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Updated: Jun 5, 2026
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
Published on: April 18, 2015
Precision analysis of kinetic modelling estimates in dynamic contrast enhanced MRI
Dieter De Naeyer1, Yves De Deene, Wim P Ceelen
1Department of Civil Engineering, Institute Biomedical Technology, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium. dieter.denaeyer@Ugent.be
Object:
Dynamic contrast enhanced MRI and pharmacokinetic modelling provide a powerful tool for tumour diagnosis and treatment evaluation. However, several studies show low reproducibility of the technique and poor precision of the transendothelial transfer constant K (trans). This work proposes a theoretical framework describing how finite signal-noise-ratio (SNR) in the MR images is propagated throughout the measurement protocol to uncertainty on the kinetic parameter estimates.
Materials And Methods:
After deriving a distribution for the contrast agent concentration, a maximum likelihood estimator (MLM) is proposed that exhibits Cramer-Rao lower bounds (CRLB). An analytical expression is derived for the CRLB that can be used to determine confidence intervals for kinetic parameters and to investigate the influence of protocol parameters as scan time and temporal resolution on K (trans)-precision.
Results:
K (trans)-uncertainty can be reduced up to 30% by using MLM in comparison with least square estimator. K (trans)-precision is proportional to the SNR and depends strongly on the kinetic parameter values themselves. Minimal scan time and temporal resolution were found to be 15 min and 15 s, respectively, for Gd-DTPA. Temporal resolution should be enhanced by decreasing the NEX parameter (NEX ≤ 1).
Conclusion:
CRLB provide a golden standard to construct 95% confidence intervals, which can be used to perform protocol optimization and to test the statistical significance of K (trans)-changes in treatment evaluation.
Insights
This study introduces a method to improve the precision of K(trans) estimates in dynamic contrast-enhanced MRI. By using a maximum likelihood estimator, K(trans) uncertainty is reduced, enhancing tumor diagnosis and treatment evaluation.
Area of Science:
- Medical Imaging
- Biophysics
- Pharmacokinetics
Background:
- Dynamic contrast-enhanced MRI (DCE-MRI) is vital for tumor diagnosis and treatment assessment.
- Low reproducibility and precision in K(trans) estimates are significant challenges in DCE-MRI.
- Signal-noise-ratio (SNR) directly impacts the accuracy of kinetic parameter estimation.
Purpose of the Study:
- To develop a theoretical framework for understanding SNR propagation in DCE-MRI.
- To propose a maximum likelihood estimator (MLE) for improved kinetic parameter precision.
- To establish a method for optimizing DCE-MRI protocols and evaluating treatment efficacy.
Main Methods:
- Derived a contrast agent concentration distribution.
- Developed a maximum likelihood estimator (MLE) with Cramer-Rao lower bounds (CRLB).
- Analyzed the influence of scan time and temporal resolution on K(trans) precision.
Main Results:
- MLE reduced K(trans) uncertainty by up to 30% compared to least squares.
- K(trans) precision is directly proportional to SNR and dependent on kinetic parameter values.
- Optimal parameters include a 15-minute scan time and 15-second temporal resolution for Gd-DTPA, with NEX ≤ 1.
Conclusions:
- CRLB serve as a benchmark for constructing confidence intervals.
- Protocol optimization and statistical testing of K(trans) changes are facilitated by CRLB.
- Enhanced precision in K(trans) estimation improves DCE-MRI's diagnostic and therapeutic evaluation capabilities.
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