Trial reportEuropean radiology experimental2024
Amide proton transfer-weighted CEST MRI for radiotherapy target delineation of glioblastoma: a prospective pilot study.
Trial report in European radiology experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05970757 (Physiological MRI for Precision Radiotherapy IDH-wildtype Glioblastoma), which is not on this map. Cited by 6 papers.
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.
Physiological MRI for Precision Radiotherapy IDH-wildtype Glioblastoma
Who cites it
6 citing papers in PubMed.
- FlexCENT: A frequency-flexible CEST imaging network combining frequency offset encoding and three-dimensional U-Net.Magnetic resonance letters · 2026Article
- Grading of glioma and prediction of IDH mutation status via longitudinal relaxation time in rotating frame mapping on 5-T magnetic resonance imaging: added value to amide proton transfer-weighted imaging.Quantitative imaging in medicine and surgery · 2026Article
- MixBranchNet: a task-adaptive network for glioma segmentation and genotype prediction by exploiting spatial-spectral correlations in CEST MRI.Frontiers in oncology · 2026Article
- Personalised medicine through AI-enhanced integration of diagnostic imaging and radiation therapy.European radiology experimental · 2025Review
- Non-invasive identification of mesenchymal glioblastoma using quantitative radiomic features from advanced diffusion MRI: a preclinical-to-clinical transfer learning strategy.European radiology experimental · 2025Article
- Advances of MR imaging in glioma: what the neurosurgeon needs to know.Acta neurochirurgica · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExtensive glioblastoma infiltration justifies a 15-mm margin around the gross tumor volume (GTV) to define the radiotherapy clinical target volume (CTV). Amide proton transfer (APT)-weighted imaging could enable visualization of tumor infiltration, allowing more accurate GTV delineation. We quantified the impact of integrating APT-weighted imaging into GTV delineation of glioblastoma and compared two APT-weighted quantification methods-magnetization transfer ratio asymmetry (MTR
methodsNine glioblastoma patients underwent an extended imaging protocol prior to radiotherapy, yielding APT-weighted MTR
resultsThe GTV
conclusionLarger biological GTVs compared to the conventional GTV highlight the potential of APT-weighted imaging for radiotherapy target delineation of glioblastoma. APT-weighted LD mapping may be advantageous for target delineation as it may be more robust against motion artifacts. RELEVANCE STATEMENT: The introduction of APT-weighted imaging may, ultimately, enhance visualization of tumor infiltration and eliminate the need for the substantial 15-mm safety margin for target delineation of glioblastoma. This could reduce the risk of radiation toxicity while still effectively irradiating the tumor.
trial registrationNCT05970757 (ClinicalTrials.gov). KEY POINTS: Integration of APT-weighted imaging into target delineation for radiotherapy is feasible. The integration of APT-weighted imaging yields larger GTVs in glioblastoma. APT-weighted LD mapping may be more robust against motion artifacts than APT-weighted MTR
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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.