Diagnostic performance of a 3-D automated quantification method of dopamine D2 receptor SPECT studies in the differential diagnosis of parkinsonism

SPECT molecular imaging in Parkinson's disease

Parkinson's disease (PD) is a common disorder, and the diagnosis of Parkinson's disease is clinical and relies on the presence of characteristic motor symptoms. The accuracy of the clinical diagnosis of PD is still limited. Functional neuroimaging using SPECT technique is helpful in patients with first signs of parkinsonism. The changes detected may reflect the disease process itself and/or compensatory responses to the disease, or they may arise in association with disease- and/or treatment-related complications. This paper addresses the value of SPECT in early differential diagnosis of PD and its potential as a sensitive tool to assess the pathophysiology and progression, as well as the therapeutic efficacy of PD.

SPECT imaging evaluation in movement disorders: far beyond visual assessment

Single photon emission computed tomography (SPECT) imaging with (123)I-FP-CIT is of great value in differentiating patients suffering from Parkinson's disease (PD) from those suffering from essential tremor (ET). Moreover, SPECT with (123)I-IBZM can differentiate PD from Parkinson's "plus" syndromes. Diagnosis is still mainly based on experienced observers' visual assessment of the resulting images while many quantitative methods have been developed in order to assist diagnosis since the early days of neuroimaging. The aim of this work is to attempt to categorize, briefly present and comment on a number of semi-quantification methods used in nuclear medicine neuroimaging. Various arithmetic indices have been introduced with region of interest (ROI) manual drawing methods giving their place to automated procedures, while advancing computer technology has allowed automated image registration, fusion and segmentation to bring quantification closer to the final diagnosis based on the whole of the patient's examinations results, clinical condition and response to therapy. The search for absolute quantification has passed through neuroreceptor quantification models, which are invasive methods that involve tracer kinetic modelling and arterial blood sampling, a practice that is not commonly used in a clinical environment. On the other hand, semi-quantification methods relying on computers and dedicated software try to elicit numerical information out of SPECT images. The application of semi-quantification methods aims at separating the different patient categories solving the main problem of finding the uptake in the structures of interest. The semi-quantification methods which were studied fall roughly into three categories, which are described as classic methods, advanced automated methods and pixel-based statistical analysis methods. All these methods can be further divided into various subcategories. The plethora of the existing semi-quantitative methods reinforces the feeling that visual assessment is still the base of image interpretation and that the unambiguous numerical results that will allow the absolute differentiation between the known diseases have not been standardized yet. Switching to a commonly agreed-ideally PC-based-automated software that may take raw or mildly processed data (checked for consistency and maybe corrected for attenuation and/or scatter and septal penetration) as input, work with basic operator's inference and produce validated numerical results that will support the diagnosis is in our view the aim towards which efforts should be directed. After all, semi-quantification can improve sensitivity, strengthen diagnosis, aid patient's follow-up and assess the response to therapy. Objective diagnosis, altered diagnosis in marginal cases and a common approach to multicentre trials are other benefits and future applications of semi-quantification.

[Experience with 123I-Iodobenzamide in the differential diagnosis of Parkinson's disease and Parkinson-plus disease]

OBJECTIVE

To perform a descriptive analysis of the clinical and diagnostic implications of (123)I-IBZM SPECT in the patients studied in our center for movement disorders suggestive of Parkinson-Plus Disease (PP).

SUBJECTS AND METHODS

(123)I-IBZM SPECT was performed in 46 patients referred from the movement disorders consultation due to suspicion of PP. According to their symptoms, they were distributed into 3 groups: 35 patients had atypical symptoms (AS) for Parkinson's Disease, 2 showed no response to standard therapy (NR) and 9 presented both factors (AS, NR). The results of SPECT were only assessed qualitatively.

RESULTS

The (123)I-IBZM supported the diagnosis of PP in 15(42.9%) out of the 35 patients with AS. The (123)I-IBZM was pathological in one of the two NR patients. Regarding the third group of patients (AS+NR), the (123)I-IBZM was pathological in 6 cases (66.7%). In 95.7% of our sample (44 patients), AS with or without NR was the main factor leading to suspicion of PP and the (123)I-IBZM was altered in only 47.7% (22 patients). Of these 22 cases, the final diagnosis was PP (with high positive predictive value) in 20(91%).

