31,926 research outputs found

    The clinical application of PET/CT: a contemporary review

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    The combination of positron emission tomography (PET) scanners and x-ray computed tomography (CT) scanners into a single PET/CT scanner has resulted in vast improvements in the diagnosis of disease, particularly in the field of oncology. A decade on from the publication of the details of the first PET/CT scanner, we review the technology and applications of the modality. We examine the design aspects of combining two different imaging types into a single scanner, and the artefacts produced such as attenuation correction, motion and CT truncation artefacts. The article also provides a discussion and literature review of the applications of PET/CT to date, covering detection of tumours, radiotherapy treatment planning, patient management, and applications external to the field of oncology

    A hybrid 3d reconstruction/registration algorithm for correction of head motion in emission tomography

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    Even with head restraint, small head movements can occur during data acquisition for emission tomography, sufficiently large to result in detectable artifacts in the final reconstruction. Direct measurement of motion can be cumbersome and difficult to implement, whereas previous attempts to correct for motion based on measured projections have been limited to simple translation orthogonal to the projection. A fully 3D algorithm is proposed that estimates the patient orientation at any time based on the projection of motion-corrupted data, with incorporation of the measured motion within subsequent OSEM sub-iterations. Preliminary studies have been performed using a digital version of the Hoffman brain phantom. Movement was simulated by constructing a mixed set of projections in two discrete positions of the phantom. The algorithm determined the phantom orientation that best aligned each constructed projection with its corresponding, measured projection. In the case of simulated movement of 24 of 64 projections, all mis-positioned projections were correctly identified. The algorithm resulted in a reduction of mean square difference (MSD) between motion corrected and motion-free reconstructions compared to the MSD between uncorrected and motion-free reconstructions by a factor of 2.7

    Visualization-Based Mapping of Language Function in the Brain

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    Cortical language maps, obtained through intraoperative electrical stimulation studies, provide a rich source of information for research on language organization. Previous studies have shown interesting correlations between the distribution of essential language sites and such behavioral indicators as verbal IQ and have provided suggestive evidence for regarding human language cortex as an organization of multiple distributed systems. Noninvasive studies using ECoG, PET, and functional MR lend support to this model; however, there as yet are no studies that integrate these two forms of information. In this paper we describe a method for mapping the stimulation data onto a 3-D MRI-based neuroanatomic model of the individual patient. The mapping is done by comparing an intraoperative photograph of the exposed cortical surface with a computer-based MR visualization of the surface, interactively indicating corresponding stimulation sites, and recording 3-D MR machine coordinates of the indicated sites. Repeatability studies were performed to validate the accuracy of the mapping technique. Six observers—a neurosurgeon, a radiologist, and four computer scientists, independently mapped 218 stimulation sites from 12 patients. The mean distance of a mapping from the mean location of each site was 2.07 mm, with a standard deviation of 1.5 mm, or within 5.07 mm with 95% confidence. Since the surgical sites are accurate within approximately 1 cm, these results show that the visualization-based approach is accurate within the limits of the stimulation maps. When incorporated within the kind of information system envisioned by the Human Brain Project, this anatomically based method will not only provide a key link between noninvasive and invasive approaches to understanding language organization, but will also provide the basis for studying the relationship between language function and anatomical variability

    Practical aspects of a data-driven motion correction approach for brain SPECT

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    Patient motion can cause image artifacts in single photon emission computed tomography despite restraining measures. Data-driven detection and correction of motion can be achieved by comparison of acquired data with the forward projections. This enables the brain locations to be estimated and data to be correctly incorporated in a three-dimensional (3-D) reconstruction algorithm. Digital and physical phantom experiments were performed to explore practical aspects of this approach. Noisy simulation data modeling multiple 3-D patient head movements were constructed by projecting the digital Hoffman brain phantom at various orientations. Hoffman physical phantom data incorporating deliberate movements were also gathered. Motion correction was applied to these data using various regimes to determine the importance of attenuation and successive iterations. Studies were assessed visually for artifact reduction, and analyzed quantitatively via a mean registration error (MRE) and mean square difference measure (MSD). Artifacts and distortion in the motion corrupted data were reduced to a large extent by application of this algorithm. MRE values were mostly well within 1 pixel (4.4 mm) for the simulated data. Significant MSD improvements (>2) were common. Inclusion of attenuation was unnecessary to accurately estimate motion, doubling the efficiency and simplifying implementation. Moreover, most motion-related errors were removed using a single iteration. The improvement for the physical phantom data was smaller, though this may be due to object symmetry. In conclusion, these results provide the basis of an implementation protocol for clinical validation of the technique

    GATE : a simulation toolkit for PET and SPECT

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    Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/

    Modeling and inference of multisubject fMRI data

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    Functional magnetic resonance imaging (fMRI) is a rapidly growing technique for studying the brain in action. Since its creation [1], [2], cognitive scientists have been using fMRI to understand how we remember, manipulate, and act on information in our environment. Working with magnetic resonance physicists, statisticians, and engineers, these scientists are pushing the frontiers of knowledge of how the human brain works. The design and analysis of single-subject fMRI studies has been well described. For example, [3], chapters 10 and 11 of [4], and chapters 11 and 14 of [5] all give accessible overviews of fMRI methods for one subject. In contrast, while the appropriate manner to analyze a group of subjects has been the topic of several recent papers, we do not feel it has been covered well in introductory texts and review papers. Therefore, in this article, we bring together old and new work on so-called group modeling of fMRI data using a consistent notation to make the methods more accessible and comparable

    Image Derived Input Functions: Effects of Motion on Tracer Kinetic Analyses

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    Purpose: To quantify the effects of motion affected image-derived input functions (IDIF) on the outcome of tracer kinetic analyses. Procedures: Two simulation studies, one based on high and the other on low cortical uptake, were performed. Different degrees of rotational and axial translational motion were added to the final frames of simulated dynamic positron emission tomography scans. Extracted IDIFs from motion affected simulated scans were compared to original IDIFs and to outcome of tracer kinetic analysis (volume of distribution, V T). Results: Differences in IDIF values of up to 239 % were found for the last frames. Patient motion of more than 6 ° or 5 mm resulted in at least 10 % higher or lower VT values for the high cortical tracer. Conclusion: The degrees of motion studied are commonly observed in clinical studies and hamper the extraction of accurate IDIFs. Therefore, it is essential to ensure that patient motion is minimal and corrected for
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