Discoveries in cancer research are impacting patients through development of new therapeutics and better diagnostic tools. However, there is still a lack of understanding about heterogeneity in patient response to these therapeutics, optimizing therapeutic dosing schedules, or predicting complex metastatic patterns due to the complexity of the disease. Heterogeneity of patient response to treatment stems from the intricate interactions with the microenvironment, and distant organs and other environmental pressures including low oxygen, high acidity, and toxic drugs. To deconvolute some of this complexity physical scientists are using intricate tools to improve cancer diagnosis and predict drug resistance. Also to predict tumor growth and response to therapeutics, computational scientists are developing mathematical tools that link physical sciences or evolutionary sciences approaches with experimental and clinical data. These models yield predictions based on initial parameters obtained from patient clinical data, such as noninvasive imaging. This session will highlight the utilization of these mathematical and physical tools to predict patient response to treatment options, predict the optimal drug dosing schedule, and improve cancer diagnosis. This approach could be further enhanced by developing tools and models to chart the progress of stressed, aging tissue towards the progression to uncontrolled cell growth and mutational meltdown even before the diagnosis. Learning Objectives: 1. To learn about treatment response heterogeneity 2. To learn about tumor evolutionary capabilities 3. To learn about mathematical tools that link physical sciences with experimental and clinical data

Measurements of the neutron activation constants Q 0 and k 0 for the 27 Al( n , γ ) 28 Al reaction have been performed in two irradiation channels with different spectral characteristics at the JSI TRIGA Mark II reactor. In the determination of Q 0 the fission spectrum contribution to the reaction rates has been corrected for. The final experimental value of the Q 0 factor was found to differ significantly from the adopted value in the k 0 -database. The experimental value of the k 0 factor is in agreement with the recommended value in the k 0 -database. The thermal cross-section and resonance integral for the reaction were found to be in good agreement with the values calculated from the cross-sections from the ENDF/B-VII.1 library.

The definition of tumor hypoxia is multifaceted, ranging from a simple physiological absence of molecular oxygen in tumor cells to a major factor associated with aggressive tumor phenotype; therefore, imaging of tumor hypoxia is equally poorly defined. Several compounds have been synthesized for PET hypoxia imaging studies: 18F‐fluoromisonidazole (FMISO), Cu‐diacetyl‐bis(N4‐methylthiosemicarbazone) (Cu‐ATSM), 2‐nitroimidazoles based markers such as 2‐(2‐nitroimidazol‐1[H]‐yl)‐N‐(3‐[F‐18]fluoropropyl) acetamide (EF1) and [2‐(2‐nitroimidazol‐1‐yl)‐N‐(3,3,3‐trifluoropropyl)‐acetamide], [2‐(2‐nitro‐1[H]‐imidazol‐1‐yl)‐N‐(2,2,3,3,3‐penta‐fluoropropyl)‐acetamide] (EF5), and most recently 1‐(5‐fluoro‐5‐deoxy‐alpha‐D‐arabinofuranosyl)‐2‐nitroimidazole (FAZA). All these compounds diffuse into normally oxygenated and hypoxic cells but are retained in substantially higher concentrations in hypoxic issues. Clinically most commonly used PET hypoxia tracers are FMISO and Cu‐ATSM. In this lecture, different PET hypoxia tracers will be reviewed, focusing on differences in their uptake mechanisms, which lead to differences in their clinical appearance. In addition, the most important clinical trials utilizing PET hypoxia imaging will be reviewed.Learning objectives:1. To learn about clinical PET imaging of hypoxia2. To learn about differences between various PET hypoxia tracers3. To learn about clinical trials utilizing PET hypoxia imaging

This 1‐hour symposium will be aimed at introducing new (or junior) AAPM members engaged in research to NIH funding. Recently there have been new changes to the grant submission process. and new initiatives to enhance research using “Multiple‐PI” models. We plan to have two segments. The first segment would be to present some of the tools available within the NIH website and how to navigate through it; present briefly the new changes to the submission process and focus on the new scoring system and the new review criteria that would be essential to submitting a successful grant. The second segment will cover aspects on how to set‐up a clinical research program. This would include practical advice for those researchers who are not at the “NIH submission” level yet as well as the many medical physicists that do not have protected research time but are still eager to do clinically relevant research that sometimes could lead to NIH funding. The symposium will be followed with a 10–15 min interactive Q&A session with the audience.Learning objectives:1. Navigate the NIH website and learn about the new tools2. New changes to the NIH scoring system3. New NIH review criteria4. Practical advice for those researchers who are not at the “NIH submission” level yet.

