Evidence map›Paper›PMID 36246986›Full record

ArticleBioMed research international2022

Multimodal MRI-Based Radiomic Nomogram for the Early Differentiation of Recurrence and Pseudoprogression of High-Grade Glioma.

Hui Jing, Fan Yang, Kun Peng, Danlei Qin, Yexin He, Guoqiang Yang, Hui Zhang

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In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Hui JingCollege of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0002-4412-764X
Fan YangCollege of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0002-3337-4821
Kun PengDepartment of Radiology, The Sixth Hospital, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0002-4844-2815
Danlei QinCollege of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0002-5855-1011
Yexin HeDepartment of Radiology, Shanxi Provincial People's Hospital, Affiliated People's Hospital of Shanxi Medical University, Taiyuan, China.ORCID https://orcid.org/0000-0003-1816-4065
Guoqiang YangDepartment of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0001-8824-244X
Hui ZhangCollege of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.ORCID https://orcid.org/0000-0002-0565-0411

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the diagnostic value of multimodal MRI radiomics based on T2-weighted fluid attenuated inversion recovery imaging (T2WI-FLAIR) combined with T1-weighted contrast enhanced imaging (T1WI-CE) in the early differentiation of high-grade glioma recurrence from pseudoprogression. Methods: A total of one hundred eighteen patients with brain gliomas who were diagnosed from March 2014 to April 2020 were retrospectively analyzed. According to the clinical characteristics, the patients were randomly split into a training group ( Results: There were 75 cases of recurrence and 43 cases of pseudoprogression. The diagnostic efficacies of the multimodal MRI-based radiomic model were relatively high. The AUC values and ACC of the training group were 0.831 and 77.11%, respectively, and the AUC values and ACC of the test group were 0.829 and 88.57%, respectively. The calibration curve of the nomogram showed that the discrimination probability was consistent with the actual occurrence in the training group, and the discrimination probability was roughly the same as the actual occurrence in the test group. In the decision curve analysis, the Conclusion: The multimodal MRI radiomic model has relatively high efficiency in the early differentiation of recurrence from pseudoprogression, and it could be helpful for clinicians in devising correct treatment plans so that patients can be treated in a timely and accurate manner.

Indexed as

GliomaNomogramsHumansMagnetic Resonance ImagingRetrospective StudiesROC Curve

Identifiers

PMID36246986
PMCPMC9553483

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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.