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The ROI method applied to Ga-68 EDTA PET dynamic study data for the quantitative determination of brain tumor BBB permeability assumes that the tumor is homogeneous in terms of Ga-68 EDTA kinetics, even though it is known that brain tumors are highly heterogeneous in structure. The relatively high image noise of Ga-68 PET studies have prevented the examination of Ga-68 EDTA kinetics by nonlinear regression on a single pixel basis. In this study, we have developed an efficient and effective method to separate brain tumor tissue into sub-regions with different Ga-68 EDTA kinetics on a pixel-by-pixel basis. Computer simulation and ten Ga-68 EDTA PET patient studies were used to evaluate the performance of the new method. During a PET dynamic study (total 64 min), 20-25 arterial samples were taken for the input function. Whole-tumor ROIs were defined on T1-weighted MRI images and then copied to the registered PET dynamic images to measure whole-tumor time activity curves. The method uses a two-compartment model to extract three component factors (vascular component, fast and slow component factors) from whole-tumor kinetics by model fitting. The kinetics in each pixel were expressed as a linear combination of the three factors. The three coefficients in the expression can be estimated by the linear least-square method and produce three factor images corresponding, respectively, to the permeability of the fast and the slow component factors and the plasma volume. Whole-tumor regions were separated into two regions-one with mainly fast kinetics that was evident in the fast factor images and one with slow kinetics that was evident in slow factor images. The two regions have markedly different uptake (0.036/spl plusmn/0.015 ml/min/g and 0.009/spl plusmn/0.006 ml/min/g for fast and slow kinetic sub-regions, respectively) and clearance rates (0.22/spl plusmn/0.15 /min and 0.023/spl plusmn/0.021 /min for fast and slow sub-regions, respectively). The overlap of the two resulting sub-regions is small (3.5/spl plusmn/1.7% of the two regions). Computer simulation and patient studies show that the method is robust for a wide range of noise levels. This method has combined the advantages of statistical factor analysis and the modeling approach.

The use of positron emission tomography (PET) in quantitative fluorodeoxyglucose (FDG) studies of aging and dementia has been limited by partial volume effects. A general method for correction of partial volume effects (PVE) in PET involves the following common procedures: segmentation of MRI brain images into gray matter (GM), white matter (WM), cerebral spinal fluid (CSF), and muscle (MS) components: MRI PET registration; and generation of simulated PET images. Afterward, two different approaches can be taken. The first approach derives first a pixel-by-pixel correction map as the ratio of the measured image to the simulated image [with realistic full-width at half-maximum (FWHM)]. The correction map was applied to the MRI segmentation image. Regions of interest (ROI's) can then be applied to give results free of partial volume effects. The second approach uses the ROI values of the simulated "pure" image (with negligible FWHM) and those of the simulated and the measured PET images to correct for the PVE effect. By varying the ratio of radiotracer concentrations for different tissue components, the in-plane FWHM's of a three-dimensional point spread function, and the ROI size, the authors evaluated the performance of these two approaches in terms of their accuracy and sensitivity to different simulation configurations. The results showed that both approaches are more robust than the approach developed by Muller-Gartner et al. (1992), and the second approach is more accurate and more robust than the first. In conclusion, the authors recommend that the second approach should be used on FDG PET images to correct for partial volume effects and to determine whether an apparent change in GM radiotracer concentration is truly due to metabolic changes.

We propose to develop a high resolution positron emission tomography (PET) detector designed for animal imaging. The detector consists of a 2-D array of small bismuth germanate (BGO) crystals coupled via optical fibers to a multi-channel photomultiplier tube (MC-PMT). Though this approach offers several advantages over the conventional BGO block design, it does require that a sufficient number of scintillation photons be transported from the crystal, down the fiber and into the PMT. In this study we use simulations and experimental data to determine how to maximize the signal reaching the PMT. This involves investigating factors such as crystal geometry, crystal surface treatment, the use of reflectors, choice of optical fiber, coupling of crystal to the optical fiber and optical fiber properties. Our results indicate that using 2/spl times/2/spl times/10 mm BGO crystals coupled to 30 cm of clad optical fiber, roughly 50 photoelectrons are produced at the PMT photocathode for a 511 keV interaction. This is sufficient to clearly visualize the photopeak and provide adequate timing resolution for PET. Based on these encouraging results, a prototype detector will now be constructed. >

A technique that can register anatomic/structural brain images (e.g., MRI) with various functional images (e.g., PET-FDG and PET-FDOPA) of the same subject has been developed. The procedure of this technique includes the following steps: (1) segmentation of MRI brain images into gray matter (GM), white matter (WM), cerebral spinal fluid (CSF), and, muscle (MS) components, (2) assignment of appropriate radio-tracer concentrations to various components depending on the kind of functional image that is being registered, (3) generation of simulated functional images to have a spatial resolution that is comparable to that of the measured ones, (4) alignment of the measured functional images to the simulated ones that are based on MRI images. A self-organization clustering method is used to segment the MRI images. The image alignment is based on the criterion of least squares of the pixel-by-pixel differences between the two sets of images that are being matched and on the Powell's algorithm for minimization. The technique was applied successfully for registering the MRI, PET-FDG, and PET-FDOPA images. This technique offers a general solution to the registration of structural images to functional images and to the registration of different functional images of markedly different distributions. >

The evaluation of a multiplane tomograph designed for brain imaging requires particular attention to certain design parameters that tend to be comprised in such designs. These parameters include resolution uniformity, axial slice thickness uniformity with emphasis on the interplane slices, scatter fraction, accidentals fraction, and system dead time. In addition, the final performance specifications should be relevant to the manner in which the system will actually be employed in the clinic. These specifications should be measured under realistic scatter and count rate conditions using the same reconstruction techniques that are employed in patient imaging. These parameters were evaluated on the NeuroECAT positron tomograph (1,2) and the effect of choice of manner of presentation and type of measurement condition on the apparent performance of the system is shown. The results indicate that clearly defined conditions are a necessity in evaluating the true performance of a positron tomograph.

A new system (NEUROECAT) has been designed and built for quantitative positron emission computed tomography (PCT) of the brain. It consists of three octagonal arrays of bismuth germanate detectors (BGO) providing 5 simultaneous image planes. The design utilizes unique shielding and detector geometries which optimize uniformity in image and axial resolution and also minimize scatter and accidental coincidence rates. The basic system image resolution is 11.0±.4 mm FWHM with a total system sensitivity of 270,000 counts/sec/microcurie/cc uniformly dispersed in a 20 cm diameter cylinder.

The ECAT III is a whole body positron tomograph which has been designed in a collaborative effort between investigators at UCLA and EGandG/Ortec (Oak Ridge, Tennessee). The primary emphasis in the design has been on the problems of imaging the heart. In our experience with the ECAT II at UCLA, the primary problems in heart imaging were: 1) gated studies of the heart would have serious image artifacts if the scanning period was too short, and 2) the resolution of the system made quantitative measurements difficult, particularly in those cases in which there was significant activity in the blood pool. In this communication, we will briefly describe the ECAT III and then present some of the theoretical and experimental data which influenced the design.