CONCLUSION

The study with (123)I-IBZM is useful in the clinical practice because it provides objective diagnostic information with implications for the treatment and prognosis of patients with suspicion of PP.

Meta-analysis of the literature on diagnostic accuracy of SPECT in parkinsonian syndromes

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disorder. One of the most widely used techniques to diagnose PD is a Single Photon Emission Computer Tomography (SPECT) scan to visualise the integrity of the dopaminergic pathways in the brain. Despite this there remains some discussion on the value of SPECT in the differential diagnosis of PD. We did a meta-analysis of all the existing literature on the diagnostic accuracy of both pre- and post-synaptic SPECT imaging in the differential diagnosis of PD.

METHODS

Relevant studies were searched in Medline, EMBASE and Cochrane databases with back-searching of their reference lists. We limited our analysis to studies with a clinically relevant methodology: i.e. when they assessed the ability of the SPECT to provide 1. diagnosis of PD in an early phase vs. normalcy; 2 diagnostic differentiation between PD and essential tremor (ET); 3. distinguishing between PD and vascular parkinsonism (VP); 4. delineation of PD from atypical parkinsonian syndromes (APS). Gold standard was, dependent on the study type, clinical examination at initial visit or follow-up, and/or response to dopaminergic agents.

RESULTS

The search gave 185 hits, of which we deemed 32 suitable for our analysis. From these we recalculated the diagnostic odds ratio of SPECT for the clinical questions above. The pooled odds ratio (with 95%CI) for presynaptic SPECT scan's ability to distinguish between early PD and normalcy was 60 (13 - 277). For the ability to differentiate between PD and ET this ratio was 210 (79-562). The ratio for presynaptic SPECT's ability to delineate PD from VP was 105 (32 - 348). The mean odds ratio for the presynaptic SPECT scans to differentiate between PD and the two APS was 2 (1 - 4), and for the postsynaptic SPECT imaging this was 19 (9-36).

CONCLUSION

SPECT with presynaptic radiotracers is relatively accurate to differentiate patients with PD in an early phase from normalcy, patients with PD from those with ET, and PD from VP. The accuracy of SPECT with both presynaptic and postsynaptic tracers to differentiate between PD and APS is relatively low.

Does combined imaging of the pre- and postsynaptic dopaminergic system increase the diagnostic accuracy in the differential diagnosis of parkinsonism?

PURPOSE

We hypothesized that combining pre- and postsynaptic quantitative information about the dopaminergic system would provide a higher diagnostic accuracy in the differential diagnosis of parkinsonism than specific striatal D(2) receptor binding alone. Therefore, the aim of the study was to introduce new semi-quantitative parameters and evaluate their ability to discriminate between Parkinson's disease (IPS) and non-idiopathic parkinsonian syndromes (non-IPS).

METHODS

In 100 patients (69 IPS, 31 non-IPS), postsynaptic [(123)I]IBZM and presynaptic [(123)I]FP-CIT SPECT scans were evaluated by observer-independent techniques. The diagnostic performances of striatal dopamine transporter (DAT) and D(2) receptor binding, their respective asymmetries, and a combination of pre- and postsynaptic asymmetry were evaluated with ROC analyses. A logistic regression model was generated combining factors to calculate the probability for each patient of belonging to either diagnostic group.

RESULTS

D(2) receptor binding provided a sensitivity of 87.1% and a specificity of 72.5% with an area under the curve (AUC) of 0.866. The AUCs of other single parameters were lower than that of D(2) binding. A gain of diagnostic power (p = 0.026) was reached with a model combining pre- and postsynaptic asymmetries and D(2) binding (sensitivity 90.3%, specificity 73.9%, AUC 0.893).

CONCLUSION

The combination of quantitative parameters of presynaptic DAT and postsynaptic D(2) receptor binding demonstrates superior diagnostic power in the differentiation of patients with IPS and non-IPS than the established approach based on D(2) binding alone. Striatal D(2) receptor binding and the combination of DAT and IBZM binding asymmetries are the factors contributing most in separating these diagnostic groups.

Discrimination between parkinsonian syndrome and essential tremor using artificial neural network classification of quantified DaTSCAN data

BACKGROUND

In the semi-quantitative assessment of DaTSCAN images, it has been suggested that the ratio of tracer accumulation in the putamen to that in the caudate nucleus may be helpful and could allow parkinsonian syndromes progression to be assessed. Separation of ratio values has been reported when early Parkinson's disease is compared with essential tremor. The separation is lost, however, when the Parkinson's disease is not early stage.

