Literature DB >> 19577997

Validation of in vivo plaque characterisation by virtual histology in a rabbit model of atherosclerosis.

Jozef Van Herck1, Guido De Meyer, Guy Ennekens, Paul Van Herck, Arnold Herman, Christiaan Vrints.   

Abstract

AIMS: Most acute coronary syndromes are caused by plaque rupture. The risk of plaque rupture is related to plaque composition. The purpose of this study was to validate VH-IVUS for in vivo plaque characterisation. METHODS AND
RESULTS: Six rabbits were fed a cholesterol-supplemented diet for 12 to 18 months. Thereafter, VH-IVUS imaging of the aorta was performed. After sacrifice, the VH-IVUS images were matched to the corresponding histological cross sections. A total of 260 atherosclerotic plaques were analysed. VH-IVUS had a high sensitivity, specificity and positive predictive value for the detection of non-calcified thin cap fibroatheroma (88%, 96%, 87%, respectively) and calcified thin cap fibroatheroma (95%, 99%, 93%, respectively). These values were respectively 82%, 94%, 85% for non-calcified fibroatheroma and 78%, 98%, 84% for calcified fibroatheroma. The lowest values were obtained for pathological intimal thickening (74%, 92%, 70%, respectively). For all plaque types, VH-IVUS had a kappa-value of 0.79. Linear regression analysis and Bland-Altman plots showed a strong correlation between VH-IVUS and histology for fibrous tissue, fibrofatty tissue, necrotic calcified tissue and confluent necrotic core.
CONCLUSIONS: VH-IVUS showed a good accuracy for in vivo plaque characterisation and is a promising technique for the detection of the vulnerable plaque.

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Year:  2009        PMID: 19577997     DOI: 10.4244/eijv5i1a23

Source DB:  PubMed          Journal:  EuroIntervention        ISSN: 1774-024X            Impact factor:   6.534


  10 in total

Review 1.  Emerging applications of nanotechnology for the diagnosis and management of vulnerable atherosclerotic plaques.

Authors:  Shann S Yu; Ryan A Ortega; Brendan W Reagan; John A McPherson; Hak-Joon Sung; Todd D Giorgio
Journal:  Wiley Interdiscip Rev Nanomed Nanobiotechnol       Date:  2011-08-10

Review 2.  What Is the Clinical Utility of Intravascular Ultrasound?

Authors:  Eisha Wali; Sandeep Nathan
Journal:  Curr Cardiol Rep       Date:  2018-09-28       Impact factor: 2.931

3.  A Domain Enriched Deep Learning Approach to Classify Atherosclerosis using Intravascular Ultrasound Imaging.

Authors:  Max L Olender; Lambros S Athanasiou; Lampros K Michalis; Dimitris I Fotiadis; Elazer R Edelman
Journal:  IEEE J Sel Top Signal Process       Date:  2020-06-15       Impact factor: 6.856

4.  Site-specific intravascular ultrasound analysis of remodelling index and calcified necrosis patterns reveals novel blueprints for coronary plaque instability.

Authors:  Scott W Murray; Billal Patel; Rodney H Stables; Raphael A Perry; Nicholas D Palmer
Journal:  Cardiovasc Diagn Ther       Date:  2014-08

Review 5.  Whole animal imaging.

Authors:  Gurpreet Singh Sandhu; Luis Solorio; Ann-Marie Broome; Nicolas Salem; Jeff Kolthammer; Tejas Shah; Chris Flask; Jeffrey L Duerk
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010 Jul-Aug

6.  Multicenter assessment of the reproducibility of volumetric radiofrequency-based intravascular ultrasound measurements in coronary lesions that were consecutively stented.

Authors:  Jennifer Huisman; Rasmus Egede; Adam Rdzanek; Dirk Böse; Raimund Erbel; Janusz Kochman; Lisette Okkels Jensen; Job van der Palen; Marc Hartmann; Gary S Mintz; Clemens von Birgelen
Journal:  Int J Cardiovasc Imaging       Date:  2012-01-14       Impact factor: 2.357

Review 7.  IVUS-based imaging modalities for tissue characterization: similarities and differences.

Authors:  Hector M Garcìa-Garcìa; Bill D Gogas; Patrick W Serruys; Nico Bruining
Journal:  Int J Cardiovasc Imaging       Date:  2011-02-17       Impact factor: 2.357

8.  Impact of analyzing fewer image frames per segment during offline volumetric radiofrequency-based intravascular ultrasound measurements of target lesions prior to percutaneous coronary interventions.

Authors:  Jennifer Huisman; Marc Hartmann; Gary S Mintz; Gert K van Houwelingen; Martin G Stoel; Frits H A F de Man; Hans W Louwerenburg; Clemens von Birgelen
Journal:  Int J Cardiovasc Imaging       Date:  2011-03-19       Impact factor: 2.357

Review 9.  Molecular imaging of plaques in coronary arteries with PET and SPECT.

Authors:  Zhong-Hua Sun; Hairil Rashmizal; Lei Xu
Journal:  J Geriatr Cardiol       Date:  2014-09       Impact factor: 3.327

10.  Automated classification of dense calcium tissues in gray-scale intravascular ultrasound images using a deep belief network.

Authors:  Juhwan Lee; Yoo Na Hwang; Ga Young Kim; Ji Yean Kwon; Sung Min Kim
Journal:  BMC Med Imaging       Date:  2019-12-30       Impact factor: 1.930

  10 in total

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