Michael E. Casey

Bio: Michael E. Casey is an academic researcher from Siemens. The author has contributed to research in topics: Iterative reconstruction & Imaging phantom. The author has an hindex of 46, co-authored 215 publications receiving 9041 citations. Previous affiliations of Michael E. Casey include Max Planck Society & University of Tennessee.

Measuring PET scanner sensitivity: relating countrates to image signal-to-noise ratios using noise equivalents counts

Abstract: True coincidence count (TCC) and noise equivalent count (NEC) curves were measured with a standardized 20-cm-diameter nylon cylinder for five different CTI/Siemens PET (positron emission tomography) scanners with several scanner-collimator combinations: (1) 831/08-12 with 1-mm collimator septa; (2) 933/08-12 and 933/08-16 with 3 to 1-mm tapered collimator septa; and (3) 931/08-12 with 3 to 1-mm tapered and a 1-mm collimator septa and the 931/08-16 with 3 to 1-mm tapered collimator septa In addition, TCC and NEC curves on the 933/08-12 were compared with those from an Alderson brain phantom In general, it is found that the TCC curves indicated peak count rates and activity levels that were as much as 50% higher than the corresponding values from NEC curves The primary factor causing this difference is the noise effect of the randoms component It is demonstrated that, compared to the Alderson brain phantom, the standard 20-cm cylinder is a poor predictor of count rate performance for PET brain imaging >

Fully 3-D PET reconstruction with system matrix derived from point source measurements

Abstract: The quality of images reconstructed by statistical iterative methods depends on an accurate model of the relationship between image space and projection space through the system matrix. The elements of the system matrix for the clinical Hi-Rez scanner were derived by processing the data measured for a point source at different positions in a portion of the field of view. These measured data included axial compression and azimuthal interleaving of adjacent projections. Measured data were corrected for crystal and geometrical efficiency. Then, a whole system matrix was derived by processing the responses in projection space. Such responses included both geometrical and detection physics components of the system matrix. The response was parameterized to correct for point source location and to smooth for projection noise. The model also accounts for axial compression (span) used on the scanner. The forward projector for iterative reconstruction was constructed using the estimated response parameters. This paper extends our previous work to fully three-dimensional. Experimental data were used to compare images reconstructed by the standard iterative reconstruction software and the one modeling the response function. The results showed that the modeling of the response function improves both spatial resolution and noise properties

A Multicrystal Two Dimensional BGO Detector System for Positron Emission Tomography

Abstract: This paper presents a discussion of a new multicrystal detector system as it is implemented in Positron Emission Tomography. The system consists of a 32 × 8 matrix of BGO crystals, a tuned light pipe, and four photomultipliers. The electronics that decodes the position consists of fast preamps, gated integrators, and level comparators. This detector represents a major development toward reducing the cost of PET.

Physical and clinical performance of the mCT time-of-flight PET/CT scanner

Abstract: Time-of-flight (TOF) measurement capability promises to improve PET image quality. We characterized the physical and clinical PET performance of the first Biograph mCT TOF PET/CT scanner (Siemens Medical Solutions USA, Inc.) in comparison with its predecessor, the Biograph TruePoint TrueV. In particular, we defined the improvements with TOF. The physical performance was evaluated according to the National Electrical Manufacturers Association (NEMA) NU 2-2007 standard with additional measurements to specifically address the TOF capability. Patient data were analyzed to obtain the clinical performance of the scanner. As expected for the same size crystal detectors, a similar spatial resolution was measured on the mCT as on the TruePoint TrueV. The mCT demonstrated modestly higher sensitivity (increase by 19.7 ± 2.8%) and peak noise equivalent count rate (NECR) (increase by 15.5 ± 5.7%) with similar scatter fractions. The energy, time and spatial resolutions for a varying single count rate of up to 55 Mcps resulted in 11.5 ± 0.2% (FWHM), 527.5 ± 4.9 ps (FWHM) and 4.1 ± 0.0 mm (FWHM), respectively. With the addition of TOF, the mCT also produced substantially higher image contrast recovery and signal-to-noise ratios in a clinically-relevant phantom geometry. The benefits of TOF were clearly demonstrated in representative patient images.

