Evidence map›Paper›PMID 36204543›Full record

ArticleRadiology. Artificial intelligence2022

Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks.

Jeffrey D Rudie, Evan Calabrese, Rachit Saluja, David Weiss, John B Colby, Soonmee Cha, Christopher P Hess, Andreas M Rauschecker, Leo P Sugrue, Javier E Villanueva-Meyer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology. Artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

10 authors.

Jeffrey D RudieDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0001-8609-8421
Evan CalabreseDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-1464-0354
Rachit SalujaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-2567-9465
David WeissDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-7494-2987
John B ColbyDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0001-8816-711X
Soonmee ChaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-5924-5876
Christopher P HessDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-5132-5302
Andreas M RauscheckerDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0003-0633-9876
Leo P SugrueDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0001-7315-4519
Javier E Villanueva-MeyerDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, Suite S-261D, Box 0628, San Francisco, CA 94143 (J.D.R., E.C., D.W., J.B.C., S.C., C.P.H., A.M.R., L.P.S., J.E.V.M.); and Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (R.S.).ORCID https://orcid.org/0000-0002-5910-0757

Funding

Biomedical Imaging for Clinician ScientistsT32EB001631 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI THOMAS M LINK · 2005 to 2026
$5.6M
NIBIB NIH HHS T32 EB001631
6 · The paper itself

Abstract

Neural networks were trained for segmentation and longitudinal assessment of posttreatment diffuse glioma. A retrospective cohort (from January 2018 to December 2019) of 298 patients with diffuse glioma (mean age, 52 years ± 14 [SD]; 177 men; 152 patients with glioblastoma, 72 patients with astrocytoma, and 74 patients with oligodendroglioma) who underwent two consecutive multimodal MRI examinations were randomly selected into training (

Indexed as

Brain/Brain StemCNSConvolutional Neural Network (CNN)MR ImagingNeural NetworksNeuro-OncologyQuantificationSegmentation

Identifiers

PMID36204543
PMCPMC9530762

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.