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Myocardial perfusion imaging (MPI) is an effective technique used to study the left ventricular ejection function (LVEF), myocardial perfusion, wall motion, and wall thickening. Positron emission tomography (PET) and single photon emission computed tomography (SPECT) are two modalities that can be used to quantify the left global and regional perfusion at rest and stress. While PET and SPECT rely on similar principles to produce images, important differences in instrumentation and experimental applications are dictated by inherent differences in their respective physics of radioactive decay. With a sensitivity > 90% in combination with a high specificity, PET is today the best available nuclear imaging technique for the diagnosis of coronary artery disease (CAD). The short half-life of the perfusion tracers in combination with highly sophisticated hard- and software enables rapid PET studies with high patient throughput. Rubidium-82 (82Rb) is a PET perfusion imaging agent that has a shot half-life of 76 seconds which enables multiple sequential data acquisitions in a short duration of time. It also reduces the number of false-positive SPECT scans and artifacts from soft tissue attenuation due to the routine application of attenuation correction. However 82Rb PET imaging is under-utilized clinically due to difficulty optimizing the imaging parameters. The major challenge of 82Rb imaging is determining when to begin the image acquisition post infusion, as imaging too early results in images with high background (low contrast), and imaging too late results in noisy images due to low count statistics. 82Rb rest/stress dynamic and gated data from 16 patients were available for analysis. The FWHM of the 82Rb infusion, LV cavity and LV myocardial uptake in time activity curves were generated and compared to isolate the dominant parameter in determining image quality. The measured and actual infusion-time correlated only at rest (r = 0.93, P = 0.006). Splitting-time at rest and stress correlated (r = 0.74, P = 0.09). But the study was not able to identify a single dominant parameter that would determine the image quality due to the unpredictable nature of hemodynamics during the vasodilatory induced cardiovascular stress. First pass radionuclide angiography (FPRNA) is the gold standard for quantification of ejection fraction. We examined the quantification of the ejection function (LVEF) to determine whether the gated 82Rb PET data, using quantitative gated SPECT (QGS), would accurately predict changes in the chamber volume and correlated the results with those obtained from FPRNA technique. There was a good correlation between the resting FPRNA data and resting gated 82Rb QGS data (r= 0.81, P=0.0005) showing that this method can be applied to 82Rb PET.99mTc SPECT was considered the gold standard for this study, as it is the most widely used technique for myocardial perfusion imaging. The under-perfused area of the myocardium is defined as defect. 99mTc agents, 18F-FDG, and 82Rb can all be used for cardiac imaging 1-7. However, count rates, energy and camera differences can yield image differences that are independent of the actual biological distribution. We examined whether PET with an 82Rb-labeled tracer would provide information on defect size similar to that provided by 99mTc SPECT, using a cardiac phantom in which the true defect size is known. Since 82Rb has such a short half-life (76 seconds), filling and imaging a phantom was going be a great challenge. Hence 124I which is a high-energy radioisotope like 82Rb, was used in this phantom study as a surrogate for 82Rb. Static cardiac phantom studies with 99mTc, 18F and 124I (surrogate for 82Rb) were conducted. The percent defect sizes were measured and compared with the true defect size. Our results demonstrated that at 45% threshold, the measured defect size was representative of true defect size for 99mTc SPECT data. Using this threshold as the standard, we smoothed the 18F and 124I PET data until the measured defect size for PET was representative of the true defect size. An optimal filter cutoff frequency (Butterworth filter, cutoff = 0.80 cycles/pixel, order=5 at 45% threshold for 124I or 82Rb) was found for the PET data within the range of values studied, and this frequency was higher than the clinical norm for SPECT data. Our results also illustrated that the measured SPECT defect size varied greatly depending on the thresholds used to define a defect, whereas measure PET defect size was relatively constant over the range of cutoffs tested7. The optimal cutoff may depend on defect size, patient variability, and noise level. When assessing myocardial defect size, physical properties need to be taken into consideration, particularly when comparing images obtained using different nuclides (i.e. 82Rb or 99mTc agent perfusion and 18F FDG viability).

Alzheimer’s disease (AD) is a progressive, degenerative neurological disorder for which there is no cure. The causative agent is ?-amyloid (A?) which becomes neurotoxic upon conformational change from ?-helix to ?-sheet. In silico methods have been used to indentify endogenous small molecules of the brain that are capable of binding to A? to inhibit conformational changes; this is a novel approach to the disease. Through the use of computational methods, several small molecules that are endogenous to the brain, such as phosphoserine, have been identified as being capable of binding to the monomeric forms of A?; in vitro studies support their role as anti-aggregants. One of the small molecules identified through these in silico methods, 3-hydroxyanthranilic acid (3HAA) has been developed through the use of Quantitative Structure-Activity Relationship (QSAR) studies to design more potent analogues. These in silico studies have also examined the capacity of synthetic compounds (structurally similar to endogenous molecules) to bind to both A? and other proteins affiliated with AD. Results indicate the potential for a single molecule to bind “promiscuously” to multiple proteins bearing a common BBXB (where B is a basic amino acid) motif affiliated with AD. This will allow for the development of molecules to target AD in a multifaceted approach. Furthermore, these small molecules can be selected through the use of “physinformatics” to bind with equal efficacy to the HHQK and LVFF regions (which play a role in the misfolding process) of A?; this will prevent conformational changes of the protein. A novel diagnostic imaging agent for AD has also been developed through computational methods; solapsone (formerly used to treat leprosy) has been identified as being structurally similar to species that bind to A? to initiate conformational changes. Results show that solapsone can chelate gadolinium, used in MRI, and bind to the soluble forms of A?, allowing for imaging of the toxic species in the human brain, and thus a definitive diagnosis of AD (which is not currently possible with living patients). Computational methods have proved useful in developing a new approach to treating AD, and designing a novel imaging agent.

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