Evidence map›Paper›PMID 22047396›Full record

ArticleMedical physics2011

Automatic 3D registration of dynamic stress and rest (82)Rb and flurpiridaz F 18 myocardial perfusion PET data for patient motion detection and correction.

Jonghye Woo, Balaji Tamarappoo, Damini Dey, Ryo Nakazato, Ludovic Le Meunier, Amit Ramesh, Joel Lazewatsky, Guido Germano, Daniel S Berman, Piotr J Slomka

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.9field-weighted citation impact, top 10% 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

24 citing papers in PubMed, 40 citations in OpenAlex.

  1. Dynamic frame-by-frame motion correction forEuropean journal of nuclear medicine and molecular imaging · 2026
    Article
  2. Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging.IEEE transactions on radiation and plasma medical sciences · 2024
    Article
  3. Article
  4. TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction.Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI (Workshop) · 2023
    Article
  5. Impact of motion correction on [Physics in medicine and biology · 2023
    Article
  6. Article
  7. Article
  8. Automated dynamic motion correction using normalized gradient fields forJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  9. Vulnerable plaque imaging usingThe British journal of radiology · 2020
    Review
  10. Motion correction to enhance absolute myocardial blood flow quantitation by PET.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  11. Blood pool and tissue phase patient motion effects onJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2019
    Article
  12. Article
  13. Data-Driven Gross Patient Motion Detection and Compensation: Implications for CoronaryJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
    Article
  14. Impact of pharmacological stress agent on patient motion during rubidium-82 myocardial perfusion PET/CT.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Article
  15. Review
  16. Advances in PET/MR instrumentation and image reconstruction.The British journal of radiology · 2018
    Review
  17. Article
  18. Review
  19. Imaging moving heart structures with PET.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2016
    Article
  20. 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

10 authors at 3 institutions in 1 country.

Jonghye WooDepartment of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Balaji Tamarappoo
Damini Dey
Ryo Nakazato
Ludovic Le Meunier
Amit Ramesh
Joel Lazewatsky
Guido Germano
Daniel S Berman
Piotr J Slomka
Cedars-Sinai Medical Center · USLantheus Medical Imaging (United States) · USSiemens Healthcare (United States) · US

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 HL089765NHLBI NIH HHS R01HL089765-01
6 · The paper itself

Abstract

purposeThe authors aimed to develop an image-based registration scheme to detect and correct patient motion in stress and rest cardiac positron emission tomography (PET)/CT images. The patient motion correction was of primary interest and the effects of patient motion with the use of flurpiridaz F 18 and (82)Rb were demonstrated.

methodsThe authors evaluated stress/rest PET myocardial perfusion imaging datasets in 30 patients (60 datasets in total, 21 male and 9 female) using a new perfusion agent (flurpiridaz F 18) (n = 16) and (82)Rb (n = 14), acquired on a Siemens Biograph-64 scanner in list mode. Stress and rest images were reconstructed into 4 ((82)Rb) or 10 (flurpiridaz F 18) dynamic frames (60 s each) using standard reconstruction (2D attenuation weighted ordered subsets expectation maximization). Patient motion correction was achieved by an image-based registration scheme optimizing a cost function using modified normalized cross-correlation that combined global and local features. For comparison, visual scoring of motion was performed on the scale of 0 to 2 (no motion, moderate motion, and large motion) by two experienced observers.

resultsThe proposed registration technique had a 93% success rate in removing left ventricular motion, as visually assessed. The maximum detected motion extent for stress and rest were 5.2 mm and 4.9 mm for flurpiridaz F 18 perfusion and 3.0 mm and 4.3 mm for (82)Rb perfusion studies, respectively. Motion extent (maximum frame-to-frame displacement) obtained for stress and rest were (2.2 ± 1.1, 1.4 ± 0.7, 1.9 ± 1.3) mm and (2.0 ± 1.1, 1.2 ±0 .9, 1.9 ± 0.9) mm for flurpiridaz F 18 perfusion studies and (1.9 ± 0.7, 0.7 ± 0.6, 1.3 ± 0.6) mm and (2.0 ± 0.9, 0.6 ± 0.4, 1.2 ± 1.2) mm for (82)Rb perfusion studies, respectively. A visually detectable patient motion threshold was established to be ≥2.2 mm, corresponding to visual user scores of 1 and 2. After motion correction, the average increases in contrast-to-noise ratio (CNR) from all frames for larger than the motion threshold were 16.2% in stress flurpiridaz F 18 and 12.2% in rest flurpiridaz F 18 studies. The average increases in CNR were 4.6% in stress (82)Rb studies and 4.3% in rest (82)Rb studies.

conclusionsFully automatic motion correction of dynamic PET frames can be performed accurately, potentially allowing improved image quantification of cardiac PET data.

Indexed as

MovementPyridazinesRubidium RadioisotopesStress, PhysiologicalAlgorithmsAutomationFemaleHumansImaging, Three-DimensionalMaleMiddle AgedMyocardial Perfusion ImagingPositron-Emission TomographyRestBMS 747158-02PyridazinesRubidium Radioisotopes

Identifiers

PMID22047396
PMCPMC3223511
OpenAlexW2013678417

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.