bluuebunny/crossref_metadata_2025 huggingface dataset:
MO‐D‐BRD‐01: Memorial to Bengt Bjarngard – Memorial Lecture
Authors: Das I
Published: July 2014

We lost a legendary medical physicist, Dr. Bengt Erik Bjarngard, to angiosarcoma an aggressive type of cancer. He devoted his life to providing improved methods of radiation treatment for this devastating disease over the last 36 years. Bengt was born in a rural village of Bjarnum in southern Sweden, located near forest and is known for its furniture making. He migrated to USA at the age of 35 and was recruited by Dr. Samuel Hellman to lead a group of physicists that became the “mecca of medical physics” known as the Joint Center of Radiation Therapy (JCRT) at Harvard Medical School in Boston. Bengt mentored some of the best physicists in the country, and many of our modern treatments go back to the early days of research at the JCRT. These accomplishments, dating from 1969–1989, include: dose optimization using computer control; soft wedges; stereotactic radiosurgery (SRS); total‐body irradiation (TBI); CT‐planning; and radiation dosimetry. Bengt worked at Brown University in Rhode Island and at the University of Pennsylvania in Philadelphia, where he provided major contributions in radiation dosimetry, specifically with the head scatter model. He advocated superior calculation algorithm through the Helax treatment planning system that was on par from most commercial systems. Bengt served as AAPM president in 1979 and was a recipient of the Coolidge Award in 1998. He had a lifelong love of nature, retiring in 2000 from the University of Pennsylvania to take care of his 200 acres of homestead forest in Maine. His legacy continues through his contributions to radiation dosimetry. This session, on small field dosimetry, is a small tribute to his memory. Further details can be found in his obituary in Med Phy, 41(4), 040801, 2014.
MO‐E‐18A‐01: Imaging: Best Practices In Pediatric Imaging
Authors: Willis C , Strauss K , MacDougall R , Sammet C
Published: July 2014

This imaging educational program will focus on solutions to common pediatric imaging challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children's hospitals. Areas of focus will include general radiography, the use of manual and automatic dose management in computed tomography, and enterprise‐wide radiation dose management in the pediatric practice.

The educational program will begin with a discussion of the complexities of exposure factor control in pediatric projection radiography. Following this introduction will be two lectures addressing the challenges of computed tomography (CT) protocol optimization in the pediatric population. The first will address manual CT protocol design in order to establish a managed radiation dose for any pediatric exam on any CT scanner. The second CT lecture will focus on the intricacies of automatic dose modulation in pediatric imaging with an emphasis on getting reliable results in algorithmbased technique selection. The fourth and final lecture will address the key elements needed to developing a comprehensive radiation dose management program for the pediatric environment with particular attention paid to new regulations and obligations of practicing medical physicists.

Learning Objectives:

To understand how general radiographic techniques can be optimized using exposure indices in order to improve pediatric radiography.

To learn how to establish diagnostic dose reference levels for pediatric patients as a function of the type of examination, patient size, and individual design characteristics of the CT scanner.

To learn how to predict the patient's radiation dose prior to the exam and manually adjust technique factors if necessary to match the patient's dose to the department's established dose reference levels.

To learn how to utilize manufacturer‐provided automatic dose modulation technology to consistently achieve patient doses within the department's established size‐based diagnostic reference range.

To understand the key components of an enterprise‐wide pediatric dose management program that integrates the expanding responsibilities of medial physicists in the new era of dose monitoring.
MO‐E‐BRE‐01: Determination, Minimization and Communication of Uncertainties in Radiation Therapy
Authors: Van Dyk J , Palta J , Bortfeld T , Mijnheer B
Published: July 2014

Medical Physicists have a general understanding of uncertainties in the radiation treatment process, both with respect to dosimetry and geometry. However, there is a desire to be more quantitative about uncertainty estimation. A recent International Atomic Energy Agency (IAEA) report (about to be published) recommends that we should be as “accurate as reasonably achievable, technical and biological factors being taken into account”. Thus, a single recommendation as a goal for accuracy in radiation therapy is an oversimplification. That report also suggests that individual clinics should determine their own level of uncertainties for their specific treatment protocols. The question is “how do we implement this in clinical practice”? AAPM Monograph 35 (2011 AAPM Summer School) addressed many specific aspects of uncertainties in each of the steps of a course of radiation treatment. The intent of this symposium is: (1) to review uncertainty considerations in the entire radiation treatment process including uncertainty determination for each step and uncertainty propagation for the total process, (2) to consider aspects of robust optimization which optimizes treatment plans while protecting them against uncertainties, and (3) to describe various methods of displaying uncertainties and communicating uncertainties to the relevant professionals. While the theoretical and research aspects will also be described, the emphasis will be on the practical considerations for the medical physicist in clinical practice.

Learning Objectives:

To review uncertainty determination in the overall radiation treatment process.

To consider uncertainty modeling and uncertainty propagation.

To highlight the basic ideas and clinical potential of robust optimization procedures to generate optimal treatment plans that are not severely affected by uncertainties.

