Evidence map›Paper›PMID 22996051›Full record

ArticlePhysics in medicine and biology2012

Improving quantification of intravascular fluorescence imaging using structural information.

Georgios Mallas, Dana H Brooks, Amir Rosenthal, R Nika Nudelman, Adam Mauskapf, Farouc A Jaffer, Vasilis Ntziachristos

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

7 authors.

Georgios MallasDepartment of Electrical and Computer Engineering, Communications and Digital Signal Processing Research Center, 409 Dana Building, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA. mallasgeo@gmail.com
Dana H Brooks
Amir Rosenthal
R Nika Nudelman
Adam Mauskapf
Farouc A Jaffer
Vasilis Ntziachristos

Funding

Intravascular Fluorescence Molecular Imaging of Inflammation in AtherosclerosisR01HL108229 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI JAFFER, FAROUC AMIN · 2010 to 2014
$2.1M
Whole body tomography of fluorescent proteins in vivoR01EB004382 · NIBIB · NORTHEASTERN UNIVERSITY · PI BROOKS, DANA HENRY · 2007 to 2010
$1.3M
NHLBI NIH HHS R01 HL 108229NHLBI NIH HHS R01 HL108229NIBIB NIH HHS 1R01EB004382-01A2NIBIB NIH HHS R01 EB004382
6 · The paper itself

Abstract

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.

Indexed as

AlgorithmsAnimalsBlood VesselsOptical ImagingPhantoms, ImagingPhotonsRabbits

Identifiers

PMID22996051
PMCPMC3591519

What OpenQuestion holds

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Registered trials

None linked

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.