Masaki Ohkubo

A Multicenter Validation of Regional Cerebral Blood Flow Quantitation Using [123I]Iodoamphetamine and Single Photon Emission Computed Tomography

Recently, two methods have been proposed for regional cerebral blood flow (rCBF) quantitation using [123I]iodoamphetamine (IMP) and single-photon emission computed tomography (SPECT). The table look-up (TLU) method has been shown to provide both rCBF and volume of distribution, Vd, images from two SPECT scans, while a single-scan autoradiographic (ARG) technique provided rCBF using a fixed and assumed Vd. In both methods, a single blood sample was referred to calibrate the previously determined standard input function The present multicenter project was designed to evaluate the accuracy of both methods for use as clinical investigative tools. Ten independent institutions performed [123I]IMP-SPECT studies according to both methods in 76 subjects (10 normal volunteers, 32 patients with cerebrovascular disease, and 34 patients with other diseases). Calculated rCBF values were compared with those obtained by the following reference methods available in the participating institutions; [15O] H2O positron emission tomography (PET) (five institutions), [133Xe]SPECT (four institutions), and the [123I]IMP microsphere method (three institutions). Both ARG and TLU methods provided rCBF values that were significantly correlated with those measured by the [15O] H2O PET technique (p < 0.001 for all subjects; overall regression equation, y = 15.14 + 0.54×) and those measured by the [123I]IMP-microsphere method (p < 0.001 for all subjects; y = 2.0 + 0.80×). Significant correlation (p < 0.05) was observed in 18 of 24 subjects studied with the [133Xe] SPECT reference technique (overall regression equation, y = 15.0 + 0.55×). Mean cortical gray matter rCBF in a group of normal subject was 43.9 ± 3.3 and 43.4 ± 2.0 ml/min/100 g for the ARG and TLU methods, respectively. Regional Vd of [123I]IMP estimated by the TLU method was 45 ml/ml ± 20% in the normal cortical region. Close agreement between ARG and TLU rCBF values was observed (y = −3.21 + 1.07×, r = 0.97), confirming the validity of assuming a fixed Vd in the ARG method. Results of this study demonstrate that both the ARG and TLU methods accurately and reliably estimate rCBF in a variety of clinical settings.

Parietal white matter abnormalities in obsessive-compulsive disorder : a magnetic resonance spectroscopy study at 3-Tesla

Objective:  To identify a neurochemical basis for the hypothesis that an aberrant cortico‐subcortical circuit underlies obsessive–compulsive disorder (OCD). The white matter was also investigated because of recent research which suggests the altered connectivity of axons.

An effective method to verify line and point spread functions measured in computed tomography

This study describes an effective method for verifying line spread function (LSF) and point spread function (PSF) measured in computed tomography (CT). The CT image of an assumed object function is known to be calculable using LSF or PSF based on a model for the spatial resolution in a linear imaging system. Therefore, the validities of LSF and PSF would be confirmed by comparing the computed images with the images obtained by scanning phantoms corresponding to the object function. Differences between computed and measured images will depend on the accuracy of the LSF and PSF used in the calculations. First, we measured LSF in our scanner, and derived the two-dimensional PSF in the scan plane from the LSE Second, we scanned the phantom including uniform cylindrical objects parallel to the long axis of a patients body (z direction). Measured images of such a phantom were characterized according to the spatial resolution in the scan plane, and did not depend on the spatial resolution in the z direction. Third, images were calculated by two-dimensionally convolving the true object as a function of space with the PSF. As a result of comparing computed images with measured ones, good agreement was found and was demonstrated by image subtraction. As a criterion for evaluating quantitatively the overall differences of images, we defined the normalized standard deviation (SD) in the differences between computed and measured images. These normalized SDs were less than 5.0% (ranging from 1.3% to 4.8%) for three types of image reconstruction kernels and for various diameters of cylindrical objects, indicating the high accuracy of PSF and LSF that resulted in successful measurements. Further, we also obtained another LSF utilizing an inappropriate manner, and calculated the images as above. This time, the computed images did not agree with the measured ones. The normalized SDs were 6.0% or more (ranging from 6.0% to 13.8%), indicating the inaccuracy of the PSF and LSE We could verify LSFs and PSFs for three types of reconstruction kernels, and demonstrated differences between modulation transfer functions (MTFs) derived from validated LSFs and inaccurate LSFs. Our technique requires a simple phantom that is suitable for clinical scanning, and does not require a particular phantom containing some metals or specific fine structures, as required in methods previously used for measurements of spatial resolution. Therefore, the scanned image of the phantom will be reliable and of good quality, and this is used directly as a confident reference image for the verification. When one obtains LSF, PSF or MTF values, verification using our method is recommended. Further, when another method for the measurement of LSF and PSF is developed, it could be validated using our technique, as illustrated in the method proposed by Boone [Med. Phys. 28, 356-360 (2001)] and used in this paper.

