Evidence map›Paper›PMID 33557411›Full record

ArticleBrain sciences2021

Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia.

Salvatore Nigro, Benedetta Tafuri, Daniele Urso, Roberto De Blasi, Maria Elisa Frisullo, Maria Rosaria Barulli, Rosa Capozzo, Alessia Cedola, Giuseppe Gigli, Giancarlo Logroscino

Abstract read
In one paragraph

Article in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. 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

10 authors.

Salvatore NigroInstitute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy.
Benedetta TafuriCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.ORCID 0000-0002-2931-6039
Daniele UrsoCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.ORCID 0000-0002-4503-0110
Roberto De BlasiCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.
Maria Elisa FrisulloCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.
Maria Rosaria BarulliCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.
Rosa CapozzoCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.
Alessia CedolaInstitute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy.
Giuseppe GigliInstitute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy.
Giancarlo LogroscinoCenter for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari 'Aldo Moro, "Pia Fondazione Cardinale G. Panico", 73039 Tricase, Italy.

Funding

Regione Puglia and CNR for Tecnopolo per la Medicina di Precisione. D.G.R. n. 2117 of 21.11.2018. D.G.R. n. 2117 of 21.11.2018.Regione Puglia (DGR n. 1284 - 27.05.2015) for the project "Registro Regionale per la SLA, la FTD-P e le patologie affini in Regione Puglia (SLAPDem register- www.slapdem.it) and from Italian Ministry of Health (Ricerca Corrente) DGR n. 1284 - 27.05.2015
6 · The paper itself

Abstract

Recent research on behavioral variant frontotemporal dementia (bvFTD) has shown that personality changes and executive dysfunctions are accompanied by a disease-specific anatomical pattern of cortical and subcortical atrophy. We investigated the structural topological network changes in patients with bvFTD in comparison to healthy controls. In particular, 25 bvFTD patients and 20 healthy controls underwent structural 3T MRI. Next, bilaterally averaged values of 34 cortical surface areas, 34 cortical thickness values, and six subcortical volumes were used to capture single-subject anatomical connectivity and investigate network organization using a graph theory approach. Relative to controls, bvFTD patients showed altered small-world properties and decreased global efficiency, suggesting a reduced ability to combine specialized information from distributed brain regions. At a local level, patients with bvFTD displayed lower values of local efficiency in the cortical thickness of the caudal and rostral middle frontal gyrus, rostral anterior cingulate, and precuneus, cuneus, and transverse temporal gyrus. A significant correlation was also found between the efficiency of caudal anterior cingulate thickness and Mini-Mental State Examination (MMSE) scores in bvFTD patients. Taken together, these findings confirm the selective disruption in structural brain networks of bvFTD patients, providing new insights on the association between cognitive decline and graph properties.

Indexed as

behavioral variant frontotemporal dementiagraph analysisMRIstructural covariance network

Identifiers

PMID33557411
PMCPMC7915789

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.