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Bolus-tracking MRI with a simultaneous T1- and T2*-measurement.

S Sourbron1, M Heilmann, A Biffar

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This study introduces a new method to analyze dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI data together. The approach improves tumor characterization by modeling tracer leakage and tissue structure.

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Area of Science:

  • Biomedical Imaging
  • Magnetic Resonance Imaging
  • Pharmacokinetics

Background:

  • Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are powerful tools for assessing tissue perfusion and vascularity.
  • Simultaneous acquisition and analysis of both DSC and DCE MRI data can provide a more comprehensive understanding of tumor microenvironment.
  • Accurate modeling of tracer kinetics, including leakage and compartmental distribution, is crucial for reliable quantitative analysis.

Purpose of the Study:

  • To develop and validate a methodology for the simultaneous analysis of DSC-MRI and DCE-MRI data.
  • To propose generalized models for T2*-relaxation accounting for tracer leakage.
  • To utilize a two-compartment exchange model to differentiate intravascular and extravascular tracer spaces.

Main Methods:

  • Acquisition of simultaneously T2*-weighted DSC-MRI and T(1)-weighted DCE-MRI data.
  • Application of two generalized T2*-relaxation models to address tracer leakage.
  • Employment of a two-compartment exchange model for intra- and extravascular tracer separation.
  • Evaluation of methods using data from human colorectal tumors implanted in mice.

Main Results:

  • Established a practical experimental paradigm for measuring T2*-relaxivities by comparing plasma flow from DCE-MRI and DSC-MRI.
  • Observed a significant reduction in susceptibility weighting in DSC-MRI during tracer leakage, quantified by comparing mean transit times.
  • Demonstrated that a variable T2*-relaxivity model more accurately captures susceptibility loss than a one-parameter gradient correction model.
  • Identified new parameters reflecting cellular and vessel geometry, extractable only through the combined analysis.

Conclusions:

  • The proposed methodology enables simultaneous analysis of DSC-MRI and DCE-MRI data, offering enhanced insights into tumor characteristics.
  • Accurate modeling of tracer leakage and susceptibility loss is critical for reliable DSC-MRI interpretation.
  • The combined approach allows for a more complete characterization of tissue structure by extracting parameters beyond those obtainable from individual techniques.