bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐FF‐I‐91: Diagnostic Medical Physics Characterization of a High Field MR Scanner Using a State of the Art MR Head Coil
Authors: Hussain I , Jain J , Kaufman R 
Published: July 2007

Purpose: To discuss design characteristics of state of the art “multi‐element” coil technology and performance testing of 3.0T MR imager. Method and Materials: All tests were conducted on a Siemens Trio 3.0T imager using a 12 element head coil. ACR accreditation phantom and manufacturer provided phantoms were used. With the development of new imaging techniques such as parallel imaging, manufacturers have developed multi‐element coils for advanced imaging capabilities. These receive only coils can be applied independently or subsets of elements can be used for a particular exam. The signals are combined by a hardware called Mode‐Matrix. Multi‐element coils, however, have associated problems such as drop in signal uniformity across the image. Further image distortion can be more significant with high performance gradients. Various processing filters are available to address these issues.Our tests included:a. Operational characterization of MR scanner at the coil element level.b. Effect of image quality filters available.Image quality in parallel imaging. Results: ACR tests passed without the application of image quality filters except for uniformity, for which pre‐scan normalize was used. Raw filter reduced truncation artifact with loss of spatial resolution. No major impact on SNR or distortion correction when using Elliptical and LargeFOV filters, respectively. With GRAPPA based parallel imaging, low contrast detectibility decreased along with slight reduction in maximum uniformity (around 99%, 98% and 96%) for acceleration factors of 2, 3 and 4, respectively. Number of spokes visible varied as 8, 5, and 0, for acceleration factors of 2, 3 and 4, respectively, in slice number 11 (ACR recommended phantom and slice prescription). Spatial resolution remained unchanged at 0.9 mm. Uncombined images showed individual coil elements with different SNR values while noise remained approximately constant.Conclusion: System design and application‐based testing of magnetic resonance imagers provide valuable insight into scanner capabilities.
SU‐FF‐I‐102: Signal Dependence On Frequency in Magnetic Particle Imaging
Authors: Weaver J , Rauwerdink A , Sullivan C , Baker I 
Published: July 2007

Purpose: To evaluate the frequency dependence of signal detection in magnetic particle imaging (MPI) using heterodyne mixing of the odd harmonics down to DC for detection. Method and Materials: Magnetic particle imaging detects the odd numbered harmonics generated when a sinusoidal driving field saturates the nanoparticles. A solenoidal coil was used to generate the driving field of approximately 10 mT in a 3.2 cm inner diameter tube. Smaller diameter loops were connected to a phase‐lock amplifier to detect the harmonics. The difference in the third harmonic with and without a 1 ml sample of 300 microgram/ml, 40 nanometer, nanoparticles was measured over a one minute acquisition. The contrast to noise ratio (CNR) was calculated for frequencies between 500 Hz and 20 kHz. Results: The CNR increased linearly with frequency; the linear correlation coefficient was 0.993 (p‐value 10−7). Further, the CNR per cycle was essentially constant (p‐value 10−6) over the entire range of frequencies. The sensitivity allowed detection of nanoparticles down to 20 microgram/ml concentrations.The original work found that the best SNR was obtained using a swept low frequency excitation. However, filters were used to isolate the driving field from the harmonics. In contrast, the phase‐lock amplifier heterodyne mixes the harmonic frequencies to DC before filtering so the filtering is much more effective. The difference in detection is probably responsible for the different results. The harmonic signal is generated from the edges in the magnetization occurring when the nanoparticles saturate so the harmonics should increase linearly with the number of edges which would result in a linear increase with frequency. Conclusions: The CNR increases linearly with frequency. The constant CNR per cycle over all frequencies implies that distortion of the hysteresis curve that can reduce the harmonics for higher driving frequencies is not significant below 20 kHz for these nanoparticles.
SU‐FF‐I‐128: Regional Time Density Curves (R‐TDC) Derived From Angiographic Sequences for Analysis of Aneurysmal Flow Modification Resulting From Endovascular Image‐Guided Interventions
Authors: Dohatcu AC , Ionita CN , Sherman JR , Rangwalla HS , Bednarek DR , Hoffman K , Rudin S 
Published: July 2007