Decrease in benzodiazepine receptor binding in a patient with Angelman syndrome detected by iodine-123 iomazenil and single-photon emission tomography

A receptor mapping technique using iodine-123 iomazenil and single-photon emission tomography (SPET) was employed to examine benzodiazepine receptor binding in a patient with Angelman syndrome (AS). AS is characterized by developmental delay, seizures, inappropriate laughter and ataxic movement. In this entity there is a cytogenic deletion of the proximal long arm of chromosome 15g11–q13, where the gene encoding the GABAA receptorβ3 subunit (GABRB3) is located. Since the benzodiazepine receptor is constructed as a receptor-ionophore complex that contains the GABAA receptor, it is a suitable marker for GABA-ergic synapsis. To determine whether benzodiazepine receptor density, which indirectly indicates changes in GABAA receptor density, is altered in the brain in patients with AS, we investigated a 27-year-old woman with AS using123I-iomazenil and SPET. Receptor density was quantitatively assessed by measuring the binding potential using a simplified method. Regional cerebral blood flow was also measured withN-isopropyl-p-[123I]iodoamphetamine. We demonstrated that benzodiazepine receptor density is severely decreased in the cerebellum, and mildly decreased in the frontal and temporal cortices and basal ganglia, a result which is considered to indicate decreased GABAA receptor density in these regions. Although the deletion of GABRB3 was not observed in the present study, we indirectly demonstrated the disturbance of inhibitory neurotransmission mediated by the GABAA receptor in the investigated patient.123I-iomazenil with SPET was useful to map benzodiazepine receptors, which indicate GABAA receptor distribution and their density.

Medical image classification using genetic-algorithm based fuzzy-logic approach

In this paper we present a genetic-algorithm-based fuzzy-logic approach for computer-aided diagnosis scheme in medical imaging. The scheme is applied to discriminate myocardial heart disease from echocardiographic images and to detect and classify clustered microcalcifications from mammograms. Unlike the conventional types of membership functions such as trapezoid, triangle, S curve, and singleton used in fuzzy reasoning, Gaussian-distributed fuzzy membership functions (GDMFs) are employed in the present study. The GDMFs are initially generated using various texture-based features obtained from reference images. Subsequently the shapes of GDMFs are optimized by a genetic-algorithm learning process. After optimization, the classifier is used for disease discrimination. The results of our experiments are very promising. We achieve an average accuracy of 96% for myocardial heart disease and accuracy of 88.5% at 100% sensitivity level for microcalcification on mammograms. The results demonstrated that our proposed genetic-algorithm-based fuzzy-logic approach is an effective method for computer-aided diagnosis in disease classification.

Determination of point spread function in computed tomography accompanied with verification