Medical PhysicsVolume 37, Issue 6Part6 p. 3352-3352 Fifty-second annual meeting of the american association of physicists in medicine MO-EE-A4-05: Reproducibility of DCE-CT Kinetic Analysis M La Fontaine, M La Fontaine University of Wisconsin, Madison, Madison, WISearch for more papers by this authorM Deveau, M Deveau University of Wisconsin, Madison, WISearch for more papers by this authorL Forrest, L Forrest University of Wisconsin, Madison, Madison, WISearch for more papers by this authorR Jeraj, R Jeraj University of Wisconsin, Madison, WISearch for more papers by this author M La Fontaine, M La Fontaine University of Wisconsin, Madison, Madison, WISearch for more papers by this authorM Deveau, M Deveau University of Wisconsin, Madison, WISearch for more papers by this authorL Forrest, L Forrest University of Wisconsin, Madison, Madison, WISearch for more papers by this authorR Jeraj, R Jeraj University of Wisconsin, Madison, WISearch for more papers by this author First published: 02 June 2010 https://doi.org/10.1118/1.3469101About ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract Purpose: Reproducibility of dynamic contrast enhanced (DCE) CT kinetic analysis is sensitive to both the inherent uncertainties associated with data acquisition and the applied model. This study aims to ascertain the DCE-CT reproducibility of canine sinonasal tumors using three different kinetic models: a commercial deconvolution software and in-house deconvolution and distributed parameter models. Methods and Materials: Anesthetized canine patients with sinonasal tumors were immobilized and underwent two DCE-CT scans approximately two days apart. Gross tumor volumes (GTV) were contoured by a veterinary oncologist and evaluated for each scan. Blood flow (BF), blood volume ratio (BVR), mean transit time (MTT), and permeability were generated using two in-house MATLAB deconvolution-based kinetic models and the commercially available GE Advantage Perfusion 4.0 software. Paired t-tests using the Bonferroni correction (α = 0.025) were applied to assess the mean differences of the slices of a tumor GTV. Results: Between the two reproducibility scans, BF had an average variation of 90% among the three models, which was significantly different (p<0.02). MTT and BVR had an average variation of 30%, where the former was significantly different using commercial software (p<0.01), while the latter was significantly different using in-house models (p<0.01). Permeability had an average variation of 10%, which was not significantly different for any of the kinetic models. Conclusions: None of the four perfusion parameters were found to be consistently reproducible among the applied kinetic models. The uncertainties may be linked to errors in patient setup and post-anesthetized scan time, which are associations of data acquisition rather than kinetic analysis. Further investigation is required to determine the extent to which these uncertainties may limit the reproducibility of DCE-CT kinetic analysis. Volume37, Issue6Part6June 2010Pages 3352-3352 RelatedInformation

Purpose: Accurate quantification is paramount when using PET imaging to gauge response to treatments or optimize biologically prescribed doses. This study examines the quantitative accuracy of PET protocols by analyzing external reference sources scanned concurrently with patients in dynamic and whole body scans. Method and Materials: Canine and human patients were scanned using dynamic or whole body protocols on a GE Discovery LS PET/CT. In each scan a 50 ml reference vial containing a known amount of radioactive or was placed on the couch edge, in the scanner's field of view. Reference activity concentrations ranged from 20–300 kBq/ml. Dynamic scans consisted of 10, 30, 60, and 600 second frames while whole body scans used 8–10 minute bed positions. CT images were used to define two regions of interest for each reference source: (1) an inner cylindrical contour (ROIinner) of 6–8 mm for activity concentration and, (2) a contour with a 5 mm margin surrounding the source (ROItotal) for total activity. Results: A systematic bias was observed in both reference activity concentration and total reference activity for whole body and dynamic scanning protocols. ROItotal provided total activity measurements an average of 8 ± 3% lower than dose calibrator measurements in whole body scans. Dynamic scans imaged total reference activity approximately 4% lower for hotter sources in dynamic scans. Both contours showed reproducibility to within 2% when repeating scans with the same reference. Over the course of six months references held a standard deviation of 3%. Conclusion: This study provided a quantitative assessment of our clinical scanning protocols and provided error estimates for the uptake in clinical patients based on reference sources. A bias was discovered prompting further cross‐calibration with the dose calibrator. Further error reduction and quantification study using longer lived nuclides will continue to be clinically investigated.

