ArticleNeuroImage. Clinical2022
Learning-based analysis of amide proton transfer-weighted MRI to identify true progression in glioma patients.
Article in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 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
- Performance of amide proton transfer imaging to differentiate true progression from therapy-related changes in gliomas and metastases.European radiology · 2025Pooled it
- Multiparametric MRI radiomics integrating Arterial Spin Labeling, Quantitative Susceptibility Mapping, and Amide Proton Transfer imaging for differentiating glioma recurrence from post-treatment response.Frontiers in oncology · 2026Article
- Chemical Exchange Saturation Transfer Imaging in Neuroinflammation: Methods, Challenges, and Recommendations.International journal of molecular sciences · 2025Review
- AI-Driven Innovations in Neuroradiology and Neurosurgery: Scoping Review of Current Evidence and Future Directions.Cancers · 2025Review
- IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI.Diagnostics (Basel, Switzerland) · 2024Article
- Advances in diffuse glioma assessment: preoperative and postoperative applications of chemical exchange saturation transfer.Frontiers in neuroscience · 2024Review
- MoViT: Memorizing Vision Transformers for Medical Image Analysis.Machine learning in medical imaging. MLMI (Workshop) · 2024Article
- CEST2022: Amide proton transfer-weighted MRI improves the diagnostic performance of multiparametric non-contrast-enhanced MRI techniques in patients with post-treatment high-grade gliomas.Magnetic resonance imaging · 2023Article
- Accelerated and quantitative three-dimensional molecular MRI using a generative adversarial network.Magnetic resonance in medicine · 2023Article
- Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.International journal of molecular sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
The purpose of this study was to develop and verify a convolutional neural network (CNN)-based deep-learning algorithm to identify tumor progression versus response by adding amide proton transfer-weighted (APTw) MRI data to structural MR images as the proposed model input. 145 scans with 2175 MR instances from 98 patients with malignant glioma (acquired between April 2010 and February 2018) were re-analyzed. An end-to-end classification framework based on a ResNet backbone was developed. The architecture includes a learnable subtraction layer and a hierarchical classification paradigm, and synthesizes information over multiple MR slices using a long short-term memory. Areas under the receiver-operating-characteristic curves (AUCs) were used to assess the impact of adding APTw MRI to structural MRI (T
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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.