Evidence map›Paper›PMID 34436460›Full record

ReviewMetabolites2021

Mathematical Models for FDG Kinetics in Cancer: A Review.

Sara Sommariva, Giacomo Caviglia, Gianmario Sambuceti, Michele Piana

Abstract readReview
In one paragraph

Review in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

4 authors.

Sara SommarivaLife Science Computational Laboratory (LISCOMP), Largo Rosanna Benzi 10, 16132 Genova, Italy.ORCID 0000-0003-1835-9399
Giacomo CavigliaDipartimento di Matematica, Università di Genova, Via Dodecaneso 35, 16146 Genova, Italy.
Gianmario SambucetiDipartimento di Scienze della Salute, Università di Genova, Largo Rosanna Benzi 10, 16132 Genova, Italy.ORCID 0000-0003-2979-6500
Michele PianaLife Science Computational Laboratory (LISCOMP), Largo Rosanna Benzi 10, 16132 Genova, Italy.

Funding

Associazione Italiana per la Ricerca sul Cancro IG 230201
6 · The paper itself

Abstract

Compartmental analysis is the mathematical framework for the modelling of tracer kinetics in dynamical Positron Emission Tomography. This paper provides a review of how compartmental models are constructed and numerically optimized. Specific focus is given on the identifiability and sensitivity issues and on the impact of complex physiological conditions on the mathematical properties of the models.

Indexed as

2-deoxy-2-[18F]fluoro-D-glucose (FDG)compartmental analysisPositron Emission Tomography (PET)tracer kinetics

Identifiers

PMID34436460
PMCPMC8398381

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.