Evidence map›Paper›PMID 38927953›Full record

ArticleCancers2024

A Radiomic Approach for Evaluating Intra-Subgroup Heterogeneity in SHH and Group 4 Pediatric Medulloblastoma: A Preliminary Multi-Institutional Study.

Marwa Ismail, Hyemin Um, Ralph Salloum, Fauzia Hollnagel, Raheel Ahmed, Peter de Blank, Pallavi Tiwari

Abstract read
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 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. 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

7 authors.

Marwa IsmailDepartment of Radiology, University of Wisconsin-Madison, Madison, WI 53706, USA.
Hyemin UmDepartment of Radiology, University of Wisconsin-Madison, Madison, WI 53706, USA.
Ralph SalloumNationwide Children's Hospital, Columbus, OH 43205, USA.
Fauzia HollnagelDepartment of Medicine, University of Wisconsin-Madison, Madison, WI 53792, USA.
Raheel AhmedDepartment of Neurological Surgery, University of Wisconsin-Madison, Madison, WI 53792, USA.
Peter de BlankDepartment of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.ORCID 0000-0001-6623-3040
Pallavi TiwariDepartment of Radiology, University of Wisconsin-Madison, Madison, WI 53706, USA.

Funding

Radiomic spatial maps for identifying viable tumor extent on multi-parametric MRI for GlioblastomaR01CA277728 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Manmeet Ahluwalia, Pallavi Tiwari · 2024 to 2026
$3.0M
Quantitative imaging phenotypic classifier for distinguishing radiation effects from tumor recurrence in Glioblastoma .R01CA264017 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Manmeet Ahluwalia, Pallavi Tiwari · 2022 to 2026
$2.9M
RadxTools for assessing tumor treatment response on imagingU01CA248226 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI TIWARI, PALLAVI, VISWANATH, SATISH EASWAR · 2020 to 2022
$1.4M
NCI NIH HHS R01 CA264017NCI NIH HHS R01 CA277728NCI NIH HHS U01 CA248226The Dana Foundation David Mahoney Neuroimaging Program, The V Foundation Translational Research Award, The Johnson & Johnson WiSTEM2D Award, Musella Foundation Grant, R&D Pilot Award, Departments of Radiology and Medical Physics, University of Wisconsin-M NIH/NCI/ITCR: 1U01CA248226-01, NIH/NCI: 1R01CA264017-01A1, NIH/NCI: 3U01CA248226-03S1
6 · The paper itself

Abstract

Medulloblastoma (MB) is the most frequent malignant brain tumor in children with extensive heterogeneity that results in varied clinical outcomes. Recently, MB was categorized into four molecular subgroups, WNT, SHH, Group 3, and Group 4. While SHH and Group 4 are known for their intermediate prognosis, studies have reported wide disparities in patient outcomes within these subgroups. This study aims to create a radiomic prognostic signature, medulloblastoma radiomics risk (mRRisk), to identify the risk levels within the SHH and Group 4 subgroups, individually, for reliable risk stratification. Our hypothesis is that this signature can comprehensively capture tumor characteristics that enable the accurate identification of the risk level. In total, 70 MB studies (48 Group 4, and 22 SHH) were retrospectively curated from three institutions. For each subgroup, 232 hand-crafted features that capture the entropy, surface changes, and contour characteristics of the tumor were extracted. Features were concatenated and fed into regression models for risk stratification. Contrasted with Chang stratification that did not yield any significant differences within subgroups, significant differences were observed between two risk groups in Group 4 (

Indexed as

Group 4medulloblastomarisk stratificationshapeSHHtexture

Identifiers

PMID38927953
PMCPMC11201623

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Registered trials

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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.