bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐A‐213A‐02: Quantitative PET/CT Imaging for Drug Discovery, Clinical Trials, and Individual Response to Therapy
Authors: Kinahan P
Published: April 2010

Recent publications have established quantitative measures of tracer uptake used in positron emission tomography (PET) imaging as a predictor of patient outcome including pathologic response, disease‐free survival and overall survival in single institution imaging and therapy trials. There is increasing interest in using PET as a biomarker to evaluate response to therapy and possibly as an endpoint for cancer therapeutic response in multi‐center trials. However, several sources of variance and inherent in quantifying PET tracer uptake should understood and determined in order to ascertain the significance of differences in serial measurements and aid estimation of expected variances during clinical trial design.

In this presentation we will review the major sources of bias and variability from the patient, imaging protocol, data processing, and image analysis. We will also briefly discuss artifacts from PET and PET/CT imaging.

The presentation will conclude with a review of efforts to address complexities that arise from combining quantitative PET/CT data from multiple patients at multiple sites. Research partially supported by NCI Contract 24XS036‐004 (RIDER).
TU‐B‐211A‐01: Treatment Planning of Complex Cases: Strategies and Tradeoffs
Authors: Nurushev T , Hunt M
Published: April 2010

The rapid increase in the complexity of treatment planning is a reflection of recent advances in the clinical technology. These include the use of multi‐modality and 4D imaging for planning, advanced treatment delivery and imaging capabilities available now on many linear accelerators. Intensity modulated radiotherapy (IMRT), already the most common form of treatment at some institutions, is increasingly being combined with other complex treatment capabilities such as respiratory monitoring or control, in‐room 2D or 3D imaging, or intra‐fractional patient motion monitoring.

Successful integration of any of these methods into the clinic relies on the increasing sophistication and ability of treatment planning staff to design and prepare not just the dose distribution but all data and images required for treatment. Although IMRT optimization and leaf sequencing algorithms are fairly mature, confidently identifying an “optimum” plan and appropriately evaluating the normal tissue and target trade‐offs can still be difficult and time consuming particularly for complex cases. Complex treatment procedures such as image‐guided treatment or respiratory monitoring can present a substantial challenge in terms of the effort required to manage, evaluate and appropriately use the many image sets acquired during planning and treatment. Dose escalation protocols and stereotactic body radiosurgery programs are being initiated at more institutions. Each of these demands a careful evaluation of initial and daily patient preparation and setup and a thorough understanding of the uncertainties associated with planning and treatment.

This course will focus on strategies and techniques for coping with some of the more complex planning issues that arise in today's technology‐intensive department on all stages, from planning image acquisition to dose delivery.

Learning Objectives:

1. Understand the trade‐offs in IMRT planning and the role of target/normal tissue geometry and beam geometry in creating IMRT plans

2. Understand the increasing role of treatment planning staff in the analysis, use and preparation of images for planning and treatment

3. Identify sources of inter‐ and intra‐fractional uncertainty and their impact on dose escalation and stereotactic body radiosurgery programs
TU‐B‐303A‐01: Digital Mammography: A Radiologist's Perspective
Authors: Gutierrez R
Published: April 2010

Full Field Digital Mammography (FFDM) systems are rapidly gaining in popularity and are replacing conventional film‐screen mammography (FSM) systems in breast centers throughout the country. Radiolgists are faced with unique challenges brought about by this transition of technology.

In this lecture, the utility of full field digital mammography in clinical practice will be presented. Some of the challenges faced by radiologists who have transitioned from film screen mammography to digital mammography will also be discussed, and case examples illustrating the utility of FFDM will be presented. The clinical utility of computer‐aided detection (CAD) software packages will also be addressed.

Learning objectives:

1. Understand the clinical impact that full‐field digital mammography has had on the daily practice of breast imaging.

2. Recognize the advantages and disadvantages of FFDM systems.

3. Understand some of the challenges that breast imagers face when transitioning from FSM to FFDM systems.

4. Understand how computer‐aided detection (CAD) systems are used in clinical practice.
TU‐C‐211A‐01: Becoming a Better Teacher
Authors: Hendee W , Giger M , Starkschall G , Molloy J , Peroni C , Seibert J , Dobbins J , Smilowitz J , Hogstrom K , Montemayor V , Jackson E
Published: April 2010

Every medical physicist is a teacher, either formally in the classroom or informally in the clinic. Some physicists skillfully fulfill their educational obligations, while others struggle with their teaching responsibilities. However, everyone can be a good teacher — what are required are determination, dedication and diligence. This objective was the focus of a 3‐day AAPM Educational Summit held immediately after the 2008 AAPM annual meeting in Houston. It will also be the goal of a second Educational Summit scheduled to follow the 2010 annual meeting in Philadelphia. Discussion of the outcomes of the 2008 Educational Summit, and plans for the 2010 Summit, are the topics of this educational session scheduled for the 2009 annual meeting. This session will include solicitation of suggestions from the audience for the 2010 Educational Summit.
TU‐C‐BRD‐03: An Integrated Robotic‐Based Irradiation System for Small Animal Research
Authors: Moros E , Sharma S , Corry P , Chao M , Griffin R , Mihaylov I , Penagaricano J
Published: April 2010

