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Open Access Research article

Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

Robert Rusina1*, Jaromír Kukal2, Tomáš Bělíček2, Marie Buncová3 and Radoslav Matěj4

Author Affiliations

1 Department of Neurology, Thomayer Teaching Hospital and Institute for Postgraduate Education in Medicine, Prague, Czech Republic

2 Department of Software Engineering in Economy, Faculty of Nuclear Science and Physical Engineering, Czech Technical University, Prague, Czech Republic

3 Department of Nuclear Medicine, Institute for Clinical and Experimental Medicine, Prague, Czech Republic

4 Department of Pathology and Molecular Medicine, Thomayer Teaching Hospital, Prague, Czech Republic

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BMC Medical Imaging 2010, 10:20  doi:10.1186/1471-2342-10-20

Published: 1 September 2010

Abstract

Background

Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose.

Methods

We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups.

Results

AD patients had a significantly reduced number of watershed regions compared to controls (p < 0.01). A sensitivity of 94.1% and specificity of 80% was obtained with a threshold value of 57.11 for the watershed domain number. The narrowing of the SPECT analysis to parietal regions leads to a substantial increase in both sensitivity and specificity.

Conclusions

Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.