The team

Marieke Heisen

PhD student

the central PhD ​student. She spent 6 months in 2007 at the University of Chicago, Chicago, USA.

Thorsten Twellmann

Postdoc

joined us as a Senior Research Scientist in cooperation with Philips Medical Systems, Best, NL

Geert Litjens

MSc student

joined as a BME MSc student. His MSc thesis  work greatly contributed to the project.

Hans Buurman

Senior Research Scientist

led the activities at Philips Healthcare at Best.

Next to the core members more people participated. In Eindhoven: prof. Frans Gerritsen, Natal van Riel, Anna Vilanova, Ursula Kose and in Chicago: Greg Karzmar, Dev Mustafi, Xiaobing Fan and Abbie Wood.

Dynamic Contrast-Enhanced MRI (DCE-MRI).

It turns out that, after an injection of contrast medium in the blood stream of the patient, the wash-out of this contrast medium is faster in the leaky angiogenic vasculature. This can be measured with s small series of MRI images at three or four time points:

The intensity is measured in the center of the tumor. If the intensity decreases fast, there is fast washout, and the tissue may be malignant (tumor). If the intensity keeps increasing: this indicates benign (healthy) tissue.

T1-weighted, fat-suppressed
T1: longitudinal relaxation time, voxel-specific, influenced by the contrast agent

Source: 
Weinstein et al., Radiology, 1999 [url], Kelcz et al. AJR, 2002 [url].

As always, we formulated a number of key questions to be addressed:

The wash-out process

Can we model this washout process, to better understand it?

Best model

What is the best model?

TEMPORAl RESOLUTION

Low temporal resolution is easier in the clinic: what is the best imaging speed: fast or slow?

INTENSITY <-> CONCENTRATION

How is the MRI intensity related to the contrast medium concentration?

PERFORMANCE

How does the method perform in practice?

1. Two-compartment modeling

is the common way to model the flow of contrast medium between two compartments. This is known as the extended Tofts-Kety model [Tofts 1999].

Differential equation:
[v_e frac{d C_e (t)}{d t} = K^{trans} (C_p (t) - C_e (t))]
Solution:
[ C_e (t) = frac{K^{trans}}{v_e} int_{ 0}^{t} C_p (t') cdot e^{-K^{trans} (t-t')/ , v_e} d t' ]
Total tissue concentration:
[ C_t (t) = v_p cdot C_p (t) + v_e cdot C_e (t) ]

There is a higher uptake of contrast agent in tissue with high perfusion and high vessel wall permeability.
The final curve assessment is done by applying shape models, e.g. a three-time-point model.

  • Cp = concentration in arterial blood plasma, 
  • Cv = concentraion in venous blood plasma,
  • Ce = concentration in extravascular space
  • Vc = volume of the capillary compartment,
  • K-trans = perfusion parameter.

2. The best model

We investigated a total of four models:

  • the standard Tofts model,
  • the extended Tofts model,
  • the shutter speed model and
  •  the Brix model.

The model evaluation and selection was done by Geert Litjens in his MSc project and thesis: We decided on the standard Tofts model.

3. Trade-off between spatial and temporal resolution

Low temporal resolution is easier in the clinic: what is the best model: fast or slow?
This was studied in a rat model at the University of Chicago.

High-spatial and
low-temporal
resolution

Low-spatial and
high-temporal
resolution

Abstract from the paper:
We investigated the influence of the temporal resolution of dynamic contrast-enhanced MRI data on pharmacokinetic parameter estimation. Dynamic Gd-DTPA (Gadolinium-diethylene triamine pentaacetic acid) enhanced MRI data of implanted prostate tumors on rat hind limb were acquired at 4.7 T, with a temporal resolution of ∼5 sec. The data were subsequently downsampled to temporal resolutions in the range of 15 sec to 85 sec, using a strategy that involves a recombination of k-space data. A basic two-compartment model was fit to the contrast agent uptake curves. The results demonstrated that as temporal resolution decreases, the volume transfer constant (K-trans) is progressively underestimated (∼4% to ∼25%), and the fractional extravascular extracellular space (ve) is progressively overestimated (∼1% to ∼10%). The proposed downsampling strategy simulates the influence of temporal resolution more realistically than simply downsampling by removing samples. 

It turned out that, if we could measure the Arterial Input Function (AIF) accurately, the low teporal resolution sampling could be used with minimal errors.
The AIF is the pulse shape of the concentration of the contrast medium, just after the injection. The injection should be as short as possible.

4: How is the MRI intensity related to the contrast medium concentration?

In Chicago, at the Magnetic Resonance Imaging and Spectroscopy Laboratory, Department of Radiology, University of Chicago, Marieke worked with the local team, led by Greg Karczmar (physicist) to develop a unique air bubble free agar phantom to standardize and calibrate dynamic contrast-enhanced breast MRI.
The relation between MRI intensity and contrast medium concentration could be precisely quantified. 

5. How does the method perform in practice?

We were able to use 14 patient data sets. Although a small number, we were able to establish a relation between malignancy and K-trans values. Benign tissues have lower K-trans values when compared to malignant tissues. 

