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Tracer Kinetic Analysis for PET and SPECT
Published in Troy Farncombe, Krzysztof Iniewski, Medical Imaging, 2017
For some radioligands, reference regions that do not have high-affinity receptors are available. The single-tissue compartment model is used for such reference regions (Figure 17.5). If we assume that the distribution volumes of free and nonspecifically bound radioligand in an ROI and in a reference region are the same (K1/k2 = K′1/k′2) for some radioligands, biological constraint can be applied to improve the stability of rate constant estimates or to replace the arterial input function by the time–activity curve for a reference region. The ratio of K′1 and k′2 which are obtained by fitting the time–activity curve from the reference region, can be fixed during rate constant estimation for ROIs.19,20
Quantitative imaging using MRI
Published in Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin, Radiomics and Radiogenomics, 2019
David A. Hormuth, John Virostko, Ashley Stokes, Adrienne Dula, Anna G. Sorace, Jennifer G. Whisenant, Jared A. Weis, C. Chad Quarles, Michael I. Miga, Thomas E. Yankeelov
DCE-MRI begins with measurements of the baseline, or native, tissue T1 for each voxel in the field of view. Following the T1 mapping protocol, a dynamic acquisition of serial 3D T1-weighted spoiled gradient echo sequences are then acquired before, during, and after the intravascular injection of the low molecular weight, gadolinium-based contrast agent. The initial pass of the contrast reflects perfusion, while subsequent imaging (typically 3 minutes–10 minutes) allows for characterizing the passage of the contrast agent into the extravascular space [95]. By considering each voxel in each image over the course of time, a time-concentration curve can be measured and then analyzed in a semi-quantitative fashion or with quantitative analysis to quantify a range of physiological parameters within the tissue [85]. Quantitative parameters are most commonly derived in the Tofts-Kety pharmacokinetic model [84,98], which is a two compartment model of the contrast agent distribution within the body [99]. One compartment represents the vascular space, and the other represents the tissue compartment (Figure 5.6). To perform quantitative DCE-MRI, the following measurements are required: the baseline T1 map and the dynamic T1-weighted data introduced above, estimation of the time rate of change of the concentration of contrast agent in the blood plasma (i.e., the arterial input function, AIF), and a pharmacokinetic model to analyze the resulting data. An AIF can be measured directly from a large vessel within an individual subject [100,101], a population average [102,103], or alternatively through a reference region model [101,102]. DCE-MRI analysis is then completed by fitting the data to the pharmacokinetic model (region of interest or voxel basis) to estimate the physiological parameters, as seen in Eq. (5.8): () Ct(T)=Ktrans∫0TCp(u)•exp(−(Ktransve)(T−u))du+vpCp(T),
Non-invasive imaging techniques to assess myocardial perfusion
Published in Expert Review of Medical Devices, 2020
Olivier Villemain, Jérôme Baranger, Zakaria Jalal, Christopher Lam, Jérémie Calais, Mathieu Pernot, Barbara Cifra, Mark K. Friedberg, Luc Mertens
Interpretation in clinical practice is qualitative [30], with hypoenhancement greater than 25% myocardial extent typically considered pathological. However, numerous automated quantitative CMR myocardial perfusion methods are under investigation and beginning to make headway into clinical practice. Quantitative myocardial perfusion is based on mathematical models of myocardial structure and thus contrast perfusion. Measured parameters include myocardial blood flow (MBF; ml/g/min) at stress and rest, and myocardial perfusion reserve (MPR), which is the ratio of MBF at stress to MBF at rest. Relative flow reserve can also be determined at each myocardial segment. A requirement of quantitative methods is precise measurement of the arterial input function (AIF), which represents the varying signal intensity of blood in the left ventricle due to contrast transit. This has traditionally been labor-intensive and prone to errors, though has now been improved with automated methods, including for obtaining whole-heart slice coverage using simultaneous multi-slice techniques [31–34]. In the largest quantitative perfusion CMR study to date (1049 patients), Knott KD and colleagues use stress CMR myocardial perfusion mapping via an automated artificial-intelligence-based approach to show, quantitative measures of MBF and perfusion reserve to be independent predictors for death and major adverse cardiovascular events [35]. Future trials will be needed to validate the utility of quantitative CMR myocardial perfusion imaging for clinical practice.