Evidence map›Paper›PMID 30027577›Full record

ArticleMedical physics2018

Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction.

Debasis Mitra, Mahmoud Abdalah, Rostyslav Boutchko, Haoran Chang, Uttam Shrestha, Elias Botvinick, Youngho Seo, Grant T Gullberg

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Debasis MitraSchool of Computing, Florida Institute of Technology, 150 West University Blvd., Melbourne, FL, 32901, USA.
Mahmoud AbdalahRadiology and Cancer Imaging, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA.
Rostyslav BoutchkoMolecular Biophys. & Integ. Bio., Lawrence Berkeley National Lab, MS 55R0121, Berkeley, CA, 94720, USA.
Haoran ChangSchool of Computing, Florida Institute of Technology, 150 West University Blvd., Melbourne, FL, 32901, USA.
Uttam ShresthaPhysics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA.
Elias BotvinickPhysics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA.
Youngho SeoPhysics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA.
Grant T GullbergMolecular Biophys. & Integ. Bio., Lawrence Berkeley National Lab, MS 55R0121, Berkeley, CA, 94720, USA.

Funding

DYNAMIC CARDIAC SPECT IMAGINGR01HL050663 · NHLBI · UNIVERSITY OF UTAH · PI GULLBERG, GRANT T · 1995 to 2014
$7.0M
Molecular Imaging of Cardiac Hypertrophy Using microPET and Pinhole SPECTR01EB007219 · NIBIB · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI GULLBERG, GRANT T · 2008 to 2011
$3.0M
Energy-independent single photon molecular imaging technologyR01EB026331 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CUI, YONGGANG, SEO, YOUNGHO · 2018 to 2022
$2.6M
Dynamic cardiac SPECTR01HL135490 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GULLBERG, GRANT T, SEO, YOUNGHO · 2017 to 2020
$2.4M
Pretherapy 124I-MIBG Dosimetry for Planning 131I-MIBG Neuroblastoma TherapyR01CA154561 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SEO, YOUNGHO · 2011 to 2016
$1.9M
National Institute of Health R01HL50663NCI NIH HHS R01 CA154561NCI NIH HHS R01CA154561NHLBI NIH HHS R01 HL050663NHLBI NIH HHS R01 HL135490NHLBI NIH HHS R01HL135490NIBIB NIH HHS R01 EB007219NIBIB NIH HHS R01 EB026331NIBIB NIH HHS R01EB026331NIBIB NIH HHS R01EB07219
6 · The paper itself

Abstract

purposeDynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction.

methodsSIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects.

resultsFor SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS.

conclusionThe analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.

Indexed as

Tomography, Emission-Computed, Single-PhotonAnimalsDogsHumansImaging, Three-Dimensionalcardiac imagingconvergence measures in optimizationdynamic SPECT reconstructionmatrix factorization

Identifiers

PMID30027577
PMCPMC6211286

What OpenQuestion holds

Textmetadata
LicenceTDM
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.