An integrated, image‐guided irradiation system for small animal research has been developed. The system is capable of precise, accurate, reproducible and quantifiable 3D conformal delivery of radiation dose distributions to organs/tumors. The main hardware components are: (1) A Seifert Isovolt Titan 225 kV X‐ray tube with beam collimation provided by a custom‐made variable diameter “cone” or a set of motor‐driven symmetric “jaws”, thereby allowing field sizes from 0.5 mm in diameter to 7 cm square field at ∼33.5 cm SSD. (2) A six‐degrees‐of‐freedom (6DOF) robotic arm (Adept Viper s650) was integrated for precise animal positioning/motion (repeatability of ±0.020 mm in XYZ direction and angular precision of ±0.2°). The system is housed in a custom 6 × 6 × 6 ft3 shielded enclosure inside a laboratory. When the beam is aimed horizontally to (3) a flat panel amorphous silicon detector (XRD 0820 CN3, Perkin Elmer, Fremont, CA) a series of 2D‐radiographs can be recorded while the robot rotates the animal. Each image is composed of 1024 by 1024 pixels with a 200 μm pixel size at a frame rate of 7.5 Hz. An open source cone beam computed tomography (CBCT) reconstruction tool (OSCAR‐2, University of Toronto) using the Feldkamp‐Davis‐Kress (FDK) filtered back projection algorithm was implemented for CBCT image reconstruction. Thus, targeting can be accomplished by the use of orthogonal radiographs and/or CBCT. A dose engine and CBCT‐based treatment planning are ongoing projects.

Dosimetric measurements and preliminary animal experiments have demonstrated the basic capabilities of the system in terms of radiation dose, dose rate and precision targeting. The system has also been used successfully in experiments to detect the molecular signaling occurring after spatially fractionated radiation therapy (GRID) in vivo.

A description of the system and a summary of experiments performed to date will be presented.

Learning Objectives:

1. Appreciate the challenges of developing a high precision 3D conformal irradiator for small animals.

2. Learn about the main hardware components of the system and their integration.

3. Understand the advantages of using a 6DOF robot for imaging (motion) and beam delivery (positioning).

4. Learn about some of the potential research projects that such a system can make possible.

This research was sponsored by the Arkansas Biosciences Institute and the Central Arkansas Radiation Therapy Institute.
TU‐C‐BRB‐03: Radiation Dose Response of Plasma Cell Neoplasms
Authors: Garcia L , Nyiri B , Wilkins D , Gerig L , Atkins H , Samant R , Raaphorst G
Published: April 2010

Purpose: To review the available clinical dose response data for extramedullary plasmacytomas (EMP) and solitary plasmacytomas of the bones (SPB), including standard 12 Gy TBI treatments for multiple myeloma (MM), to compute the expected dose response for plasma cell neoplasms and evaluate differences between EMP and SPB dose response. Method and Materials: Articles from 27 published studies on plasmacytomas were analyzed. Local control (LC) was used as the end point. Clinical data are often reported as LC for the median of a dose range — only data from ranges of width ⩽10 Gy were used. The maximum likelihood method (ML) was used to estimate the parameters of a tumour control probability (TCP) model based on Poisson statistics, and approximate likelihood confidence regions (CR) were determined. A Monte Carlo experiment (MC) assessed the parameters' uncertainty due to the 10 Gy dose interval. A statistical test based on the ability of the MC distributions of the parameters to discriminate between different kinds of tumors was performed. Results: Radiation therapy was used as the sole treatment in more than 70% of the patients and in 8 of the 12 studies selected. Parameters characterizing TCP and 95% confidence intervals from MC are reported, along with graphical representations of the dose response, and 2D MC histograms and the CRs on the parameter space. Conclusion: An extensive review of plasmacytoma clinical data was performed. Although the data suffer from a lack of low dose data and are mostly reported within a dose range, this approach is a preliminary assessment of dose response relationship for plasma cell neoplasms. The parameters of the TCP model were determined. Significant difference was seen between EMP and SPB dose response. The models could be used to interpolate clinical data and estimate TCP when assessing new therapies and comparing different treatment planning approaches.
TU‐C‐BRB‐04: Enhanced Modeling of Radiation Therapy for Head and Neck Cancers with Probabilistic Outcomes Using Mixed Predictors
Authors: Smith WP , Parvathaneni U , Liao J , Phillips M
Published: April 2010

