Evidence map›Paper›PMID 36315374›Full record

ArticleMolecular imaging and biology2023

Rapid and Quantitative Intraoperative Pathology-Assisted Surgery by Paired-Agent Imaging-Derived Confidence Map.

Cheng Wang, Sassan Hodge, Divya Ravi, Eunice Y Chen, P Jack Hoopes, Kenneth M Tichauer, Kimberley S Samkoe

Open access · greenAbstract read
In one paragraph

Article in Molecular imaging and biology, 2023. 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
0.7field-weighted citation impact, top 27% of its field
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, 7 citations in OpenAlex.

  1. Article
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  4. Review
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  7. Paired-agent imaging as a rapidFrontiers in oncology · 2023
    Article
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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 at 2 institutions in 1 country.

Cheng WangThayer School of Engineering, Dartmouth College, Hanover, NH, USA.
Sassan HodgeThayer School of Engineering, Dartmouth College, Hanover, NH, USA.
Divya RaviGeisel School of Medicine, Dartmouth College, Hanover, NH, USA.
Eunice Y ChenDepartment of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
P Jack HoopesThayer School of Engineering, Dartmouth College, Hanover, NH, USA.
Kenneth M TichauerBiomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Kimberley S SamkoeThayer School of Engineering, Dartmouth College, Hanover, NH, USA. Kimberley.S.Samkoe@dartmouth.edu.ORCID 0000-0002-8234-2308
Dartmouth College · USIllinois Institute of Technology · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
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 P30 CA023108NCI NIH HHS R01 CA167413NCI NIH HHS R37 CA212187
6 · The paper itself

Abstract

purposeIn nonmetastatic head and neck cancer treatment, surgical margin status is the most important prognosticator of recurrence and patient survival. Fresh frozen sectioning (FFS) of tissue margins is the standard of care for intraoperative margin assessment. However, FFS is time intensive, and its accuracy is not consistent among institutes. Mapping the epidermal growth factor receptor (EGFR) using paired-agent imaging (PAI) has the potential to provide more consistent intraoperative margin assessment in a fraction of the time as FFS. PROCEDURES: PAI was carried out through IV injection of an anti-epidermal growth factor receptor (EGFR) affibody molecule (ABY-029, eIND 122,681) and an untargeted IRDye680LT carboxylate. Imaging was performed on 4 µm frozen sections from three oral squamous cell carcinoma xenograft mouse models (n = 24, 8 samples per cell line). The diagnostic ability and tumor contrast were compared between binding potential, targeted, and untargeted images. Confidence maps were constructed based on group histogram-derived tumor probability curves. Tumor differentiability and contrast by confidence maps were evaluated.

resultsPAI outperformed ABY-029 and IRDye 680LT alone, demonstrating the highest individual receiver operating characteristic (ROC) curve area under the curve (PAI AUC: 0.91, 0.90, and 0.79) and contrast-to-noise ratio (PAI CNR: 1, 1.1, and 0.6) for FaDu, Det 562, and A253. PAI confidence maps (PAI CM) maintain high tumor diagnostic ability (PAI CMAUC: 0.91, 0.90, and 0.79) while significantly enhancing tumor contrast (PAI CMCNR: 1.5, 1.3, and 0.8) in FaDu, Det 562, and A253. Additionally, the PAI confidence map allows avascular A253 to be differentiated from a healthy tissue with significantly higher contrast than PAI. Notably, PAI does not require additional staining and therefore significantly reduces the tumor delineation time in a 5 [Formula: see text] 5 mm slice from ~ 35 min to under a minute.

conclusionThis study demonstrated that PAI improved tumor detection in frozen sections with high diagnostic accuracy and rapid analysis times. The novel PAI confidence map improved the contrast in vascular tumors and differentiability in avascular tumors. With a larger database, the PAI confidence map promises to standardize fluorescence imaging in intraoperative pathology-assisted surgery (IPAS).

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsMouth NeoplasmsAnimalsErbB ReceptorsHumansMiceOptical ImagingErbB ReceptorsConfidence mapEpidermal growth factor receptorHead and neck cancerIntraoperative pathology-assisted surgeryPaired-agent imaging

Identifiers

PMID36315374
PMCPMC11841742
OpenAlexW4307771174

What OpenQuestion holds

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LicenceTDM
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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.