Evidence map›Paper›PMID 38672606›Full record

ArticleCancers2024

Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study.

Jing Liu, Angela Jakary, Javier E Villanueva-Meyer, Nicholas A Butowski, David Saloner, Jennifer L Clarke, Jennie W Taylor, Nancy Ann Oberheim Bush, Susan M Chang, Duan Xu and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

11 authors.

Jing LiuDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.ORCID 0000-0002-3571-2230
Angela JakaryDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
Javier E Villanueva-MeyerDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
Nicholas A ButowskiDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
David SalonerDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
Jennifer L ClarkeDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Jennie W TaylorDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Nancy Ann Oberheim BushDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Susan M ChangDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Duan XuDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
Janine M LupoDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.

Funding

3D Multi-Contrast MRI with Automatic Brain Tissue and Lesion SegmentationR21CA238137 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIU, JING, LUPO, JANINE MARIE · 2020 to 2021
$414k
NCI NIH HHS R21 CA238137NIH HHS R21CA238137
6 · The paper itself

Abstract

This study aimed to develop a rapid, 1 mm

Indexed as

automatic lesion detectiongliomasmacromolecular proton fractionmulti-contrastmulti-parametric mappingtwo-compartment model

Identifiers

PMID38672606
PMCPMC11049314

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.