Trial reportEuropean radiology2013
Analysis of the layering pattern of the apparent diffusion coefficient (ADC) for differentiation of radiation necrosis from tumour progression.
Trial report in European radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Value of DWI Combined with Magnetic Resonance Spectroscopy in the Differential Diagnosis between Recurrent Glioma and Radiation Injury: A Meta-Analysis.International journal of clinical practice · 2022Pooled it
- Radiological diagnosis of brain radiation necrosis after cranial irradiation for brain tumor: a systematic review.Radiation oncology (London, England) · 2019Pooled it
- Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis.European radiology · 2014Pooled it
- Response Assessment in Pediatric Neuro-Oncology: Implementation and Expansion of the RANO Criteria in a Randomized Phase II Trial of Pediatric Patients with Newly Diagnosed High-Grade Gliomas.AJNR. American journal of neuroradiology · 2016Trial
- Post-therapy imaging of adult brain tumours: patterns, pitfalls, and practical framework.Insights into imaging · 2026Article
- Combining quantitative susceptibility mapping, arterial spin labeling and diffusion weighted imaging for distinguishing true progression from pseudoprogression in high-grade gliomas.Neuroradiology · 2025Article
- A Radiologist's Guide to IDH-Wildtype Glioblastoma for Efficient Communication With Clinicians: Part II-Essential Information on Post-Treatment Imaging.Korean journal of radiology · 2025Review
- Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.Korean journal of radiology · 2023Article
- The centrally restricted diffusion sign on MRI for assessment of radiation necrosis in metastases treated with stereotactic radiosurgery.Journal of neuro-oncology · 2021Article
- Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation.Scientific reports · 2021Article
- Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas.Journal of neuro-oncology · 2020Article
- Pseudoprogression of brain tumors.Journal of magnetic resonance imaging : JMRI · 2018Article
- Diagnostic Accuracy of Centrally Restricted Diffusion in the Differentiation of Treatment-Related Necrosis from Tumor Recurrence in High-Grade Gliomas.AJNR. American journal of neuroradiology · 2018Article
- Differentiation of Hemangioblastoma from Metastatic Brain Tumor using Dynamic Contrast-enhanced MR Imaging.Clinical neuroradiology · 2017Article
- Reevaluating stereotactic radiosurgery for glioblastoma: new potential for targeted dose-escalation.Journal of neuro-oncology · 2016Review
- A Simple Automated Method for Detecting Recurrence in High-Grade Glioma.AJNR. American journal of neuroradiology · 2016Article
- Diffusion and perfusion MRI to differentiate treatment-related changes including pseudoprogression from recurrent tumors in high-grade gliomas with histopathologic evidence.AJNR. American journal of neuroradiology · 2015Article
- A Gamma-Knife-Enabled Mouse Model of Cerebral Single-Hemisphere Delayed Radiation Necrosis.PloS one · 2015Article
- Multimodal imaging for early functional response assessment of (90)Y-/ (177)Lu-DOTATOC peptide receptor targeted radiotherapy with DW-MRI and (68)Ga-DOTATOC-PET/CT.Molecular imaging and biology · 2014Article
- The basics of diffusion and perfusion imaging in brain tumors.Applied radiology · 2014Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the added value of diffusion-weighted imaging (DWI) to perfusion-weighted imaging (PWI) for differentiating tumour progression from radiation necrosis.
methodsSixteen consecutive patients who underwent removal of a metastatic brain tumour that increased in size after stereotactic radiosurgery were retrospectively reviewed. The layering of the ADC was categorised into three patterns. ADC values were measured on each layer, and the maximum rCBV was measured. rCBV and the layering pattern of the ADC of radiation necrosis and tumour progression were compared.
resultsNine cases of radiation necrosis and seven cases of tumour progression were pathologically confirmed. Radiation necrosis (88.9 % vs. 14.3 %) showed a three-layer pattern of ADC with a middle layer of minimum ADC more frequently. If rCBV larger than 2.6 was used to differentiate radiation necrosis and tumour progression, the sensitivity was 100 % but specificity was 56 %. If the lesions with the three-layer pattern of ADC with moderately increased rCBV (2.6-4.1) were excluded from tumour progression, the sensitivity and specificity increased to 100 %.
conclusionsThe three-layer pattern of ADC shows high specificity in diagnosing radiation necrosis; therefore, combined analysis of the ADC pattern with rCBV may have added value in the correct differentiation of tumour progression from radiation necrosis.
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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.