Evidence map›Paper›PMID 31721093›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2021

Iterative reconstruction incorporating background correction improves quantification of [

Mercy I Akerele, Nicolas A Karakatsanis, Rachael O Forsythe, Marc R Dweck, Maaz Syed, Robert G Aykroyd, Steven Sourbron, David E Newby, Charalampos Tsoumpas

Open access · hybridAbstract read
In one paragraph

Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Quantifying sodium [EJNMMI research · 2022
    Article
  4. Assessment of different quantification metrics of [Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022
    Article
  5. Optimizing arterialJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021
    Article
  6. Prospect of positron emission tomography for abdominal aortic aneurysm risk stratification.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021
    Review
  7. Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021
    Article
  8. Review
  9. Comparison of Correction Techniques for the Spill in Effect in Emission Tomography.IEEE transactions on radiation and plasma medical sciences · 2020
    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

9 authors at 5 institutions in 2 countries.

Mercy I AkereleBiomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9NL, UK.
Nicolas A KarakatsanisDivision of Radiopharmaceutical Sciences, Department of Radiology, Weil Cornell Medical College of Cornell University, New York, NY, USA.
Rachael O ForsytheBritish Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Marc R DweckBritish Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Maaz SyedBritish Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Robert G AykroydDepartment of Statistics, University of Leeds, Leeds, UK.
Steven SourbronBiomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9NL, UK.
David E NewbyEdinburgh Imaging Facility, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.
Charalampos TsoumpasBiomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9NL, UK. c.tsoumpas@leeds.ac.uk.
University of Leeds · GBThe Queen's Medical Research Institute · GBBritish Heart Foundation · GBCornell University · USUniversity of Edinburgh · GB

Funding

British Heart Foundation FS/14/78/31020British Heart Foundation FS/18/31/33676Chief Scientist Office ETM/365Medical Research Council G0701127Medical Research Council MC_PC_12040Wellcome Trust
6 · The paper itself

Abstract

backgroundA confounding issue in [

methodsSeventy-two (72) datasets of patients with AAA were reconstructed with the standard ordered subset expectation maximization (OSEM) algorithm incorporating point spread function (PSF) modelling. The spill in effect in the aneurysm was investigated using two target regions of interest (ROIs): one covering the entire aneurysm (AAA), and the other covering the aneurysm but excluding the part close to the bone (AAA

resultsThere is a statistically significant higher [

conclusionThe background correction (OSEM + PSF + BC) technique provided more robust AAA quantitative assessments regardless of the AAA ROI delineation method, and thus it can be considered as an effective spill in correction method for [

Indexed as

AlgorithmsImage Processing, Computer-AssistedPositron Emission Tomography Computed TomographyAgedAortic Aneurysm, AbdominalBone and BonesCohort StudiesFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedPredictive Value of TestsRadiopharmaceuticalsReproducibility of ResultsSodium FluorideFluorodeoxyglucose F18RadiopharmaceuticalsSodium FluorideAbdominal aortic aneurysmbackground correctionpositron emission tomographyspill in

Identifiers

PMID31721093
PMCPMC8648624
OpenAlexW2983021428

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.