It has been shown that supercriticality might occur for some postulated accident conditions at the TRIGA spent-fuel pool. However, the effect of burnup was not accounted for in previous studies. In this work, the combined effect of fuel burnup, pitch among fuel elements, and number of uniformly mixed absorber rods for a square arrangement on the spent-fuel pool k(eff) is investigated.The Monte Carlo computer code MCNP4B with the ENDF-B/VI library and detailed three dimensional geometry was used. The WIMS-D code was used to model the isotopic composition of the standard TRIGA and FLIP fuel for 5, 10, 20 and 30% burnup level and 2- and 4-yr cooling time.The results show that out of the three studied effects, pitch from contact (3.75 cm) up to rack design pitch (8 cm), number of absorbers from zero to eight, and burnup up to 30%, the pitch has the greatest influence on the multiplication factor keff. In the interval in which the pitch was changed, keff decreased for up to similar to0.4 for standard and similar to0.3 for FLIP fuel. The number of absorber rods affects the multiplication factor much less. This effect is bigger for more compact arrangements, e.g., for contact of standard fuel elements with eight absorber rods among them, keff values are smaller for similar to0.2 (similar to0.1 for FLIP) than for arrangements without absorber rods almost regardless of the burnup. The effect of burnup is the smallest. For standard fuel elements, it is similar to0.1 for almost all pitches and numbers of absorbers. For FLIP fuel, it is smaller for a factor of 3, but increases with the burnup for compact arrangements. Cooling time of fuel has just a minor effect on the keff of spent-fuel pool and can be neglected in spent-fuel pool design.

A criticality benchmark experiment performed at the Jozef Stefan Institute TRIGA Mark II research reactor is described. This experiment and its evaluation are given as examples of benchmark experiments at research reactors. For this reason the differences and possible problems compared to other benchmark experiments are particularly emphasized. General guidelines for performing criticality benchmarks in research reactors are given. The criticality benchmark experiment was performed in a normal operating reactor core using commercially available fresh 20% enriched fuel elements containing 12 wt% uranium in uranium-zirconium hydride fuel material. Experimental conditions to minimize experimental errors and to enhance computer modeling accuracy are described. Uncertainties in multiplication factor due to fuel composition and geometry data are analyzed by sensitivity analysis. The simplifications in the benchmark model compared to the actual geometry are evaluated. Sample benchmark calculations with the MCNP and KENO Monte Carlo codes are given.

Use of Monte Carlo methods in burnup calculations of nuclear fuel has become practical due to increased speed of computers. Monteburns is an automated computational tool that links the Monte Carlo code MCNP with the burnup and decay code ORIGEN2.1. This code system was used to simulate a criticality benchmark experiment with burned fuel on a TRIGA Mark II research reactor. Two core configurations were simulated and keff values calculated. The comparison between the calculated and experimental values shows good agreement, which indicates that the MCNP/Monteburns/ORIGEN2.1 system gives reliable results for neutronic simulations of TRIGA reactors.

Transport calculations can often provide useful information about irradiation field characteristics in addition to the measurements. For this reason Monte Carlo simulations were used to characterise irradiation facilities in the TRIGA Mark II (Ljubljana, Slovenia) reactor core. Several locations in two different core configurations were investigated. Some of the Monte Carlo results were also compared to the measurements. It was found out that the flux as well as its spectral characteristics depend very much on the position of the irradiation channel in the core and can vary significantly between different core configurations. The highest flux is achieved in the central channel of the core, and then decreases to about 10% in the rotary groove. The fast-to-thermal neutron flux ratio also varies significantly and achieves values of about 1.4 in the central channel but only 0.2 in the rotary groove. The core configuration can introduce up to 40% change in the fast-to-thermal neutron ratio, which enables optimisation of the core configuration for different irradiation channels and different irradiation goals. Comparison to the measurements showed that our Monte Carlo model can successfully predict absolute values of the flux as well as its spectral characteristics to within a few percent.

