of dose distributions and fraction sizes. These complex relationships are often summarized in dose‐volume histograms (DVH).

Depending on the suspected volume effect, treatment planners use various DVH‐based metrics to estimate complication risks. These include single DVH points (e.g. maximum dose or percent or absolute volume above a dose cut‐point), combinations of such points, generalized equivalent uniform dose (including mean dose) and models (e.g. Lyman model). Co‐morbidities, chemotherapies and other medical factors may also need to be considered. We will describe commonly used evaluation metrics, some of which date back to the early 1990's and others from more recent publications or in‐house experience.

The current metrics used to evaluate normal tissue DVHs are sub‐optimal. Under the QUANTEC (Quantitative Analysis of Normal Tissue Effects in the Clinic) initiative, a project that is jointly funded by AAPM and ASTRO, approximately 60 physicists and physicians have critically surveyed the NTCP literature. Their updated consensus guidelines will be published in the near future. Some of their preliminary findings will be discussed here (check the proffered sessions for other presentations).

Learning Objectives:

1. Understand the general features of the volume effect as applied to NTCP.

2. Be familiar with the dose/volume metrics commonly used for complications risk estimation in treatment planning.

3. Understand some of the difficulties in determining reliable dosimetric predictors of normal tissue complications.
MO‐C‐BRB‐01: Present and Future Role of Computers in Medicine
Authors: Foster I
Published: April 2010

Computational methods will transform both biological science and clinical practice over the next decades. Dramatic increases in the quantities of experimental, clinical, and other data, and in our ability to federate data from many sources, are enabling powerful computational approaches such as the mining and integration of data from huge databases in search of novel patterns and correlations. Rapid advances in both computer power and numerical methods enable the use of computational modeling and simulation to study previously inaccessible phenomena at the molecular, cellular, anatomical, and population levels. This marriage of modern biological and medical research with the computational sciences is destined to capture new levels of biological complexity that will motivate new theory, unearth novel biological concepts, and ultimately, drive new diagnostic strategies and treatment approaches.

This keynote is given by Ian Foster, who is known as the “father of grid computing”. He is currently The Arthur Holly Compton Distinguished Service Professor of Computer Science, Director of the Computation Institute, and Argonne Distinguished Fellow at The University of Chicago and Argonne National Laboratory. Foster has received the Lovelace Medal of the British Computer Society, the Gordon Bell Prize for high‐performance supercomputing, and is a fellow of the American Association for the Advancement of Science.
MO‐D‐BRD‐02: Dielectric Wall Accelerators for Proton Therapy
Authors: Caporaso G , Chen Y , Sampayan S , Akana G , Anaya R , Anderson D , Blackfield D , Carroll J , Cook E , Falabella S , Guethlein G , Harris J , Hawkins S , Hickman B , Holmes C , Horner A , Nelson S , Paul A , Pearson D , Poole B , Richardson R , Sanders D , Selenes K , Sullivan J , Stanley J , Wang L , Watson J , Weir J
Published: April 2010

A new type of compact induction accelerator is under development at the Lawrence Livermore National Laboratory that promises to increase the average accelerating gradient by at least an order of magnitude over that of existing induction machines. The machine is based on the use of high gradient vacuum insulators, advanced dielectric materials and switches and is being developed for a variety of applications. Research describing an extreme variant of this technology aimed at producing a compact, variable output linear accelerator for proton therapy for cancer will be described along with the technical challenges and issues. The goal of the development is to produce a proton accelerator that will fit in a standard linac vault and deliver intensity modulated proton therapy. Tomotherapy, Inc. has licensed the new accelerator technology from the Lawrence Livermore National Laboratory and the Compact Particle Acceleration Corporation (CPAC) is supporting development of the system. Research sponsored by Tomotherapy, Inc. and CPAC.