Purpose: Digital subtraction angiography (DSA) is currently used to evaluate the result of endovascular treatments, either visually or using time‐density curves (TDC) which quantitate the change of contrast as a function of time for the entire aneurysm. Regional analysis (R‐TDCs) of flow patterns in sub‐volumes of an aneurysm was employed in this study to extract local flow information to determine the result of treatment with a partially‐occluding asymmetric vascular stent (AVS). Method and Materials: A patient‐specific, elastomer aneurysm phantom was placed in an in‐vitro pulsatile flow loop containing a glycerin‐water (25/75) solution simulating blood. One cc volumes of iodinated contrast were delivered 20 cm from the aneurysm entrance through a 6‐Fr catheter with an automatic injector. DSA sequences were acquired at 30 frames/sec using a 5‐inch II mode. The neck of the aneurysm was partially covered by a polyurethane‐patch AVS positioned to occlude either the proximal or the distal portion of the orifice. R‐TDCs were obtained for untreated and treated cases. Results: Differences in R‐TDC parameters for untreated, proximally covered, and distally covered cases indicate important modifications of flow occurred in different areas inside the aneurysm that are not evident from the total volume TDC. For example, in one sub‐region with the proximal patch, we measured a 2.3 times increase in peak density compared to the untreated case and a residence time 3.9 times longer, whereas the total aneurysm measurement showed the peak density to be reduced to 0.8 times and the residence time to be increased by a factor of only 1.9 compared to the untreated case. Conclusion: R‐TDC parameters derived from angiographic sequences present a great potential for quantitative in‐vivo assessment of local hemodynamic effects. This approach may provide a valuable, minimally invasive tool for assessing endovascular treatments during the procedure.Support: NIH R01‐NS43924, R01‐EB002873, Toshiba‐Corp.
SU‐FF‐T‐74: An Objective Function for TCP/NTCP Curve Fitting
Authors: Stavrev P , Stavreva N , Schinkel C , Fallone BG 
Published: July 2007

Purpose: To propose an objective function for TCP/NTCP curve fitting. Method and Materials: One of the widely used objective functions by physicists, when fitting theoretical models to experimental data, is the χ2 one, where:
urn:x-wiley:00942405:media:mp0725:mp0725-math-0001 which is the maximum likelihood function in case of Gaussian random variables. In the case of a binary outcome, as is the nature of clinical or experimental animal radiation outcome data, the random variable has a binomial distribution and the maximum likelihood function for ungrouped data becomes:
urn:x-wiley:00942405:media:mp0725:mp0725-math-0002 where Ptheor stands for TCPtheor or NTCPtheor. The maximization of L is often used by different authors for the estimation of the TCP/NTCP model parameters. Results: However, sometimes χ2 is used to fit TCP/NTCP functions for different purposes like theoretical comparison between different models. In this case the application of χ2 becomes inaccurate and inadequate especially when the function values are close to the ends of the interval in which they are defined, namely 0 or 1. This is why we propose t he application of the double logarithmic transformation, presuming that the random variable is not normally but log‐log‐normally distributed.Conclusion: Thus the objective function in case of model comparison would become:
urn:x-wiley:00942405:media:mp0725:mp0725-math-0003 where . Here stands for the values of P predicted by one of the models that are being compared and stands for the values of P predicted by the other model.
SU‐FF‐T‐98: Characterization of Buildup Effects in OneDosePlus MOSFET‐Based Dosimeters
Authors: Pursley J , Beyer GP , Craciunescu O , Fraisse C , Carroll J , Oldham M 
Published: July 2007

