Evidence map›Paper›PMID 23636489›Full record

ArticleMolecular imaging and biology2013

Dual-tracer PET using generalized factor analysis of dynamic sequences.

Georges El Fakhri, Cathryn M Trott, Arkadiusz Sitek, Ali Bonab, Nathaniel M Alpert

Abstract read
In one paragraph

Article in Molecular imaging and biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Simultaneous radiomethylation of [Scientific reports · 2022
    Article
  6. Article
  7. PET Parametric Imaging: Past, Present, and Future.IEEE transactions on radiation and plasma medical sciences · 2020
    Article
  8. Dynamic whole-body PET imaging: principles, potentials and applications.European journal of nuclear medicine and molecular imaging · 2019
    Review
  9. Multi-Tracer Guided PET Image Reconstruction.IEEE transactions on radiation and plasma medical sciences · 2018
    Article
  10. Article
  11. Clustering-initiated factor analysis application for tissue classification in dynamic brain positron emission tomography.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2015
    Article
  12. Review
  13. Article
  14. Article
  15. 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

5 authors.

Georges El FakhriCenter for Advanced Medical Imaging Sciences NMMI, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, elfakhri@pet.mgh.harvard.edu.
Cathryn M Trott
Arkadiusz Sitek
Ali Bonab
Nathaniel M Alpert

Funding

Quantitative Oncologic PET-MRR01CA165221 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI EL FAKHRI, GEORGES · 2012 to 2023
$4.7M
Quantitative Cardiac PETR01HL110241 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI EL FAKHRI, GEORGES · 2011 to 2014
$1.9M
NCI NIH HHS R01 CA165221NCI NIH HHS R01CA165221NHLBI NIH HHS R01 HL110241NHLBI NIH HHS R01-HL110241
6 · The paper itself

Abstract

purposeWith single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions. PROCEDURES: To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG) (brain metabolism) and (11)C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously.

resultsThe theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3 ± 1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9 ± 3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation.

conclusionsDynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct.

Indexed as

Factor Analysis, StatisticalAlgorithmsAnimalsBrainBrain ChemistryComputer SimulationFemaleFluorodeoxyglucose F18HumansMacaca mulattaModels, BiologicalNeuroimagingPositron-Emission TomographyRadiopharmaceuticalsFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID23636489
PMCPMC3812387

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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.