Evidence map›Paper›PMID 34301784›Full record

ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2022

A Path to Qualification of PET/MRI Scanners for Multicenter Brain Imaging Studies: Evaluation of MRI-Based Attenuation Correction Methods Using a Patient Phantom.

Ciprian Catana, Richard Laforest, Hongyu An, Fernando Boada, Tuoyu Cao, David Faul, Bjoern Jakoby, Floris P Jansen, Bradley J Kemp, Paul E Kinahan and 13 more

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Synthetic PET via Domain Translation of 3-D MRI.IEEE transactions on radiation and plasma medical sciences · 2023
    Article
  6. Review
  7. 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

23 authors at 20 institutions in 5 countries.

Ciprian CatanaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts; ccatana@mgh.harvard.edu.
Richard LaforestMallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri.
Hongyu AnMallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri.
Fernando BoadaCenter for Advanced Imaging Innovation and Research, Department of Radiology, New York University Langone Medical Center, New York, New York.
Tuoyu CaoShanghai United Imaging Healthcare Co., Ltd., Shanghai, China.
David FaulSiemens Medical Solutions USA, Inc., Malvern, Pennsylvania.
Bjoern JakobySiemens MR, Siemens Healthcare GmbH, Erlangen, Germany.
Floris P JansenPET/MR Engineering, GE Healthcare, Chicago, Illinois.
Bradley J KempDivision of Nuclear Medicine, Mayo Clinic, Rochester, Minnesota.
Paul E KinahanImaging Research Laboratory, University of Washington, Seattle, Washington.
Peder LarsonDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California.
Michael A LevineAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts.
Piotr ManiawskiAdvanced Molecular Imaging, Philips Healthcare, Cleveland, Ohio.
Osama MawlawiDepartment of Imaging Physics, University of Texas M.D. Anderson Cancer Center, Houston, Texas.
Jonathan E McConathyDepartment of Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
Alan B McMillanDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.
Julie C PriceAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts.
Abhejit RajagopalDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California.
John SunderlandDivision of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa.
Patrick Veit-HaibachToronto Joint Department of Medical Imaging, University Health Network, Sinai Health System, and Women's College Hospital, Department of Medical Imaging, University of Toronto, Toronto, Canada.
Kristen A WangerinGE Healthcare, Chicago, Illinois; and.
Chunwei YingDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri.
Thomas A HopeDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California.
University of California, San Francisco · USMallinckrodt (United States) · USAthinoula A. Martinos Center for Biomedical Imaging · USGeneral Electric (Israel) · ILHarvard University · USHealth Net · USMassachusetts General Hospital · USNYU Langone Health · USPhilips (United States) · USScripps MD Anderson Cancer Center · USSiemens Healthcare (Germany) · DESiemens Healthcare (United States) · USSiemens (United States) · USUnited Imaging Healthcare (China) · CNUniversity of Alabama at Birmingham · USUniversity of Iowa · USUniversity of Washington Medical Center · USUniversity of Wisconsin–Madison · USWashington University in St. Louis · USWinnMed · US

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Daniel K Sodickson · 2014 to 2026
$19.3M
Development of the Human Dynamic Neurochemical Connectome ScannerU01EB029826 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2020 to 2025
$7.1M
Multimodal MR-PET Machine Learning Approaches for Primary Prostate Cancer CharacterizationR01CA218187 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2018 to 2023
$3.3M
Qualification and Harmonization of PET/MRI for Cancer Clinical TrialsR01CA212148 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOPE, THOMAS, LAFOREST, RICHARD ANDRE · 2017 to 2022
$2.7M
Development of 7-T MR-compatible TOF-DOI PET Detector and System Technology for the Human Dynamic Neurochemical Connectome ScannerR01EB026995 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2018 to 2019
$959k
Multi-modal and Extreme PET/MRI Reconstruction MethodsF32EB030411 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RAJAGOPAL, ABHEJIT · 2020 to 2022
$142k
NCI NIH HHS R01 CA212148NCI NIH HHS R01 CA218187NIBIB NIH HHS F32 EB030411NIBIB NIH HHS P41 EB017183NIBIB NIH HHS R01 EB026995NIBIB NIH HHS U01 EB029826
6 · The paper itself

Abstract

PET/MRI scanners cannot be qualified in the manner adopted for hybrid PET/CT devices. The main hurdle with qualification in PET/MRI is that attenuation correction (AC) cannot be adequately measured in conventional PET phantoms because of the difficulty in converting the MR images of the physical structures (e.g., plastic) into electron density maps. Over the last decade, a plethora of novel MRI-based algorithms has been developed to more accurately derive the attenuation properties of the human head, including the skull. Although promising, none of these techniques has yet emerged as an optimal and universally adopted strategy for AC in PET/MRI. In this work, we propose a path for PET/MRI qualification for multicenter brain imaging studies. Specifically, our solution is to separate the head AC from the other factors that affect PET data quantification and use a patient as a phantom to assess the former. The emission data collected on the integrated PET/MRI scanner to be qualified should be reconstructed using both MRI- and CT-based AC methods, and whole-brain qualitative and quantitative (both voxelwise and regional) analyses should be performed. The MRI-based approach will be considered satisfactory if the PET quantification bias is within the acceptance criteria specified here. We have implemented this approach successfully across 2 PET/MRI scanner manufacturers at 2 sites.

Indexed as

Image Processing, Computer-AssistedPositron Emission Tomography Computed TomographyBrainHumansMagnetic Resonance ImagingNeuroimagingPositron-Emission Tomographyattenuation correctionmulticenter trialsPET/MRIqualification

Identifiers

PMID34301784
PMCPMC8973286
OpenAlexW3184638900

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.