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Improving quantification of intravascular fluorescence imaging using structural information.
Phys. Med. Biol. 57, 6395-6406 (2012)
Intravascular near-infrared fluorescence (iNIRF) imaging can enable the in vivo visualization of biomarkers of vascular pathology, including high-risk plaques. The technique resolves the bio-distribution of systemically administered fluorescent probes with molecular specificity in the vessel wall. However, the geometrical variations that may occur in the distance between fibre-tip and vessel wall can lead to signal intensity variations and challenge quantification. Herein we examined whether the use of anatomical information of the cross-section vessel morphology, obtained from co-registered intravascular ultrasound (IVUS), can lead to quantification improvements when fibre-tip and vessel wall distance variations are present. The algorithm developed employs a photon propagation model derived from phantom experiments that is used to calculate the relative attenuation of fluorescence signals as they are collected over 360° along the vessel wall, and utilizes it to restore accurate fluorescence readings. The findings herein point to quantification improvements when employing hybrid iNIRF, with possible implications to the clinical detection of high-risk plaques or blood vessel theranostics.
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Times Cited
Times Cited
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2.829
1.585
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9
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
OPTICAL COHERENCE TOMOGRAPHY; RAY COMPUTED-TOMOGRAPHY; IN-VIVO; CARDIOVASCULAR-DISEASE; ULTRASOUND IMAGES; CONTRAST AGENT; ATHEROSCLEROSIS; SEGMENTATION; INFLAMMATION; SYSTEM
Language
english
Publication Year
2012
HGF-reported in Year
2012
ISSN (print) / ISBN
0031-9155
e-ISSN
1361-6560
Journal
Physics in Medicine and Biology
Quellenangaben
Volume: 57,
Issue: 20,
Pages: 6395-6406
Publisher
Institute of Physics Publishing (IOP)
Publishing Place
Bristol
Reviewing status
Peer reviewed
Institute(s)
Institute of Biological and Medical Imaging (IBMI)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-505500-001
PubMed ID
22996051
WOS ID
WOS:000309549600007
Erfassungsdatum
2012-10-30