Evidence map›Paper›PMID 26301337›Full record

ArticlePhysics in medicine and biology2015

Task-based evaluation of a 4D MAP-RBI-EM image reconstruction method for gated myocardial perfusion SPECT using a human observer study.

Taek-Soo Lee, Takahiro Higuchi, Riikka Lautamäki, Frank M Bengel, Benjamin M W Tsui

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Virtual clinical trials in medical imaging: a review.Journal of medical imaging (Bellingham, Wash.) · 2020
    Review
  2. Review
  3. Article
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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

5 authors at 2 institutions in 3 countries.

Taek-Soo LeeRadiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, JHOC Room 4263, Baltimore, MD 21287, USA.
Takahiro HiguchiRadiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, JHOC Room 4263, Baltimore, MD 21287, USA.
Riikka LautamäkiRadiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, JHOC Room 4263, Baltimore, MD 21287, USA.
Frank M BengelRadiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, JHOC Room 4263, Baltimore, MD 21287, USA.
Benjamin M W TsuiRadiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, JHOC Room 4263, Baltimore, MD 21287, USA.
Johns Hopkins University · USUniversity of Würzburg · DE

Funding

Task-Based Optimization of Gated Myocardial SPECTR01HL068075 · NHLBI · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI TSUI, BENJAMIN M. W. · 2001 to 2010
$1.5M
NHLBI NIH HHS NIH R01 HL68075NHLBI NIH HHS R01 HL068075
6 · The paper itself

Abstract

We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion abnormality. We concluded that the NMSE-NSDav trade-off was shown to agree with observer performance for the detection task of the regional motion abnormality, and the optimized 4D MAP-RBI-EM method with ADS corrections provides significant improvement compared to 3D FBP and 3D OS-EM with ADS corrections in detecting regional myocardial wall motion abnormali in 4D gated MP SPECT.

Indexed as

Observer VariationPhantoms, ImagingTask Performance and AnalysisAlgorithmsArea Under CurveCardiac-Gated Single-Photon Emission Computer-Assisted TomographyHeartHumansImage Processing, Computer-AssistedModels, CardiovascularMyocardial Perfusion ImagingROC Curve

Identifiers

PMID26301337
PMCPMC4582998
OpenAlexW1140350419

What OpenQuestion holds

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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.