| 71. |
- Toft, Jens, et al.
(författare)
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The optimal reference population for cardiac normality in myocardial SPET in the detection of coronary artery stenoses: patients with normal coronary angiography or subjects with low likelihood of coronary artery disease?
- 2001
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Ingår i: European Journal Of Nuclear Medicine. - : Springer Science and Business Media LLC. - 1432-105X .- 0340-6997 .- 1619-7089. ; 28:7, s. 831-835
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Tidskriftsartikel (refereegranskat)abstract
- Both subjects with a low likelihood for coronary artery disease (CAD) and patients with normal findings on coronary angiography have been used as reference populations in non-invasive stress testing, including myocardial perfusion scintigraphy. Both of these criteria of normality--low likelihood of CAD and normal coronary angiography--have been criticised, and consensus on this issue is lacking. The aim of this study was to compare two different reference populations by testing the performance of artificial neural networks designed to interpret myocardial scintigrams. The networks were trained on myocardial perfusion scintigrams from 87 patients with angiographically documented CAD and on studies from one of two different reference groups: 48 patients with no signs of CAD based on angiography or 128 healthy volunteers with a likelihood for CAD <5%. The performance of the two different networks was then tested using scintigrams from a separate test group of 68 patients. Coronary angiography was used as the gold standard in this group. The network trained on patients with no signs of CAD based on angiography showed an area under the receiver operating characteristic (ROC) curve of 93%. The ROC area for the network trained on healthy volunteers was 72%, and this difference was statistically significant (P=0.03). The results of this study using artificial neural networks suggest that normal angiography should be preferred as the reference standard in myocardial scintigraphy when a patient is examined for CAD prior to possible angiography. Whether the same is true for other indications, e.g. in prognostic evaluation, is unknown.
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| 72. |
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| 73. |
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| 74. |
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| 75. |
- Xu, Jiahua, et al.
(författare)
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Quantitative analysis of inhomogeneity in ventilation SPET
- 2001
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Ingår i: European Journal of Nuclear Medicine. - : Springer. - 0340-6997 .- 1432-105X .- 1619-7070 .- 1619-7089. ; 28:12, s. 1795-1800
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to evaluate a method for quantification of inhomogeneity in ventilation single-photon emission tomography (SPET). Nine emphysematous patients, nine life-long non-smokers and nine smokers were included in the study. The SPET investigation was performed after 50 MBq (99m)Tc-Technegas had been inhaled by each subject in the supine position. A single-head gamma camera, equipped with a general-purpose parallel-hole collimator using 64 projections (20 s each) over 360 degrees, was used. Data were acquired in 128x128 matrices. Attenuation correction was applied based upon computed tomography (CT) density maps. Lung regions of interest were delineated manually on CT images and then positioned on SPET images. Several attenuation-corrected transaxial SPET slices (thickness 1 cm, spacing 3.5 cm) were reconstructed. Each SPET slice was divided into several 2x2x1 cm(3) elements. Inhomogeneity was assessed by the coefficient of variation (CV) of the pixel counts within these elements (micro-level) and the CV of the total counts of the elements (macro-level). Micro-level CVs in non-smokers varied between 1% and 41%, whereas they were dispersed over a wide range (1%-600%) in emphysematous patients. In seven smokers, the frequency distribution of micro-level CVs was within the normal range, whereas in the other two smokers the values were between the normal range and the range in emphysematous patients. The pooled mean values of micro-level CVs and macro-level CVs in each subject clearly separated the patients from the others. Parametric images of micro-level CV indicated the localisation and severity of ventilation inhomogeneity. We conclude that the present method enables quantification and localisation of regional inhomogeneity in ventilation SPET images.
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