Evidence map›Paper›PMID 32871968›Full record

ArticleMedicine2020

Diagnostic performance of a whole-body dynamic 68GA-DOTATOC PET/CT acquisition to differentiate physiological uptake of pancreatic uncinate process from pancreatic neuroendocrine tumor.

Philippe Thuillier, David Bourhis, Nicolas Karakatsanis, Ulrike Schick, Jean Philippe Metges, Pierre-Yves Salaun, Véronique Kerlan, Ronan Abgral

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. PET/MRI imaging in neuroendocrine neoplasm.Abdominal radiology (New York) · 2023
    Review
  3. DynamicQuantitative imaging in medicine and surgery · 2023
    Article
  4. Article
  5. DynamicRadiology. Imaging cancer · 2022
    Article
  6. Clinical perspectives for the use of total body PET/CT.European journal of nuclear medicine and molecular imaging · 2021
    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

8 authors at 2 institutions in 2 countries.

Philippe ThuillierDepartment of Endocrinology.
David BourhisEA GETBO 3878.ORCID 0000-0001-8224-2027
Nicolas KarakatsanisDivision of Radiopharmaceutical Sciences, Department of Radiology, Weil Cornell Medical College of Cornell University, New York, NY, USA.ORCID 0000-0001-7326-3053
Ulrike SchickDepartment of Radiotherapy.
Jean Philippe MetgesDepartment of Oncology, University Hospital of Brest, France.
Pierre-Yves SalaunEA GETBO 3878.ORCID 0000-0002-3899-2135
Véronique KerlanDepartment of Endocrinology.
Ronan AbgralEA GETBO 3878.
Centre Hospitalier Régional Universitaire de Brest · FRCornell University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To evaluate the diagnostic performance of net influx rate (Ki) values from a whole-body dynamic (WBD) Ga-DOTATOC-PET/CT acquisition to differentiate pancreatic neuroendocrine tumors (pNETs) from physiological uptake of pancreatic uncinate process (UP).Patients who were benefited from a WBD acquisition for the assessment of a known well-differentiated neuroendocrine tumor (NET)/suspicion of disease in the prospective GAPET-NET cohort were screened. Only patients with a confirmed pNET/UP as our gold standard were included. The positron emission tomography (PET) procedure consisted in a single-bed dynamic acquisition centered on the heart, followed by a whole-body dynamic acquisition and then a static acquisition. Dynamic (Ki calculated according to Patlak method), static (SUVmax, SUVmean, SUVpeak) parameters, and tumor-to-liver and tumor-to-spleen ratio (TLRKi and TSRKi (according to hepatic/splenic Ki)), tumor SUVmax to liver SUVmax (TM/LM), tumor SUVmax to liver SUVmean (TM/Lm), tumor SUVmax to spleen SUVmax (TM/SM), and tumor SUVmax to spleen SUVmean (TM/Sm) (according to hepatic/splenic SUVmax and SUVmean respectively) were calculated. A Receiver Operating Characteristic (ROC) analysis was performed to evaluate their diagnostic performance to distinguish UP from pNET.One hundred five patients benefited from a WBD between July 2018 and July 2019. Eighteen (17.1%) had an UP and 26 (24.8%) a pNET. For parameters alone, the Ki and SUVpeak had the best sensitivity (88.5%) while the Ki, SUVmax, and SUVmean had the best specificity (94.4%). The best diagnostic accuracy was obtained with Ki (90.9%). For ratios, the TLRKi and the TSRKi had the best sensitivity (95.7%) while the TM/SM and TM/Sm the best specificity (100%). TLRKi had the best diagnostic accuracy (95.1%) and the best area under the curve (AUC) (0.990).Our study is the first one to evaluate the interest of a WBD acquisition to differentiate UP from pNETs and shows excellent diagnostic performances of the Ki approach.

Indexed as

Positron Emission Tomography Computed TomographyWhole Body ImagingDiagnosis, DifferentialFemaleHumansLiverMaleMiddle AgedNeuroendocrine TumorsOctreotideOrganometallic CompoundsPancreasPancreatic NeoplasmsProspective StudiesRadiopharmaceuticalsSensitivity and SpecificityGa(III)-DOTATOCOctreotideOrganometallic CompoundsRadiopharmaceuticals

Identifiers

PMID32871968
PMCPMC7437793
OpenAlexW3049731723

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.