Evidence map›Paper›PMID 26133621›Full record

ArticleMedical physics2015

Pulmonary imaging using respiratory motion compensated simultaneous PET/MR.

Joyita Dutta, Chuan Huang, Quanzheng Li, Georges El Fakhri

Open access · hybridAbstract readValidation Study
In one paragraph

Article in Medical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021
    Review
  4. Additional Value of IntegratedKorean journal of radiology · 2021
    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

4 authors at 1 institution in 1 country.

Joyita DuttaCenter for Advanced Medical Imaging Sciences, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115.
Chuan HuangCenter for Advanced Medical Imaging Sciences, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts 02114; Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115; and Departments of Radiology and Psychiatry, Stony Brook Medicine, Stony Brook, New York 11794.
Quanzheng LiCenter for Advanced Medical Imaging Sciences, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115.
Georges El FakhriCenter for Advanced Medical Imaging Sciences, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts 02114 and Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115.
Harvard University · US

Funding

Quantitative Oncologic PET-MRR01CA165221 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI EL FAKHRI, GEORGES · 2012 to 2023
$4.7M
Quantitative Cardiac PETR01HL110241 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI EL FAKHRI, GEORGES · 2011 to 2014
$1.9M
Quantitative Methods for Clinical Whole Body Dynamic PETR01EB013293 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI LI, QUANZHENG · 2012 to 2015
$1.5M
NCI NIH HHS 1R01CA165221NCI NIH HHS R01 CA165221NHLBI NIH HHS 1R01HL110241NHLBI NIH HHS R01 HL110241NIBIB NIH HHS 1R01EB013293NIBIB NIH HHS R01 EB013293
6 · The paper itself

Abstract

purposePulmonary positron emission tomography (PET) imaging is confounded by blurring artifacts caused by respiratory motion. These artifacts degrade both image quality and quantitative accuracy. In this paper, the authors present a complete data acquisition and processing framework for respiratory motion compensated image reconstruction (MCIR) using simultaneous whole body PET/magnetic resonance (MR) and validate it through simulation and clinical patient studies.

methodsThe authors have developed an MCIR framework based on maximum a posteriori or MAP estimation. For fast acquisition of high quality 4D MR images, the authors developed a novel Golden-angle RAdial Navigated Gradient Echo (GRANGE) pulse sequence and used it in conjunction with sparsity-enforcing k-t FOCUSS reconstruction. The authors use a 1D slice-projection navigator signal encapsulated within this pulse sequence along with a histogram-based gate assignment technique to retrospectively sort the MR and PET data into individual gates. The authors compute deformation fields for each gate via nonrigid registration. The deformation fields are incorporated into the PET data model as well as utilized for generating dynamic attenuation maps. The framework was validated using simulation studies on the 4D XCAT phantom and three clinical patient studies that were performed on the Biograph mMR, a simultaneous whole body PET/MR scanner.

resultsThe authors compared MCIR (MC) results with ungated (UG) and one-gate (OG) reconstruction results. The XCAT study revealed contrast-to-noise ratio (CNR) improvements for MC relative to UG in the range of 21%-107% for 14 mm diameter lung lesions and 39%-120% for 10 mm diameter lung lesions. A strategy for regularization parameter selection was proposed, validated using XCAT simulations, and applied to the clinical studies. The authors' results show that the MC image yields 19%-190% increase in the CNR of high-intensity features of interest affected by respiratory motion relative to UG and a 6%-51% increase relative to OG.

conclusionsStandalone MR is not the traditional choice for lung scans due to the low proton density, high magnetic susceptibility, and low T2 (∗) relaxation time in the lungs. By developing and validating this PET/MR pulmonary imaging framework, the authors show that simultaneous PET/MR, unique in its capability of combining structural information from MR with functional information from PET, shows promise in pulmonary imaging.

Indexed as

AgedArtifactsComputer SimulationFemaleHumansLungMagnetic Resonance ImagingMaleMiddle AgedModels, BiologicalMotionMultimodal ImagingPhantoms, ImagingPositron-Emission TomographyRespirationRespiratory-Gated Imaging Techniques

Identifiers

PMID26133621
PMCPMC4474958
OpenAlexW612367301

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.