To describe methods of uncertainty communication and display.
MO‐E‐BRD‐01: Adapt‐A‐Thon – Texas Hold’em Invitational
Authors: Kessler M , Brock K , Pouliot J , Dong L
Published: July 2014

Software tools for image‐based adaptive radiotherapy such as deformable image registration, contour propagation and dose mapping have progressed beyond the research setting and are now commercial products available as part of both treatment planning systems and stand‐alone applications. These software tools are used together to create clinical workflows to detect, track and evaluate changes in the patient and to accumulate dose. Deviations uncovered in this process are used to guide decisions about replanning/adaptation with the goal of keeping the delivery of prescribed dose “on target” throughout the entire course of radiotherapy. Since the output from one step of the adaptive process is used as an input for another, it is essential to understand and document the uncertainty associated with each of the step and how these uncertainties are propagated. This in turn requires an understanding how the underlying tools work. Unfortunately, important details about the algorithms used to implement these tools are scarce or incomplete, too often for competitive reasons. This is in contrast to the situation involving other basic treatment planning algorithms such as dose calculations, where the medical physics community essentially requires vendors to provide physically important details about their underlying theory and clinical implementation. Vendors should adopt this same level of information sharing when it comes to the tools and techniques for image guided adaptive radiotherapy. The goal of this session is to start this process by inviting vendors and medical physicists to discuss and demonstrate the available tools and describe how they are intended to be used in clinical practice. The format of the session will involve a combination of formal presentations, interactive demonstrations, audience participation and some friendly “Texas style” competition.

Learning Objectives:

Understand the components of the image‐based adaptive radiotherapy process.

Understand the how these components are implemented in various commercial systems.

Understand the different use cases and workflows currently supported these tools.
MO‐E‐17A‐02: Incorporation of Contrast Medium Dynamics in Anthropomorphic Phantoms: The Advent of 5D XCAT Models
Authors: Sahbaee P , Samei E , Segars W
Published: July 2014

Purpose:

To develop a unique method to incorporate the dynamics of contrast‐medium propagation into the anthropomorphic phantom, to generate a five‐dimensional (5D) patient model for multimodality imaging studies.

Methods:

A compartmental model of blood circulation network within the body was embodied into an extended cardiac‐torso (4D‐XCAT) patient model. To do so, a computational physiologic model of the human cardiovascular system was developed which includes a series of compartments representing heart, vessels, and organs. Patient‐specific cardiac output and blood volume were used as inputs influenced by the weight, height, age, and gender of the patient's model. For a given injection protocol and given XCAT model, the contrast‐medium transmission within the body was described by a series of mass balance differential equations, the solutions to which provided the contrast enhancement‐time curves for each organ; thereby defining the tissue materials including the contrastmedium within the XCAT model. A library of time‐dependent organ materials was then defined. Each organ in each voxelized 4D‐XCAT phantom was assigned to a corresponding time‐varying material to create the 5D‐XCAT phantom in which the fifth dimension is blood/contrast‐medium within the temporal domain.

Results:

The model effectively predicts the time‐varying concentration behavior of various contrast‐medium administration in each organ for different patient models as function of patient size (weight/height) and different injection protocol factors (injection rate and pattern, iodine concentration or volume). The contrast enhanced XCAT patient models was developed based on the concentration of iodine as a function of time after injection.

Conclusion:

Majority of medical imaging systems take advantage of contrast‐medium administration in terms of better image quality, the effect of which was ignored in previous optimization studies. The study enables a comprehensive optimization of contrast administration both in terms of image quality and radiation dose, and can be used in different modalities such as CT, MRI, and ultrasound.
MO‐E‐17A‐06: Organ Dose in Abdomen‐Pelvis CT: Does TG 111 Equilibrium Dose Concept Better Accounts for KVp Dependence Than Conventional CTDI?
Authors: Li X , Morgan A , Dong F , Primak A , Davros W , Segars W
Published: July 2014

Purpose:

In CT imaging, a desirable quality assurance (QA) dose quantity should account for the dose variability across scan parameters and scanner models. Recently, AAPM TG 111 proposed to use equilibrium dose‐pitch product, in place of CT dose index (CTDI100), for scan modes involving table translation. The purpose of this work is to investigate whether this new concept better accounts for the kVp dependence of organ dose than the conventional CTDI concept.

Methods:

The adult reference female extended cardiac‐torso (XCAT) phantom was used for this study. A Monte Carlo program developed and validated for a 128‐slice CT system (Definition Flash, Siemens Healthcare) was used to simulate organ dose for abdomenpelvis scans at five tube voltages (70, 80, 100, 120, 140 kVp) with a pitch of 0.8 and a detector configuration of 2×64×0.6 mm. The same Monte Carlo program was used to simulate CTDI100 and equilibrium dose‐pitch product. For both metrics, the central and peripheral values were used together with helical pitch to calculate a volume‐weighted average, i.e., CTDIvol and (Deq)vol, respectively.

