Mathematical Data Processing of Gated SpectMyocardial Perfusion Imaging with Using Wavelet

AnalysisAndrey V. Babin

Saint Petersburg State University,Saint-Petersburg, Russia, 198504,

Universitetskij pr. 35E-mail: babinandrew@mail.ru

Elena D. KotinaSaint Petersburg State University,Saint-Petersburg, Russia, 198504,

Universitetskij pr. 35E-mail: ekotina123@mail.ru

Abstract—The problem of mathematical data processing ofgated SPECT myocardial perfusion imaging (MPI) is consideredin the study. MPI is modern radionuclide cardiac study thatallows evaluating a function of a myocardium. In the studywe developed method to measure and visualize myocardialdyssynchrony using wavelet transforms from MPI data.

The problem of mathematical data processing ofelectrocardiogram-gated single-photon emission computedtomography (GSPECT) myocardial perfusion imaging (MPI)studies are considered in the study [1-4]. MPI is a modernradionuclide study which is used for diagnosis and differentialdiagnosis of a ischemic heart disease.

The purpose of this study was to develop a wavelet anal-ysis method to measure systolic and diastolic dyssynchronyfrom conventional GSPECT MPI data. Phase analysis usingFourier harmonic functions has been developed for measuringLV systolic dyssynchrony from gated SPECT MPI [5].It isimportant that dyssynchrony as assessed by phase analysis canprovide incremental prognostic information to other parame-ters measured from gated SPECT MPI such as perfusion andLV ejection fraction (LVEF) and predict response to cardiacresynchronization therapy (CRT).

Input data for this method is sequence of three-dimensionaldistribution density of radio-pharmaceuticals, corresponding tointervals of cardiac cycle. This distributions are represented aspolar diagrams of perfusion which are used for constructionof sequence of wall thickening curves. Using approximationof the curves based on wavelet analysis, we obtain functionalimages of systolic and diastolic dyssynchrony. As waveletsare considered two of the family of complex wavelets withthe following basal functions:

1) Morlet wavelet ψ(t) = e2πte−t2

2 ;2) B-spline wavelet ψ(t) = e2πt

sin(( t3 )

3)

( t3 )

3 ;

The functional images of dyssyncrony were constructedusing Fourier phase analysis [5-8] for comparative analysis(Fig. 1). Phase analysis using wavelet functions can betterapproximate the variation of myocardial wall thickness overthe cardiac cycle to calculate the onset of mechanical con-traction (OMC) and onset of mechanical relaxation (OMR) as

Figure 1. Approximation of thickening curve using wavelet analysis (a) and3-harmonic phase analysis (b)

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measures of LV systolic and diastolic dyssynchrony. Waveletanalysis using more accurate approximation of wall thickeningcurves allows to get a more detailed functional images.

The wavelet analysis tool to measure systolic and diastolicdyssynchrony from conventional gated SPECT MPI data wasdeveloped in this study.

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