Purpose: To develop a probabilistic model of outcomes of radiation therapy which includes both dosimetric and non‐dosimetric predictors, and includes a decision‐making component to quantify the balance between disease cure and radiation‐induced side‐effects. This model was implemented to assess IMRT treatment plans for individual patients for head and neck cancer. Materials and Methods: Physicians have available many resources that may not be easily reconcilable to predict patient outcomes. Dosimetric indicators, such as the EUD and NTCP are probabilistic in nature, without explicit representation of the underlying biology. Clinical trials focus on patient and disease characteristics, such as disease location, T‐stage, nodal involvement, Karnofsky performance status, and often include one treatment variable, such as DVH‐cutpoints or chemotherapy regimes. Newly recognized factors, such as HPV positivity, may affect outcome, however, without definitive clinical data, integrating such factors into clinical decision‐making is not straightforward. Finally, experience‐driven beliefs affect treatment choices and may vary between physicians. We combine all of the aforementioned resources using a Bayesian network in order to make an outcome prediction for each IMRT plan. Outcome predictions highlight the stark trade‐off between preventing recurrent disease that generally has a fatal prognosis and preventing radiation‐induced side effects that range from xerostemia to blindness to paralysis. We use a Markov Model to compute a quality‐adjusted life expectancy using patient preferences for health states. Results: Probabilities of local and distant control matched published values well, as did life expectancies. The trade‐offs between quality of life and quantity of life are explored. Sensitivity analysis highlighted physician beliefs that affected treatment choices. Conclusions: Modeling of radiation therapy has grown progressively more sophisticated. We present a method by which probabilities and expected values of clinically relevant outcomes, based on a range of variables, are calculated.
TU‐C‐BRB‐07: Incorporation of Angiogenesis Into a Stochastic Imaging‐Based Tumor Vasculature Model
Authors: Adhikarla V , Titz B , Kozak K , Jeraj R
Published: April 2010

Aim Controlling interaction between tumor growth and vasculature development are the basis of anti‐angiogenic therapies. A model simulating tumor growth and angiogenesis was developed and the tumor oxygenation status was evaluated with respect to two parameters: tumor proliferation rate (TPR) and endothelial cell proliferation rate (EPR). Methods and Materials Our previous image‐based model of vasculature was expanded by incorporating angiogenic development. The tissue volume encapsulating the tumor and vasculature was simulated as a MATLAB matrix. Vessels were simulated to sprout from the existing vasculature towards the tumor driven by hypoxia‐induced growth factors. The relative magnitude of TPR and EPR determined the simulation time steps. Xenografted and spontaneous tumors were simulated and the tumor oxygenation status was evaluated with respect to TPR & EPR. The model was verified against the experimental data obtained from CE‐CT and Cu‐ATSM PET imaging. Results The time‐dependant growth of vessels towards hypoxic regions in the tumor was demonstrated. TPR was found to have the most profound impact on development of hypoxia and heterogeneity of the oxygen concentration inside the tumor. Higher TPR led to faster development of hypoxia. Due to the limited vasculature available, xenografted tumors become hypoxic faster than spontaneous tumors for similar TPRs. When comparing simulations to the experiments, the overall development of vasculature and consequent hypoxia matched well with the imaging data. Conclusions A model capable of simulating temporal development of tumor and vasculature has been developed and tested on the imaging‐derived experimental data. The presented model has a potential to study the response of tumor and the vasculature to therapy, which can be a valuable input for optimizing anti‐angiogenic therapies.
TU‐C‐BRC‐01: Imaging as a Biomarker
Authors: Mankoff DA
Published: April 2010

There is an increasing trend towards more individualized, targeted cancer therapy. This places new demands for tools to help guide treatment selection and evaluate early response to the selected therapy. While cancer treatment selection has traditionally depended on tissue‐based biomarkers, functional and molecular imaging can play an important and complementary role in directing targeted cancer therapy and monitoring early response. Imaging has several capabilities distinct from tissue sampling and assay, including the ability to measure the heterogeneity of target expression and to characterize in vivo pharmacodynamics. The use of molecular imaging to direct cancer therapy departs from the traditional role of cancer imaging to detect and localize cancer sites. This implies an expansion of the scope of cancer imaging from detection methods that rely on features such as aberrant glycolysis that are present in tumors but not in normal tissues, to a broader approach using imaging to quantify in vivo phenotype. In the latter case, the absence of a particular tumor feature, such as a target receptor, may be as important as its presence. The need to simultaneously localize and characterize tumor sites places an emphasis on multi‐modality imaging such as PET/CT or multiple PET images using combinations of different imaging probes. This talk will review applications of molecular imaging to targeted cancer therapy for clinical trials and clinical practice, focusing mostly on PET. Examples using molecular imaging to (1) predict tumor clinical behavior, (2) identify therapeutic targets, (3) predict therapeutic resistance, and (4) evaluate early response to therapy will be shown. The theme of the presentation will be that quantitative in vivo measures of tumor phenotype using imaging are complementary to in vitro assay in directing targeted, individualized cancer therapy.

Learning Objectives:

1. Describe ways in which molecular imaging can help direct cancer therapy.

2. Discuss the complementary role of in vitro assay and in vivo imaging in measuring cancer phenotype.

3. List examples of how imaging can be used to help direct cancer therapy.
TU‐C‐303A‐03: Real‐Time Profiling of Respiratory Motion and Its Application to Continuous Horizon Prediction
Authors: Ruan D , Fessler J , Balter J , Keall P
Published: April 2010

