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Reference and Target Region Modeling of [¹¹C]-(R)-PK11195 Brain Studies

¹ Division of Neuroscience, Department of Clinical Neuroscience, Imperial College London, London, United Kingdom; ² Hammersmith Imanet, Hammersmith Hospital, London, United Kingdom; ³ PET Neurology Group, MRC CSC, Hammersmith Hospital, London, United Kingdom; ⁴ Division of Neuroscience, Department of Neuropathology, Imperial College London, London, United Kingdom; ⁵ PET Epilepsy Group, Hammersmith Hospital, London, United Kingdom; and ⁶ Department of Psychiatry, University of Mainz, Germany

View larger version (11K): [in this window] [in a new window]   FIGURE 1.  Compartmental model for [11C]-(R)-PK11195 assumes a target region with a specific bound fraction and a compartment for a free fraction plus possibly a nonspecific bound fraction (NS) that equilibrates fast with the unbound fraction. The (ideal) reference region should be devoid of PBBSs and, therefore, be fitted best with a 1-tissue compartment model. K1 and k2 represent first-order rate constants for transport of ligand from plasma to tissue and vice versa (K1' and k2' for reference region); k3 and k4 represent rate constants between the free and specifically bound compartments in tissue.

View larger version (155K): [in this window] [in a new window]   FIGURE 2.  Immunostaining of PBBS in normal brain (monoclonal, clone 8D7 [kindly supplied by Dr. Pier Casellas, Department of Immunology–Oncology, Sanofi Synthelabo, Montpellier, France], dilution 1:200). Expression of PBBS is seen in smooth muscle cells of tunica media of medium-sized artery in cerebellar white matter (A) and of small cortical artery of frontal cortex (B). (C) PBBS expression is seen in some cuboidal cells (white arrows) of choroid plexus and in some macrophages in underlying fibrovascular core (black arrow). (D) Ependymal cells show expression of PBBS, which is mainly localized in apical cytoplasm.

View larger version (49K): [in this window] [in a new window]   FIGURE 3.  HD patient. (A) Map of gray matter reference region extracted by supervised algorithm as overlaid on the coregistered MR image. (B) Map of high PBBS density class. It includes voxels belonging to striatum and frontal cortex (arrows), where microglia activation is expected. (C) Maximum-intensity rendering of blood fraction cluster. Both posterior (left) and lateral (right) views are shown. Note clear detection of venous system but also of major arteries (arrow points to anterior cerebral artery).

View larger version (12K): [in this window] [in a new window]   FIGURE 4.  Time–activity curves extracted from [11C]-(R)-PK11195 dynamic scan of HD patient. ROIs were drawn on areas where high density of PBBS related to microglia activation was expected (caudate, putamen, and globus pallidus), whole gray and white matter. Activity in gray matter reference region and in blood fraction region as extracted by supervised clustering is illustrated. Time–activity curves are decay corrected.

View larger version (7K): [in this window] [in a new window]   FIGURE 5.  Results of application of ESA with blood input function to time–activity curve of whole normal gray matter for 2 healthy control subjects. Time–activity curves are decay corrected. Also shown are ESA fit to data (squares), kinetic components extracted (continuous lines), plus slowly equilibrating component (dashed line) that, by end of scan, accounts for 75% of total radioactivity.

View larger version (9K): [in this window] [in a new window]   FIGURE 6.  For the same subjects as in Figure 7, the slowly equilibrating component of vascular origin was subtracted from the whole gray matter time–activity curve (squares), producing a time–activity curve (dashed line) that was comparable with the time–activity curve of reference region extracted by supervised clustering method (triangles). The ability of the supervised methodology to filter out pixels with significant endothelial binding is illustrated.

View larger version (9K): [in this window] [in a new window]   FIGURE 7.  Correlation between reference region-derived and plasma-derived BP values. Reference region was extracted by supervised algorithm. BP values with reference region input were calculated using RS-ESA (A) and SRTM (B). In the case of RS-ESA, there was very close agreement and high correlation (r = 0.811, P < 10–5) between BP values calculated by reference tissue input and those derived from plasma input. SRTM consistently underestimated BP values and correlation with plasma-derived measures was poorer (r = 0.507, P = 0.004).