Evidence map›Paper›PMID 33451116›Full record

ReviewInternational journal of molecular sciences2021

Cell-Based Tracers as Trojan Horses for Image-Guided Surgery.

Vincent Q Sier, Margreet R de Vries, Joost R van der Vorst, Alexander L Vahrmeijer, Cornelis van Kooten, Luis J Cruz, Lioe-Fee de Geus-Oei, Valerie Ferreira, Cornelis F M Sier, Frauke Alves and 1 more

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Engineering platelets as cancer therapeutics.Nature reviews. Clinical oncology · 2026
    Review
  3. Article
  4. Molecular Imaging in Nanomedical Research.International journal of molecular sciences · 2022
    Article
  5. 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

11 authors.

Vincent Q SierDepartment of Surgery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0003-3463-1217
Margreet R de VriesDepartment of Surgery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0002-3648-9130
Joost R van der VorstDepartment of Surgery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0002-0669-4272
Alexander L VahrmeijerDepartment of Surgery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
Cornelis van KootenDepartment of Nephrology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
Luis J CruzDepartment of Radiology, Translational Nanomaterials and Imaging Group, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
Lioe-Fee de Geus-OeiDepartment of Radiology, Section of Nuclear Medicine, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0003-1817-2743
Valerie FerreiraDepartment of Research and Development, UniQure, 1100 DA Amsterdam, The Netherlands.
Cornelis F M SierDepartment of Surgery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0002-4337-2758
Frauke AlvesTranslational Molecular Imaging, Clinic of Hematology and Medical Oncology, Institute of Diagnostic and Interventional Radiology, University Medicine Center Göttingen and Max-Planck-Institute for Experimental Medicine, 37075 Göttingen, Germany.ORCID 0000-0002-6258-5409
Munitta MuthanaDepartment of Infection and Immunity, University of Sheffield, Sheffield S10 2RX, UK.

Funding

Cancer Research UK 24321Cancer Research UK C25574/A24321
6 · The paper itself

Abstract

Surgeons rely almost completely on their own vision and palpation to recognize affected tissues during surgery. Consequently, they are often unable to distinguish between different cells and tissue types. This makes accurate and complete resection cumbersome. Targeted image-guided surgery (IGS) provides a solution by enabling real-time tissue recognition. Most current targeting agents (tracers) consist of antibodies or peptides equipped with a radiolabel for Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), magnetic resonance imaging (MRI) labels, or a near-infrared fluorescent (NIRF) dye. These tracers are preoperatively administered to patients, home in on targeted cells or tissues, and are visualized in the operating room via dedicated imaging systems. Instead of using these 'passive' tracers, there are other, more 'active' approaches of probe delivery conceivable by using living cells (macrophages/monocytes, neutrophils, T cells, mesenchymal stromal cells), cell(-derived) fragments (platelets, extracellular vesicles (exosomes)), and microorganisms (bacteria, viruses) or, alternatively, 'humanized' nanoparticles. Compared with current tracers, these active contrast agents might be more efficient for the specific targeting of tumors or other pathological tissues (e.g., atherosclerotic plaques). This review provides an overview of the arsenal of possibilities applicable for the concept of cell-based tracers for IGS.

Indexed as

Contrast MediaCell-Derived MicroparticlesCell TrackingHumansLeukocytesMagnetic Resonance ImagingMesenchymal Stem CellsNanoparticlesPositron-Emission TomographySurgery, Computer-AssistedContrast Mediacell-based imagingextracellular vesicleleukocytemagnetic resonance imagingmesenchymal stromal cellmicroorganismsnanoparticlenear-infrarednuclear imagingplatelets

Identifiers

PMID33451116
PMCPMC7828607

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.