Evidence map›Paper›PMID 24191175›Full record

ArticleComputational and mathematical methods in medicine2013

Estimate of FDG excretion by means of compartmental analysis and ant colony optimization of nuclear medicine data.

Sara Garbarino, Giacomo Caviglia, Massimo Brignone, Michela Massollo, Gianmario Sambuceti, Michele Piana

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. 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

6 authors at 3 institutions in 1 country.

Sara GarbarinoDipartimento di Matematica, Università di Genova, Via Dodecaneso 35, 16146 Genova, Italy ; CNR-SPIN, Via Dodecaneso 33, 16146 Genova, Italy.
Giacomo Caviglia
Massimo Brignone
Michela Massollo
Gianmario Sambuceti
Michele Piana
University of Genoa · ITOspedale Policlinico San Martino · ITSuperconducting and other Innovative Materials and Devices Institute · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

[(18)F]fluoro-2-deoxy-D-glucose (FDG) is one of the most utilized tracers for positron emission tomography (PET) applications in oncology. FDG-PET relies on higher glycolytic activity in tumors compared to normal structures as the basis of image contrast. As a glucose analog, FDG is transported into malignant cells which typically exhibit an increased radioactivity. However, different from glucose, FDG is not reabsorbed by the renal system and is excreted to the bladder. The present paper describes a novel computational method for the quantitative assessment of this excretion process. The method is based on a compartmental analysis of FDG-PET data in which the excretion process is explicitly accounted for by the bladder compartment and on the application of an ant colony optimization (ACO) algorithm for the determination of the tracer coefficients describing the FDG transport effectiveness. The validation of this approach is performed by means of both synthetic data and real measurements acquired by a PET device for small animals (micro-PET). Possible oncological applications of the results are discussed in the final section.

Indexed as

Models, BiologicalAlgorithmsAnimalsBiological Transport, ActiveComputer SimulationFluorodeoxyglucose F18HumansKidneyMicePositron-Emission TomographyRadiopharmaceuticalsUrinary BladderFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID24191175
PMCPMC3804351
OpenAlexW2098440711

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.