Results:

While other scan parameters were kept constant, organ dose depended strongly on kVp; the coefficient of variation (COV) across the five kVp values ranged between 70–75% for liver, spleen, stomach, pancreas, kidneys, colon, small intestine, bladder, and ovaries, all of which were inside the primary radiation beam. One‐way analysis of variance (ANOVA) for the effect of kVp was highly significant (p=3e−30). When organ dose was normalized by CTDIvol, the COV across the five kVp values reduced to 7–16%. The effect of kVp was still highly significant (p=4e−4). When organ dose was normalized by (Deq)vol, the COV further reduced to 4−12%. The effect of kVp was borderline significant (p=0.04).

Conclusion:

In abdomen‐pelvis CT, TG 111 equilibrium dose concept better accounts for kVp dependence than the conventional CTDI.

This work is supported by a faculty startup fund from the Cleveland State University.
MO‐E‐17A‐11: In‐Phantom Detector Response in a Kilovoltage X‐Ray Beam
Authors: Lawless M , DeWerd L
Published: July 2014

Purpose:

To investigate changes in detector response in a kilovoltage x‐ray beam as a function of depth in phantom.

Methods:

Detector response in a 120kVp x‐ray beam as a function of depth in a PMMA phantom was determined for a reference class Exradin A12 ionization chamber, an Exradin A1SL ionization chamber, TLD‐100 and EBT3 radiochromic film and normalized to a depth of 1cm. The output of each detector was referenced to the A12 ionization chamber reading to assess changes in detector response as a function of depth. The BEAMnrc, DOSxyz, and egs_chamber user codes of the EGSnrc Monte Carlo code were used to calculate the dose delivered to the detectors from an x‐ray source with similar beam quality to the one used in the measurements.

Results:

Changes in detector response relative to the A12 ionization chamber of 2%, 7%, and 14% for the A1SL, TLDs, and film, respectively, were observed with the larger changes in response occurring at larger depths. The Monte Carlo calculated changes in dose response showed less deviation, with the largest difference being within 2%.

Conclusion:

The Monte Carlo simulations show that doses delivered to the different detectors are quite similar, while measurements show that the detector output varies drastically. This indicates that the detector output per unit dose is changing with depth, most likely due to changes in the photon spectrum that occur because of scatter and attenuation of the primary beam. Because detector calibration is often performed at a single point in the kilovoltage energy range, the change in detector response needs to be considered when the measurement conditions differ from those of the calibration. This is of particular concern in computed tomography dose measurement, where calibrations are performed at shallow depths or in air, and measurements are made at deeper locations.
MO‐E‐18C‐01: Open Access Web‐Based Peer‐To‐Peer Training and Education in Radiotherapy
Authors: Pawlicki T , Brown D , Dunscombe P , Mutic S
Published: July 2014

Purpose:

Current training and education delivery models have limitations which result in gaps in clinical proficiency with equipment, procedures, and techniques. Educational and training opportunities offered by vendors and professional societies are by their nature not available at point of need or for the life of clinical systems. The objective of this work is to leverage modern communications technology to provide peer‐to‐peer training and education for radiotherapy professionals, in the clinic and on demand, as they undertake their clinical duties.

Methods:

We have developed a free of charge web site (https://i.treatsafely.org) using the Google App Engine and datastore (NDB, GQL), Python with AJAX‐RPC, and Javascript. The site is a radiotherapy‐specific hosting service to which user‐created videos illustrating clinical or physics processes and other relevant educational material can be uploaded. Efficient navigation to the material of interest is provided through several RT specific search tools and videos can be scored by users, thus providing comprehensive peer review of the site content. The site also supports multilingual narration\translation of videos, a quiz function for competence assessment and a library function allowing groups or institutions to define their standard operating procedures based on the video content.

Results:

The website went live in August 2013 and currently has over 680 registered users from 55 countries; 27.2% from the United States, 9.8% from India, 8.3% from the United Kingdom, 7.3% from Brazil, and 47.5% from other countries. The users include physicists (57.4%), Oncologists (12.5%), therapists (8.2%) and dosimetrists (4.8%). There are 75 videos to date including English, Portuguese, Mandarin, and Thai.

Conclusion:

Based on the initial acceptance of the site, we conclude that this open access web‐based peer‐to‐peer tool is fulfilling an important need in radiotherapy training and education. Site functionality should expand in the future to include document sharing and continuing education credits.
MO‐E‐18C‐04: Advanced Computer Simulation and Visualization Tools for Enhanced Understanding of Core Medical Physics Concepts
Authors: Naqvi S
Published: July 2014

Purpose:

Most medical physics programs emphasize proficiency in routine clinical calculations and QA. The formulaic aspect of these calculations and prescriptive nature of measurement protocols obviate the need to frequently apply basic physical principles, which, therefore, gradually decay away from memory. E.g. few students appreciate the role of electron transport in photon dose, making it difficult to understand key concepts such as dose buildup, electronic disequilibrium effects and Bragg‐Gray theory. These conceptual deficiencies manifest when the physicist encounters a new system, requiring knowledge beyond routine activities.

Methods:

Two interactive computer simulation tools are developed to facilitate deeper learning of physical principles. One is a Monte Carlo code written with a strong educational aspect. The code can “label” regions and interactions to highlight specific aspects of the physics, e.g., certain regions can be designated as “starters” or “crossers,” and any interaction type can be turned on and off. Full 3D tracks with specific portions highlighted further enhance the visualization of radiation transport problems. The second code calculates and displays trajectories of a collection electrons under arbitrary space/time dependent Lorentz force using relativistic kinematics.

