ArticleJournal of magnetic resonance imaging : JMRI2008
Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging.
Article in Journal of magnetic resonance imaging : JMRI, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 34 citations in OpenAlex.
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- The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI.Tomography (Ann Arbor, Mich.) · 2022Article
- An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques.Tomography (Ann Arbor, Mich.) · 2022Article
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- Gadolinium-labeled affibody-XTEN recombinant vector for detection of HER2+ lesions of ovarian cancer lung metastasis using quantitative MRI.Journal of controlled release : official journal of the Controlled Release Society · 2021Article
- Comparison of data-driven and general temporal constraints on compressed sensing for breast DCE MRI.Magnetic resonance in medicine · 2021Article
- A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2017Article
- Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA.Journal of pharmacokinetics and pharmacodynamics · 2016Article
- Identifying the association between contrast enhancement pattern, surgical resection, and prognosis in anaplastic glioma patients.Neuroradiology · 2016Article
- Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma.Seminars in radiation oncology · 2014Review
- Advanced magnetic resonance imaging of the physical processes in human glioblastoma.Cancer research · 2014Review
- DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data.BMC bioinformatics · 2013Article
- BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems.Journal of pharmacokinetics and pharmacodynamics · 2012Article
- Delayed contrast extravasation MRI for depicting tumor and non-tumoral tissues in primary and metastatic brain tumors.PloS one · 2012Article
- Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI.NMR in biomedicine · 2011Review
- Changes in vascular permeability and expression of different angiogenic factors following anti-angiogenic treatment in rat glioma.PloS one · 2010Article
- PKQuest_Java: free, interactive physiologically based pharmacokinetic software package and tutorial.BMC research notes · 2009Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle. MATERIALS AND
methodsThree published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases.
resultsThe dispersion model produced better fits than the delay model in the SSS (P < 0.0001) and cerebral cortex (P < 0.0001), and better fits than the well-mixed model in psoas muscle (P < 0.005). No model produced better fits than the dispersion model at any of the three locations.
conclusionIn this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.
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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.