Purpose: Respiration‐induced tumor motions are semi‐periodic and exhibit different variations that have distinct clinical implications. We develop and investigate a system that is capable of estimating baseline drift, frequency variation and fundamental change (oscillatory amplitude and shape) in real time and utilize such information to predict abdominal or thoracic tumor positions. Method and Materials: The observation is modeled as a periodic fundamental pattern modulated in both frequency and baseline, which is subsequently corrupted by independent additive noise. To jointly estimate these coupled components online, we utilize three key techniques : (1) augment state to capture system dynamics and hysteresis; (2) create a low order elliptical shape model to characterize semi‐periodicity; (3) perform Poincare sectioning to automatically identify iso‐phase instances. Linear interpolation/extrapolation from iso‐phase points provides a continuous phase warping function. The baseline drift is obtained by projecting the elliptical center onto the original time‐displacement axis. A least squared error (LSE) estimate for the fundamental pattern is obtained by inversely phase‐ warping the observed trajectory and compensating for the mean drift. The proposed method is applied to simulated data with known “ground‐truth”. In a preliminary prediction test with RPM data, each component (baseline, phase and fundamental pattern) is extrapolated respectively, and then reassembled to provide a “predicted trajectory”. Results: The proposed method provides the first unsupervised system that achieves robust real‐time estimation of mean displacement, phase and fundamental pattern. Application of the online profiling system to prediction yields continuous horizon prediction of 3∼5 seconds, with similar behavior to what is expected from human observers.

Conclusion: We have proposed an online profiling paradigm for describing and characterizing respiratory motions. Tests on simulation data and RPM signals have demonstrated the efficacy of the proposed method.

This work was partially sponsored by NIH P01‐CA59827.
TU‐C‐303A‐04: Slow Gantry Rotation Acquisition Protocol for Four‐Dimensional Digital Tomosynthesis
Authors: Maurer J , Pan T , Yin F
Published: April 2010

Purpose: Four‐dimensional digital tomosynthesis (4D‐DTS) was recently introduced as a novel on‐board 4D imaging technique. The purpose of this study is to develop and implement a slow gantry rotation acquisition protocol for 4D‐DTS. A formalism for determining appropriate acquisition parameters based on patients' respiratory characteristics was derived and tested. Methods & Materials: Equations were derived to explain the relationships between slow gantry acquisition parameters (scan speed, frame rate and scan angle) and respiratory characteristics (average period and regularity). Additional equations relate acquisition parameters with resultant scan times, projection numbers and the distribution of projections within phase bins once sorting and binning are complete. Phantom studies were conducted to test the new protocol. A body phantom was mounted on a moving platform to simulate short and long respiratory cycles (3 and 6‐s) and scanned using the slow gantry protocol with a 1.1‐deg/sec scan speed and a 7.8‐fps frame rate. Projections were binned and sorted into 10 phases with 10% phase windows. Resultant distributions of projections within phase bins were compared with expected distributions based on the derived formalism. Reconstructions were completed to investigate dependence on respiratory period. Results: The maximum angular intervals between projections within phase bins were estimated by the formalism to be 3.5 and 6.8° for the 3 and 6‐s profiles, respectively. Actual values ranged 3.4 to 3.6° for the 3‐s profile and from 6.8 to 7.16° for the 6‐s profile. Reconstructions demonstrated the importance of adjusting scan speed according to respiratory cycle length. Conclusion: A 4D‐DTS slow gantry rotation acquisition protocol was developed, implemented, and tested. The derived formalism has proven useful for determining appropriate acquisition parameters based on respiratory characteristics and will be used as a framework for further optimization and testing of the protocol.

Conflict of Interest: Partially supported by a Varian research grant.
TU‐C‐303A‐07: Pediatric Organ Motion Evaluated by Respiratory‐Correlated CT with a Pressure‐Sensitive Abdominal Belt
Authors: Hua C , Panandiker A Pai , Sharma S , Hoth K , Naik M , Krasin M
Published: April 2010

Purpose: We present the first report of pediatric thoracic and abdominal organ motion extent measured using respiratory‐correlated CT with an abdominal sensor belt. The knowledge is essential for defining internal target volumes and planning organ at risk volumes. It is also critical for safe employment of treatment techniques producing high dose gradient such as IMRT and intensity‐modulated proton therapy. Methods and Materials: Seventeen pediatric patients have undergone radiotherapy simulation including a respiratory‐correlated 4D CT scan in supine position for evaluation of target and internal organ motion. A pressure‐sensitive belt was wrapped around the abdomen just below the diaphragm. The pressure change was used as a respiratory surrogate. Each respiration cycle was divided into eight phases. Liver, left and right kidneys, and the representative 3rd, 7th, and 11th rib pairs were contoured on each of the eight CT datasets. Results: The center‐of‐mass displacements of kidneys in the lateral and anterior/posterior directions due to respiration were small (0–2mm). The superior/inferior displacement was larger (0.6–4.6mm). Younger pediatric patients tend to have smaller kidney motion than their older counterparts. Diaphragm motion (4–10mm) was larger than kidney motion. The magnitude of diaphragm motion did not predict the magnitude of kidney motion. The rib motion ranged from 0.5 to 2mm maximum displacement in the lateral direction and 2 to 4mm in the anterior/posterior and superior/inferior directions. The 11th pair of ribs had smaller respiratory motion than the 3rd and the 7th pair. Conclusion: Pediatric internal organ motion was smaller compared to adult data reported in the literature. Conventional large planning margin of 5–10mm may be reduced for tumors neighboring these organs such as neuroblastoma or chest wall sarcoma if treated with 3D conformal technique and verified with on‐treatment imaging. Whether motion management is required for proton beam scanning in children needs further investigation.
TU‐C‐303A‐08: A Hybrid Strategy Using Discriminant Analysis for Prostate Intrafraction Motion Management
Authors: Adamson J , Wu Q , Yan D
Published: April 2010