Results:

Using the Monte Carlo code, the student can interactively study photon and electron transport through visualization of dose components, particle tracks, and interaction types. The code can, for instance, be used to study kerma‐dose relationship, explore electronic disequilibrium near interfaces, or visualize kernels by using interaction forcing. The electromagnetic simulator enables the student to explore accelerating mechanisms and particle optics in devices such as cyclotrons and linacs.

Conclusion:

The proposed tools are designed to enhance understanding of abstract concepts by highlighting various aspects of the physics. The simulations serve as virtual experiments that give deeper and long lasting understanding of core principles. The student can then make sound judgements in novel situations encountered beyond routine clinical activities.
MO‐F‐16A‐04: Case Study: Estimation of Peak Skin Dose Following a Physician Reported “High Dose” Case and Sentinel Event Considerations
Authors: Supanich M , Chu J , Wehmeyer A
Published: July 2014

Purpose:

This work offers as a teaching example a reported high dose fluoroscopy case and the workflow the institution followed to self‐report a radiation overdose sentinel event to the Joint Commission.

Methods:

Following the completion of a clinical case in a hybrid OR room with a reported air kerma of >18 Gy at the Interventional Reference Point (IRP) the physicians involved in the case referred study to the institution's Radiation Safety Committee (RSC) for review. The RSC assigned a Diagnostic Medical Physicist (DMP) to estimate the patient's Peak Skin Dose (PSD) and analyze the case. Following the DMP's analysis and estimate of a PSD of >15 Gy the institution's adverse event committee was convened to discuss the case and to self‐report the case as a radiation overdose sentinel event to the Joint Commission. The committee assigned a subgroup to perform the root cause analysis and develop institutional responses to the event.

Results:

The self‐reporting of the sentinel event and the associated root cause analysis resulted in several institutional action items that are designed to improve process and safety. A formal reporting and analysis mechanism was adopted to review fluoroscopy cases with air kerma greater than 6 Gy at the IRP. An improved and formalized radiation safety training program for physicians using fluoroscopy equipment was implemented. Additionally efforts already under way to monitor radiation exposure in the Radiology department were expanded to include all fluoroscopy equipment capable of automated dose reporting.

Conclusion:

The adverse event review process and the root cause analysis following the self‐reporting of the sentinel event resulted in policies and procedures that are expected to improve the quality and safe usage of fluoroscopy throughout the institution.
MO‐F‐16A‐07: Establishing Reference Values for All CT Exams and Monitoring Them: The Texas Experience
Authors: Clements J , Moirano J , Lindsey R
Published: July 2014

Purpose:

To establish reference levels (RLs) in terms of standard dose metrics (CTDIvol and DLP) for all CT exams performed in a community hospital and monitor clinical exams performed against RLs.

Methods:

Clinical CT exams already performed were categorized by body region and CTDIvol and DLP values were analyzed. RLs for the dose metrics were established at either the ACR RL or at approximately the 75th percentile for the patient population performed at the facility. Once RLs were set, all patient exams performed were compared to the RLs. Monthly summaries were completed which include the exam type, applicable RL, actual dose metric, and initials of the technologist performing the exam. Performance summaries are posted in the department and discussed quarterly at CT dose committee meetings.

Results:

Initially, significant overages were observed for abdomen/pelvis exams that used the CTDIvol RL established by the ACR (25 mGy). This RL is for 70 kg patients while a disproportionate number of the patients in our patient population exceed this weight. As a Result, a separate RL was established for abdomen pelvis exams for patients greater than 90kg. After adjusting the abdomen/pelvis RL for patient weight, the total number of exams exceeding RLs has dropped by 50% over a period of 6 months.

Conclusion:

This work indicates the potential for optimizing CT exams with respect to patient exposure by establishing region‐specific RLs, monitoring values, publishing results, and providing education to staff performing exams. Reasonable RLs have been set for body region and modified based on patient size. This illustrates the need for considering more than an absolute maximum value as a RL and the process of continuous quality improvement. Commercial software has been purchased and will allow for the establishment of more refined RLs and more comprehensive analysis.
MO‐G‐BRE‐05: Clinical Process Improvement and Billing in Radiation Oncology: A Case Study of Applying FMEA for CPT Code 77336 (continuing Medical Physics Consultation)
Authors: Spirydovich S , Huq M
Published: July 2014

Purpose:

The improvement of quality in healthcare can be assessed by Failure Mode and Effects Analysis (FMEA). In radiation oncology, FMEA, as applied to the billing CPT code 77336, can improve both charge capture and, most importantly, quality of the performed services.

Methods:

We created an FMEA table for the process performed under CPT code 77336. For a given process step, each member of the assembled team (physicist, dosimetrist, and therapist) independently assigned numerical values for: probability of occurrence (O, 1–10), severity (S, 1–10), and probability of detection (D, 1–10) for every failure mode cause and effect combination. The risk priority number, RPN, was then calculated as a product of O, S and D from which an average RPN was calculated for each combination mentioned above. A fault tree diagram, with each process sorted into 6 categories, was created with linked RPN. For processes with high RPN recommended actions were assigned. 2 separate R&V systems (Lantis and EMR‐based ARIA) were considered.

