Differential diagnosis of parkinsonism: a head-to-head comparison of FDG PET and MIBG scintigraphy

Accuracy of 18F-FDG PET Imaging in Differentiating Parkinson's Disease from Atypical Parkinsonian Syndromes: A Systematic Review and Meta-Analysis

RATIONALE AND OBJECTIVE

To quantitatively assess the accuracy of 18F-FDG PET in differentiating Parkinson's Disease (PD) from Atypical Parkinsonian Syndromes (APSs).

METHODS

PubMed, Embase, and Web of Science databases were searched to identify studies published from the inception of the databases up to June 2024 that used 18F-FDG PET imaging for the differential diagnosis of PD and APSs. The risk of bias in the included studies was assessed using the QUADAS-2 or QUADAS-AI tool. Bivariate random-effects models were used to calculate the pooled sensitivity, specificity, and the area under the curves (AUC) of summary receiver operating characteristic (SROC).

RESULTS

24 studies met the inclusion criteria, involving a total of 1508 PD patients and 1370 APSs patients. 12 studies relied on visual interpretation by radiologists, of which the pooled sensitivity, specificity, and SROC-AUC for direct visual interpretation in diagnosing PD were 96% (95%CI: 91%, 98%), 90% (95%CI: 83%, 95%), and 0.98 (95%CI: 0.96, 0.99), respectively; the pooled sensitivity, specificity, and SROC-AUC for visual interpretation supported by univariate algorithms in diagnosing PD were 93% (95%CI: 90%, 95%), 90% (95%CI: 85%, 94%), and 0.96 (95%CI: 0.94, 0.97), respectively. 12 studies relied on artificial intelligence (AI) to analyze 18F-FDG PET imaging data. The pooled sensitivity, specificity, and SROC-AUC of machine learning (ML) for diagnosing PD were 87% (95%CI: 82%, 91%), 91% (95%CI: 86%, 94%), and 0.95 (95%CI: 0.93, 0.96), respectively. The pooled sensitivity, specificity, and SROC-AUC of deep learning (DL) for diagnosing PD were 97% (95%CI: 95%, 98%), 95% (95%CI: 89%, 98%), and 0.98 (95%CI: 0.96, 0.99), respectively.

CONCLUSION

18F-FDG PET has a high accuracy in differentiating PD from APS, among which AI-assisted automatic classification performs well, with a diagnostic accuracy comparable to that of radiologists, and is expected to become an important auxiliary means of clinical diagnosis in the future.

Cerebral Glucose Metabolism Is a Valuable Predictor of Survival in Patients with Lewy Body Diseases

OBJECTIVE

Patients with Lewy body diseases have an increased risk of dementia, which is a significant predictor for survival. Posterior cortical hypometabolism on [18F]fluorodeoxyglucose positron emission tomography (PET) precedes the development of dementia by years. We therefore examined the prognostic value of cerebral glucose metabolism for survival.

METHODS

We enrolled patients diagnosed with Parkinson's disease (PD), Parkinson's disease with dementia, or dementia with Lewy bodies who underwent [18F]fluorodeoxyglucose PET. Regional cerebral metabolism of each patient was analyzed by determining the expression of the PD-related cognitive pattern (Z-score) and by visual PET rating. We analyzed the predictive value of PET for overall survival using Cox regression analyses (age- and sex-corrected) and calculated prognostic indices for the best model.

RESULTS

Glucose metabolism was a significant predictor of survival in 259 included patients (n = 118 events; hazard ratio: 1.4 [1.2-1.6] per Z-score; hazard ratio: 1.8 [1.5-2.2] per visual PET rating score; both p < 0.0001). Risk stratification with visual PET rating scores yielded a median survival of 4.8, 6.8, and 12.9 years for patients with severe, moderate, and mild posterior cortical hypometabolism (median survival not reached for normal cortical metabolism). Stratification into 5 groups based on the prognostic index revealed 10-year survival rates of 94.1%, 78.3%, 34.7%, 0.0%, and 0.0%.

INTERPRETATION

Regional cerebral glucose metabolism is a significant predictor of survival in Lewy body diseases and may allow an earlier survival prediction than the clinical milestone "dementia." Thus, [18F]fluorodeoxyglucose PET may improve the basis for therapy decisions, especially for invasive therapeutic procedures like deep brain stimulation in Parkinson's disease. ANN NEUROL 2024;96:539-550.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

PURPOSE

Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA).

METHODS

FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level.

RESULTS

Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912).

CONCLUSION

Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy

BACKGROUND

To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS).

OBJECTIVES

To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice.

METHODS

This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern.

RESULTS

Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample.

CONCLUSIONS

Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Primary lateral sclerosis plus parkinsonism: a case report

BACKGROUND

The standard of diagnosing primary lateral sclerosis, the Pringle criteria, requires three years of purely upper motor neuron symptom presentation before confirming diagnosis. This classic standard has been questioned on occasion due to its restrictive range of both time period and symptomatic exhibition.