Purpose: Prostate intrafraction motion has been shown to be patient specific; however most current compensation strategies are population wide. We evaluate the feasibility of applying margins based on a subpopulation of patients with similar intrafraction motion characteristics and of predicting group membership within the initial treatment fractions. Method and Materials: 22 prostate patients from a hypofractionated radiotherapy protocol with online CBCT image guidance and kV fluoroscopy measurements of intrafraction motion were divided into small and large motion groups using k‐means clustering of the 90th percentile of vector displacement during treatment delivery. Group margins were computed containing 90% of measured prostate displacements at treatment delivery. Descriptive statistics from the intrafraction motion in the AP and SI‐axes and rectal filling status were used to predict group membership after 2–10 fractions using a perceptron linear discriminant function. Results: ∼75% of patients (17/22) were categorized as having relatively small intrafraction motion, with ∼25% (5/22) having large motion. Population margins were 1.7, 4.0, and 3.9 mm in the RL, AP, and SI axis. When classified into groups, margins for the small motion group reduced to 1.6, 2.9, and 3.0 mm and for the large motion group increased to 2.0, 6.4, and 6.0 mm in the RL, AP, and SI‐axes respectively. The percentage of patients correctly classified after 2, 3, 4, 5, 6, and 10 fractions was 65%, 85%, 90%, 90%, 95%, and 95% when both motion characteristics and rectal filling status were used. Omitting rectal filling status decreased the ability to correctly classify patients with large motion. Conclusion: Discriminant analysis may be used to incorporate intrafraction motion measurements from initial fractions into prostate margin calculation with reasonable accuracy, leading to margin reductions in the AP and SI‐axes for ∼75% of patients and increased coverage for ∼25%.

Conflict of Interest: Partially supported by NIH Grant CA118037.
TU‐C‐304A‐04: Monte Carlo Based Multidetector CT Modeling and Dose Calculations for Pregnant Patients
Authors: Gu J , Caracappa P , Xu X
Published: April 2010

Purpose: To model and validate the multidector CT (MDCT) scanner and to assess radiation dose to the fetus and pregnant patient in three different gestational periods. Method and Materials: Monte Carlo code, MCNPX, was used to simulate the x‐ray source including the energy spectrum, filter, and scan trajectory. Detailed CT scanner components were specified using an iterative trial‐and‐error procedure for a GE LightSpeed CT scanner. The scanner model was validated by comparing simulated results against measured CTDI values and dose profiles reported in the literature. The source movement along the helical trajectory was simulated using the pitch of 0.9375 and 1.375, respectively. The validated scanner model was then integrated with phantoms of a pregnant patient in three different gestational periods to calculate organ doses and fetal doses. Results: Comparison between simulated results and reported results in literature shows good agreement in terms of CTDI values as well as dose profiles. It was found that the dose to the fetus of the 3‐month pregnant patient phantom was 0.13 mGy/100mAs and 0.57 mGy/100mAs from the chest and kidney scan, respectively. For the chest scan of the 6‐month patient phantom and the 9‐month patient phantom, the fetal doses were 0.21 mGy/100mAs and 0.26 mGy/100mAs, respectively. All these scans were performed with protocols that did not contain the fetus directly in the x‐ray beam. The paper also discusses how these fetal dose values can be used to evaluate imaging procedures and to assess risk using recommendations of the report from AAPM Task Group 36. Conclusion: This work demonstrates the ability of modeling and validating MDCT scanner by Monte Carlo method, as well as rapidly and accurately assessing fetal dose and organ doses by combining the MDCT scanner model and pregnant patient phantom.
TU‐C‐304A‐08: A Method to Adjust CTDI to Better Represent the Dose for Pediatric Patients
Authors: Toth T , Strauss K , Boedeker K , Leidecker C , Morton T
Published: April 2010

Purpose: CT manufacturers are required to report dose using standardized CTDI phantoms. However, CTDI can be confusing when applied to pediatric patients due to variations in patient size. We propose a simple method to scale standard CTDI to better represent a pediatric patient's dose by providing universal conversion tables that are indexed by patient size ranges. Method and Materials: The Medical Imaging and Technology Alliance (MITA) and Image Gently Pediatric CT Physics Work Group have obtained CTDI ratios between the 32 cm, 16 cm and 10 cm phantoms for current 16 and 64 slice scanners. X‐ray attenuation was measured for the CTDI phantoms and retrospectively determined from pediatric and adult pre‐scan projection images. Regression relationships between patient dimensions, attenuation and dose ratios were used to create tables of CTDI scale factors as a function of patient dimensions. Results: The range of attenuation ratios of the 2nd and 3rd quartiles for pediatric heads compared to the standard CTDI phantoms was 0.85 to 0.95 (16 cm) and 0.46 to 0.51 (32 cm). The range for pediatric bodies was 1.03 to 1.35 (16 cm) and 0.85 to 0.95 (32 cm). Individual measurement errors relative to the mean CTDI ratio due to manufacturer, scanner generation and kVp or bowtie filter selections were minimal. Preliminary results show errors increased from 0 % to 14 % with increasing difference between the attenuation of the pediatric patient and CTDI phantom. Conclusion: Universal dose conversion tables can be provided based on dimensions or can be automatically calculated from a patient's attenuation determined from a pre‐scan projection image with reasonable accuracy to scale CTDI or its future replacement to better represent dose for pediatric patients.
TU‐E‐304A‐06: A 3D Solution for Advanced Photon Arc Therapy Quality Assurance
Authors: Thomas A , Clift C , O'Daniel J , McMahon R , Sakhalkar H , Brown W , Adamovics J , Washington A , Oldham M
Published: April 2010