Results:

We identified 9 potential failure modes and corresponding 19 potential causes of these failure modes all resulting in unjustified 77336 charge and compromised quality of care. In Lantis, the range of RPN was 24.5–110.8, and of S values – 2–10. The highest ranking RPN of 110.8 came from the failure mode described as “end‐of‐treatment check not done before the completion of treatment”, and the highest S value of 10 (RPN=105) from “overrides not checked”. For the same failure modes, within ARIA electronic environment with its additional controls, RPN values were significantly lower (44.3 for end‐of‐treatment missing check and 20.0 for overrides not checked).

Conclusion:

Our work has shown that when charge capture was missed that also resulted in some services not being performed. Absence of such necessary services may result in sub‐optimal quality of care rendered to patients.
MO‐G‐BRE‐09: Validating FMEA Against Incident Learning Data: A Study in Stereotactic Body Radiation Therapy
Authors: Yang F , Cao N , Young L , Howard J , Sponseller P , Logan W , Arbuckle T , Korssjoen T , Meyer J , Ford E
Published: July 2014

Purpose:

Though FMEA (Failure Mode and Effects Analysis) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge it has never been validated against actual incident learning data. The objective of this study was to perform an FMEA analysis of an SBRT (Stereotactic Body Radiation Therapy) treatment planning process and validate this against data recorded within an incident learning system.

Methods:

FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, and dosimetrists. Potential failure modes were identified through a systematic review of the workflow process. Failure modes were rated for severity, occurrence, and detectability on a scale of 1 to 10 and RPN (Risk Priority Number) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that had been active for two years. Differences were identified.

Results:

FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near‐miss events related to SBRT planning. FMEA failed to anticipate 13 of these events, among which 3 were registered with severity ratings of severe or critical in the incident learning system. Combining both methods yielded a total of 76 failure modes, and when scored for RPN the 13 events missed by FMEA ranked within the middle half of all failure modes.

Conclusion:

FMEA, though valuable, is subject to certain limitations, among them the limited ability to anticipate all potential errors for a given process. This FMEA exercise failed to identify a significant number of possible errors (17%). Integration of FMEA with retrospective incident data may be able to render an improved overview of risks within a process.
MO‐G‐BRF‐09: Investigating Magnetic Field Dose Effects in Mice: A Monte Carlo Study
Authors: Rubinstein A , Guindani M , Followill D , Melancon A , Hazle J , Court L
Published: July 2014

Purpose:

In MRI‐linac treatments, radiation dose distributions are affected by magnetic fields, especially at high‐density/low‐density interfaces. Radiobiological consequences of magnetic field dose effects are presently unknown; therefore, preclinical studies are needed to ensure the safe clinical use of MRI‐linacs. This study investigates the optimal combination of beam energy and magnetic field strength needed for preclinical murine studies.

Methods:

The Monte Carlo code MCNP6 was used to simulate the effects of a magnetic field when irradiating a mouse‐sized lung phantom with a 1.0cmx1.0cm photon beam. Magnetic field effects were examined using various beam energies (225kVp, 662keV[Cs‐137], and 1.25MeV[Co‐60]) and magnetic field strengths (0.75T, 1.5T, and 3T). The resulting dose distributions were compared to Monte Carlo results for humans with various field sizes and patient geometries using a 6MV/1.5T MRI‐linac.

Results:

In human simulations, the addition of a 1.5T magnetic field caused an average dose increase of 49% (range:36%–60%) to lung at the soft tissue‐to‐lung interface and an average dose decrease of 30% (range:25%–36%) at the lung‐to‐soft tissue interface. In mouse simulations, the magnetic fields had no effect on the 225kVp dose distribution. The dose increases for the Cs‐137 beam were 12%, 33%, and 49% for 0.75T, 1.5T, and 3.0T magnetic fields, respectively while the dose decreases were 7%, 23%, and 33%. For the Co‐60 beam, the dose increases were 14%, 45%, and 41%, and the dose decreases were 18%, 35%, and 35%.

Conclusion:

The magnetic field dose effects observed in mouse phantoms using a Co‐60 beam with 1.5T or 3T fields and a Cs‐137 beam with a 3T field compare well with those seen in simulated human treatments with an MRI‐linac. These irradiator/magnet combinations are suitable for preclinical studies investigating potential biological effects of delivering radiation therapy in the presence of a magnetic field.

Partially funded by Elekta.
MO‐G‐17A‐01: Innovative High‐Performance PET Imaging System for Preclinical Imaging and Translational Researches
Authors: Sun X , Lou K , Deng Z , Shao Y
Published: July 2014

Purpose:

To develop a practical and compact preclinical PET with innovative technologies for substantially improved imaging performance required for the advanced imaging applications.

