Evidence map›Paper›PMID 28357812›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2019

Clinical performance of Rb-82 myocardial perfusion PET and Tc-99m-based SPECT in patients with extreme obesity.

David T Harnett, Samir Hazra, Ronnen Maze, Brian A Mc Ardle, Ali Alenazy, Trevor Simard, Ellen Henry, Girish Dwivedi, Christopher Glover, Robert A deKemp and 5 more

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

19 citing papers in PubMed, 30 citations in OpenAlex.

  1. Improved assessment of coronary artery disease in obese patients with flurpiridaz-Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2026
    Trial
  2. Advances in GPCR-Targeted PET Radiotracer Patents (2020-2025).Pharmaceuticals (Basel, Switzerland) · 2026
    Review
  3. Review
  4. Review
  5. Review
  6. Exponential dosing to standardize myocardial perfusion image quality with rubidium-82 PET.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  7. Review
  8. Article
  9. PET Image Denoising using a Deep-Learning Method for Extremely Obese Patients.IEEE transactions on radiation and plasma medical sciences · 2022
    Article
  10. Feasibility of exercise treadmillJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022
    Article
  11. Review
  12. Article
  13. EANM procedural guidelines for PET/CT quantitative myocardial perfusion imaging.European journal of nuclear medicine and molecular imaging · 2021
    Article
  14. The Newer, the Better; and May Be Not Good Enough?Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021
    Article
  15. Review
  16. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2019: Positron emission tomography, computed tomography and magnetic resonance.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Review
  17. Emerging Techniques for Cardiovascular PET.Cardiovascular innovations and applications · 2019
    Article
  18. Coronary Microvascular Dysfunction and Cardiovascular Risk in Obese Patients.Journal of the American College of Cardiology · 2018
    Observational
  19. SPECT but not PET remains as the working horse of the state of the art nuclear cardiac imaging laboratory: Con.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 1 institution in 1 country.

David T HarnettDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Samir HazraDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Ronnen MazeCAPITAL Research Group, Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada.
Brian A Mc ArdleDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Ali AlenazyDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Trevor SimardCAPITAL Research Group, Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada.
Ellen HenryDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Girish DwivediDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Christopher GloverCAPITAL Research Group, Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada.
Robert A deKempDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Ross A DaviesDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Terrence D RuddyDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Benjamin J W ChowDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Rob S BeanlandsDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Benjamin HibbertCAPITAL Research Group, Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada. bhibbert@ottawaheart.ca.
University of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe evaluated the performance of stress imaging with technetium-99m-labeled tetrofosmin single-photon emission computed tomography (SPECT) and rubidium-82 positron emission tomography (PET) in patients with extreme obesity, defined as body mass index ≥40 kg/m

methodsWe identified patients with extreme obesity who underwent angiography in our center and either stress SPECT or PET within the previous six months. Cohorts of patients with extreme obesity and a <5% pretest likelihood of CAD who underwent SPECT (N = 25) or PET (N = 25) were also included.

resultsIn total, 108 patients who underwent SPECT (N = 57) or PET (N = 51) were identified. Scan interpretation was classified as definitely normal or abnormal in 83.3% of PET and 60.5% of SPECT scans, respectively (P < .01). PET demonstrated higher diagnostic accuracy and normalcy rate. PET was found to have higher specificity for the pooled cohort. Similar findings were observed using stenosis cut-offs of ≥50% and ≥70%.

conclusionsIn patients with extreme obesity, PET enabled more definitive scan interpretation with less artifact compared to SPECT. PET provided higher diagnostic accuracy and specificity in the detection of obstructive coronary artery disease.

Indexed as

Positron-Emission TomographyTomography, Emission-Computed, Single-PhotonAgedCoronary AngiographyCoronary Artery DiseaseFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedMyocardial Perfusion ImagingObesity, MorbidProspective StudiesRegistriesRubidium RadioisotopesSensitivity and SpecificityRubidium-82Rubidium RadioisotopesTechnetiumMyocardial perfusion imagingobesityPET/CTSPECT

Identifiers

PMID28357812
OpenAlexW2600713729

What OpenQuestion holds

Textmetadata
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.