Evidence map›Paper›PMID 40321301›Full record

ReviewJournal of biomedical optics2025

Perspective on the use of fluorescence molecular imaging for peripheral and deep

Hang M Nguyen, Veronica C Torres, Joshua Levy, Eunice Y Chen, Matthew LeBoeuf, Kimberley S Samkoe

Abstract readReview
In one paragraph

Review in Journal of biomedical optics, 2025. 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. Article
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

6 authors.

Hang M NguyenDartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States.
Veronica C TorresDartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States.
Joshua LevyCedars-Sinai Medical Center, Department of Pathology and Laboratory Medicine, Los Angeles, California, United States.
Eunice Y ChenDartmouth-Hitchcock Medical Center, Department of Surgery, Lebanon, New Hampshire, United States.
Matthew LeBoeufDartmouth-Hitchcock Medical Center, Department of Dermatology, Lebanon, New Hampshire, United States.
Kimberley S SamkoeDartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States.ORCID 0000-0002-8234-2308

Funding

Molecular Fluorescence-Guided Surgery PlatformR01CA167413 · NCI · DARTMOUTH COLLEGE · PI PAULSEN, KEITH D., SAMKOE, KIMBERLEY · 2013 to 2025
$5.7M
Paired-agent imaging for resection during surgery (PAIRS) for head & neck cancersR37CA212187 · NCI · DARTMOUTH-HITCHCOCK CLINIC · PI SAMKOE, KIMBERLEY · 2018 to 2024
$2.7M
NCI NIH HHS R01 CA167413NCI NIH HHS R37 CA212187
6 · The paper itself

Abstract

Significance: Current standard practice for margin assessment in solid tumor resection often leads to suboptimal results due to the inability to assess margins completely in a time-efficient manner. On the other hand, for small skin cancers, peripheral and deep Aim: We aim to explore fluorescence molecular imaging (FMI) as a tool for resolving obstacles and integrating PDEMA into the surgeon-to-pathologist workflow for large solid tumors. Approach: A review of recent pre-clinical and clinical studies using FMI to assess surgical margins was conducted to highlight promising fluorescence imaging technologies utilized in the surgical suite and laboratory. Results: FMI techniques that provide macroscopic resolution are efficient in time and have a notable ability to identify true negative tissue yet have limited capability in identifying true positive tissues. Moreover, meso- and microscopic FMI methods require additional time to attain a higher resolution but deliver an enhanced sensitivity in detecting true positive tissues. In both cases, experts are still required to learn to interpret the FMI signals, which prohibits a seamless clinical integration. Conclusions: Our proposed margin assessment platform (MAP) incorporates both macroscopic and, meso- or microscopic imaging with post-processing and machine learning for interpretation, to enable the application of PDEMA into solid tumor surgery. MAP leverages the advantages of each technique and thoroughly tackles the limitations of time and expertise to optimize the efficiency and accuracy of margin assessment and ultimately improve clinical outcomes.

Indexed as

Margins of ExcisionMolecular ImagingNeoplasmsOptical ImagingHumansSkin Neoplasmsfluorescencemolecular imagingperipheral and deep en face margin assessmenttumor margin

Identifiers

PMID40321301
PMCPMC12048172

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.