OBJECTIVES

To evaluate whether a two-stage analysis can differentiate between parkinsonian syndromes, of various stages, and essential tremor, and whether such a two-stage analysis can be undertaken in a single step using artificial neural networks (ANNs).

METHODS

Data from 18 patients were analysed. Quantification was undertaken by manually drawing irregular regions of interest (ROIs): over each caudate nucleus and putamen and over an occipital cortex area near the posterior edge of the brain. A two-stage analysis was undertaken and was repeated, in a single step, using an ANN.

RESULTS

The first stage, of the two-stage analysis, identified 12 patients with non-early parkinsonian syndromes. The remaining six patients were then successfully classified into early parkinsonian syndromes and essential tremor. The ANN analysis successfully discriminated parkinsonian syndromes from essential tremor, in all patients, in a single step.

CONCLUSIONS

The two-stage process provides a method for classifying early disease without being compromised by the noise from non-early disease. The results of the single stage ANN analysis were very definite and it may be considered to have potential in the quantification of DaTSCAN images for clinical use.

IBZM tool: a fully automated expert system for the evaluation of IBZM SPECT studies

PURPOSE

Visual reading of [(123)I]IBZM SPECT scans depends on the experience of the interpreter. Therefore, semi-quantification of striatal IBZM uptake is commonly considered mandatory. However, semi-quantification is time consuming and prone to error, particularly if the volumes of interest (VOIs) are positioned manually. Therefore, the present paper proposes a new software tool ("IBZM tool") for fully automated and standardised processing, evaluation and documentation of [(123)I]IBZM SPECT scans.

METHODS

The IBZM tool is an easy-to-use SPM toolbox. It includes automated procedures for realignment and summation of multiple frames (motion correction), stereotactic normalisation, scaling, VOI analysis of striatum-to-reference ratio R, classification of R and standardised display. In order to evaluate the tool, which was developed at the University of Hamburg, the tool was transferred to the University of Hannover. There it was applied to 27 well-documented subjects: eight patients with multi-system atrophy (MSA), 12 patients with Parkinson's disease (PD) and seven controls. The IBZM tool was compared with manual VOI analysis.

RESULTS

The sensitivity and specificity of the IBZM tool for the differentiation of the MSA subjects from the controls were 100% and 86%, respectively. The IBZM tool provided improved statistical power compared with manual VOI analysis.

CONCLUSION

The IBZM tool is an expert system for the detection of reduced striatal D(2) availability on [(123)I]IBZM SPECT scans. The standardised documentation supports visual and semi-quantitative evaluation, and it is useful for presenting the findings to the referring physician. The IBZM tool has the potential for widespread use, since it appears to be fairly independent of the performance characteristics of the particular SPECT system used. The tool is available free of charge.

Comparison of different methods of DatSCAN quantification

BACKGROUND

The quantification of DaTSCAN images can be used as an adjunct to visual assessment to differentiate between Parkinson's syndrome and essential tremor. Many programs have been written to assess the relative uptake in the striatum.

AIM

To compare two of the commercially available programs: QuantiSPECT, which analyses isolated data in two dimensions, and BRASS, which performs three-dimensional processing referencing a normal image template.

METHOD

Twenty-two patients (11 with Parkinson's syndrome and 11 with essential tremor) were visually assessed by two nuclear medicine consultants. The patient data were then processed using two commercial programs to determine the relative uptake in the striatum. A comparison of the results from the programs was performed, together with a comparison with the visual assessment. The inter-operator and intra-operator variabilities were also ascertained.

RESULTS

All programs and processing methods could distinguish between Parkinson's syndrome and essential tremor. There was also a good correlation between the results from the three- and two-dimensional methods. The intra-operator and inter-operator variabilities were dependent on the amount of operator intervention.

CONCLUSION

Both programs allowed statistical differentiation between Parkinson's syndrome and essential tremor. Strict operator protocols are needed with QuantiSPECT to reduce inter- and intra-operator variation. The three-dimensional method (BRASS) gave greater concordance than the two-dimensional method (QuantiSPECT) with the visual assessment, but at a cost of increased operator time.