Evidence map›Paper›PMID 35277742›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2022

Deep learning-based attenuation correction for whole-body PET - a multi-tracer study with

Takuya Toyonaga, Dan Shao, Luyao Shi, Jiazhen Zhang, Enette Mae Revilla, David Menard, Joseph Ankrah, Kenji Hirata, Ming-Kai Chen, John A Onofrey and 1 more

Open access · greenAbstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

17 citing papers in PubMed, 21 citations in OpenAlex.

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  17. Contribution of Intravital Neuroimaging to Study Animal Models of Multiple Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    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

11 authors at 3 institutions in 3 countries.

Takuya Toyonaga *Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
Dan Shao *Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
Luyao ShiDepartment of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
Jiazhen ZhangDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
Enette Mae RevillaDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
David MenardYale New Haven Hospital, New Haven, CT, USA.
Joseph AnkrahYale New Haven Hospital, New Haven, CT, USA.
Kenji HirataDepartment of Diagnostic Imaging, School of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan.
Ming-Kai ChenDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
John A OnofreyDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
Yihuan LuDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA. yihuan.lu@yale.edu.
Yale University · USYale New Haven Hospital · USHokkaido University · JP

Funding

Data-driven Head Motion Correction in PET Imaging Using Deep LearningR21EB028954 · NIBIB · YALE UNIVERSITY · PI ONOFREY, JOHN AARON · 2020 to 2022
$866k
Data-Driven Simultaneous Respiratory and Body Motion Correction for PET/CTR03EB027209 · NIBIB · YALE UNIVERSITY · PI LU, YIHUAN · 2019 to 2020
$168k
NIBIB NIH HHS R03 EB027209NIBIB NIH HHS R21 EB028954
6 · The paper itself

Abstract

A novel deep learning (DL)-based attenuation correction (AC) framework was applied to clinical whole-body oncology studies using

methodsClinical whole-body PET/CT datasets of

resultsµ-DL yielded high resolution and fine detail recovery of the attenuation map, which was superior in quality as compared to µ-MLAA in all metrics for all tracers. Using OSEM

conclusionsThe proposed framework provides accurate and robust attenuation correction for whole-body

Indexed as

Deep LearningNeoplasmsFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedPositron-Emission TomographyPositron Emission Tomography Computed TomographyRadionuclide ImagingRadiopharmaceuticalscopper dotatate CU-64Fluorodeoxyglucose F18RadiopharmaceuticalsAttenuation correctionDeep learningImage synthesisMLAAPET

Identifiers

PMID35277742
PMCPMC10725742
OpenAlexW4220846785

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.