Conflict of Interest: Some of the co‐authors have a financial interest in Tomotherapy, Inc. and/or CPAC.
MO‐D‐BRB‐02: Using Total‐Variation Regularization for IMRT Inverse Planning with Field‐Specific Numbers of Segments
Authors: Zhu L , Lee L , Ma Y , Ye Y , Mazzeo R , Xing L
Published: April 2010

Purpose: Currently, there are two types of treatment planning algorithms for intensity modulated radiation therapy (IMRT). The beamlet‐based algorithm generates fluence maps with high complexity, resulting in large numbers of segments in the delivery. The segment‐based direct aperture optimization (DAO) algorithm uses a small number of segments. However, the number of segments is typically pre‐fixed, and the optimization is computationally intensive. In this work, a regularization based algorithm is proposed to overcome the drawbacks of the DAO method. Method and Materials: Instead of smoothing the fluence maps, we include a total‐variation term in the optimization objective function to reduce the number of signal levels of the fluence maps and therefore the number of deliverable apertures. As compared to the DAO algorithm, our method has an efficient form of quadratic optimization, with an additional advantage of optimizing field specific numbers of segments based on the modulation complexity. Results: The proposed approach is evaluated using two clinical cases. Provided that the clinical acceptance criteria of the treatment plan are satisfied, for the prostate patient, the total number of segments is reduced from 61 using the Eclipse planning system to 35 using the proposed algorithm; for the head and neck patient, the total number of segments is reduced from 107 to 28. The head and neck result is also compared to that using an equal number of 4 segments for each field. The comparison shows that using field‐specific numbers of segments achieves a much improved dose distribution. Conclusion: A total‐variation based inverse planning method is proposed in this work. As compared to other existing methods, the proposed algorithm is derived using different principles and implemented efficiently. The patient studies show that the proposed algorithm significantly reduces the total number of segments used in the treatment without compromising the delivered dose distribution.
MO‐D‐BRC‐01: Introduction: Challenges of Post‐Treatment and Real‐Time Imaging of Dose Deposition in Proton Therapy
Authors: Bortfeld T
Published: April 2010

The finite range of protons is the primary physical advantage leading to the potentially greatly improved dose distributions in proton radiation therapy. The other side of the coin is that it takes extra care to make sure that the protons actually stop at the right location. Fortunately, proton therapy provides unique opportunities to visualize interactions of the therapeutic beam with the patient. These interactions are more or less closely related to the delivered dose distribution, and can therefore be used as a dose surrogate for treatment verification. In this symposium we will highlight three examples of such interaction mechanisms, as well as their potential to provide clinically useful information about the in‐vivo dose distribution either post‐treatment or even in real‐time. Some of the methods are applicable to photon therapy as well.

In this short introduction we will discuss various reasons that lead to uncertainties in the proton range and will show estimates of the magnitude of the range uncertainties. We will then go over techniques to deal with range uncertainties in treatment planning, and will finally discuss what could be gained if we could reduce or eliminate range uncertainties.

Learning Objectives:

1. Name three reasons for range uncertainties in proton therapy.

2. Quantify the magnitude of range uncertainties.

3. Name at least one method that reduces the impact of range uncertainties.
MO‐D‐BRC‐04: Prompt Gamma Measurements for the Verification of Dose Deposition in Proton Therapy
Authors: Kim J , Kubo H , Tanimori T
Published: April 2010

The proton beam radiotherapy has a merit in that the dose deposit falls off at the end of the beam range. However, mismatch of the falloff location with the prescribed dose boundary can cause adverse effects. Measurement of gamma‐rays emitted by nuclear reactions of the incident proton beam with target materials is the only method to verify the dose distribution in situ. We have investigated two different methods of measuring the prompt gamma distribution: 1) multi‐layer collimation method, which measures the 1D distribution of gamma production at the target, to assure the endpoint of the dose deposition, 2) electron‐tracking Compton camera, which can reconstruct gamma trajectories, to verify the dose distribution. The collimation method can be effectively used when the background neutron flux is low. Hence, it can be more readily applicable to the scanning method in terms of the therapy beam delivery compared to the scattering method. Secondly, the Compton camera is a powerful tool to image the prompt gamma distribution. A preliminary experiment has been carried out with a water phantom at the beam energy of 150 MeV, and images of prompt gamma generation are attained. The clinical application could be considered with further improvement of detection efficiency.