Purpose: Recently, radiation treatment technology has out‐paced the advances in QA technology, and a critical gap has been created within the arc motion delivery systems such as Rapid Arc®, High Art®, and VMAT®. Gantry position, speed and MU rate create extra degrees of complexity unaccounted for by several traditional 2D QA verifications due to directional dependence and/or inadequate spatial resolution. We present the 1st 3D dosimetry verification of a Rapid Arc treatment and general dosimetry technique based on a radio‐chromic plastic (PRESAGE™)/optical‐CT (OCTOPUS™) combination suitable for today's complex treatment technology. Method and Materials: A radio‐chromic plastic cylinder 17cm diameter × 11cm height was used to verify a simplistic Rapid Arc 6MV prostate plan. The radiation induced OD change (proportional to dose delivered) was acquired by an optical‐CT scanner with a voxel size of 1×1×2.5mm3. The measured distribution was then compared with the corresponding dose distribution calculated by the treatment planning system (Eclipse® AAA, voxel size 2.5×2.5×2.5mm3). Comparisons between the two dose distributions were made using dose profiles and stacked 2D gamma maps (with criteria 3% dose difference and 3mm distance to agreement) for a quasi 3D gamma volume. Results: The 3D dose distribution measured profiles in the dosimeter showed agreement amongst the calculated treatment plan down to lower dose regions (down to ∼35%). Gamma map comparisons show the dosimeter measurements generally agree with the calculated treatment plan with a few low dose bath problem areas superior and inferior. More traditional QA techniques showed the same discrepancy areas of the plan. This aided in the verification of the system commissioning process. Conclusion: Radio‐chromic plastic/optical‐CT dosimetry techniques are capable of providing 3D, high spatial resolution verification for patient QA with advanced treatment techniques or commissioning, and the potential for its use at other treatment sites where the fluence is more complex.
WE‐SAM‐304A‐02: SPECT/CT: Technology Updates, Quality Assurance and Applications
Authors: Kappadath SC
Published: April 2010

Hybrid SPECT/CT is rapidly becoming a mainstream imaging modality and creating a new paradigm for SPECT imaging. The ability to contemporaneously acquire electromechanically registered dual‐modality SPECT and CT scans improves the SPECT image quality due to CT‐based attenuation correction, and enhances the diagnostic confidence of SPECT by providing an anatomical overlay. The first generation SPECT/CT systems used single‐slice CT scanners and produced CT images of limited quality for anatomical overlay. The CT systems integrated into the latest generation of SPECT/CT systems are fully‐functional diagnostic scanner (scan parameters includes tube current, tube voltage, rotation speed, collimation, pitch, slice thickness, FOV, etc.). In addition to generating high‐quality attenuation maps these CT systems can produce CT scans with diagnostic image quality, capable of greatly improving both the localization and specificity of abnormalities detected on the corresponding SPECT scan. In some cases, these systems are also capable of performing diagnostic CT scans with contrast enhancement. The widest use of SPECT/CT is currently in oncology, with applications including: tumor localization, staging and response to treatment; pre‐surgical mapping (e.g., parathyroid adenomas, sentinel lymph nodes); differentiation of skeletal metastases from other disease processes; functional image‐based radiation therapy treatment planning (e.g., lung perfusion); and quantitative SPECT/CT‐based internal radionuclide therapy dosimetry/treatment planning. Cardiac SPECT/CT is currently focused primarily on improved attenuation correction of SPECT myocardial perfusion images. SPECT/CT is also being utilized for imaging bone and other non‐malignant diseases.

This lecture will review the physics principles underlying SPECT/CT imaging, present several examples of the clinical application of SPECT/CT, and provide an overview of the currently available SPECT/CT scanner types and models.

Learning Objectives:

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

2. To understand current and future clinical applications of SPECT/CT imaging.

3. To become familiar with the various commercially‐available SPECT/CT product offerings.
WE‐A‐211A‐01: New Dosimetry Measurements — New Developments
Authors: Seuntjens J , Gibbons J , Das I
Published: April 2010

Image‐guided intensity modulated radiation therapy deliveries are becoming increasingly complex and their verification involves dosimetry measurements in situations that are no longer covered by reference dosimetry protocols or relative dosimetry procedures with simple corrections. These beams are generated as part of intensity modulation (IMRT), stereotactic radiosurgery (SRS), cyber‐knife and gamma‐knife deliveries and involve the use of extremely small fields in order of few millimeters. In this era of joint imaging‐therapy developments, accurate dosimetry techniques are sometimes trivialized and important effects not understood or ignored.

