ArticleEuropean radiology2016
Assessment of repeatability and treatment response in early phase clinical trials using DCE-MRI: comparison of parametric analysis using MR- and CT-derived arterial input functions.
Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.
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- Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group - ESOI Joint Paper.Frontiers in oncology · 2021Pooled it
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- Performance of recurrent neural networks with Monte Carlo dropout for predicting pharmacokinetic parameters from dynamic contrast-enhanced magnetic resonance imaging data.Journal of applied clinical medical physics · 2025Article
- Deep learning-based super-resolution and denoising algorithm improves reliability of dynamic contrast-enhanced MRI in diffuse glioma.Scientific reports · 2024Article
- A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging.Cancers · 2024Article
- Patient-specific arterial input function for accurate perfusion assessment in intraoperative fluorescence imaging.Journal of biomedical optics · 2024Article
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- Optimal time for early therapeutic response prediction in nasopharyngeal carcinoma with functional magnetic resonance imaging.Physics and imaging in radiation oncology · 2023Article
- Correlations of tumour permeability parameters with apparent diffusion coefficient in nasopharyngeal carcinoma.Physics and imaging in radiation oncology · 2022Article
- Maximum Entropy Technique and Regularization Functional for Determining the Pharmacokinetic Parameters in DCE-MRI.Journal of digital imaging · 2022Article
- Modified Maximum Entropy Method and Estimating the AIF via DCE-MRI Data Analysis.Entropy (Basel, Switzerland) · 2022Article
- DCE-MRI is more sensitive than IVIM-DWI for assessing anti-angiogenic treatment-induced changes in colorectal liver metastases.Cancer imaging : the official publication of the International Cancer Imaging Society · 2021Article
- Assessing the reproducibility of high temporal and spatial resolution dynamic contrast-enhanced magnetic resonance imaging in patients with gliomas.Scientific reports · 2021Article
- Differentiation between glioblastoma and primary CNS lymphoma: application of DCE-MRI parameters based on arterial input function obtained from DSC-MRI.European radiology · 2021Article
- Descriptive analysis of MRI functional changes occurring during reduced dose radiotherapy for myxoid liposarcomas.The British journal of radiology · 2021Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesPharmacokinetic (PK) modelling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data requires a reliable measure of the arterial input function (AIF) to robustly characterise tumour vascular properties. This study compared repeatability and treatment-response effects of DCE-MRI-derived PK parameters using a population-averaged AIF and three patient-specific AIFs derived from pre-bolus MRI, DCE-MRI and dynamic contrast computed tomography (DC-CT) data.
methodsThe four approaches were compared in 13 patients with abdominal metastases. Baseline repeatability [Bland-Altman statistics; coefficient of variation (CoV)], cohort percentage change and p value (paired t test) and number of patients with significant DCE-MRI parameter change post-treatment (limits of agreement) were assessed.
resultsIndividual AIFs were obtained for all 13 patients with pre-bolus MRI and DC-CT-derived AIFs, but only 10/13 patients had AIFs measurable from DCE-MRI data. The best CoV (7.5 %) of the transfer coefficient between blood plasma and extravascular extracellular space (K (trans)) was obtained using a population-averaged AIF. All four AIF methods detected significant treatment changes: the most significant was the DC-CT-derived AIF. The population-based AIF was similar to or better than the pre-bolus and DCE-MRI-derived AIFs.
conclusionsA population-based AIF is the recommended approach for measuring cohort and individual effects since it has the best repeatability and none of the PK parameters derived using measured AIFs demonstrated an improvement in treatment sensitivity. KEY POINTS: • Pharmacokinetic modelling of DCE-MRI data requires a reliable measure of AIF. • Individual MRI-DCE-derived AIFs cannot reliably be extracted from patients. • All four AIF methods detected significant K (trans) changes after treatment. • A population-based AIF can be recommended for measuring cohort treatment responses in trials.
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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.