Transfer of normal 99mTc-ECD brain SPET databases between different gamma cameras
ABSTRACT A stereotactic, normal perfusion database is imperative for optimal clinical brain single-photon emission tomography (SPET). However, interdepartmental use of normal data necessitates accurate transferability of these data sets. The aim of this study was to investigate transfer of three normal perfusion databases obtained in the same large population of healthy volunteers who underwent sequential scanning using multihead gamma cameras with different resolution. Eighty-nine healthy adults (46 females, 43 males; aged 20-81 years) were thoroughly screened by history, biochemistry, physical and full neurological examination, neuropsychological testing and magnetic resonance imaging. After injection of 925 MBq technetium-99m labelled ethyl cysteinate dimer (ECD) under standard conditions, 101 scans were acquired from all subjects (12 repeat studies) on a triple-head Toshiba GCA-9300A (measured average FWHM 8.1 mm). Ninety-one sequential scans were performed on a dual-head Elscint Helix camera (FWHM 9.6 mm) and 22 subjects also underwent imaging on a triple-head Prism 3000 (FWHM 9.6 mm). Images were transferred to the same processing platform and reconstructed by filtered back-projection with the same Butterworth filter (order 8, cut-off 0.9 cycles/cm) and uniform Sorensen attenuation correction (=0.09). After automated rigid intrasubject registration, all subjects were automatically reoriented to a stereotactic template by a nine-parameter affine transformation. The databases were analysed using 35 predefined volumes of interest (VOIs) with normalisation on total VOI counts. For comparison, the high-resolution data were smoothed with a 3D Gaussian kernel to achieve more similar spatial resolution. Hoffman phantom measurements were conducted on all cameras. Partial volume effects after smoothing varied between -6.5% and 10%, depending on VOI size. Between-camera reproducibility was 2.5% and 2.7% for the Toshiba camera versus the Helix and the Prism database, respectively. The highest reduction in between-camera variability was achieved by resolution adjustment in combination with linear washout correction and a Hoffman phantom-based correction. In conclusion, transfer of normal perfusion data between multihead gamma cameras can be accurately achieved, thereby enabling widespread interdepartmental use, which is likely to have a positive impact on the diagnostic capabilities of clinical brain perfusion SPET.
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ABSTRACT: Statistical brain imaging analysis has good objectivity and reproducibility. In Japan, statistical parametric mapping (SPM) and three-dimensional stereotactic surface projections (3D-SSP) are used nationwide as statistical imaging analysis with standard brain coordinates. They often help to interpret brain single photon emission computed tomography (SPECT) images by avoiding possible pitfalls (e.g., effects of aging, atrophy) with which clinicians are unfamiliar. However, this type of analysis presents a problem: statistical processing requires many normal subject images. The easy Z-score imaging system (eZIS) is one of the statistical analysis methods that uses SPM processing in normalization and smoothing, and it has the function of image conversion leading to statistical analysis without a control database. Therefore, statistical analysis can be used in clinical practice by sharing a prepared normal database. By unifying the image quality by processing a shared database, this program has great potential for sharing patient imaging data in many hospitals. It is expected that the eZIS will help perform detailed analysis in many functional diseases in collaborative studies. This article describes the interpretation of brain SPECT images and suggests the usefulness and potential of eZIS.Radiation Medicine 09/2006; 24(7):545-52.
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ABSTRACT: In Alzheimer disease (AD), a peculiar regional cerebral blood flow (rCBF) abnormality has been reported in the posterior cingulate gyri and precunei, even at a very early stage. We performed a multicenter brain perfusion single-photon emission tomography (SPECT) study to evaluate the discrimination ability of an easy Z-score imaging system (eZIS) with a common normal data base between patients with very early AD at the stage of mild cognitive impairment and age-matched healthy controls. For a multicenter study, SPECT images of 40 patients with AD and 40 healthy volunteers were acquired from 4 gamma camera systems in 4 different institutions. Systematic differences of SPECT images between gamma cameras were corrected by using conversion maps calculated from the SPECT images of the same brain phantom. Receiver operating characteristic (ROC) analysis was performed to discriminate patients and controls by using a Z-score in the volume of interest (VOI), which had been defined as a region related to AD in subjects other than those in a multicenter study. Bilateral posterior cingulate gyri, precunei, and parietal cortices were defined as a VOI showing rCBF reduction in very early AD. A new indicator of rCBF abnormality in the VOI provided 86% accuracy for distinction of AD and healthy controls in the multicenter study. The area under the ROC curve was 0.934. Because an eZIS can use a common normal data base by converting site-specific SPECT data to the core data, the eZIS was useful for automated diagnosis of very early AD in routine studies in multiple institutions.American Journal of Neuroradiology 05/2007; 28(4):731-6. · 3.17 Impact Factor
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ABSTRACT: Spatial covariance analysis has been used with FDG PET to identify a specific metabolic network associated with Parkinson's disease (PD). In the current study, we utilized a new, fully automated voxel-based method to quantify network expression in ECD SPECT images from patients with classical PD, patients with multiple system atrophy (MSA), and healthy control subjects. We applied a previously validated voxel-based PD-related covariance pattern (PDRP) to quantify network expression in the ECD SPECT scans of 35 PD patients, 15 age- and disease severity-matched MSA patients, and 35 age-matched healthy control subjects. PDRP scores were compared across groups using analysis of variance. The sensitivity and specificity of the prospectively computed PDRP scores in the differential diagnosis of individual subjects were assessed by receiver operating characteristic (ROC) analysis. PDRP scores were significantly increased (p < 0.001) in the PD group relative to the MSA and control groups. ROC analysis indicated that the overall diagnostic accuracy of the PDRP measures was 0.91 (AUC). The optimal cutoff value was consistent with a sensitivity of 0.97 and a specificity of 0.80 and 0.71 for discriminating PD patients from MSA and normal controls, respectively. Our findings suggest that fully automated voxel-based network assessment techniques can be used to quantify network expression in the ECD SPECT scans of parkinsonian patients.European journal of nuclear medicine and molecular imaging 05/2007; 34(4):496-501. · 5.11 Impact Factor