M.E. Phelps

A modeling-based factor extraction method for determining spatial heterogeneity of Ga-68 EDTA kinetics in brain tumors

The ROI method used in a Ga-68 EDTA PET dynamic study for quantitative determination of brain tumor (blood brain barrier) BBB permeability assumes that the tumor is homogeneous in terms of Ga-68 EDTA kinetics, even though it is known to be highly heterogeneous. It is desirable to examine regions of different kinetics separately. In this study, we have developed an efficient and effective method to separate tissue regions of different Ga-68 EDTA kinetics. The method uses a two-compartment model to extract three principal component factors (vascular component, fast and slow components) from whole-tumor kinetics by model fitting, then each pixel kinetics in the tumor was expressed in terms of these factors by least-square regression to provide factor images. The whole tumor was separated into two regions-one with mainly fast kinetics and one with slow kinetics. The two regions have markedly different uptake and clearance rates. This method has combined the advantage of statistical factor analysis and a modeling approach. The PET-to-MRI image registration program was employed in this study for registering Ga-68 EDTA PET images to MRI T1 weighted images.

Performance evaluation of PETbox: A low cost bench top PET scanner dedicated to high throughput preclinical imaging

PETbox is designed to be a low cost and easy to use bench top small animal PET scanner dedicated for high throughput quantitative pharmacokinetic and pharmacodynamic studies. To achieve this goal, the scanner is integrated with a complete animal management system that provides life support including reproducible positioning, temperature control, anesthesia, real-time monitoring of animal respiration and a pathogen barrier. This approach minimizes the overall cost and complexity of preclinical PET imaging and should enable non-imaging scientists to embrace the technology. The system uses two opposing detector heads, each one consisting of a pixilated BGO array coupled to two H8500 multi-channel photomultiplier tubes. The BGO crystals were segmented into 20 ? 44 arrays with a pixel pitch of 2.2 mm and a total active area of 44 mm ? 96.8 mm. Position and timing signals from the photomultiplier tube readout circuitry were connected to a field programmable gate array (FPGA) board with eight ADC channels, each running at 100 MHz. Signal processing algorithms were developed for the FPGA to process received PET events and raw list-mode data were generated by the FPGA board and transferred to a host PC for storage. Basic system performance parameters were measured. The system has an average intrinsic spatial resolution of 1.72 mm FWHM along detector long axis and 1.84 mm FWHM along detector short axis. The coincidence timing resolution was measured to be 4.1 ns FWHM. The average energy resolution of the crystals was 19.8% and the absolute sensitivity of the system was measured to be 3.8% at the center of the gantry. Initial imaging studies were also performed with live mice. A mouse tumor xenograft was imaged 1 hour after a 32uCi [18F]FDG injection for 20 minutes. 3D images were generated using a ML-EM method. Results demonstrate the capability and potential of the PETbox system for dedicated high throughput mouse studies such as biodistribution and organ uptake quantification.

Design and initial performance of PETbox4, a high sensitivity preclinical imaging tomograph

PETBox4, currently under development at the Crump Institute is a new tomograph dedicated to preclinical imaging of mice. This system presents a significant improvement on sensitivity and spatial resolution compared to the first generation PETBox. We report here on its design and initial performance characteristics.

MRI-based elastic-mapping method for inter-subject comparison of brain FDG-PET images

Inter-subject anatomic differences prohibits direct image-wise statistical evaluation of brain FDG-PET images of Alzheimers disease (AD) patients. In this study, the authors propose a MRI-based elastic-mapping method which enables image-wise evaluation. The method involves intra-subject MR-PET registration, 3-D elastic mapping of two set of MR images, and elastically transforming the co-registered PET images. The MR-PET registration used simulated PET images, which were based on segmentation of MR images. In the 3-D elastic mapping stage, first a global linear scaling was applied to compensate for brain size difference, then a deformation field was obtained by minimizing the regional sum of squared difference between the two sets of MR images. Two groups (AD patient and normal control), each with three subjects, were included in the current study. After processing, images from all subjects have similar shapes. Averaging the images across all subjects (either within the individual group or for both groups) give images indistinguishable from original single subject FDG images (i.e. without much spatial resolution loss), except with lower image noise level. The method is expected to allow statistical image-wise analysis to be performed across different subjects.