Evidence map›Paper›PMID 32031935›Full record

ArticleIEEE transactions on medical imaging2020

Localization of Fluorescent Targets in Deep Tissue With Expanded Beam Illumination for Studies of Cancer and the Brain.

Brian Z Bentz, Sakkarapalayam M Mahalingam, Daniel Ysselstein, Paola C Montenegro Larrea, Jason R Cannon, Jean-Christophe Rochet, Philip S Low, Kevin Webb

Abstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Brian Z Bentz
Sakkarapalayam M Mahalingam
Daniel Ysselstein
Paola C Montenegro Larrea
Jason R Cannon
Jean-Christophe Rochet
Philip S Low
Kevin Webb

Funding

In Vivo Optical Imaging of Alpha-Synuclein AggregationR21NS105048 · NINDS · PURDUE UNIVERSITY · PI WEBB, KEVIN J · 2018 to 2019
$403k
Optical Imaging of Targeted Anti-Cancer Drug Delivery KineticsR21CA182235 · NCI · PURDUE UNIVERSITY · PI WEBB, KEVIN J · 2015 to 2016
$368k
NCI NIH HHS R21 CA182235NINDS NIH HHS R21 NS105048
6 · The paper itself

Abstract

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

Indexed as

Fluorescent DyesNeoplasmsAnimalsBrainLightingMiceRatsFluorescent Dyes

Identifiers

PMID32031935
PMCPMC7428064

What OpenQuestion holds

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Registered trials

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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.