A method for verifying the point spread function (PSF) measured by computed tomography has been previously reported [Med. Phys. 33, 2757-2764 (2006)]; however, this additional PSF verification following measurement is laborious. In the present study, the previously described verification method was expanded to PSF determination. First, an image was obtained by scanning a phantom. The image was then two-dimensionally deconvolved with the object function corresponding to the phantom structure, thus allowing the PSF to be obtained. Deconvolution is implemented simply by division of spatial frequencies (corresponding to inverse filtering), in which two parameters are used as adjustable ones. Second, an image was simulated by convolving the object function with the obtained PSF, and the simulated image was compared to the above-measured image of the phantom. The difference indicates the inaccuracy of the PSF obtained by deconvolution. As a criterion for evaluating the difference, the authors define the mean normalized standard deviation (SD) in the difference between simulated and measured images. The above two parameters for deconvolution can be adjusted by referring to the subsequent mean normalized SD (i.e., the PSF is determined so that the mean normalized SD is decreased). In this article, the parameters were varied in a fixed range with a constant increment to find the optimal parameter setting that minimizes the mean normalized SD. Using this method, PSF measurements were performed for various types of image reconstruction kernels (21 types) in four kinds of scanners. For the 16 types of kernels, the mean normalized SDs were less than 2.5%, indicating the accuracy of the determined PSFs. For the other five kernels, the mean normalized SDs ranged from 3.7% to 4.8%. This was because of a large amount of noise in the measured images, and the obtained PSFs would essentially be accurate. The method effectively determines the PSF, with an accompanying verification, after one scanning of a phantom.

Imaging of small spherical structures in CT: simulation study using measured point spread function

Size and density measurements of objects undertaken using computed tomography (CT) are clinically significant for diagnosis. To evaluate the accuracy of these quantifications, we simulated three-dimensional (3D) CT image blurring; this involved the calculation of the convolution of the 3D object function with the measured 3D point spread function (PSF). We initially validated the simulation technique by performing a phantom experiment. Blurred computed images showed good 3D agreement with measured images of the phantom. We used this technique to compute the 3D blurred images from the object functions, in which functions are determined to have the shape of an ideal sphere of varying diameter and assume solitary pulmonary nodules with a uniform density. The accuracy of diameter and density measurements was determined. We conclude that the proposed simulation technique enables us to estimate the image blurring precisely of any 3D structure and to analyze clinical images quantitatively.

Evaluation of cerebral blood flow in patients with idiopathic orthostatic hypotension using Tc-99m HMPAO brain SPECT during postural testing.

To determine whether regional cerebral blood flow (rCBF) would change on standing in patients with idiopathic orthostatic hypotension (IOH), Tc-99m HMPAO SPECT studies were performed during postural testing in five patients with IOH. After 10 minutes of quiet rest on a bed, the patients arose quickly and, at the same time, the radiotracer was injected intravenously. SPECT data were obtained with a ring-type SPECT scanner. Another dose of Tc-99m HMPAO was injected with the subjects in the supine position, and SPECT was performed again. Image subtraction was used to evaluate the change in rCBF caused by postural testing. In all patients, the authors observed a decrease of rCBF in the frontal cortex and basal ganglia. This preliminary study suggests that changes in rCBF occur in patients with IOH on standing, and Tc-99m HMPAO SPECT performed during postural testing may have an important role in evaluating these changes.

125I-iomazeniI binding shows stress- and/or diazepam-induced reductions in mouse brain: Supporting data for123I-iomazenil SPECT study of anxiety disorders

Effects of repeated swim stress on the binding of125I-iomazenil were examined in the brains of diazepam-treated and non-treated mice. The mice were orally administered diazepam or vehicle (0.5% ethylene glycol) and subjected to daily swim stress (at 20°C for 10 min) for seven consecutive days. The distribution and the amount of125I-iomazenil binding were analyzed autoradiographically afterin vivo andin vitro binding experiments. Repeated swim stress decreased thein vivo binding in the hippocampus (p < 0.05) and cerebral cortex (p < 0.05) of vehicle-treated mice but caused no significant changes in diazepam-treated mice. Subchronic treatment with diazepam decreased thein vivo binding approximately 50% in all brain regions examined (p < 0.01). Thein vitro experiment, however, revealed no significant changes except in the hippocampus, where a small but significant decrease in the binding was observed after subchronic treatment with diazepam (p < 0.01). The stress- or diazepam-induced reductions seem to represent alterations in thein vivo environment related to125I-iomazenil binding. These results suggest that we can investigate the pathophysiology of stress and anxiety with123I-iomazenil SPECT. Care must be taken concerning the effects of benzodiazepines.

Accuracy of lung nodule density on HRCT: analysis by PSF‐based image simulation

A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT‐based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high‐resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF‐based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT‐based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals. PACS numbers: 87.57.‐s, 87.57.cf, 87.57.Q‐