Methods:

Several key components of detector, readout electronics and data acquisition have been developed and evaluated for achieving leapfrogged imaging performance over a prototype animal PET we had developed. The new detector module consists of an 8×8 array of 1.5×1.5×30 mm3 LYSO scintillators with each end coupled to a latest 4×4 array of 3×3 mm2 Silicon Photomultipliers (with ∼0.2 mm insensitive gap between pixels) through a 2.0 mm thick transparent light spreader. Scintillator surface and reflector/coupling were designed and fabricated to reserve air‐gap to achieve higher depth‐of‐interaction (DOI) resolution and other detector performance. Front‐end readout electronics with upgraded 16‐ch ASIC was newly developed and tested, so as the compact and high density FPGA based data acquisition and transfer system targeting 10M/s coincidence counting rate with low power consumption. The new detector module performance of energy, timing and DOI resolutions with the data acquisition system were evaluated. Initial Na‐22 point source image was acquired with 2 rotating detectors to assess the system imaging capability.

Results:

No insensitive gaps at the detector edge and thus it is capable for tiling to a large‐scale detector panel. All 64 crystals inside the detector were clearly separated from a flood‐source image. Measured energy, timing, and DOI resolutions are around 17%, 2.7 ns and 1.96 mm (mean value). Point source image is acquired successfully without detector/electronics calibration and data correction.

Conclusion:

Newly developed advanced detector and readout electronics will be enable achieving targeted scalable and compact PET system in stationary configuration with >15% sensitivity, ∼1.3 mm uniform imaging resolution, and fast acquisition counting rate capability for substantially improved imaging and quantification performance for small animal imaging and image‐guided radiotherapy applications.

This work was supported by a research award RP120326 from Cancer Prevention and Research Institute of Texas.
MO‐G‐17A‐08: Applications of Quantitative PET/CT Imaging of Yttrium‐90: A Tool for Improving Radioembolization
Authors: Pasciak A , Bradley Y
Published: July 2014

Purpose:

Yttrium‐90 (Y90) PET/CT post‐treatment imaging of radioembolization has fostered significant interest from both the interventional radiology and nuclear medicine communities over the past few years. Recent literature has demonstrated high quantitative accuracy of Y90 PET at the activity concentrations common in radioembolization. However, few have explored methods in which this information can be clinically applied toward improving patient care.

Methods:

IRB approval and informed consent was obtained for over 35 Y90 post‐treatment imaging studies, performed under 2 distinct protocols. In protocol 1, Y90 PET/CT provided quantitative post‐treatment imaging, which was then converted into 3D maps of absorbed‐dose. Both images and absorbed dose maps were used to manage patient care. In protocol 2, tumor absorbed‐dose measurements from Y90 PET/CT were compared to known tumoricidal thresholds. If insufficient absorbed dose was delivered to the tumor, the patient would have an additional Y90 infusion the same day, providing truly patient‐specific Y90 PET/CT based treatment‐planning.

Results:

Y90 PET/CT allowed for a superior post‐radioembolization evaluation of technical success compared with conventional Y90 bremsstrahlung SPECT. Due to the exceptional resolution of PET, a direct comparison between the distribution of radioembolization and pre‐treatment planning intentions can be made. Further, quantification of tumor absorbed‐dose directly from PET/CT imaging allows for the prediction of treatment efficacy based on a comparison with known tumoricidal thresholds. This immediate evaluation allowed treating physicians to consider additional or alternate therapies before discovering clinical failure weeks later. One protocol 2 patient was found to have a subtumoricidal absorbed dose following radioembolization. This patient received a same‐day infusion of additional Y90 with identical catheter placement to the first infusion. A robust treatment response was seen on follow‐up imaging.

Conclusion:

Y90 PET/CT produces quantifiable image sets, which can be transformed into 3D maps of absorbed dose. This information can be utilized to improve patient care. SIRTeX Medical, Surefire Medical
MO‐G‐17A‐09: Quantitative Autoradiography of Biopsy Specimens Extracted Under PET/CT Guidance
Authors: Fanchon L , Carlin S , Burger I , Schmidtlein C , Humm J , Yorke E , Solomon S , Deasy J , Kirov A
Published: July 2014

Purpose:

To develop a procedure for accurate determination of PET tracer co ncentration with high spatial accuracy in situ by performing Quantitative Autoradiography of Biopsy Specimens (QABS) extracted under PET/CT guidance.

Methods:

Autoradiography (ARG) standards were produced from a gel loaded with a known co ncentration of FDG biopsied with 18G and 20G biopsy needles. Specimens obtained with these needles are generally cylindrical: up to 18 mm in length and about 0.8 and 0.6 mm in diameter respectively. These standards, with similar shape and density as biopsy specimens were used to generate ARG calibration curves.Quantitative ARG was performed to measure the activity co ncentration in biopsy specimens extracted from ten patients. The biopsy sites were determined acco rding to PET/CT's obtained in the operating room. Additional CT scans were acquired with the needles in place to co nfirm co rrect needle placements. The ARG images were aligned with the needle tip in the PET/CT images using the open source CERR software. The mean SUV calculated from the specimen activities (SUVarg) were co mpared to that from PET (SUVpet) at the needle locations.

