Evidence map›Paper›PMID 39715888›Full record

ArticleEJNMMI physics2024

EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [

Mattia De Francisci, Erica Silvestri, Andrea Bettinelli, Tommaso Volpi, Manu S Goyal, Andrei G Vlassenko, Diego Cecchin, Alessandra Bertoldo

Abstract read
In one paragraph

Article in EJNMMI physics, 2024. 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
–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. Review
  2. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
    Review
  3. Article
  4. Task-evoked deactivations: dissociation between BOLD fMRI and FDG.bioRxiv : the preprint server for biology · 2026
    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

8 authors.

Mattia De Francisci *Department of Information Engineering, University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0001-5137-2697
Erica Silvestri *Department of Information Engineering, University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0002-1853-0777
Andrea BettinelliDepartment of Information Engineering, University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0002-3539-3540
Tommaso VolpiPadova Neuroscience Center, University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0002-5451-6710
Manu S GoyalNeuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.ORCID http://orcid.org/0000-0003-1970-4270
Andrei G VlassenkoNeuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
Diego CecchinPadova Neuroscience Center, University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0001-7956-1924
Alessandra BertoldoDepartment of Information Engineering, University of Padova, Padova, Italy. alessandra.bertoldo@unipd.it.ORCID http://orcid.org/0000-0002-6262-6354

Funding

Aerobic Glycolysis in the Development ofAlzheimer's DiseaseR01AG053503 · NIA · WASHINGTON UNIVERSITY · PI RAICHLE, MARCUS E, VLASSENKO, ANDREI G. · 2017 to 2021
$4.1M
Aerobic Glycolysis: A Marker of BrainResilience to Aging and Alzheimer's DiseaseR01AG057536 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2017 to 2021
$3.7M
White Matter Metabolism in the Context of Aging, White Matter Hyperintensities and Alzheimer's DiseaseRF1AG073210 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2022 to 2022
$2.3M
NIA NIH HHS RF1 AG073210NIH HHS R01AG053503NIH HHS R01AG057536NIH HHS RF1AG073210
6 · The paper itself

Abstract

purposePET imaging is a pivotal tool for biomarker research aimed at personalized medicine. Leveraging the quantitative nature of PET requires knowledge of plasma radiotracer concentration. Typically, the arterial input function (AIF) is obtained through arterial cannulation, an invasive and technically demanding procedure. A less invasive alternative, especially for [

methodsTo assess the toolbox generalizability and present example outputs, EMATA was applied to brain [

resultsEMATA consistently performs IDIF extraction across all datasets, despite differences in scanners and acquisition protocols. Remarkably high agreement is observed when comparing Patlak's K

conclusionEMATA proved adaptability to different datasets characteristics and the ability to provide arterial input functions that can be used for reliable PET quantitative analysis.

Indexed as

[18F]FDGIDIFKinetic modelingPVE

Identifiers

PMID39715888
PMCPMC11666860

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LicenceCC BY-NC-ND
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Registered trials

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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.