Evidence map›Paper›PMID 34570448›Full record

ReviewCancer journal (Sudbury, Mass.)

Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas.

Jayapalli Rajiv Bapuraj, Nicholas Wang, Ashok Srinivasan, Arvind Rao

Abstract readReview
In one paragraph

Review in Cancer journal (Sudbury, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

4 authors.

Jayapalli Rajiv BapurajFrom the Division of Neuroradiology, Department of Radiology.
Nicholas WangDepartment of Computational Medicine and Bioinformatics, Michigan Medicine.
Ashok SrinivasanFrom the Division of Neuroradiology, Department of Radiology.
Arvind Rao

Funding

Synthesizing Image-derived Heterogeneity with Genomic measurements for Assessing Disease Aggressiveness in Lower Grade GliomasR37CA214955 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KURTEK, SEBASTIAN, RAO, ARVIND · 2018 to 2024
$3.9M
NCI NIH HHS R37 CA214955
6 · The paper itself

Abstract

abstractAdvanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.

Indexed as

Brain NeoplasmsGliomaHumansMagnetic Resonance ImagingPrognosis

Identifiers

PMID34570448
PMCPMC8480516

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.