Evidence map›Paper›PMID 28521772›Full record

ArticleCardiovascular ultrasound2017

Feasibility and relevance of compound strain imaging in non-stenotic arteries: comparison between individuals with cardiovascular diseases and healthy controls.

Martijn F H Maessen, Thijs M H Eijsvogels, Ayla Grotens, Maria T E Hopman, Dick H J Thijssen, Hendrik H G Hansen

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Article in Cardiovascular ultrasound, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Martijn F H MaessenDepartment of Physiology, Radboud university medical center, Nijmegen, The Netherlands.
Thijs M H EijsvogelsDepartment of Physiology, Radboud university medical center, Nijmegen, The Netherlands.
Ayla GrotensDepartment of Physiology, Radboud university medical center, Nijmegen, The Netherlands.
Maria T E HopmanDepartment of Physiology, Radboud university medical center, Nijmegen, The Netherlands.
Dick H J ThijssenDepartment of Physiology, Radboud university medical center, Nijmegen, The Netherlands.
Hendrik H G HansenDepartment of Radiology and Nuclear Medicine, Radboud university medical center, Medical UltraSound Imaging Center (MUSIC), P.O. Box 9101 (766), 6500, HB, Nijmegen, The Netherlands. Rik.Hansen@radboudumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCompound strain imaging is a novel method to noninvasively evaluate arterial wall deformation which has recently shown to enable differentiation between fibrous and (fibro-)atheromatous plaques in patients with severe stenosis. We tested the hypothesis that compound strain imaging is feasible in non-stenotic arteries and provides incremental discriminative power to traditional measures of vascular health (i.e., distensibility coefficient (DC), central pulse wave velocity [cPWV], and intima-media thickness [IMT]) for differentiating between participants with and without a history of cardiovascular diseases (CVD).

methodsSeventy two participants (60 ± 7 years) with non-stenotic arteries (IMT < 1.1 mm) were categorized in healthy participants (CON, n = 36) and CVD patients (n = 36) based on CVD history. Participants underwent standardised ultrasound-based assessment (DC, cPWV, and IMT) and compound strain imaging (radial [RS] and circumferential [CS] strain) in left common carotid artery. Area under receiver operating characteristics (AROC)-curve was used to determine the discriminatory power between CVD and CON of the various measures.

resultsCON had a significantly (P < 0.05) smaller carotid IMT (0.68 [0.58 to 0.76] mm) than CVD patients (0.76 [0.68 to 0.80] mm). DC, cPWV, RS, and CS did not significantly differ between groups (P > 0.05). A higher CS or RS was associated with a higher DC (CS: r = -0.32;p < 0.05 and RS: r = 0.24;p < 0.05) and lower cPWV (CS: r = 0.24;p < 0.05 and RS: r = -0.25;p < 0.05). IMT could identify CVD (AROC: 0.66, 95%-CI: 0.53 to 0.79), whilst the other measurements, alone or in combination, did not significantly increase the discriminatory power compared to IMT.

conclusionsIn non-stenotic arteries, compound strain imaging is feasible, but does not seem to provide incremental discriminative power to traditional measures of vascular health for differentiation between individuals with and without a history of CVD.

Indexed as

AgedCardiovascular DiseasesCarotid Intima-Media ThicknessCase-Control StudiesCross-Sectional StudiesFeasibility StudiesHumansMaleMiddle AgedPredictive Value of TestsPulse Wave AnalysisROC CurveUltrasonographyVascular ResistanceCardiovascular assessmentIntima media thicknessMyocardial infarctionStrain imagingUltrasound imaging

Identifiers

PMID28521772
PMCPMC5437491

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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.