Purpose: Evaluate the buildup cap used on OneDosePlus™ MOSFET dosimeters and study the field size, angular, and SSD dependency. Method and Materials: OneDosePlus (ODP) dosimeters are single use, pre‐calibrated MOSFETs used to measure entrance patient dose. ODP has an integrated 1.2 mm thick tin cap. Custom dosimeters were created with buildup caps of varied thicknesses to determine the approximate tin dmax thickness for 6, 15, and 18 MV. Non‐calibrated ODP dosimeters were evaluated to assess the effect on response of the dosimeter as a function of field size, SSD, and anisotropy for different energies. Results: PDD curves for 6, 15 and 18MV show broad maximum responses centered near cap thicknesses of 1.2, 2.6 and 2.8 mm for 6, 15, and 18 MV, respectively. Evaluation of the field size response showed that higher energies have an over‐ and under‐response for larger/smaller field sizes as compared to 6 MV response, suggesting an increase in electron contamination dose contribution. Results of extended SSDs studies, typical of TBI treatments, show enhanced measurement precision, supporting these findings.For patient use, the dosimeter response is pre‐calibrated and adjusted such that the reading corresponds to Dmax in‐tissue for each specific energy. In addition, the dosimeters are corrected for the 6 MV field size and SSD dependency. Therefore, for higher energies, a slight over‐ or under‐response can be observed for larger/smaller field sizes but not in excess of the reported dosimeter accuracy (± 5%,2σ). Conclusion: The buildup cap for ODP provides a partial buildup effect with results within the expected accuracy for different dosimetric parameters. The dosimeter factory calibration corrects the response from the partial buildup effect seen from the buildup cap. Extended SSD data suggests that ODP could be used to measure dose for TBI treatments.This research was sponsored by Sicel Technologies, Inc.
SU‐FF‐T‐232: Feasibility Study of a Carbon Nanotube Field Emission Microbeam System for Cellular Irradiation
Authors: Chang S , Zhang J , Bordelon D , Graboski S , Schreiber E , Cox A , Zhou O 
Published: July 2007

Purpose: Tissue‐level radiobiological effects that influence tumor control or normal tissue complications stem from processes initiated at the cellular and sub‐cellular levels immediately following radiation energy deposition. The exact mechanisms of these processes at the critical moments are still poorly understood. We proposed to develop a nanotechnology based microbeam pixel array cellular irradiation system that promises to enable researchers to study the micro‐processes at the spatial and temporal scale of the events. This presentation reports the feasibility study results. Method and Materials: A multi‐pixel microbeam cellular irradiation system is proposed to selectively irradiate chosen target cells in a Petri dish under microscope observation. The microbeam system uses carbon nanotube (CNT) field emission technology. Each of the CNT pixels emits an electron beam and a silicon nitride window collimates the electron beam to a specific microbeam size. The electron microbeam has a tunable energy of 20–60 keV. Each of the pixel beams in the multi‐pixel microbeam can be controlled individually. The initial phase of the research is design and development of a prototype single pixel microbeam device and cell irradiation demonstration. Results: We have designed and fabricated a prototype single pixel CNT field emission microbeam system and performed dose calibration. GAFCHROMIC film is used to measure absolute dose and dose distribution. Microbeam radiation dose is calibrated as dose per radiation pulse. We performed cell irradiation using the prototype microbeam device on Rat‐1 cells. H2AX is phosphorylated at DNA damage sites and the microbeam irradiation pattern is confirmed by the pattern of DNA damage. Conclusion: We have demonstrated the feasibility of a single pixel CNT field emission microbeam for cellular irradiation. The next research step is study the feasibility of the multi‐pixel microbeam array.This work is funded by NCI (R21 CA118351) and North Carolina Biotechnology Center (2005 MRG‐111).
TU‐SAMS‐L100J‐01: Determination of Dose From CT Examinations
Authors: Boone J 
Published: July 2007

