Literature DB >> 20526859

Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) of atherosclerotic plaque angiogenesis.

Claudia Calcagno1, Venkatesh Mani, Sarayu Ramachandran, Zahi A Fayad.   

Abstract

Atherosclerosis is a progressive systemic disease of the large arteries characterized by the formation of plaques in the vessel wall. Despite our knowledge of its pathogenesis, many vulnerable plaques still remain undiagnosed while in their asymptomatic phase and manifest for the first time with dramatic clinical events, such as stroke or myocardial infarction. In recent years, it is becoming clearer that sudden clinical events do not necessarily correlate with the degree of luminal obstruction caused by lesions, but rather with plaque composition. In particular, the degree of plaque inflammation is important in the pathogenesis of atherosclerosis and is considered a good marker of high-risk/vulnerable plaques. The presence of inflammatory infiltrate and plaque neovascularization are both histological hallmarks of atherosclerotic plaque inflammation. Therefore, plaque angiogenesis represents an attractive target to try and identify asymptomatic high-risk lesions. Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a technique that has been used extensively in the past to study the vascularity of tumors and its changes following therapeutic intervention. Recently, delayed and dynamic contrast enhanced (CE) MRI have been proposed as non-invasive tools to study the extent of plaque neovascularization in animals and patients with atherosclerosis. In this review, we will provide a brief introduction on DCE-MRI acquisition and analysis techniques. We will follow this with a description of contrast enhanced MR methods for the detection and quantification of neovasculature in atherosclerosis, with an emphasis on DCE-MRI. Finally, we will examine the current limitations and challenges faced by DCE-MRI and briefly discuss its future applications in the context of atherosclerosis.

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Year:  2010        PMID: 20526859     DOI: 10.1007/s10456-010-9172-2

Source DB:  PubMed          Journal:  Angiogenesis        ISSN: 0969-6970            Impact factor:   9.596


  20 in total

Review 1.  Lymphocytes and the adventitial immune response in atherosclerosis.

Authors:  Kirsti A Campbell; Michael J Lipinski; Amanda C Doran; Marcus D Skaflen; Valentin Fuster; Coleen A McNamara
Journal:  Circ Res       Date:  2012-03-16       Impact factor: 17.367

2.  Imaging the efficacy of anti-inflammatory liposomes in a rabbit model of atherosclerosis by non-invasive imaging.

Authors:  Mark E Lobatto; Claudia Calcagno; Josbert M Metselaar; Gert Storm; Erik S G Stroes; Zahi A Fayad; Willem J M Mulder
Journal:  Methods Enzymol       Date:  2012       Impact factor: 1.600

3.  Multimodal Positron Emission Tomography Imaging to Quantify Uptake of 89Zr-Labeled Liposomes in the Atherosclerotic Vessel Wall.

Authors:  Mark E Lobatto; Tina Binderup; Philip M Robson; Luuk F P Giesen; Claudia Calcagno; Julia Witjes; Francois Fay; Samantha Baxter; Chang Ho Wessel; Mootaz Eldib; Jason Bini; Sean D Carlin; Erik S G Stroes; Gert Storm; Andreas Kjaer; Jason S Lewis; Thomas Reiner; Zahi A Fayad; Willem J M Mulder; Carlos Pérez-Medina
Journal:  Bioconjug Chem       Date:  2019-06-07       Impact factor: 4.774

4.  Tumor angiogenesis phenotyping by nanoparticle-facilitated magnetic resonance and near-infrared fluorescence molecular imaging.

Authors:  Peter A Jarzyna; Lisette H Deddens; Benjamin H Kann; Sarayu Ramachandran; Claudia Calcagno; Wei Chen; Anita Gianella; Rick M Dijkhuizen; Arjan W Griffioen; Zahi A Fayad; Willem J M Mulder
Journal:  Neoplasia       Date:  2012-10       Impact factor: 5.715

5.  Three-dimensional dynamic contrast-enhanced MRI for the accurate, extensive quantification of microvascular permeability in atherosclerotic plaques.

Authors:  Claudia Calcagno; Mark E Lobatto; Hadrien Dyvorne; Philip M Robson; Antoine Millon; Max L Senders; Olivier Lairez; Sarayu Ramachandran; Bram F Coolen; Alexandra Black; Willem J M Mulder; Zahi A Fayad
Journal:  NMR Biomed       Date:  2015-08-30       Impact factor: 4.044

6.  Assessment of carotid plaque neovascularization by contrast-enhanced ultrasound and high sensitivity C-reactive protein test in patients with acute cerebral infarction: a comparative study.

Authors:  Rong Xu; Xiaohua Yin; Weixin Xu; Lin Jin; Min Lu; Yingchun Wang
Journal:  Neurol Sci       Date:  2016-03-28       Impact factor: 3.307

7.  Relationship between particulate matter exposure and atherogenic profile in "Ground Zero" workers as shown by dynamic contrast enhanced MR imaging.

Authors:  Venkatesh Mani; Stephanie K Wong; Simonette T Sawit; Claudia Calcagno; Cynara Maceda; Sarayu Ramachandran; Zahi A Fayad; Jacqueline Moline; Mary Ann McLaughlin
Journal:  Int J Cardiovasc Imaging       Date:  2012-11-23       Impact factor: 2.357

8.  Spatio-temporal texture (SpTeT) for distinguishing vulnerable from stable atherosclerotic plaque on dynamic contrast enhancement (DCE) MRI in a rabbit model.

Authors:  Tao Wan; Anant Madabhushi; Alkystis Phinikaridou; James A Hamilton; Ning Hua; Tuan Pham; Jovanna Danagoulian; Ross Kleiman; Andrew J Buckler
Journal:  Med Phys       Date:  2014-04       Impact factor: 4.071

9.  PET/MR Imaging of Malondialdehyde-Acetaldehyde Epitopes With a Human Antibody Detects Clinically Relevant Atherothrombosis.

Authors:  Max L Senders; Xuchu Que; Young Seok Cho; Calvin Yeang; Hannah Groenen; Francois Fay; Claudia Calcagno; Anu E Meerwaldt; Simone Green; Phuong Miu; Mark E Lobatto; Thomas Reiner; Zahi A Fayad; Joseph L Witztum; Willem J M Mulder; Carlos Pérez-Medina; Sotirios Tsimikas
Journal:  J Am Coll Cardiol       Date:  2018-01-23       Impact factor: 24.094

10.  Quantitative 3D dynamic contrast-enhanced (DCE) MR imaging of carotid vessel wall by fast T1 mapping using Multitasking.

Authors:  Nan Wang; Anthony G Christodoulou; Yibin Xie; Zhenjia Wang; Zixin Deng; Bill Zhou; Sangeun Lee; Zhaoyang Fan; Hyukjae Chang; Wei Yu; Debiao Li
Journal:  Magn Reson Med       Date:  2018-10-28       Impact factor: 4.668

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