The following sections describe the methodology used in the tracer kinetic
analysis of dynamic PET and SPECT. A few examples of their application in
radionanomaterial studies have also been discussed.
16.2 Tissue Time–Activity Curves and Input Functions
In general, there exist two sources of data required for a tracer kinetic model: the
time course of the measured concentration of the radiotracer disposed in the tissue
(the tissue response) and that of the injected radiotracer in the blood or plasma (the
input function) [6].
Tissue time–activity curves are usually obtained by drawing a region of interest
(ROI) or volume of interest (VOI) on PET or SPECT images. Template- or
atlas-based ROIs (and VOIs) could be used as an alternative to them being drawn
manually, which is a laborious and time-consuming process [7–9]. Parametric
images can also be generated by applying the kinetic analysis to time–activity
curves of every image voxel. Each voxel of a parametric image then represents a
value of some physiological parameter [10–14].
The standard method to obtain a plasma input function consists of manual or
automated continuous arterial blood sampling. Plasma is extracted from arterial
blood samples using a centrifuge, and the radioactivity concentration in these
plasma samples is measured using a gamma counter and corrected for radioactive
decay. If the radioactive metabolite of the injected radiotracer in the plasma does
not reach the target (ROI), the metabolite fraction should be measured to obtain a
metabolite corrected input function. In brain studies, metabolite correction is necessary, since radioactive metabolites usually cannot cross the blood–brain barrier
due to their decreased lipophilicity. Dispersion and time delay corrections may be
done if necessary [15, 16].
For radiotracers that do not require metabolite correction (or if applying the
population-based metabolite fraction is a feasible option), one can use an
image-derived input function (IDIF) obtained by applying the ROIs to heart cavities
or large arteries. The IDIF approach is commonly used in myocardial perfusion
PET studies using [
13 N]NH 3 (ammonia) and
82 Rb. IDIF is also important in small
animal imaging studies, wherein frequent blood sampling is not possible [17–19].
However, in human brain PET studies, there still exist many methodological
challenges facing the routine use of the IDIF approach. Some of these challenges
include accurate segmentation of carotid arteries and the partial volume effect [20].
Multivariate analysis techniques, such as factor and independent component analyses, may, at times, prove useful for separating the IDIF approach from the tissue
time–activity curves [21–23].
Another less-invasive alternative to arterial sampling is the population-based
input function (PBIF), which has been validated mostly for [
18 F]FDG PET studies
[24, 25]. The arterial plasma input functions obtained from the subject population
are averaged after normalization. PBIF is then scaled using few blood samples to
16 Tracer Kinetics in Radionanomedicine
295
analysis of dynamic PET and SPECT. A few examples of their application in
radionanomaterial studies have also been discussed.
16.2 Tissue Time–Activity Curves and Input Functions
In general, there exist two sources of data required for a tracer kinetic model: the
time course of the measured concentration of the radiotracer disposed in the tissue
(the tissue response) and that of the injected radiotracer in the blood or plasma (the
input function) [6].
Tissue time–activity curves are usually obtained by drawing a region of interest
(ROI) or volume of interest (VOI) on PET or SPECT images. Template- or
atlas-based ROIs (and VOIs) could be used as an alternative to them being drawn
manually, which is a laborious and time-consuming process [7–9]. Parametric
images can also be generated by applying the kinetic analysis to time–activity
curves of every image voxel. Each voxel of a parametric image then represents a
value of some physiological parameter [10–14].
The standard method to obtain a plasma input function consists of manual or
automated continuous arterial blood sampling. Plasma is extracted from arterial
blood samples using a centrifuge, and the radioactivity concentration in these
plasma samples is measured using a gamma counter and corrected for radioactive
decay. If the radioactive metabolite of the injected radiotracer in the plasma does
not reach the target (ROI), the metabolite fraction should be measured to obtain a
metabolite corrected input function. In brain studies, metabolite correction is necessary, since radioactive metabolites usually cannot cross the blood–brain barrier
due to their decreased lipophilicity. Dispersion and time delay corrections may be
done if necessary [15, 16].
For radiotracers that do not require metabolite correction (or if applying the
population-based metabolite fraction is a feasible option), one can use an
image-derived input function (IDIF) obtained by applying the ROIs to heart cavities
or large arteries. The IDIF approach is commonly used in myocardial perfusion
PET studies using [
13 N]NH 3 (ammonia) and
82 Rb. IDIF is also important in small
animal imaging studies, wherein frequent blood sampling is not possible [17–19].
However, in human brain PET studies, there still exist many methodological
challenges facing the routine use of the IDIF approach. Some of these challenges
include accurate segmentation of carotid arteries and the partial volume effect [20].
Multivariate analysis techniques, such as factor and independent component analyses, may, at times, prove useful for separating the IDIF approach from the tissue
time–activity curves [21–23].
Another less-invasive alternative to arterial sampling is the population-based
input function (PBIF), which has been validated mostly for [
18 F]FDG PET studies
[24, 25]. The arterial plasma input functions obtained from the subject population
are averaged after normalization. PBIF is then scaled using few blood samples to
16 Tracer Kinetics in Radionanomedicine
295