Evidence map›Paper›PMID 35432151›Full record

ArticleFrontiers in neurology2022

Semi-automated Segmentation and Quantification of Perivascular Spaces at 7 Tesla in COVID-19.

Mackenzie T Langan, Derek A Smith, Gaurav Verma, Oleksandr Khegai, Sera Saju, Shams Rashid, Daniel Ranti, Matthew Markowitz, Puneet Belani, Nathalie Jette and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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

17 authors at 3 institutions in 1 country.

Mackenzie T LanganIcahn School of Medicine at Mount Sinai, New York, NY, United States.
Derek A SmithBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Gaurav VermaBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Oleksandr KhegaiBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Sera SajuBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Shams RashidBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Daniel RantiIcahn School of Medicine at Mount Sinai, New York, NY, United States.
Matthew MarkowitzThe Graduate Center, City University of New York, New York, NY, United States.
Puneet BelaniDepartment of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Nathalie JetteDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Brian MathewDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Jonathan GoldsteinDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Claudia F E KirschBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Laurel S MorrisBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Jacqueline H BeckerDivision of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Bradley N DelmanBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Priti BalchandaniBiomedical Engineering and Imaging Institute at Mount Sinai School of Medicine, New York, NY, United States.
Icahn School of Medicine at Mount Sinai · USNorthwell Health · USThe Graduate Center, CUNY · US

Funding

7T Neurosurgical Mapping Protocol for Endoscopic Resection of Skull Base TumorsR01CA202911 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BALCHANDANI, PRITI · 2016 to 2020
$2.1M
Identifying the Long-Term Neurological Effects of COVID-19 Using 7 Tesla Multi-Modal MRIR21NS122389 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BALCHANDANI, PRITI · 2021 to 2021
$465k
NCI NIH HHS R01 CA202911NINDS NIH HHS R21 NS122389
6 · The paper itself

Abstract

While COVID-19 is primarily considered a respiratory disease, it has been shown to affect the central nervous system. Mounting evidence shows that COVID-19 is associated with neurological complications as well as effects thought to be related to neuroinflammatory processes. Due to the novelty of COVID-19, there is a need to better understand the possible long-term effects it may have on patients, particularly linkage to neuroinflammatory processes. Perivascular spaces (PVS) are small fluid-filled spaces in the brain that appear on MRI scans near blood vessels and are believed to play a role in modulation of the immune response, leukocyte trafficking, and glymphatic drainage. Some studies have suggested that increased number or presence of PVS could be considered a marker of increased blood-brain barrier permeability or dysfunction and may be involved in or precede cascades leading to neuroinflammatory processes. Due to their size, PVS are better detected on MRI at ultrahigh magnetic field strengths such as 7 Tesla, with improved sensitivity and resolution to quantify both concentration and size. As such, the objective of this prospective study was to leverage a semi-automated detection tool to identify and quantify differences in perivascular spaces between a group of 10 COVID-19 patients and a similar subset of controls to determine whether PVS might be biomarkers of COVID-19-mediated neuroinflammation. Results demonstrate a detectable difference in neuroinflammatory measures in the patient group compared to controls. PVS count and white matter volume were significantly different in the patient group compared to controls, yet there was no significant association between PVS count and symptom measures. Our findings suggest that the PVS count may be a viable marker for neuroinflammation in COVID-19, and other diseases which may be linked to neuroinflammatory processes.

Indexed as

7 T MRIcoronavirusFrangi filterneuroinflammationsemiautomatedVirchow Robin spaces

Identifiers

PMID35432151
PMCPMC9010775
OpenAlexW4220998777

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.