List-Mode Maximum Likelihood Reconstruction of Compton Scatter Camera Images in Nuclear Medicine

A Maximum Likelihood (ML) image reconstruction technique using list-mode data has been applied to Compton scattering camera imaging. List-mode methods are appealing in Compton camera image reconstruction because the total number of data elements in the list (the number of detected photons) is significantly smaller than the number of possible combinations of position and energy measurements, leading to a much smaller problem than that faced by traditional iterative reconstruction techniques. For a realistic size device, the number of possible detector bins can be as large as 10 billion per pixel of the image space, while the number of counted photons would typically be a very small fraction of that. The primary difficulty in applying the list-mode technique is in determining the parameters which describe the response of the imaging system. In this work, a simple method for determining the required system matrix coefficients is employed, in which a back-projection is performed in list-mode, and response coefficients determined for only tallied pixels. Projection data has been generated for a representative Compton camera system by Monte Carlo simulation for disk sources with hot and cold spots and energies of 141, 364, and 511 keV, and reconstructions performed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85815/1/Fessler155.pd

Improved Modeling of System Response in List Mode EM Reconstruction of Compton Scatter Camera Images

An improved List Mode EM method for reconstructing Compton scattering camera images has been developed. First, an approximate method for computation of the spatial variation in the detector sensitivity has been derived and validated by Monte Carlo computation. A technique for estimating the relative weight of system matrix coefficients for each gamma in the list has also been employed, as has a method for determining the relative probabilities of emission having some from pixels tallied in each list-mode back-projection. Finally, a technique has been developed for modeling the effects of Doppler broadening and finite detector energy resolution on the relative weights for pixels neighbor to those intersected by the back-projection, based on values for the FWHM of the spread in the cone angle computed by Monte Carlo. Memory issues typically associated with list mode reconstruction are circumvented by storing only a list of the pixels intersected by the back-projections, and computing the weights of the neighboring pixels at each iteration step. Simulated projection data has been generated for a representative Compton camera system (CSPRINT) for several source distributions and reconstructions performed. Reconstructions have also been performed for experimental data for distributed sources.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86027/1/Fessler157.pd

List Mode EM Reconstruction of Compton Scatter Camera Images in 3-D

A method has been developed for List Mode EM reconstruction of Compton scattering camera images in 3D, using a previously reported 2-D technique and refining and adapting it to three dimensions. Spatial variation in the system sensitivity is determined by an approximate numerical integration which accounts for solid angle effects, absorption and escape probabilities, and variation in the differential angular scattering cross section. The method for computing the system transition probabilities uses a similar method to determine values in pixels along exact back-projected cones for each detected event, and uses pre-computed values of the inherent system resolution (which includes the effects of spatial and energy measurement resolution and Doppler broadening) to model the response in pixels neighboring the back-projected cone. The algorithm has been parallelized, permitting reconstruction of images using larger number of detected events in relatively constant time by adding additional processors. Results are presented using 3-D simulated data.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85814/1/Fessler162.pd

A vectorized Monte Carlo detector simulation program for electromagnetic interactions

MC4 is a detector simulation program combining a vectorized ray-tracing algorithm with a vectorized version of the electromagnetic interaction routines from GEANT3. The implementation of ray tracing is able to represent moderately complex geometries such as single calorimeter modules or test-beam situations. Results from MC4 are compared with EGS4 simulations and with experimental results. Timing results are given for scalar machines and on a vector supercomputer. Production applications and applications to future versions of the GEANT code are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27643/1/0000019.pd

Biological-Effect Modeling of Radioimmunotherapy for Non-Hodgkins Lymphoma: Determination of Model Parameters

