Evidence map›Paper›PMID 40488989›Full record

ArticleLa Radiologia medica2025

Clinical MRI to predict motor and non-motor effects of deep brain stimulation in Parkinson disease.

Corrado Campisi, Giovanni Giulietti, Carlo Alberto Artusi, Federico D'Agata, Giovanni Morana, Claudia Ledda, Elisa Montanaro, Mario Coriasco, Leonardo Lopiano, Marco Bozzali

Abstract read
In one paragraph

Article in La Radiologia medica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Corrado Campisi'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Giovanni GiuliettiNeuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.
Carlo Alberto Artusi'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Federico D'Agata'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Giovanni Morana'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Claudia Ledda'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Elisa Montanaro'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Mario Coriasco'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Leonardo Lopiano'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy.
Marco Bozzali'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Via Cherasco 15, 10126, Turin, Italy. marco.bozzali@unito.it.ORCID http://orcid.org/0000-0002-0568-2026

Funding

Ministero della Salute PNRR-MAD-2022-12376496
6 · The paper itself

Abstract

purposeSubthalamic deep brain stimulation (STN-DBS) is a well-established intervention for advanced Parkinson's disease (PD). Routine neuroimaging can be used to estimate location and volume of activated tissue (VTA), by modeling the type of stimulator and stimulation parameters. We aimed here at developing a strategy based on clinical brain MRI scans to predict motor and non-motor outcomes of STN-DBS. MATERIALS AND

methodsWe included 25 consecutive patients with advanced PD eligible for STN-DBS. At baseline, patients underwent a comprehensive motor and cognitive/behavioral assessment, and conventional MRI. They underwent STN-DBS surgery, followed by a CT scan. Patients were reassessed 1 year later, while STN-DBS was active. Their neuroimaging data were used to calculate individual VTAs. The voxel-lesion-symptom-mapping (VLSM) toolbox, which allows to associate clinical variables with brain features of interest, was used to investigate associations between changes (in either direction) of motor, cognitive/behavioral scores between baseline and follow-up, and VTA subregions. Six newly enrolled patients were used to test the predictive value of this approach at a single subject level.

resultsVLSM analysis (p values corrected for multiple comparisons < 0.05) identified specific VTA subclusters associated with improved bradykinesia, verbal fluency, and mood state, and some others associated with worsening of tremor, long-term memory, and apathy. When considering cognitive/behavioral changes, an effect of hemisphere lateralization was observed, with modulation of the right basal ganglia being associated with symptoms' worsening, and left-side modulation associated with improvements. VTA subclusters predictive for clinical changes were mostly located outside the STN, indicating the importance of networks over single nuclei simulation.

conclusionThis approach suggests a possible way to personalize surgical planning, DBS-implant choice, and stimulation programing in the framework of precision medicine.

Indexed as

Deep Brain StimulationMagnetic Resonance ImagingParkinson DiseaseAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsSubthalamic NucleusTreatment OutcomeBehaviorCognitionElectrical stimulationMRIParkinson’s disease

Identifiers

PMID40488989
PMCPMC12367973

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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.