Evidence map›Paper›PMID 28138354›Full record

ArticleCurrent cardiovascular imaging reports2016

Normal Databases for the Relative Quantification of Myocardial Perfusion.

Mathieu Rubeaux, Yuan Xu, Guido Germano, Daniel S Berman, Piotr J Slomka

Abstract read
In one paragraph

Article in Current cardiovascular imaging reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Diagnostic accuracy of stress-only myocardial perfusion SPECT improved by deep learning.European journal of nuclear medicine and molecular imaging · 2021
    Article
  8. Effect of reduced photon count levels and choice of normal data on semi-automated image assessment in cardiac SPECT.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  9. Effect of reduced photon count levels and choice of normal data on semi-automated image assessment in cardiac SPECT: Doing more with fewer counts.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  10. Article
  11. Impact of non-specific normal databases on perfusion quantification of low-dose myocardial SPECT studies.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2019
    Article
  12. Article
  13. The long way to dose reduction in myocardial perfusion imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Article
  14. Single Photon Emission Computed Tomography (SPECT) Myocardial Perfusion Imaging Guidelines: Instrumentation, Acquisition, Processing, and Interpretation.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Review
  15. Factors affecting appearance of a normal myocardial perfusion scan.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Article
  16. Article
  17. 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.

Mathieu RubeauxCedars-Sinai Medical Center, Los Angeles, CA.
Yuan XuCedars-Sinai Medical Center, Los Angeles, CA.
Guido GermanoCedars-Sinai Medical Center, Los Angeles, CA; David Geffen School of Medicine, University of California, Los Angeles, CA.
Daniel S BermanCedars-Sinai Medical Center, Los Angeles, CA; David Geffen School of Medicine, University of California, Los Angeles, CA.
Piotr J SlomkaCedars-Sinai Medical Center, Los Angeles, CA; David Geffen School of Medicine, University of California, Los Angeles, CA.

Funding

Quantitative Prediction of Disease and Outcomes from Next Generation SPECT and CTR01HL089765 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI SLOMKA, PIOTR J · 2007 to 2021
$6.1M
NHLBI NIH HHS R01 HL089765
6 · The paper itself

Abstract

purpose of reviewMyocardial perfusion imaging (MPI) with SPECT is performed clinically worldwide to detect and monitor coronary artery disease (CAD). MPI allows an objective quantification of myocardial perfusion at stress and rest. This established technique relies on normal databases to compare patient scans against reference normal limits. In this review, we aim to introduce the process of MPI quantification with normal databases and describe the associated perfusion quantitative measures that are used. RECENT

findingsNew equipment and new software reconstruction algorithms have been introduced which require the development of new normal limits. The appearance and regional count variations of normal MPI scan may differ between these new scanners and standard Anger cameras. Therefore, these new systems may require the determination of new normal limits to achieve optimal accuracy in relative myocardial perfusion quantification. Accurate diagnostic and prognostic results rivaling those obtained by expert readers can be obtained by this widely used technique. SUMMARY: Throughout this review, we emphasize the importance of the different normal databases and the need for specific databases relative to distinct imaging procedures. use of appropriate normal limits allows optimal quantification of MPI by taking into account subtle image differences due to the hardware and software used, and the population studied.

Indexed as

coronary artery diseasemyocardial perfusion imagingnormal databasessingle photon emission computed tomography (SPECT)

Identifiers

PMID28138354
PMCPMC5270769

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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.