This lecture will review the uses of multi‐layer shielding and the Compton camera in the measurement of prompt gamma‐rays emitted from the target to verify the dose deposition during proton therapy.

Learning Objectives:

1. Understand the physics of dose deposition by the proton therapy

2. Understand multi‐layer shielding techniques to measure the prompt gamma distribution for the verification of the proton dose.

3. Understand the use of an electron‐tracking Compton camera for imaging the prompt gamma generation by a proton beam.
MO‐D‐303A‐06: ImaSim, An Animated Tool for Teaching Imaging
Authors: Landry G , DeBlois F , Bazalova M , Verhaegen F
Published: April 2010

Purpose: To enhance the teaching and the self study of diagnostic and radiotherapy photon imaging by the creation of an interactive educational software package (SP) based on a simulation environment. Various imaging modalities found in a radiology or radiation oncology department are included in the SP, namely conventional kV planar imaging, MV portal imaging, CT imaging and cone beam CT imaging. Materials and Methods: The SP aims at faithfully reproducing the physics behind these modalities while keeping the operation simple and straightforward. Simulated geometries are split into three parts in a modular approach: (1) source geometry, (2) object geometry and (3) detector geometry. (1) kV simulations are based on a validated theoretical model while MV outputs are obtained from the literature. Photons simulated fall into the energy range encompassing radiology and radiation oncology (1 keV ‐ few MeV). (2) They are transported through user created virtual three‐dimensional objects of various materials. Photon attenuation is modeled, while scattering is ignored to reduce calculation times. (3) Virtual detectors, with various energy responses are used to collect photons. The user can interactively vary many parameters. Results: The SP enables a user to quickly demonstrate and study principles associated with the creation of a radiological image in a classroom or in a self‐learning setting. Simulations are managed via an aesthetically appealing and intuitive user interface that simplifies user control to facilitate the learning process. Many imaging phenomena can be studied with the aid of the SP, namely the heel effect, focal spot blurring, contrast vs. photon energy, CT and CBCT reconstruction, backprojection filtering, etc. The SP will be made available to the community by early 2010. Conclusion: This work, by rendering accurate image creation easily accessible, has the potential to enhance textbook based teaching and heighten student interest in medical photon imaging.
MO‐D‐304A‐01: Spatial and Fourier Analysis of Non‐Stationarity in 3D X‐Ray Computed Tomography
Authors: Pineda A , Tward D , Gonzalez A , Siewerdsen J
Published: April 2010

Purpose: To analyze the stationarity of 3D x‐ray cone‐beam computed tomography (CBCT) through spatial and frequency domain descriptions of noise. Such analysis of the stationarity assumption is an essential component of task‐based assessment of CBCT imaging performance. Method and Materials: Three objects (air, water cylinder + bowtie filter, and water cylinder only) were imaged using a CBCT benchtop and the Feldkamp algorithm for 3D filtered backprojection. Noise‐only 3D images were analyzed from the difference of two CBCT volumes under the three conditions. In the spatial domain, noise stationarity was analyzed in terms of variance maps, and in the frequency domain, in terms of the covariance matrix of the Fourier coefficients — of which the diagonal is the noise‐power spectrum (NPS). For a stationary random process, the Fourier covariance matrix (FCM) is diagonal and the same at every location in the image. Results: The three experimental conditions affected the degree of stationarity: air (highest stationarity), water+bowtie, water cylinder (least stationary). This rank order was consistent in terms of variance maps and the NPS. The off‐diagonal elements of the FCM were non‐negligible in comparison to the NPS and believed to have measurable effect on detectability. Conclusion: The degree of non‐stationarity in CBCT can be controlled experimentally and analyzed through both spatial and frequency domain techniques. From a practical standpoint of system design and evaluation, the findings suggest strategies for meaningful CBCT noise and NPS analysis. Model observer analysis should assess the validity of the stationarity assumption, recognizing its potential effect on task performance.