The assessment of radiation dose from computed tomography has become an important issue due to the increased utilization of computed tomography in a large number of clinical applications, from CT urography to cardiac CT. The traditional metrics used for CT dose assessment (CTDI‐100) have come under assault from a number of investigators, because of its limitations in describing the radiation dose in realistic CT examinations. While there remains no real consensus in the field, a number of groups are working on the development of CT dose metrics which convey a better understanding of the radiation dose received by individual patients for specific CT examinations. In this presentation, the perspective of a number of groups will be presented. Primarily, the work of a committee of the International Commission of Radiological Units (ICRU) commissioned in 2005 will be discussed.The ICRU committee has preliminarily defined a multi‐tier system for the assessment of radiation dose metrics in computed tomography. At the first level, machine‐dependent performance factors are described and measured, and these include the traditional CTDI‐100 metric for the 16 cm and 32 cm diameter polymethylmethacrylate dosimetry phantoms, at the center and at the periphery. There is a consensus amongst the ICRU community that radiation dose to patients undergoing CT examinations is best established using the known geometry of the CT examination, coupled with measured output characteristics of the specific CT scanner (including bow‐tie characteristics), combined with Monte Carlo computations. In the rare instance in which the CT dose to a specific patient needs to be computed, image‐based methodologies will be presented which enable these computations with a high degree of accuracy. It is emphasized that the effective dose (measured in milliseiverts) is not an appropriate measure for individual patient doses, as this metric includes population‐based radiation epidemiological data which may not be applicable to a specific individual. Therefore, the ICRU efforts towards radiation dosimetry of the individual patient focus on dosimetric units which are physical in nature, and describe the individual organ doses and the overall average dose to the patient, depending upon the specific CT examination and the patient's physical characteristics.Educational Objectives:1. Convey some of the issues in accurate dose assessment in CT.2. Describe some of the ongoing efforts of the ICRU committee on CT towards dose assessment.
TU‐C‐AUD‐08: A Web‐Based and Database‐Centric Radiotherapy Treatment Plan Review and Reporting System
Authors: Khullar D , Mullen D , Deasy J 
Published: July 2007

Purpose: The typical current treatment plan approval process is to assemble the planner and the reviewing physician at the planning workstation and review the plan using the planning software system. We are developing a new web‐based and database‐centric tool to address these problems, called WEBTREV (Web‐based TReatment EValuation). Method: WEBTREV utilizes several development tools, including the object oriented web development platform Ruby‐on‐Rails (ROR), the open‐source database MySQL, and CERR, the Matlab‐based open‐source treatment planning research system. CERR is used to extract DICOM‐RT data from planning systems and to generate customized views and reports. The corresponding extracted plan images and plan evaluation parameters are stored in the MySQL database. Ruby‐on‐Rails dynamically defines views and serves data over web pages via the Apache web‐server system.Results: The resulting workflow is: A dosimetrist uses a secure login via ROR at the planning system to push DICOM to a receiver where CERR is used to generate static images of overlaid scans, doses, and structures. As soon as this process is complete, ROR sends an e‐mail to the dosimetrist to confirm the upload. Once confirmed, a physician can log into a personal database work queue and select the patient to review. The dynamic webpage contains standard views of slices and structures, as well as dose‐volume‐histogram data and customized reports giving plan metric values (e.g., D95 and minimum dose to target volumes). Approval or a request for further modifications is transmitted back to the dosimetrist, who may view comments linked to graphics. Conclusions: WEBTREV provides a promising platform for reviewing treatment planning data remotely. This framework provides a tool for generating consistent representations and reports of dose characteristics, images, and structure data, as well as plan evaluation parameters, across different planning systems.
TU‐D‐L100F‐02: PET Biomarkers in Radiation Oncology
Authors: Pugachev A 
Published: July 2007

