Fully automated 3D basal ganglia activity measurement in dopamine transporter scintigraphy (Spectalyzer)

Mirzaei, Siroos; Rodrigues, Margarida; Schwarzgruber, Thomas; Brücke, Thomas; Bakala, Jiří; Borbély, Katalin; Leners, N.; Kabos, Peter; Donner, René

doi:10.1007/s12149-010-0353-2

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…Another difference from other automated approaches is that our new method located the maximum activity of basal ganglia within the brain volume based on SSmask. In contrast to other techniques [27,28], this was rather simple to implement.…”

Section: Discussionmentioning

confidence: 99%

Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson’s disease patients

et al. 2011

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Section: Discussionmentioning

confidence: 99%

Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson’s disease patients

et al. 2011

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“…In the majority of these studies, the focus is on the use of DaTSCAN to separate different classes of patients or patients from healthy controls. Recently, authors [ 24 ] developed and evaluated Spectalizer, a fully automated method for 3D ROI extraction and SBR evaluation. The method performed well in separating patients with PD from those with ET but did not consider shape nor extension features of the striatum.…”

Section: Introductionmentioning

confidence: 99%

CADA—computer-aided DaTSCAN analysis

et al. 2016

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BackgroundDopamine transporter (DaT) imaging (DaTSCAN) is useful for the differential diagnosis of parkinsonian syndromes. Visual evaluation of DaTSCAN images represents the generally accepted diagnostic method, but it is strongly dependent on the observer’s experience and shows inter- and intra-observer variability. A reliable and automatic method for DaTSCAN evaluation can provide objective quantification; it is desirable for longitudinal studies, and it allows for a better follow-up control. Moreover, it is crucial for an automated method to produce coherent measures related to the severity of motor symptoms.MethodsIn this work, we propose a novel fully automated technique for DaTSCAN analysis that generates quantitative measures based on striatal intensity, shape, symmetry and extent. We tested these measures using a support vector machine (SVM) classifier.ResultsThe proposed measures reached 100 % accuracy in distinguishing between patients with Parkinson’s disease (PD) and control subjects. We also demonstrate the existence of a linear relationship and an exponential trend between pooled structural and functional striatal characteristics and the Unified Parkinson’s disease Rating Scale (UPDRS) motor score.ConclusionsWe present a novel, highly reproducible, user-independent technique for DaTSCAN analysis producing quantitative measures directly connected to striatum uptake and shape. In our method, no a priori assumption is required on the spatial conformation and localization of striatum, and both uptake and symmetry contribute to the index quantification. These measures can reliably support a computer-assisted decision system.Electronic supplementary materialThe online version of this article (doi:10.1186/s40658-016-0140-9) contains supplementary material, which is available to authorized users.

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“…In conventional SPECT image evaluation, visual inspection or manual selection of ROI for semiquantitative analysis is mainly used to evaluate the degree of striatal defects [ 4 ]. However, these methods are dependent on the subjective opinions of observers, which lead to human errors, and have shortcomings such as long duration, increased effort, and low reproducibility [ 6 , 7 ]. Therefore, to solve these problems, many automatic semiquantitative analytical methods and software have been created.…”

Section: Introductionmentioning

confidence: 99%

Effects of 99mTc-TRODAT-1 drug template on image quantitative analysis

Yang

Chou

et al. 2018

PLoS ONE

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99mTc-TRODAT-1 is a type of drug that can bind to dopamine transporters in living organisms and is often used in SPCT imaging for observation of changes in the activity uptake of dopamine in the striatum. Therefore, it is currently widely used in studies on clinical diagnosis of Parkinson’s disease (PD) and movement-related disorders. In conventional 99mTc-TRODAT-1 SPECT image evaluation, visual inspection or manual selection of ROI for semiquantitative analysis is mainly used to observe and evaluate the degree of striatal defects. However, these methods are dependent on the subjective opinions of observers, which lead to human errors, have shortcomings such as long duration, increased effort, and have low reproducibility. To solve this problem, this study aimed to establish an automatic semiquantitative analytical method for 99mTc-TRODAT-1. This method combines three drug templates (one built-in SPECT template in SPM software and two self-generated MRI-based and HMPAO-based TRODAT-1 templates) for the semiquantitative analysis of the striatal phantom and clinical images. At the same time, the results of automatic analysis of the three templates were compared with results from a conventional manual analysis for examining the feasibility of automatic analysis and the effects of drug templates on automatic semiquantitative analysis results. After comparison, it was found that the MRI-based TRODAT-1 template generated from MRI images is the most suitable template for 99mTc-TRODAT-1 automatic semiquantitative analysis.

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Fully automated 3D basal ganglia activity measurement in dopamine transporter scintigraphy (Spectalyzer)

Abstract: The proposed method is successful in finding the 3D ROIs and performing the subsequent measurements automatically. It is proposed as an automatic reproducible approach for semiquantitative analysis of DAT scintigraphy.

Cited by 9 publications

References 9 publications

Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson’s disease patients

Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson’s disease patients

CADA—computer-aided DaTSCAN analysis

Effects of 99mTc-TRODAT-1 drug template on image quantitative analysis

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