Evidence map›Paper›PMID 35788703›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2022

Targeted detection of cancer cells during biopsy allows real-time diagnosis of pulmonary nodules.

Gregory T Kennedy, Feredun S Azari, Elizabeth Bernstein, Bilal Nadeem, Ashley Chang, Alix Segil, Neil Sullivan, Emmanuel Encarnado, Charuhas Desphande, John C Kucharczuk and 5 more

Open access · hybridAbstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.0field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 21 citations in OpenAlex.

  1. Trial
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  5. Real-Time In Vivo Cellular-Level Imaging During Puncture.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  16. The role of confocal laser endomicroscopy in pulmonary medicine.European respiratory review : an official journal of the European Respiratory Society · 2023
    Review
  17. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 2 countries.

Gregory T KennedyDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Feredun S AzariDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Elizabeth BernsteinDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Bilal NadeemDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Ashley ChangDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Alix SegilDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Neil SullivanDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Emmanuel EncarnadoDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Charuhas DesphandeDepartment of Pathology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
John C KucharczukDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA.
Kaela LeonardMauna Kea Technologies, Paris, France.
Philip S LowDepartment of Chemistry, Purdue University, West Lafayette, IN, USA.
Silvia ChenJohnson and Johnson, New Brunswick, NJ, USA.
Aline CritonMauna Kea Technologies, Paris, France.
Sunil SinghalDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, 6 White Building, Philadelphia, PA, 19104, USA. sunil.singhal@pennmedicine.upenn.edu.
University of Pennsylvania · USMauna Kea Technologies (France) · FRJohnson & Johnson (United States) · USPurdue University West Lafayette · US

Funding

Near infrared intraoperative molecular imaging of lung adenocarcinomaR01CA193556 · NCI · UNIVERSITY OF PENNSYLVANIA · PI LOW, PHILIP STEWART, SINGHAL, SUNIL · 2016 to 2020
$3.3M
SURGICAL ONCOLOGY RESEARCH TRAINING PROGRAM AT PENNT32CA251063 · NCI · UNIVERSITY OF PENNSYLVANIA · PI Ronald P. Dematteo · 2020 to 2026
$2.6M
Intraoperative Molecular Imaging of Pulmonary Squamous Cell CarcinomaF32CA254210 · NCI · UNIVERSITY OF PENNSYLVANIA · PI KENNEDY, GREGORY T · 2020 to 2021
$143k
NCI NIH HHS F32 CA254210NCI NIH HHS R01 CA193556NCI NIH HHS T32 CA251063
6 · The paper itself

Abstract

backgroundThe diagnostic yield of biopsies of solitary pulmonary nodules (SPNs) is low, particularly in sub-solid lesions. We developed a method (NIR-nCLE) to achieve cellular level cancer detection during biopsy by integrating (i) near-infrared (NIR) imaging using a cancer-targeted tracer (pafolacianine), and (ii) a flexible NIR confocal laser endomicroscopy (CLE) system that can fit within a biopsy needle. Our goal was to assess the diagnostic accuracy of NIR-nCLE ex vivo in SPNs.

methodsTwenty patients with SPNs were preoperatively infused with pafolacianine. Following resection, specimens were inspected to identify the lesion of interest. NIR-nCLE imaging followed by tissue biopsy was performed within the lesion and in normal lung tissue. All imaging sequences (n = 115) were scored by 5 blinded raters on the presence of fluorescent cancer cells and compared to diagnoses by a thoracic pathologist.

resultsMost lesions (n = 15, 71%) were adenocarcinoma-spectrum malignancies, including 7 ground glass opacities (33%). Mean fluorescence intensity (MFI) by NIR-nCLE for tumor biopsy was 20.6 arbitrary units (A.U.) and mean MFI for normal lung was 6.4 A.U. (p < 0.001). Receiver operating characteristic analysis yielded a high area under the curve for MFI (AUC = 0.951). Blinded raters scored the NIR-nCLE sequences on the presence of fluorescent cancer cells with sensitivity and specificity of 98% and 97%, respectively. Overall diagnostic accuracy was 97%. The inter-observer agreement of the five raters was excellent (κ = 0.95).

conclusionsNIR-nCLE allows sensitive and specific detection of cancer cells in SPNs. This technology has far-reaching implications for diagnostic needle biopsies and intraprocedural decision-making.

Indexed as

AdenocarcinomaMultiple Pulmonary NodulesPancreatic NeoplasmsBiopsyEndoscopic Ultrasound-Guided Fine Needle AspirationHumansMicroscopy, ConfocalBiopsyNIR-nCLEPulmonary nodules

Identifiers

PMID35788703
PMCPMC9525441
OpenAlexW4283818655

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.