Evidence map›Paper›PMID 35314661›Full record

ArticleMethods and protocols2022

Validation of In Vivo Nodal Assessment of Solid Malignancies with USPIO-Enhanced MRI: A Workflow Protocol.

Daphne A J J Driessen, Didi J J M de Gouw, Rutger C H Stijns, Geke Litjens, Bas Israël, Bart W J Philips, John J Hermans, Tim Dijkema, Bastiaan R Klarenbeek, Rachel S van der Post and 6 more

Open access · goldAbstract read
In one paragraph

Article in Methods and protocols, 2022. 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
0.6field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Trial
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

16 authors at 1 institution in 1 country.

Daphne A J J DriessenDepartment of Radiation Oncology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.ORCID 0000-0002-7675-3987
Didi J J M de GouwDepartment of Surgery, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Rutger C H StijnsDepartment of Surgery, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Geke LitjensDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.ORCID 0000-0002-0436-9804
Bas IsraëlDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.ORCID 0000-0003-4848-4537
Bart W J PhilipsDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
John J HermansDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.ORCID 0000-0001-9207-0548
Tim DijkemaDepartment of Radiation Oncology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Bastiaan R KlarenbeekDepartment of Surgery, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Rachel S van der PostDepartment of Pathology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Iris D NagtegaalDepartment of Pathology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Adriana C H van Engen-van GrunsvenDepartment of Pathology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Lodewijk A A BrosensDepartment of Pathology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Andor VeltienDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.ORCID 0000-0002-8090-5445
Patrik ZámecnikDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Tom W J ScheenenDepartment of Medical Imaging, Radboud University Medical Center, 6525 Nijmegen, The Netherlands.
Radboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn various cancer types, the first step towards extended metastatic disease is the presence of lymph node metastases. Imaging methods with sufficient diagnostic accuracy are required to personalize treatment. Lymph node metastases can be detected with ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI), but this method needs validation. Here, a workflow is presented, which is designed to compare MRI-visible lymph nodes on a node-to-node basis with histopathology.

methodsIn patients with prostate, rectal, periampullary, esophageal, and head-and-neck cancer, in vivo USPIO-enhanced MRI was performed to detect lymph nodes suspicious of harboring metastases. After lymphadenectomy, but before histopathological assessment, a 7 Tesla preclinical ex vivo MRI of the surgical specimen was performed, and in vivo MR images were radiologically matched to ex vivo MR images. Lymph nodes were annotated on the ex vivo MRI for an MR-guided pathological examination of the specimens.

resultsMatching lymph nodes of ex vivo MRI to pathology was feasible in all cancer types. The annotated ex vivo MR images enabled a comparison between USPIO-enhanced in vivo MRI and histopathology, which allowed for analyses on a nodal, or at least on a nodal station, basis.

conclusionsA workflow was developed to validate in vivo USPIO-enhanced MRI with histopathology. Guiding the pathologist towards lymph nodes in the resection specimens during histopathological work-up allowed for the analysis at a nodal basis, or at least nodal station basis, of in vivo suspicious lymph nodes with corresponding histopathology, providing direct information for validation of in vivo USPIO-enhanced, MRI-detected lymph nodes.

Indexed as

7 Teslalymph nodemagnetic resonance imagingnodal stagingnode-to-node correlationpathology

Identifiers

PMID35314661
PMCPMC8938816
OpenAlexW4220820986

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.