CASE PRESENTATION

This case report will review a 57-year-old Caucasian female who presented with pyramidal and extrapyramidal features suggestive of the exceedingly rare disease primary lateral sclerosis plus parkinsonism. We will describe the mixture of upper motor neuron signs and striking parkinsonian symptoms experienced by the patient, as well as the full diagnostic workup leading to her preliminary diagnosis. The details of this case will then be utilized to explore the diagnostic criteria of primary lateral sclerosis, as well as to work through the differential of conditions resembling Parkinson's disease.

CONCLUSIONS

The current criteria to diagnose primary lateral sclerosis may be excluding patients with the disease and is an ongoing area of investigation. A thorough differential including other neurodegenerative conditions is necessary to consider and requires long-term follow-up.

Cardiac sympathetic innervation in Parkinson's disease versus multiple system atrophy

PURPOSE

The aims of this study were to evaluate the diagnostic accuracy of the dual imaging method combining cardiac iodine-123-metaiodobenzylguanidine single-photon emission computed tomography combined with low-dose chest computed tomography compared to routine cardiac scintigraphy, and assess regional differences in tracer distribution and the relationships between imaging and autonomic function in Parkinson's disease and multiple system atrophy.

METHODS

A prospective study including 19 Parkinson's disease and 12 multiple system atrophy patients was performed. Patients underwent clinical evaluation, iodine-123-metaiodobenzylguanidine single-photon emission computed tomography combined with chest computed tomography, planar scintigraphy, and cardiovascular autonomic function tests.

RESULTS

Co-registration of single-photon emission computed tomography and chest computed tomography resulted in three groups with distinct patterns of tracer uptake: homogeneous, non-homogeneously reduced and absent. There was a significant difference in group allocation among patients with multiple system atrophy and Parkinson's disease (p = 0.001). Most multiple system atrophy patients showed homogeneous uptake, and the majority of Parkinson's disease patients showed absent cardiac tracer uptake. We identified a pattern of heterogeneous cardiac tracer uptake in both diseases with reductions in the apex and the lateral myocardial wall. Sympathetic dysfunction reflected by a missing blood pressure overshoot during Valsalva manoeuvre correlated with cardiac tracer distribution in Parkinson's disease patients (p < 0.001).

CONCLUSIONS

The diagnostic accuracy of the dual imaging method and routine cardiac scintigraphy were similar. Anatomical tracer allocation provided by the dual imaging method of cardiac iodine-123-metaiodobenzylguanidine single-photon emission computed tomography and chest computed tomography identified a heterogeneous subgroup of Parkinson's disease and multiple system atrophy patients with reduced cardiac tracer uptake in the apex and the lateral wall. Sympathetic dysfunction correlated with cardiac imaging in Parkinson's disease patients.

The potential role of the cardiac MIBG scan in differentiating the drug-induced Parkinsonism from Parkinson’s disease

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MIBG scan is more positive in the PD group than the DIP.

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There is a significant difference in MIBG uptake between the PD and DIP groups.

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MIBG scan can be used to determine the prognosis of DIP.

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MIBG scan is 84.4% sensitive and 86.36% specific in diagnosing PD.

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MIBG scan is useful in better referring the patients to related centers.

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An Update on Gene Therapy Approaches for Parkinson's Disease: Restoration of Dopaminergic Function

At present there is a significant unmet need for clinically available treatments for Parkinson’s disease (PD) patients to stably restore balance to dopamine network function, leaving patients with inadequate management of symptoms as the disease progresses. Gene therapy is an attractive approach to impart a durable effect on neuronal function through introduction of genetic material to reestablish dopamine levels and/or functionally recover dopaminergic signaling by improving neuronal health. Ongoing clinical gene therapy trials in PD are focused on enzymatic enhancement of dopamine production and/or the restoration of the nigrostriatal pathway to improve dopaminergic network function. In this review, we discuss data from current gene therapy trials for PD and recent advances in study design and surgical approaches.

Update on neuroimaging in non-Alzheimer's disease dementia: a focus on the Lewy body disease spectrum

PURPOSE OF REVIEW

An accurate differential diagnosis between Alzheimer's disease (AD) and non-AD dementia is of paramount importance to study disease mechanisms, define prognosis, and select patients for disease-specific treatments. The purpose of the present review is to describe the most recent neuroimaging studies in Lewy body disease spectrum (LBDS), focusing on differences with AD.

RECENT FINDINGS

Different neuroimaging methods are used to investigate patterns of alterations, which can be helpful to distinguish LBDS from AD. Positron emission tomography radiotracers and advanced MRI structural and functional methods discriminate these two conditions with increasing accuracy. Prodromal disease stages can be identified, allowing an increasingly earlier diagnosis.

SUMMARY

Neuroimaging biomarkers can aid in obtaining the best diagnostic accuracy in LBDS. Despite the main role of neuroimaging in clinical setting is to exclude secondary causes of dementia, structural and metabolic imaging techniques give an essential help to study in-vivo pathophysiological mechanisms of diseases. The importance of neuroimaging in LBDS is given by the increasing number of imaging biomarker developed and studied in the last years.