Evidence map›Paper›PMID 38789122›Full record

ArticleAJNR. American journal of neuroradiology2024

Diagnostic Accuracy of Preoperative Quantitative Susceptibility Mapping for Detecting Histologic Intraplaque Hemorrhage in Cervical ICA Stenosis in Patients Undergoing Carotid Endarterectomy.

Daisuke Oomori, Yosuke Akamatsu, Ikuko Uwano, Futoshi Mori, Tsuyoshi Matsuda, Ryo Sugimoto, Michiko Suzuki, Shunrou Fujiwara, Masakazu Kobayashi, Makoto Sasaki and 3 more

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Daisuke OomoriFrom the Department of Neurosurgery (D.O., Y.A., S.F., M.K., K.O.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.
Yosuke AkamatsuFrom the Department of Neurosurgery (D.O., Y.A., S.F., M.K., K.O.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-8149-2988
Ikuko UwanoDivision of Ultrahigh Field MRI (I.U., F.M., T.M., M. Suzuki), Institute for Biomedical Sciences, Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0003-3470-7795
Futoshi MoriDivision of Ultrahigh Field MRI (I.U., F.M., T.M., M. Suzuki), Institute for Biomedical Sciences, Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-3698-2507
Tsuyoshi MatsudaDivision of Ultrahigh Field MRI (I.U., F.M., T.M., M. Suzuki), Institute for Biomedical Sciences, Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0001-8914-8236
Ryo SugimotoDepartment of Molecular Diagnostic Pathology (R.S., N.Y.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.
Michiko SuzukiDepartment of Radiology (M.S, K.Y), Iwate Medical University School of Medicine, Yahaba-cho, Japan.
Shunrou FujiwaraFrom the Department of Neurosurgery (D.O., Y.A., S.F., M.K., K.O.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-5800-515X
Masakazu KobayashiFrom the Department of Neurosurgery (D.O., Y.A., S.F., M.K., K.O.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0001-8205-3090
Makoto SasakiDivision of Ultrahigh Field MRI (I.U., F.M., T.M., M. Suzuki), Institute for Biomedical Sciences, Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-3108-4361
Kunihiro YoshiokaDepartment of Radiology (M.S, K.Y), Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-0100-042X
Naoki YanagawaDepartment of Molecular Diagnostic Pathology (R.S., N.Y.), Iwate Medical University School of Medicine, Yahaba-cho, Japan.ORCID 0000-0002-0818-7151
Kuniaki OgasawaraFrom the Department of Neurosurgery (D.O., Y.A., S.F., M.K., K.O.), Iwate Medical University School of Medicine, Yahaba-cho, Japan kuogasa@iwate-med.ac.jp.ORCID 0000-0001-8529-6688

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeQuantitative susceptibility mapping has been proposed to assess intraplaque hemorrhage (IPH) in the carotid artery. The purpose of this study was to compare the diagnostic accuracy of preoperative quantitative susceptibility mapping with that of the conventional T1-weighed 3D-FSE sequence for detecting IPH in cervical ICA stenosis in patients undergoing carotid endarterectomy by using histology as the reference standard. MATERIALS AND

methodsCarotid T1-weighted 3D-FSE and QSM images were obtained from 16 patients with cervical ICA stenosis before carotid endarterectomy. Relative signal intensity and susceptibility of the ICA were measured on 3 axial images, including the location of most severe stenosis on T1-weighted 3D-FSE and quantitative susceptibility mapping images, respectively. Three transverse sections of carotid plaques excised by carotid endarterectomy, which corresponded with images on MR imaging, were stained with H&E, antibody against glycophorin A, and Prussian blue, and the relative area of histologic IPH was calculated.

resultsThe correlation coefficient was significantly greater between susceptibility and relative area-histologic IPH (

conclusionsPre-carotid endarterectomy quantitative susceptibility mapping detects histologic IPH in cervical ICA stenosis more accurately than preoperative T1-weighted 3D-FSE imaging.

Indexed as

Carotid StenosisEndarterectomy, CarotidAgedAged, 80 and overCarotid Artery, InternalFemaleHemorrhageHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleMiddle AgedPreoperative CareReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID38789122
PMCPMC11448986

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Registered trials

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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.