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DCE-MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits.

Silvin P Knight1,2, James F Meaney1,2, Andrew J Fagan3

  • 1School of Medicine, Trinity College University of Dublin, Dublin, Ireland.

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Summary
This summary is machine-generated.

Optimizing dynamic contrast-enhanced MRI (DCE-MRI) acquisition and analysis is crucial for accurate pharmacokinetic (PK) modeling. This study quantifies the impact of temporal resolution and processing methods on PK parameters, identifying optimal strategies for precise measurements.

Keywords:
arterial input function (AIF)dynamic contrast enhancedimagingmagnetic resonance imagingphantomspharmacokinetics

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Area of Science:

  • Medical Imaging
  • Pharmacokinetic Modeling
  • Quantitative MRI

Background:

  • Dynamic contrast-enhanced MRI (DCE-MRI) is vital for assessing tissue perfusion and vascularity.
  • Accurate pharmacokinetic (PK) parameter estimation relies on precise measurement of contrast agent concentration-time curves (CTCs).
  • Variations in DCE-MRI acquisition and processing can introduce significant errors in derived PK parameters.

Purpose of the Study:

  • To quantify the impact of DCE-MRI acquisition temporal resolution and pharmacokinetic modeling methodologies on the accuracy and precision of derived PK parameters.
  • To establish ground truth values using a novel anthropomorphic phantom for direct comparison with measured data.
  • To identify optimal acquisition and analysis strategies to minimize measurement errors in PK parameters.

Main Methods:

  • An anthropomorphic phantom with known ground truth arterial input function (AIF) and tissue CTCs was used.
  • DCE-MRI data were acquired at various temporal resolutions (1.22-30.6 s) on a 3T scanner.
  • PK parameters (Ktrans, ve, kep) were calculated using linear and nonlinear Tofts models, with and without flip-angle corrections.

Main Results:

  • Arterial input function (AIF) measurement accuracy was highly sensitive to temporal resolution, with errors ranging from 3% to 222%.
  • Derived PK parameters (Ktrans, ve, kep) exhibited errors of 1%-24%, 2%-5%, and 1%-26%, respectively, across the tested temporal resolutions.
  • Flip-angle corrections and nonlinear least squares fitting significantly improved accuracy and precision, enabling error constraint below threshold levels.

Conclusions:

  • Errors in AIF measurement directly propagate to inaccuracies in PK parameter outputs.
  • An optimal temporal resolution was defined to maintain Ktrans, ve, and kep errors below 5% and 10%.
  • Flip-angle corrections and linear PK model fitting demonstrated substantial gains in PK parameter estimation accuracy.