Evidence map›Paper›PMID 31873141›Full record

ArticleScientific reports2019

Impact of iterative reconstruction with resolution recovery in myocardial perfusion SPECT: phantom and clinical studies.

Koichi Okuda, Kenichi Nakajima, Hiroto Yoneyama, Takayuki Shibutani, Masahisa Onoguchi, Shinro Matsuo, Mitsumasa Hashimoto, Seigo Kinuya

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Variational autoencoders can detect coronary artery disease in myocardial perfusion SPECT images.European journal of nuclear medicine and molecular imaging · 2026
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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

8 authors.

Koichi OkudaDepartment of Physics, Kanazawa Medical University, Uchinada, Japan. okuda@kanazawa-med.ac.jp.ORCID http://orcid.org/0000-0003-0010-6844
Kenichi NakajimaDepartment of Functional Imaging and Artificial Intelligence, Kanazawa University, Kanazawa, Japan.ORCID http://orcid.org/0000-0001-7188-8746
Hiroto YoneyamaDepartment of Radiological Technology, Kanazawa University Hospital, Kanazawa, Japan.
Takayuki ShibutaniDepartment of Quantum Medical Technology, Kanazawa University, Kanazawa, Japan.
Masahisa OnoguchiDepartment of Quantum Medical Technology, Kanazawa University, Kanazawa, Japan.
Shinro MatsuoDepartment of Nuclear Medicine, Kanazawa University Hospital, Kanazawa, Japan.
Mitsumasa HashimotoDepartment of Physics, Kanazawa Medical University, Uchinada, Japan.
Seigo KinuyaDepartment of Nuclear Medicine, Kanazawa University Hospital, Kanazawa, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The corrections of photon attenuation, scatter, and depth-dependent blurring improve image quality in myocardial perfusion single-photon emission computed tomography (SPECT) imaging; however, the combined corrections induce artifacts. Here, we present the single correction method of depth-dependent blurring and its impact for myocardial perfusion distribution in phantom and clinical studies. The phantom and clinical patient images were acquired with two conditions: circular and noncircular orbits of gamma cameras yielded constant and variable depth-dependent blurring, respectively. An iterative reconstruction with the correction method of depth-dependent was used to reconstruct the phantom and clinical patient images. We found that the single correction method improved the robustness of phantom images whether the images contained constant or variable depth-dependent blurring. The myocardial perfusion databases generated from 72 normal patients exhibited uniform perfusion distribution of whole myocardium. In summary, the single correction method of depth-dependent blurring with iterative reconstruction is helpful for myocardial perfusion SPECT.

Indexed as

MyocardiumPhantoms, ImagingHumansMyocardial Perfusion ImagingTomography, Emission-Computed, Single-Photon

Identifiers

PMID31873141
PMCPMC6928019

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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.