Publications from this project

Journal publications
  • M. Heisen, X. Fan, J. Buurman, N.A.W. van Riel, G.S. Karczmar, B.M. ter Haar Romeny (2010). “The use of a reference tissue arterial input function with low temporal resolution DCE‐MRI data” Phys Med Biol, 55, 4871‐4883
  • M. Heisen, X. Fan, J. Buurman, N.A.W. van Riel, G.S. Karczmar, B.M. ter Haar Romeny (2010). “The influence of temporal resolution in determining pharmacokinetic parameters from DCE‐MRI data” Magn Reson Med, 63, 811‐816
  • Kluza, Ewelina, Marieke Heisen, Sophie Schmid, Daisy WJ van der Schaft, Raymond M. Schiffelers, Gert Storm, Bart M. ter Haar Romeny, Gustav J. Strijkers, and Klaas Nicolay. "Multi-parametric assessment of the anti-angiogenic effects of liposomal glucocorticoids." Angiogenesis 14, no. 2 (2011): 143-153.
  • G.J.S. Litjens, M. Heisen, J. Buurman, B.M. ter Haar Romeny (submitted). “Data‐imposed limitations on pharmacokinetic models for DCE‐MRI of the breast”
  • Pineda, F., M. Heisen, A. Wood, D. Mustafi, S. Lobregt, B. Peng, G. Newstead, J. Buurman, and G. Karczmar. "TU‐A‐301‐09: Moving towards Quantitative Breast MRI: Dynamic Contrast Media Concentration Images." Medical Physics 38, no. 6Part28 (2011): 3746-3746.
  • Litjens, Geert JS, M. Heisen, Johannes Buurman, and Bart M. ter Haar Romeny. "Pharmacokinetic models in clinical practice: what model to use for DCE-MRI of the breast?." In 2010 IEEE international symposium on biomedical imaging: from nano to macro, pp. 185-188. IEEE, 2010.
  • Mustafi, D., E. Peng, M. Heisen, A. M. Wood, J. Buurman, and G. S. Karczmar. "World of phantoms: Reference standards for bench to breast MRI." In
  • Proceedings of the 17th Annual Meeting and exhibition of the international society for magnetic resonance in medicine (ISMRM 09), 18-24 April 2009, Honolulu, Hawai'i, USA, 2009, p. 2104. 2009.
Conference proceedings
  • M. Heisen, B. Peng, A.M. Wood, D. Mustafi, J. Buurman, G.M. Newstead, G.S. Karczmar (2010). “Patient‐specific calibration for breast MRI: breast‐coil insertable reference phantom” Proceedings ISMRM 18, Stockholm, Sweden, 2493
  • M. Heisen, X. Fan, J. Buurman, B.M. ter Haar Romeny (2010). “Effects of reference tissue AIF derived from low temporal resolution DCE‐MRI data on pharmacokinetic parameter estimation” Proceedings ISMRM 18, Stockholm, Sweden, 4802
  • G.J.S. Litjens, M.Heisen, J. Buurman, B.M. ter Haar Romeny (2010). “Pharmacokinetic models in clinical practice: What model to use for DCE‐MRI of the breast?” Proceedings IEEE ISBI 2010, Rotterdam, The Netherlands, 1727
  • M. Heisen, A.M. Wood, J. Buurman, D. Mustafi, B. Peng, G.M. Newstead, C. Yang, M.K. Ivancevic, G.S. Karczmar (2009). “Standardization and calibration for breast MRI: The use of a unique air bubble free agar phantom” Proceedings RSNA 2009, Chicago, USA, 421
  • Heisen, M., J. Buurman, T. Twellmann, A. Vilanova, F. A. Gerritsen, and B. M. ter Haar Romeny. "Pharmacokinetic analysis of dynamic contrast-enhanced (DCE) MR breast images." In 1st Dutch Bio-Medical Engineering Conference (BME 2007), January 18-19, 2007, Egmond aan Zee, The Netherlands, pp. 82-82. 2007.
  • M. Heisen, X. Fan, J. Buurman, B.M. ter Haar Romeny (2009). “The effect of the temporal resolution of the arterial input function (AIF) on pharmacokinetic parameter estimation from dynamic contrast‐enhanced (DCE) MRI data” Proceedings RSNA 2009, Chicago, USA, 563
  • G.J.S. Litjens, M. Heisen, J. Buurman, A.M. Wood, M. Medved, G.S. Karczmar, B.M. ter Haar Romeny (2009). “T1 quantification: Variable flip angle method vs. use of reference phantom” Proceedings RSNA 2009, Chicago, USA, 422
  • D. Mustafi, B. Peng, M. Heisen, A.M. Wood, J. Buurman, G.S. Karczmar (2009). “World of phantoms: Reference standards for bench to breast MRI” Proceedings ISMRM 17, Honolulu, USA, 2104
  • M. Heisen, X. Fan, T. Twellmann, J. Buurman, N.A.W. van Riel, G.S. Karczmar, B.M. ter Haar Romeny (2008). “The role of temporal resolution in determining pharmacokinetic parameters from DCE‐MR data” Proceedings ISMRM 16, Toronto Canada, 3836
  • M. Heisen, T. Twellmann, J. Buurman, A. Vilanova, F.A. Gerritsen, B.M. ter Haar Romeny (2007). “The influence of temporal resolution and phase‐encoding order on shape‐based classification of dynamic contrast enhanced (DCE) MRI uptake curves in the breast” Proceedings ISMRM 15, Berlin, Germany, 133
  • M. Heisen, J. Buurman, A. Vilanova, T. Twellmann, F.A. Gerritsen (2007). “Impact of the arterial input function on the classification of contrast‐agent uptake curves in dynamic contrast‐enhanced (DCE) MR images based on heuristic shape modeling” Proceedings ECR 2007, Vienna, Austria, 284
  • Twellmann, T., T. W. Nattkemper, and M. Heisen. "Pseudo-color visualizations of DCE-MR image series for MR mammography." In 1st Dutch Bio-Medical Engineering Conference (BME 2007), January 18-19, 2007, Egmond aan Zee, The Netherlands, p. 81. 2007.
  • van Aalst, W., T. Twellmann, H. Buurman, F. Gerritsen, and B. M. ter Haar Romeny. "Use of T2-weighted images in computer-aided diagnosis for breast MRI." European Congress of Radiology-ECR 2008, EPOS C-104, 2008.
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