This presentation consists of three parts: the first part revisits the guiding principles of measurement dosimetry in standard and nonstandard conditions, definitions of detectors and phantoms, reference dosimetry of conventional beams and also discusses the new developments in reference dosimetry of nonstandard beams. The second part of the presentation concentrates on practical aspects of relative dose measurements with the goal to generate 3D distributions as well as integrated measurements and derived quantities. The third part concentrates on a discussion of relative dosimetry in narrow fields and deals with the choices of possible radiation detectors, the difficulties and possible solutions to measurements in disequilibrium situations created by this era's narrow photon fields.

Learning Objectives

1. To understand the principles of clinical measurement dosimetry and applicability to standard and nonstandard beams;

2. To understand standard clinical reference dosimetry techniques and be exposed to some of the new developments in reference dosimetry in nonstandard beam configurations;

3. To get an overview of practical aspects of relative dosimetry techniques for the purpose of 3D dose distributions in standard fields, small photon fields and buil‐up regions;

4. To be aware of the complications of measurements and detector choices in electronic disequilibrium situations created by small photon fields.
WE‐A‐BRD‐02: 4D Treatment Planning: Rationale, Methods and Significance
Authors: Rosu M
Published: April 2010

The breathing‐induced motion adversely affects the radiotherapy process for pulmonary tumors at all stages. During the conventional 3D imaging, motion causes artifacts that lead to erroneous anatomical information that propagates as a systematic error during planning and delivery. For planning, the standard approach to insure tumor coverage in the presence of geometrical uncertainties is to surround the target with a safety region. The pitfall of the margin expansion approach is that additional high doses are delivered to the normal tissue adjacent to the target, thus increasing the chances of radiation‐induced disease, while also limiting tumor dose escalation and, subsequently, the potential for better tumor control. The advent of 4D computed tomography (4D CT) represented a significant step forward toward improved imaging accuracy for regions affected by the respiratory motion due to the ability of reconstructing multiple image sets corresponding to various points during the breathing cycle. The information from the 4D CT is first used to better identify the target region at various stages over the breathing cycle and the extent of motion. Next, the more complete imaging data has to be factored into the planning process. To this end, depending on the treatment delivery strategy, one or more treatment plans are designed for each breathing instance for which data is available. Dose computations are performed on multiple datasets (usually termed as 4D dose calculations), and the cumulative dose is then used to assess the plan quality similar to the conventional 3D planning. The accumulation of doses on a reference image dataset is accomplished by using deformable image registration, which maps corresponding image voxels from one dataset to the reference dataset. To date, several approaches have been developed to fulfill this task. The amount of data available from 4D scans increases significantly the amount of time and effort needed for treatment planning. However, studies have suggested that the dose accumulation process could be reduced to planning on certain datasets only, while preserving at an acceptable level the accuracy that would otherwise be achieved through a full 4D dose computation. Multiple centers have employed the 4D planning approach to study the changes in doses as a result of 4D treatment planning and addressed the clinical significance of the changes observed.

In this presentation, we will discuss the rationale for 4D treatment planning, review the methods available for cumulative dose computation, identify potential sources of error specific to the 4D planning approach, and discuss the clinical importance of the dosimetric changes resulting from 4D‐based treatment planning.

Learning Objectives:

1. Understand the rationale for accounting for respiratory motion during treatment planning.

2. Understand the principles of cumulative dose computation.

3. Learn about the clinical importance of the changes induced by the respiratory motion.
WE‐A‐BRC‐01: IMRT in Gynecological Malignancies
Authors: Aydogan B
Published: April 2010

Intensity modulated radiation therapy (IMRT) is increasingly used for the treatment of gynecological tumors. Successful implementation requires careful attention to every detail from patient selection to simulation, to planning, to setup, to localization, and to delivery. At the University of Chicago, all patients are simulated and treated in supine position using customized alpha cradles indexed to the treatment table. Oral, IV and rectal contrast are used to help in the delineation of the CTV and surrounding normal tissues. The CTV consists of the upper half of the vagina, uterus (if present), parametrial tissues, parasacral region, and the contrast enhanced vessels plus a 2cm margin to identify the common, external and internal nodal regions. PTV is constructed by adding a margin based on the setup uncertainty and organ motion data. Normal tissues contoured include bladder, rectum, small bowel and pelvic bone marrow. For treatment planning, 9 equally spaced co‐planar beams are used. Input parameters derived for the PTV and surrounding normal tissues were developed over the time, and their evolution will be discussed. Treatment plans are evaluated primarily based on the PTV coverage and normal tissue DVHs. 3‐D dose distribution plays an important role in the IMRT delivery and is rigorously evaluated by both physicists and physicians at our institutions. Acceptable plans are the ones that have a minimum coverage of 98% of the PTV volume with the prescription dose while no more than 2% of the PTV receives more than 110% of the prescription dose. Evaluation of small bowel dose is based on a NTCP analysis for the incidence of acute gastrointestinal toxicity of IMRT patients treated in our center. From this analysis, small bowel volume receiving prescription dose (45Gy) should be less than 200cc. Plan acceptance criteria for rectum and bladder will also be discussed during this course. Recent studies conducted in our center studies have associated the volume of pelvic and lumbosacral bone marrow (PBM and LSBM) receiving 10 and 20 Gy with acute hematologic toxicity (AHT) in patients receiving concurrent chemotherapy and IMRT. We will discuss and present plan consideration for bone marrow sparing IMRT to reduce AHT in these patients. QA is one of the most important and integral part of any radiation therapy procedure. IMRT QA, in our institution, is performed using independent monitor unit verification (MUV) and patient specific measurements and will be discussed in details. In addition, recent studies reporting adaptive treatment and image guided approaches in the treatment of gynecological tumors will be briefly reviewed.