Treatment with Tositumomab and 131I tositumomab anti-CD20 radioimmunotherapy (Bexxar) yields a nonradioactive antibody antitumor response (the so-called cold effect) and a radiation response. Numerical parameter determination by least-squares (LS) fitting was implemented for more accurate parameter estimates in equivalent biological-effect calculations. Methods: One hundred thirty-two tumors in 37 patients were followed using five or six SPECT/CT studies per patient, three each (typical) post-tracer (0.2 GBq) and post-therapy (?3 GBq) injections. The SPECT/CT data were used to calculate position- and time-dependent dose rates and antibody concentrations for each tumor. CT-defined tumor volumes were used to track tumor volume changes. Combined biological-effect and cell-clearance models were fit to tumor volume changes. Optimized parameter values determined using LS fitting were compared to previous fitted values that were determined by matching calculated to measured tumor volume changes using visual assessment. Absorbed dose sensitivity (α) and cold-effect sensitivity (?p) parameters were the primary fitted parameters, yielding equivalent biological-effect (E) values. Results: Individual parameter uncertainties were approximately 10% and 30% for α and ?p, respectively. LS versus previously fit parameter values were highly correlated, although the averaged α value decreased and the averaged ?p value increased for the LS fits compared to the previous fits. Correlation of E with 2-month tumor shrinkage data was similar for the two fitting techniques. The LS fitting yielded improved fit quality and likely improved parameter estimation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140326/1/cbr.2012.1467.pd

Microfocus X-ray sources for 3D microtomography

An analytic model for the performance of cone beam microtomography is described. The maximum power of a microfocus X-ray source is assumed to be approximately proportional to the focal spot size. Radiation flux penetrating the specimen is predicted by a semi-empirical relation which is valid for X-ray energies less than 20 keV. Good signal to noise ratio is predicted for bone specimens of 0.1 to 10 mm when scanned at the optimal energy. A flux of about 1 x 1010 photons/mm2/s is identified for 0.2 mm specimens. Cone beam volumetric microtomography is found to compare favorably with synchrotron based methods.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31116/1/0000012.pd

Evaluation of dual energy quantitative CT for determining the spatial distributions of red marrow and bone for dosimetry in internal emitter radiation therapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135113/1/mp0378.pd

Comparison of I-131 Radioimmunotherapy Tumor Dosimetry: Unit Density Sphere Model Versus Patient-Specific Monte Carlo Calculations

High computational requirements restrict the use of Monte Carlo algorithms for dose estimation in a clinical setting, despite the fact that they are considered more accurate than traditional methods. The goal of this study was to compare mean tumor absorbed dose estimates using the unit density sphere model incorporated in OLINDA with previously reported dose estimates from Monte Carlo simulations using the dose planning method (DPMMC) particle transport algorithm. The dataset (57 tumors, 19 lymphoma patients who underwent SPECT/CT imaging during I-131 radioimmunotherapy) included tumors of varying size, shape, and contrast. OLINDA calculations were first carried out using the baseline tumor volume and residence time from SPECT/CT imaging during 6 days post-tracer and 8 days post-therapy. Next, the OLINDA calculation was split over multiple time periods and summed to get the total dose, which accounted for the changes in tumor size. Results from the second calculation were compared with results determined by coupling SPECT/CT images with DPM Monte Carlo algorithms. Results from the OLINDA calculation accounting for changes in tumor size were almost always higher (median 22%, range -1%-68%) than the results from OLINDA using the baseline tumor volume because of tumor shrinkage. There was good agreement (median -5%, range -13%-2%) between the OLINDA results and the self-dose component from Monte Carlo calculations, indicating that tumor shape effects are a minor source of error when using the sphere model. However, because the sphere model ignores cross-irradiation, the OLINDA calculation significantly underestimated (median 14%, range 2%-31%) the total tumor absorbed dose compared with Monte Carlo. These results show that when the quantity of interest is the mean tumor absorbed dose, the unit density sphere model is a practical alternative to Monte Carlo for some applications. For applications requiring higher accuracy, computer-intensive Monte Carlo calculation is needed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90433/1/cbr-2E2011-2E0965.pd

Single-scatter Monte Carlo compared to condensed history results for low energy electrons

A Monte Carlo code has been developed to simulate individual electron interactions. The code has been instrumental in determining the range of validity for the widely used condensed history method. This task was accomplished by isolating and testing the condensed history assumptions. The results show that the condensed history method fails for low energy electron transport due to inaccuracies in energy loss and spatial positioning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29795/1/0000141.pd

Benchmarking of the Dose Planning Method (DPM) Monte Carlo code using electron beams from a racetrack microtron

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135135/1/mp1512.pd