Evidence map›Paper›PMID 36057449›Full record

ArticleNMR in biomedicine2023

Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas.

Shanshan Jiang, Pengfei Guo, Hye-Young Heo, Yi Zhang, Jingpu Wu, Yuecen Jin, John Laterra, Charles G Eberhart, Michael Lim, Jaishri O Blakeley

Open access · greenAbstract read
In one paragraph

Article in NMR in biomedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. 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

10 authors at 2 institutions in 1 country.

Shanshan JiangDivision of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.
Pengfei GuoDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
Hye-Young HeoDivision of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0002-7297-2015
Yi ZhangDivision of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.
Jingpu WuDepartment of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA.
Yuecen JinDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
John LaterraDepartment of Neurology, Johns Hopkins University, Baltimore, Maryland, USA.
Charles G EberhartDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, USA.
Michael LimDepartment of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA.
Jaishri O BlakeleyDepartment of Neurology, Johns Hopkins University, Baltimore, Maryland, USA.
Johns Hopkins University · USKennedy Krieger Institute · US

Funding

TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2012 to 2020
$13.1M
Quantitative CEST MRI for GBM Early Response Prediction and Biopsy GuidanceR37CA248077 · NCI · JOHNS HOPKINS UNIVERSITY · PI Shanshan Jiang · 2021 to 2026
$2.2M
Amide Proton Transfer (APT) MRI of Brain Tumors at 3TR01CA228188 · NCI · JOHNS HOPKINS UNIVERSITY · PI ZHOU, JINYUAN · 2019 to 2022
$1.6M
NCI NIH HHS R01 CA228188NCI NIH HHS R37 CA248077NIBIB NIH HHS P41 EB015909
6 · The paper itself

Abstract

The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T

Indexed as

GliomaProtonsAmidesHumansNeoplasm Recurrence, LocalRetrospective StudiesAmidesProtonsamide proton transfer-weighted imagingglioblastomaMRIradiomicstreatment effect

Identifiers

PMID36057449
PMCPMC10502874
OpenAlexW4294712738

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.