Evidence map›Paper›PMID 31901793›Full record

ArticleNeuroImage. Clinical2020

Novel data-driven, equation-free method captures spatio-temporal patterns of neurodegeneration in Parkinson's disease: Application of dynamic mode decomposition to PET.

Jessie Fanglu Fu, Ivan S Klyuzhin, Martin J McKeown, A Jon Stoessl, Vesna Sossi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Next-generation molecular imaging of cardiac fibrosis.The international journal of cardiovascular imaging · 2026
    Review
  3. Article
  4. Article
  5. Data-driven prediction in dynamical systems: recent developments.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
    Article
  6. Article
  7. NRM 2021 Abstract Booklet.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
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 2 institutions in 1 country.

Jessie Fanglu FuDepartment of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada. Electronic address: jfu@phas.ubc.ca.
Ivan S KlyuzhinDivision of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada.
Martin J McKeownDivision of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, BC, Canada.
A Jon StoesslDivision of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, BC, Canada.
Vesna SossiDepartment of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
University of British Columbia · CAVancouver Coastal Health · CA

Funding

CIHR
6 · The paper itself

Abstract

Most neurodegenerative disorders are characterized by progressive loss of neurons throughout the course of disease in the form of specific spatio-temporal patterns. To capture and quantify these coherent patterns across both space and time, traditionally one would either fit a pre-defined model with spatial and temporal parameters or apply analysis in the spatial and temporal domains separately. In this work, we introduce and validate the use of dynamic mode decomposition (DMD), a data-driven multivariate approach, to extract coupled spatio-temporal patterns simultaneously. We apply the method to examine progressive dopaminergic degeneration in 41 patients with Parkinson's disease (PD) using [

Indexed as

AgedDopamineFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedNeuroimagingParkinson DiseasePositron-Emission TomographyPutamenTetrabenazine(11C)-(+)-alpha-dihydrotetrabenazineDopamineTetrabenazineDopaminergic systemNovel pattern analysisParkinson's diseaseSpatio-temporal patterns

Identifiers

PMID31901793
PMCPMC6948364
OpenAlexW2998516355

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.