Results:

Calibration curves show that the relation between ARG signal and activity co ncentration in those standards is linear for the investigated range (up to 150 kBq/ml). The co rrelation co efficient of SUVarg with SUVpet is 0.74. Discrepancies between SUVarg and SUVpet can be attributed to the small size of the biopsy specimens compared to PET resolution.

Conclusion:

The calibration procedure using surrogate biopsy specimens provided a method for quantifying the activity within the biopsy cores obtained under FDG‐PET guidance. QABS allows mapping the activity concentration in such biopsy specimens with a resolution of about 1mm. QABS is a promising tool for verification of biopsy adequacy by comparing specimen activity to that expected from the PET image.

A portion of this research was funded by a research grant from Biospace Lab, 13 rue Georges Auric 75019 Paris, FRANCE.
MO‐G‐18C‐02: Flow Quantification Quality Assurance for Multiple MR Scanners Using Power Injector
Authors: Ai H , Zhou Y , Clevenger T , Lin C
Published: July 2014

Purpose:

To evaluate a flow quantification QA method on multiple MR scanners with different magnetic field strength from different manufacturer.

Methods:

Our previous study proposed a low‐cost, reliable and convenient MRI flow quantification QA method based on a simple and compact flow contrast phantom and a power injector. Five different MR scanners (Siemens MAGNETOM Espree 1.5T, Aera 1.5T and Skyra 3T; GE Optima MR450w 1.5T and Discovery MR750w 3T) were used to test the reproducibility and sensitivity of the QA method. Flow phantom phase contrast images were acquired at magnetic field isocenter for all the MR scanners. Eight repeated acquisitions and measurements were performed on each scanner. In addition, off‐center effects were tested on Siemens Espree and two GE scanners.

Results:

The positive flow rates measured at isocenter of five MR scanners range from +1.84± 0.01 mL/s to +2.01± 0.02 mL/s, within 8% difference from the 2mL/s flow rate provided by the power injector. The negative flow rate measured at isocenter range from −1.89± 0.01 mL/s to ‐2.14± 0.03 mL/s, within 7% difference from 2mL/s flow rate. Flow rate measures were most affected by off‐center effect when the flow phantom was shifted 12 cm transversely and 12 cm longitudinally from the isocenter. For GE Optima scanner, positive flow of +1.53± 0.01 mL/s was measured, which is 24.5% difference from power injector flow rate. For GE Discovery scanner, negative flow of −2.68± 0.02 mL/s was measured, which is 34% difference from 2mL/s flow rate.

Conclusion:

This QA method was sensitive enough to detect flow quantification difference between scanners. Flow quantification errors at locations away from magnetic field isocenter due to the worse gradient fidelity can be detected by our flow quantification QA method. In conclusion, flow phantom coupled with power injector is presented to be a widely available, consistent and low cost flow quantification method.
MO‐G‐18C‐04: Improved Synthetic 4D‐MRI Using Linear Polynomial Fitting Model
Authors: Yang J , Yin F , Wang H , Chang Z , Czito B , Bashir M , Palta M , Cai J
Published: July 2014

Purpose:

To reduce deformable image registration error by fitting the displacement vector field (DVF) to smooth the motion trajectory of each pixel in synthetic 4D‐MRI.

Methods:

Five patients with cancers in the liver were enrolled in this study. For a 4D MR image data set, the DVF matrices relative to a specific reference phase were calculated using an in‐house deformable image registration based on b‐spline. The displacement trajectory of each voxel throughout the respiratory cycle was constituted by concatenating the corresponding displacement values from all DVF matrices. A linear polynomial fitting model was then used to fit the DVFs in three spatial and the temporal dimension, respectively. By warpping the source MR images using the remodeled DVFs, we synthesized MR images at selected phases. Tumor motion trajectories were derived from source 4DMRI, original synthetic images and improved synthetic images. These were analyzed in the superior‐inferior (SI), anterior‐posterior (AP), and mediallateral (ML) directions, respectively. Correlation coefficients (CC) and differences in motion amplitude (D) were calculated for comparison.

Results:

For all patients, tumor motion trajectories were strongly correlated between source 4D‐MRI images and improved synthetic 4D‐MRI (mean CC 0.98±0.01). Differences in motion amplitude were small (mean D 0.46±0.14 mm) in all directions. Correlation between source 4D‐MRI and original synthetic 4D‐MRI was slightly less strong (mean CC 0.97±0.01) and motion amplitude differences were slightly larger (0.55±0.19 mm).

Conclusion:

The feasibility of synthesizing T2w 4D‐MRI using remodeled DVFs has been investigated in this study. Preliminary results in oncologic patients demonstrated the potential of reducing inaccuracies in original synthetic 4DMRI caused by registration errors using the linear polynomial fitting model without much loss of respiratory motion information.

