Evidence map›Paper›PMID 34679440›Full record

ArticleDiagnostics (Basel, Switzerland)2021

An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms.

Sricharan S Veeturi, Nandor K Pinter, Andre Monteiro, Ammad A Baig, Hamid H Rai, Muhammad Waqas, Adnan H Siddiqui, Hamidreza Rajabzadeh-Oghaz, Vincent M Tutino

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

9 authors.

Sricharan S VeeturiCanon Stroke and Vascular Research Center, Buffalo, NY 14203, USA.ORCID 0000-0002-8114-3817
Nandor K PinterDepartment of Neurosurgery, University at Buffalo, Buffalo, NY 14203, USA.ORCID 0000-0002-7714-143X
Andre MonteiroDepartment of Neurosurgery, University at Buffalo, Buffalo, NY 14203, USA.
Ammad A BaigDepartment of Neurosurgery, University at Buffalo, Buffalo, NY 14203, USA.ORCID 0000-0002-8241-6864
Hamid H RaiDepartment of Neurosurgery, University at Buffalo, Buffalo, NY 14203, USA.
Muhammad WaqasCanon Stroke and Vascular Research Center, Buffalo, NY 14203, USA.
Adnan H SiddiquiCanon Stroke and Vascular Research Center, Buffalo, NY 14203, USA.
Hamidreza Rajabzadeh-OghazCanon Stroke and Vascular Research Center, Buffalo, NY 14203, USA.
Vincent M TutinoCanon Stroke and Vascular Research Center, Buffalo, NY 14203, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a tool for the visualization, quantification and objective identification of regions with VWE.

methodsN = 41 3D T1-MRI and 3D TOF-MRA IA images from 38 patients were obtained and co-registered. A contrast-enhanced MRI was normalized by the enhancement intensity of the pituitary stalk and signal intensities were mapped onto the surface of IA models generated from segmented MRA. N = 30 IAs were used to identify the optimal signal intensity value to distinguish the enhancing and non-enhancing regions (marked by an experienced neuroradiologist). The remaining IAs (n = 11) were used to validate the threshold. We tested if the enhancement area ratio (EAR-ratio of the enhancing area to the IA surface-area) could identify high risk aneurysms as identified by the ISUIA clinical score.

resultsA normalized intensity of 0.276 was the optimal threshold to delineate enhancing regions, with a validation accuracy of 81.7%. In comparing the overlap between the identified enhancement regions against those marked by the neuroradiologist, our method had a dice coefficient of 71.1%. An EAR of 23% was able to discriminate high-risk cases with an AUC of 0.7.

conclusionsWe developed and validated a pipeline for the visualization and objective identification of VWE regions that could potentially help evaluation of IAs become more reliable and consistent.

Indexed as

contrast-enhanced MRIintracranial aneurysmsrupture risksemi-automatedT1 non-enhanced MRIvessel wall enhancement

Identifiers

PMID34679440
PMCPMC8534502

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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.