1. Li HAN and Neal H. Clinthorne University of Michigan, Ann Arbor, MI, USA Performance comparison and system modeling of a Compton medical imaging system and a collimated Anger camera Contact: Li HAN (lhan@umich.edu)lhan@umich.edu I. Motivation Radionuclide cancer therapy requires imaging radiotracers that concentrate in tumors and emit high energy charged particles that kill the tumor cells. These tracers such as I-131 generally emit high energy gamma photons that need to be imaged to estimate tumor dose and size during treatment. The conventional Anger Camera with high energy general purpose lead collimator has poor spatial resolution and poor detection efficiency for higher energy photons due to septal penetration and scattering. Compton imaging systems have the potential to obtain improved imaging performance for higher energy photons. Decouple the tradeoff between sensitivity and resolution. Improve spatial resolution due to the reduced influence of Doppler broadening. II. Methods and Algorithms Assuming conditionally Poisson statistics the Fisher Information Matrix is given as: A is the binned-mode system response matrix, Λ is the mean total number of events in the measurement interval, Y =[Y 1, …,Y D ] is a vector of the projection measurements, θ =[θ 1, …, θ P ] T is the parameterized image space vector A. Fisher Information Matrix B. Modified Uniform Cramer-Rao Bound f is the desired mean gradient vector, i.e. the target local impulse response or PSF; g is the actual mean gradient vector or the PSF actually achieved; δ is an allowable tolerance of the difference between f and g ; F is the Fisher information Matrix; I is the identity matrix with same size of F; λ is a positive scalar which parametrically controls both the variance and the tolerance. C. Monte Carlo Integration of Fisher Information From the definition of observed Fisher Information, the value of each entry is The Monte Carlo calculation for an element of the Fisher Information Matrix is Λ is a desired mean number of detected events, N is the fixed number of sampled events for Monte Carlo integration is the probability an event from source bin i leads to a measurement Y l M is the total number of source bins f n is the number of photons emitted from source bin n, the intensity in the nth source bin D. M-UCRB Computed by FFT If one assumes shift-invariance, the FIM F and [F+λI] are circulant-block-circulant (CBC) matrices. Their inversion can be efficiently computed by FFT Q is DFT matrix, and Q* is IDFT matrix are element-wise division and multiplication II. System Modeling A. Studied Systems PSF at 10cm Probability of photon transmission Probability of Compton process with Doppler broadening at given deposited energy and scattering angle B. Anger Camera with HEGP C. The Compton Imaging System Profiles are modeled by combining a Gaussian function with an exponential function. Geometry of Compton Camera with two parallel block detectors. Φ1 is the zenith angle of source photon; Φ2 is the zenith angle of scattered photon; θ is the Compton scatter angle; r1=r01+rin; r2=r1out+r12+r2in Use pre-calculated matrix, that is the blurred joint probability density function. IV. Results and Analysis 2D, 26cm diameter disk at 10cm Modified Uniform Cramer-Rao bound curves and MUCRB Ratio center pixel for the proposed Compton Camera (red), Gaussian Exponential modeled Anger Camera with HEGP (blue) (FWHM 12.2mm), and Gaussian modeled Anger Camera with HEGP(black)(FWHM 12.6mm). The abscissa is the FWHM of Target PSF from 5mm to 20mm and ordinate is variance for equal number of acquired events. Sensitivity curve for Collimated Anger Camera Sensitivity map for Compton Imaging System 10cm from source to the first detector is Sensitivity map is 20x20cm Compton Camera Collimated Anger Camera Same number of events 200 thousand events Same imaging time 3 million events 100 iterations MLEM Collimated Anger Camera