ArticleCancers2020
A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 6 of them syntheses that pooled 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.
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.
Who cites it
25 citing papers in PubMed, 6 syntheses or guidelines pooled it, 39 citations in OpenAlex.
- Artificial intelligence algorithms for differentiating pseudoprogression from true progression in high-grade gliomas: A systematic review and meta-analysis.Neurosurgical review · 2025Pooled it
- Systematic review and epistemic meta-analysis to advance binomial AI-radiomics integration for predicting high-grade glioma progression and enhancing patient management.Scientific reports · 2025Pooled it
- Comparing [18F]FET PET and [18F]FDOPA PET for glioma recurrence diagnosis: a systematic review and meta-analysis.Frontiers in oncology · 2023Pooled it
- Machine learning imaging applications in the differentiation of true tumour progression from treatment-related effects in brain tumours: A systematic review and meta-analysis.Journal of medical imaging and radiation oncology · 2022Pooled it
- Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis.Scientific reports · 2022Pooled it
- Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies.Frontiers in oncology · 2022Pooled it
- PET-based Radiomics Analysis for Predicting Prognosis and Differentiation Treatment-Related Changes in Glioma: A Systematic Review.Journal of biomedical physics & engineering · 2026Article
- Timepoint-Specific Benchmarking of Deep Learning Models for Glioblastoma Follow-Up MRI.Cancers · 2025Article
- Review
- Pseudoprogression versus true progression in glioblastoma: what neurosurgeons need to know.Journal of neurosurgery · 2023Review
- Diagnostic accuracy of glioma pseudoprogression identification with positron emission tomography imaging: a systematic review and meta-analysis.Quantitative imaging in medicine and surgery · 2023Article
- Review
- Digital Case Manager-A Data-Driven Tool to Support Family Caregivers with Initial Guidance.International journal of environmental research and public health · 2023Article
- Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas.Frontiers in oncology · 2023Article
- A deep learning model for discriminating true progression from pseudoprogression in glioblastoma patients.Journal of neuro-oncology · 2022Article
- Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression.Journal of neuro-oncology · 2022Article
- The Utility of Conventional Amino Acid PET Radiotracers in the Evaluation of Glioma Recurrence also in Comparison with MRI.Diagnostics (Basel, Switzerland) · 2022Review
- Applications of Artificial Intelligence Based on Medical Imaging in Glioma: Current State and Future Challenges.Frontiers in oncology · 2022Review
- Review
- TERT-Promoter Mutational Status in Glioblastoma - Is There an Association With Amino Acid Uptake on DynamicFrontiers in oncology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.