Learning Objectives:

1. To understand the practical and fundamental aspects of IMRT planning for gynecological malignancies

2. To discuss the GYN‐IMRT plan evaluation and acceptance criteria

3. To review and discuss the IMRT quality assurance issues for this disease site.

4. To briefly review and critique adaptive and image guided GYN‐IMRT approaches.
WE‐A‐213A‐01: Ultrasound Beamformation and Image Reconstruction
Authors: Moore W
Published: April 2010

Modern technologically intensive diagnostic ultrasound systems are utilizing numerous new and powerful beamformation and image construction processes integrated into the design of the transmit, receive and processing chain of the system. These new processes, how the imaging and Doppler data is captured, processed and displayed need to be well understood by both medical physicists and clinicians to ensure proper testing and performance evaluation of the ultrasound device, as well as their attendant transducers (probes), and to ensure the safety and clinical efficacy of the ultrasound study. This presentation will focus on these new processes and advanced imaging technologies, how they can be tested and evaluated for effectiveness and what new imaging and display formats we will likely see in the next 2 to 3 years.

Learning Objectives:

1. Understand modern beamforming techniques

2. Understand ultrasound image processing

3. Understand modern image reconstruction techniques
WE‐B‐211A‐01: Strengths and Limitations of Anatomical and Spectroscopic MRI in Radiation Oncology Treatment Planning
Authors: Bayouth J
Published: April 2010

Magnetic resonance imaging (MRI) is playing an increasingly important role in radiation oncology treatment planning. As compared to computed tomography (CT), MRI provides excellent soft tissue contrast making it ideal for imaging brain tumors. Other anatomical sites (e.g., prostate, pelvis, head and neck, extremities, abdomen, etc.) also benefit from the soft tissue contrast provided by MRI, but are limited by difficulties in reproducing CT patient positioning in the MRI as well as geometric distortions introduced within the MRI datasets. These issues will be described, along with techniques for their minimization and quantification. MRI is also a powerful and non‐invasive imaging modality to assess tissue motion, caused by a host of physiological processes (respiration, peristalsis, bladder and/or rectal filling, etc.). Clinical approaches to using MRI for motion management will be described.

In addition to morphological imaging, magnetic resonance spectroscopic imaging (MRSI) provides a non‐invasive spatial mapping of abnormal tumor metabolism. This information may provide critically relevant assessment of the presence and extent of tumor activity, which may be substantially different from those considered to contain tumor based on T1 and T2 imaging. Many uncertainties remain: geometric and quantification accuracy of the acquired MRSI data due to magnetic field imperfections, lack of adequate anatomical details with MRSI images for registration with planning CT, and lacking essential DICOM objects hamper the incorporation of MRSI information into the treatment planning process. Clinical approaches to using MRSI for tumor target delineation will also be described.

This lecture will outline the indications for MRI in radiation oncology treatment planning for both external beam and brachytherapy. Examples are provided for many anatomical sites, along registration of MRI datasets with PET/CT. Approaches that can be used to validate MRI applications will be provided, along with a description of the current limitations.

Learning Objectives:

1. Widespread applications of MRI in radiation oncology treatment planning

2. Assessment of geometric distortion when MRI is utilized as one of several imaging modalities: reproducibility of patient setup and image distortion

3. Application of MRI to quantify and validate motion management models

4. Review obstacles to clinical utilization of magnetic resonance spectroscopic imaging (MRSI)

Research sponsored by Siemens Medical Solutions
WE‐C‐211A‐01: Requirements and Opportunities for Maintenance of Certification
Authors: Ibbott G , Frey G , Morin R , Thomas S
Published: April 2010

The ABR began issuing time‐limited certificates for physicists in 2002. As a result, many physicists are two‐thirds the way through their MOC cycles, and should have reached several milestones by now. This course will discuss the origins of the MOC program, the requirements for physicists, and some of the opportunities available for meeting the requirements. Specific information will be provided to help physicists understand how they can satisfy the requirements for professional standing, through licensure or attestation; life‐long learning and self assessment, through the accumulation of continuing education credits, self‐assessment modules (SAMs) and self‐directed educational projects (SDEPs); cognitive expertise, through participation in a cognitive exam; and assessment of performance in practice, through the conduct of a practice quality improvement (PQI) program. Examples of each aspect will be given. Use of the personal database (PDB) provided by the ABR for each diplomate to facilitate the MOC process will be described, and the opportunities for guidance in accomplishing SDEPs and PQI projects will be presented.

Learning Objectives:

1. Understand the maintenance of certification program, its history and requirements.

2. Learn about opportunities for satisfying the MOC requirements.

3. Become familiar with sources of assistance from the ABR, including the personal database.

4. Identify opportunities for guidance from sources such as the AAPM.