Recently, the role of PET and PET/CT imaging in oncology has grown dramatically. The following characteristics of PET make it an ideal imaging modality for providing functional information that can be incorporated into radiation treatment planning:1. Ability to image nanomolar tracer concentrations.2. Excellent tissue penetration.3. Ability to use tracers analogous from the chemical point of view to their naturally‐occurring counterparts.However, while general paradigm of biologically‐conformal radiation therapy has been proposed long time ago, we are still far from its implementation in routine clinical radiation treatment planning. Even in the case of such a well established tracer as 18FDG, we are still not certain of how to incorporate the information content of an FDG PET image into radiation treatment plan. While multiple approaches to FDG PET image segmentation designed to allow for tumor delineation have been proposed, all of them are failing to take into account the following factors:1. Complexity of the tumor boundary (even assuming that the boundary does exist).2. Highly heterogeneous morphology of the lesion.3. Variability of intratumoral FDG uptake even in homogeneous animal tumor models.We believe that in order to facilitate further incorporation of PET imaging in radiation treatment planning, the following developments have to take place:1. Implementation of higher standards of tracer validation. It is not sufficient to show that a tracer designed to image a certain function, like cell division, or an environmental parameter, like hypoxia, is characterized by high tumor uptake. Instead, it is necessary to demonstrate and in‐vivo that the tracer is in fact binding to the desired target. This can be done by performing carefully designed validation studies utilizing animal tumor models and patient tumor tissue specimens.2. Discrete approaches to PET image segmentation (tumor vs. normal tissue, hypoxia vs. normoxia) have to be dropped in favor of probabilistic approaches. For example, gradual change of FDG uptake from low level in normal tissue to high level in the lesion has to be interpreted as a gradual change in probability of finding a tumor cell, rather than used to randomly assign location of a step‐like target boundary.The overall goal of this presentation is to provide a short overview of the role of PET in radiation therapy treatment planning and to outline some of the research directions that should allow for the development of PET‐based biologically‐conformal radiation therapy.
TU‐D‐L100F‐03: Quantification of PET and SPECT Biomarkers
Authors: Saffer J 
Published: July 2007

The metabolic information provided by PET and SPECT has great potential for diagnosing and staging disease, customizing treatment doses for a particular patient, and tracking a patients' response to treatment. However, quantifying the information in these images remains challenging. This presentation will review the sources of variability in the data, grouped into three broad categories: patient — related factors (e.g. body habitus, medications); scanner‐related factors (spatial and energy resolution, sensitivity, data acquisition mode (2D or 3D), attenuation and scatter correction method, image reconstruction algorithm, respiratory and cardiac motion‐correction method); and operator‐related factors such as acquisition and reconstruction protocols, instrument and image quality control, instrument calibrations, and method of image analysis. The impact of these variables on quantification will be discussed, along with methods for minimizing those that are controllable.The presentation will conclude with a review of current efforts by government agencies, professional organizations, academic institutions, and sponsors of multicenter trials to grapple with the additional complexities that arise from combining data from multiple patients at multiple sites. Particular emphasis will be placed on the author's experience as a member of the PET Quality Assurance Committee at the American College of Radiology Imaging Network (ACRIN) PET Core Lab, which has credentialed more than 100 PET scanners for participation in quantitative PET multicenter trials.Research partially supported by ACRIN. ACRIN is sponsored by the National Cancer Institute and receives additional support from industry partners, other governmental agencies and the ACRIN Fund for Imaging Innovation.NOTE: ACRIN is sponsored by the National Cancer Institute and receives additional support from industry partners, other governmental agencies and the ACRIN Fund for Imaging Innovation.Educational Objectives:1. Understand the factors that affect the variability and accuracy of PET and SPECT biomarker quantification, with particular emphasis on scanner‐related parameters.2. Understand the importance of minimizing variability in order to enhance the ability to distinguish signal from noise.3. Understand the efforts currently underway to standardize acquisition and processing protocols and to monitor equipment performance through credentialing and periodic quality control checks.