NIH (1R21CA165384‐01A1), Golfers Against Cancer (GAC) Foundation, The China Scholarship Council (CSC)
MO‐G‐9A‐01: Imaging Refresher for Standard of Care Radiation Therapy
Authors: Labby Z , Sensakovic W , Hipp E , Altman M
Published: July 2014

Imaging techniques and technology which were previously the domain of diagnostic medicine are becoming increasingly integrated and utilized in radiation therapy (RT) clinical practice. As such, there are a number of specific imaging topics that are highly applicable to modern radiation therapy physics. As imaging becomes more widely integrated into standard clinical radiation oncology practice, the impetus is on RT physicists to be informed and up‐to‐date on those imaging modalities relevant to the design and delivery of therapeutic radiation treatments. For example, knowing that, for a given situation, a fluid attenuated inversion recovery (FLAIR) image set is most likely what the physician would like to import and contour is helpful, but may not be sufficient to providing the best quality of care. Understanding the physics of how that pulse sequence works and why it is used could help assess its utility and determine if it is the optimal sequence for aiding in that specific clinical situation. It is thus important that clinical medical physicists be able to understand and explain the physics behind the imaging techniques used in all aspects of clinical radiation oncology practice. This session will provide the basic physics for a variety of imaging modalities for applications that are highly relevant to radiation oncology practice: computed tomography (CT) (including kV, MV, cone beam CT [CBCT], and 4DCT), positron emission tomography (PET)/CT, magnetic resonance imaging (MRI), and imaging specific to brachytherapy (including ultrasound and some brachytherapy specific topics in MR). For each unique modality, the image formation process will be reviewed, trade‐offs between image quality and other factors (e.g. imaging time or radiation dose) will be clarified, and typically used cases for each modality will be introduced. The current and near‐future uses of these modalities and techniques in radiation oncology clinical practice will also be discussed.

Learning Objectives:

To review the basic physical science principles of CT, PET, MR, and ultrasound imaging.

To understand how the images are created, and present their specific role in patient management and treatment planning for therapeutic radiation (both external beam and brachytherapy).

To discuss when and how each specific imaging modality is currently used in clinical practice, as well as how they may come to be used in the near future.
MO‐H‐19A‐03: Patient Specific Bolus with 3D Printing Technology for Electron Radiotherapy
Authors: Zou W , Fisher T , Swann B , Siderits R , McKenna M , Khan A , Yue N , Zhang M
Published: July 2014

Purpose:

Bolus is widely used in electron radiotherapy to achieve desired dose distribution. 3D printing technologies provide clinicians with easy access to fabricate patient specific bolus accommodating patient body surface irregularities and tissue inhomogeneity. This study presents the design and the clinical workflow of 3D printed bolus for patient electron therapy in our clinic.

Methods:

Patient simulation CT images free of bolus were exported from treatment planning system (TPS) to an in‐house developed software package. Bolus with known material properties was designed in the software package and then exported back to the TPS as a structure. Dose calculation was carried out to examine the coverage of the target. After satisfying dose distribution was achieved, the bolus structure was transferred in Standard Tessellation Language (STL) file format for the 3D printer to generate the machine codes for printing. Upon receiving printed bolus, a quick quality assurance was performed with patient resimulated with bolus in place to verify the bolus dosimetric property before treatment started.

Results:

A patient specific bolus for electron radiotherapy was designed and fabricated in Form 1 3D printer with methacrylate photopolymer resin. Satisfying dose distribution was achieved in patient with bolus setup. Treatment was successfully finished for one patient with the 3D printed bolus.

Conclusion:

The electron bolus fabrication with 3D printing technology was successfully implemented in clinic practice.
MO‐H‐19A‐04: Multichannel CW Ultrasonic Thermometry for Imaging Therapeutic Dose Fields in Water
Authors: Tosh R
Published: July 2014

Purpose:

To develop a scalable, multichannel ultrasonic thermometry system suitable for imaging clinical‐beam dose distributions in a water phantom.

Method:

A small, glass‐walled rectangular water phantom (15 cm × 20 cm × 30 cm) was filled with distilled water, and two ultrasonic transducers were placed on the outside, against opposing walls, approximately 5 cm below the water line, and were aligned to optimize transmission/reception of ultrasound between them. Two synchronized lock‐in amplifiers were connected to the transducers to enable full‐duplex operation of two separate ultrasonic frequency channels configured to transmit simultaneously through the same volume of water and thereby provide independent measurements of the temperature‐dependent ultrasonic phase lag. Controlled heating of the water via immersed power resistors provided a means to study dependence of measured phase lag on temperature change for both channels; cross‐correlation of the phase outputs enabled much smaller temperature fluctuations in the phantom to be used to ascertain the noise floor and achievable temperature resolution.

Results:

Temperature measurements from both channels, converted from phase measurements via polynomials available in the literature, exhibited the expected linear dependence of ultrasonic phase on temperature change (measured via calibrated thermistor probe). Cross‐correlation analysis of phase fluctuations yielded rms noise estimates of approximately 1‐2 microKelvin, comparable to that observed in standard water calorimeters.

Conclusion:

Phase‐sensitive detection of cw ultrasound has been shown to provide temperature sensitivity needed for calorimetry of external treatment beams, and the present simple demonstration establishes that multiple channels may be run simultaneously without phase disturbances that currently affect time‐of‐flight techniques utilizing phase‐detection. Immediate plans include doubling the number of sensors, to enable a simple tomographic reconstruction, and to test the system in Clinac x‐rays and electron beams.