Quantitative assessment of brain perfusion with magnetic resonance imaging
Bleeker, E.J.W.
Citation
Bleeker, E. J. W. (2011, June 1). Quantitative assessment of brain perfusion with magnetic resonance imaging. Retrieved from
https://hdl.handle.net/1887/17680
Version: Publisher's Version
License: Licence agreement concerning inclusion of doctoral thesis in the Institutional Repository of the University of Leiden
Downloaded from: https://hdl.handle.net/1887/17680
Note: To cite this publication please use the final published version (if
applicable).
9
Chapter 1: general introduction
the human body is a wonderful creation and it is worth investigating its beauty. the order and complexity of life and living beings is surprising, especially the robust unity of all the complicated systems involved in sustaining and creating life. this thesis focuses on the human brain. More specifically, it focuses on the measurement of blood supply to brain tissue (or brain- perfusion) with Magnetic resonance Imaging (MrI).
An MrI scanner is a unity of complicated electrical systems, software and physical principles that allow an investigator to study the inside of the human body, especially soft tissue. MrI can make a series of images each with different diagnostic information that helps the physi- cian in determining the condition of patients. Furthermore, post processing of a single image or a series of images can reveal additional (diagnostic) information, such as brain activation, functional brain connections, structural brain connections or hemodynamic properties. One of the intriguing facts of MrI is that, in general, the signal for image formation is based on free water molecules, one of life’s most essential molecules, whereas each specific MrI technique reflects completely different aspects of the functioning of the brain.
In the human body, water can diffuse freely over the membranes but nutrients have to be supplied by the blood stream. blood must flow slowly (like in the capillaries) to allow exchange of nutrients. Measuring the blood supply to brain tissue (and thereby indirectly the nutrients supply) is relevant in multiple clinical conditions. An example is measurement of blood supply in a brain tumor in order to asses its (degree of) malignancy. Another example is assessing the extent of tissue at risk following an ischemic stroke. In both conditions, flow measurements have important therapeutic consequences.
this thesis focuses on assessing blood supply to brain tissue using MrI. Chapter 2 is a review on measurements of blood supply to brain tissue and describes two techniques for measuring brain perfusion with MrI. One technique uses a contrast agent to measure the perfusion, the other employs water in the arteries as a label to measure the cerebral blood flow. the other chapters of this thesis focus on perfusion measurements with dynamic susceptibility contrast (DSC-) MrI, which uses gadolinium-based contrast agents and dynamic t2(*) weighted images.
For DSC-MrI (or bolus tracking MrI) a series of images is acquired during the passage of a bolus contrast agent through the brain up to the point that the contrast agent is equally mixed within the total blood pool. the concentration-time curve (determined using the Mr-signal
Chapter 1 10
change) measured in tissue holds the hemodynamic information and the cerebral blood flow and volume can be determined when the input of the microvasculature is a delta (or Dirac) function. Contrast agent is injected in the antecubital vein as a short bolus. Subsequently, the bolus travels through the right side of the heart, the lungs circulation, and the left side of the heart. After the second passage through the heart, the bolus contrast agent enters the oxygen rich arterial stream that supplies the body with oxygen and nutrients. When the bolus reaches the brain-feeding arteries the bolus no longer has a clearly defined beginning and end due to the dispersion in the heart and lungs, and consequently the shape of the concentration profile is no longer the same as at its injection site. For this reason, a reference or calibration measurement close to the brain tissue is required to enable quantification of perfusion. the measurement of the change in concentration contrast agent in a brain-feeding artery is called an arterial input function (AIF) measurement.
A special focus of this thesis lies on how to measure a correct AIF. A correct shape of the AIF is crucial for absolute or even relative perfusion values. A correct peak-height is necessary for absolute perfusion quantification, but an erroneous peak-height in combination with a correct shape of the AIF can still produce correct relative values for cerebral blood flow and volume.
therefore, the first objective should be to measure the correct shape of the AIF, whereas the measurement of the peak-height of the AIF should be considered of secondary importance.
Partial volume effects are known to corrupt the shape of the AIF measurement, and a relevant question is: where to select an AIF with a correct shape? Another relevant question is: can an AIF with correct shape also be selected automatically?
We used numerical simulations, modeling physical principles present in AIF measurements, to determine the optimal location for correct AIF measurements near two of the main brain- feeding arteries, the left and right middle cerebral artery. these manual AIF measurements can be performed using the magnitude of the Mr signal, which is described in chapter 3, as well as using the phase of the Mr signal (see Chapter 4). Phase-based AIF measurements have a number of potential advantages compared to the magnitude-based AIF measurements. both chapters focus on manual AIF selection within the acquired dataset.
Several research groups have proposed automatic AIF selection procedures, however if the selection criteria do not prevent the inclusion of incorrect AIF measurements the results are not reliable. An additional criterion can improve the reliability of the automatic AIF selection methods or aid manual AIF selection. the proposed criterion is based on tracer kinetic theory and tests whether the AIF measurement has an erroneous shape of the concentration-time curve (see Chapter 5). More specifically, specific shape errors that are normally not detected by the current automatic selection criteria. Most automatic AIF selection procedures focus on selecting local AIF measurements (region specific AIF measurements in small brain-feeding arteries). However, do the local AIF measurements reflect the true concentration-time curve of small arteries? Chapter 6 investigates the question whether automatic local AIF measurement can in theory select the correct AIFs of small brain-feeding arteries.
general introduction 11
Finally, we performed and analyzed a DSC-MrI study in patients with migraine to investigate whether interictal perfusion changes occur in the migraine patients, since this has not been convincingly demonstrated yet (see Chapter 7). this thesis concludes with a general discussion in chapter 8, a summary in English and Dutch, as well as a list of publications, Curriculum Vitae and Acknowledgements.