The analysis of the importance of different calculation models for fuel element burnup accuracy is presented in this paper. In-house developed computer code TRIGLAV was used in calculations. The calculation parameters variations included: two different unit-cell transport calculation codes (WIMS-D/4 and WIMS-D/5), two cross section libraries, two homogenisation methods (FVH and EDH), and two reactor reflector unit-cell models. The results of neutron flux distribution calculations, core and fuel element's burnup calculations, and fuel element reactivity worth calculations are presented and compared to experiments.

MCNP is widely used Monte Carlo program in reactor and nuclear physics. However, an option of simulating electrons was added into the code a few years ago. With this extension MCNP became a code, potentially applicable for applications in medical physics. In 1997, a new version of the code, named MCNP4B was released, which contains several improvements in electron transport modelling. To test suitability of the code, several important issues were considered and examined. Default sampling in MCNP electron transport was found to be inappropriate, because it gives wrong depth dose curves for electron energies of interest in radiotherapy (MeV range). The problem can be solved if ITS-style energy sampling is used instead. One of the most difficult problems in electron transport is simulation of electron backscattering, which MCNP predicts well for all, low and high Z materials. One of the potential drawbacks, if somebody wanted to use MCNP for dosimetry on real patient geometries is that MCNP lattice calculation (e.g. when calculating dose distributions) becomes very slow for large number of scoring voxels. However, if just one scoring voxel is used, the number of geometry voxels only slightly affects the speed. In the study it was found that MCNP could be reliably used for many applications in medical physics. However, the established limitations should be taken into account when MCNP is used for a particular application.

A Monte Carlo computer code MCNP4A simulation of the TRIGA Mark II benchmark experiment performed in 1992 is presented. It may be noted that this benchmark experiment is one of very few high-enrichment benchmarks available. To minimize errors due to an inexact geometry model, the TRIGA Mark II reactor core was very thoroughly modeled. All fresh fuel and control elements as well as the vicinity of the core were precisely described. MCNP4A input was prepared in such a way that any desired core configuration could be simulated easily. Continuous energy cross-section data from ENDF / B-VI and ENDF / B-V(for nat Cr, natFe, and natNi) libraries and S(α, β) scattering functions from the ENDF / B-IV library were used in our calculations. The differences between ENDF / B-VI and ENDF / B-V evaluations were examined on critical experiments. Most of the steady-state operation experiments were simulated, including two critical experiments, namely, measurements of the excess reactivity of the core, and the determination of control rod worths and fuel element reactivity worth distribution. Excellent agreement with the experimental results was observed.

The Monte Carlo simulation of DIMPLE SO1A and TRIGA Mark II benchmark experiment with MCNP4A code is presented. Nuclear data from ENDF/B-V and ENDF/B-VI libraries were used. The results of the criticality as well as several spectral indices calculation with ENDF/B-VI data library, confirm the MCNP4A full core model of a DIMPLE reactor as a good benchmark for testing basic evaluated data files. The complete 3D MCNP model of the TRIGA Mark II reactor enables precise calculations of broad range of quantities of interest in a steady-state mode cf operation. Excellent agreement of core criticality, excess reactivity and control rod worths to experimental values was observed.

The complete 3D MCNP model of the TRIGA Mark II reactor is presented. It enables precise calculations of some quantities of interest in a steady-state mode of operation. Calculational results are compared to the experimental results gathered during reactor reconstruction in 1992. Since the operating conditions were well defined at that time, the experimental results can be used as a benchmark. It may be noted that this benchmark is one of very few high enrichment benchmarks available. In our simulations experimental conditions were thoroughly simulated: fuel elements and control rods were precisely modeled as well as entire core configuration and the vicinity of the core. ENDF/B-VI and ENDF/B-V libraries were used. Partial results of benchmark calculations are presented. Excellent agreement of core criticality, excess reactivity and control rod worths can be observed.

The TRIGA research reactor at Jozef Stefan Institute is used for irradiation of various samples. The Monte Carlo code for transport of neutrons and photons, MCNP, was used to calculate dose rates in irradiation channels in the operating TRIGA research reactor. Several measurements of dose rates in individual irradiation channels were performed with CaF2 and LiF TLDs. The calculated dose rates significantly differ from the measured ones especially for the neutron dose rate. The second experimental method used was tooth enamel dosimetry. Results indicate that human teeth are suitable for radiation dose assessment in mixed neutron/gamma radiation fields with dose rates of several Gy per second.