Evidence map›Paper›PMID 31774054›Full record

ReviewDeutsches Arzteblatt international2019

Nuclear Imaging in the Diagnosis of Clinically Uncertain Parkinsonian Syndromes.

Ralph Buchert, Carsten Buhmann, Ivayla Apostolova, Philipp T Meyer, Jürgen Gallinat

Open access · bronzeAbstract readReview
In one paragraph

Review in Deutsches Arzteblatt international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Molecular Imaging Findings on Acute and Long-Term Effects of COVID-19 on the Brain: A Systematic Review.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
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  13. Differences in Striatal Metabolism in [Diagnostics (Basel, Switzerland) · 2022
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  15. [EJNMMI research · 2022
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  20. [Molecules (Basel, Switzerland) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Ralph BuchertDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf; Department of Neurology, University Medical Center Hamburg-Eppendorf; Department of Nuclear Medicine, Medical Center-University of Freiburg; Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf.
Carsten Buhmann
Ivayla Apostolova
Philipp T Meyer
Jürgen Gallinat
University Medical Center Hamburg-Eppendorf · DEKlinik und Poliklinik für Psychiatrie und Psychotherapie · DEUniversität Hamburg · DEUniversity of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParkinsonian syndromes are classified by etiology mainly on clinical grounds, that is, on the basis of the clinical manifestations and with the aid of conventional ancillary studies. In most cases, the clinical diagnosis is clear. In up to 30% of cases, however, the etiological classification remains uncertain after completion of the basic clinical diagnostic evaluation, and additional investigation with nuclear imaging may be indicated. In particular, cerebral single-photon emission computed tomography (SPECT) with dopamine transporter (DAT) ligands may be helpful. DAT-SPECT can be used to demonstrate or rule out nigrostriatal degeneration and thereby differentiate neurodegenerative parkinsonian syndromes from symptomatic parkinsonian syndromes and other differential diagnoses. Positron emission tomography (PET) with the glucose analogue [18F]fluorodeoxyglucose (FDG) can be used to identify disease-specific patterns of neuronal dysfunction/degeneration in order to differentiate the various neurodegenerative parkinsonian syndromes from one another.

methodsIn this review, we summarize the current state of the evidence on DAT-SPECT and FDG-PET for the indications mentioned above on the basis of a selective review of the literature.

resultsDAT-SPECT has been adequately validated as an in vivo marker for nigrostriatal degeneration. Studies using the clinical diagnosis of a movement disorders specialist over the course of the disease as a reference have shown that DAT- SPECT is 78-100% sensitive (median, 93%) and 70-100% specific (median, 89%) for the differentiation of neurodegenerative parkinsonian syndromes from symptomatic parkinsonism and other differential diagnoses in clinically unclear cases. DAT- SPECT scanning led to a change of diagnosis in 27-56% of patients (median, 43%) and to a change of treatment in 33-72% (median, 43%). FDG-PET enables the differentiation of atypical neurodegenerative parkinsonian syndromes from the idiopathic parkinsonian syndrome (i.e., Parkinson's disease proper) with high sensitivity and specificity (both approximately 90%), when the clinical diagnosis by a movement disorders specialist over the course of the disease is used as a reference.

conclusionDAT-SPECT has been well documented to be highly diagnostically accurate and to have a relevant influence on the diagnosis and treatment of patients with clinically uncertain parkinsonian or tremor syndrome. It has not yet been shown to improve patient-relevant endpoints such as mortality, morbidity, and health-related quality of life; proof of this will probably have to await the introduction of neuroprotective treatments. The current evidence for the high differential diagnostic accuracy of FDG-PET in neurodegenerative parkinsonian syndromes needs to be reinforced by prospective studies with neuropathological verification of the diagnosis.

Indexed as

Diagnosis, DifferentialHumansParkinsonian DisordersTomography, Emission-Computed, Single-Photon

Identifiers

PMID31774054
PMCPMC6912128
OpenAlexW2981597422

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.