The ECAT HRRT: performance and first clinical application of the new high resolution research tomograph

Abstract: The ECAT HRRT is a three-dimensional (3-D) only dedicated brain tomograph employing the new scintillator lutetium-oxy-orthosilicate (LSO) and using depth of interaction (DOI) information to achieve uniform isotropic resolution across a 20-cm diameter volume. With its unique technological innovations it represents the prototype of a new generation of high-resolution brain tomographs. The physical performance with respect to count rate, live time, scatter, sensitivity, and resolution was evaluated with phantom studies and measurements with a point source. The HRRTs imaging performance was tested with phantoms and fluorodeoxyglucose (FDG) scans performed in animal and human brains. We find that due to the significantly improved resolution and the large solid angle covered by the panel detectors, several issues that have been adequately solved for older generation scanners demand new attention for the HRRT, like acquiring and handling large amounts of data effectively, strategies for optimal reconstruction, shielding, and correction of random coincidences.

A default mode of brain function.

Abstract: A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

Statistical parametric maps in functional imaging: A general linear approach

Abstract: + Abstract: Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of statistical parametric maps (e.g., Friston et al. (1991): J Cereb Blood Flow Metab 11:690-699; Worsley et al. 119921: J Cereb Blood Flow Metab 12:YOO-918) are based on linear models, for example ANCOVA, correlation coefficients and t tests. In the sense that these examples are all special cases of the general linear model it should be possible to implement them (and many others) within a unified framework. We present here a general approach that accommodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors). This approach brings together two well established bodies of theory (the general linear model and the theory of Gaussian fields) to provide a complete and simple framework for the analysis of imaging data. The importance of this framework is twofold: (i) Conceptual and mathematical simplicity, in that the same small number of operational equations is used irrespective of the complexity of the experiment or nature of the statistical model and (ii) the generality of the framework provides for great latitude in experimental design and analysis.

Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B.

Abstract: This report describes the first human study of a novel amyloid-imaging positron emission tomography (PET) tracer, termed Pittsburgh Compound-B (PIB), in 16 patients with diagnosed mild AD and 9 controls. Compared with controls, AD patients typically showed marked retention of PIB in areas of association cortex known to contain large amounts of amyloid deposits in AD. In the AD patient group, PIB retention was increased most prominently in frontal cortex (1.94-fold, p = 0.0001). Large increases also were observed in parietal (1.71-fold, p = 0.0002), temporal (1.52-fold, p = 0.002), and occipital (1.54-fold, p = 0.002) cortex and the striatum (1.76-fold, p = 0.0001). PIB retention was equivalent in AD patients and controls in areas known to be relatively unaffected by amyloid deposition (such as subcortical white matter, pons, and cerebellum). Studies in three young (21 years) and six older healthy controls (69.5 +/- 11 years) showed low PIB retention in cortical areas and no significant group differences between young and older controls. In cortical areas, PIB retention correlated inversely with cerebral glucose metabolism determined with 18F-fluorodeoxyglucose. This relationship was most robust in the parietal cortex (r = -0.72; p = 0.0001). The results suggest that PET imaging with the novel tracer, PIB, can provide quantitative information on amyloid deposits in living subjects.

Spatial registration and normalization of images

Abstract: This paper concerns the spatial and intensity transformations that map one image onto another. We present a general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment. This technique minimizes the sum of squares between two images following nonlinear spatial deformations and transformations of the voxel (intensity) values. The spatial and intensity transformations are obtained simultaneously, and explicitly, using a least squares solution and a series of linearising devices. The approach is completely noninteractive (automatic), nonlinear, and noniterative. It can be applied in any number of dimensions. Various applications are considered, including the realignment of functional magnetic resonance imaging (MRI) time-series, the linear (affine) and nonlinear spatial normalization of positron emission tomography (PET) and structural MRI images, the coregistration of PET to structural MRI, and, implicitly, the conjoining of PET and MRI to obtain high resolution functional images. © 1995 Wiley-Liss, Inc.

Functional and effective connectivity in neuroimaging: A synthesis

Abstract: The brain appears to adhere to two principles of functional organization; junctional segregation and functional intryration. The integration within and between functionally specialized areas is mediated by functional or ejectiue connectioity. The characterization of this sort of connectivity is an important theme in many areas of neuroscience. This article presents one approach that has been used in functional imaging. This article reviews the basic distinction between functional and effective connectivity (as the terms are used in neuroimaging) and their role in addressing several aspects of functional organization (e.g. the topography of distributed systems, integration between cortical areas, time-dependent changes in connectivity and nonlinear interactions). Emphasis is placed on the points of contact between the apparently diverse applications of these concepts and in particular the central role of eigenimages or spatial modes. Although the framework that has been developed is inherently linear, it has been extended to assess nonlinear interactions among cortical areas.