Koon-Pong Wong

A technique for extracting physiological parameters and the required input function simultaneously from PET image measurements: theory and simulation study

Positron emission tomography (PET) is an important tool for enabling quantification of human brain function. However, quantitative studies using tracer kinetic modeling require the measurement of the tracer time-activity curve in plasma (PTAC) as the model input function. It is widely believed that the insertion of arterial lines and the subsequent collection and processing of the biomedical signal sampled from the arterial blood are not compatible with the practice of clinical PET, as it is invasive and exposes personnel to the risks associated with the handling of patient blood and radiation dose. Therefore, it is of interest to develop practical noninvasive measurement techniques for tracer kinetic modeling with PET. In this paper, a technique is proposed to extract the input function together with the physiological parameters from the brain dynamic images alone. The identifiability of this method is tested rigorously by using Monte Carlo simulation. The results show that the proposed method is able to quantify all the required parameters by using the information obtained from two or more regions of interest (ROIs) with very different dynamics in the PET dynamic images. There is no significant improvement in parameter estimation for the local cerebral metabolic rate of glucose (LCMRGlc) if there are more than three ROIs. The proposed method can provide very reliable estimation of LCMRGlc, which is our primary interest in this study.

In vivo characterization of chronic traumatic encephalopathy using (F-18)FDDNP PET brain imaging

Significance Mild traumatic brain injuries are frequent events in the general population and are associated with a severe neurodegenerative disease, chronic traumatic encephalopathy (CTE). This disease is characterized by abnormal accumulation of protein aggregates, primarily tau proteins, which accumulate in brain areas responsible for mood, fear, stress, and cognition. There is no definitive clinical diagnosis of CTE at the present time, and this new work shows how a tau-sensitive brain imaging agent, [F-18]FDDNP, may be able to detect the disease in living people with varying degrees of symptoms. Early detection would facilitate the most effective management strategies and provide a baseline to measure the effectiveness of treatments. Chronic traumatic encephalopathy (CTE) is an acquired primary tauopathy with a variety of cognitive, behavioral, and motor symptoms linked to cumulative brain damage sustained from single, episodic, or repetitive traumatic brain injury (TBI). No definitive clinical diagnosis for this condition exists. In this work, we used [F-18]FDDNP PET to detect brain patterns of neuropathology distribution in retired professional American football players with suspected CTE (n = 14) and compared results with those of cognitively intact controls (n = 28) and patients with Alzheimer’s dementia (AD) (n = 24), a disease that has been cognitively associated with CTE. [F-18]FDDNP PET imaging results in the retired players suggested the presence of neuropathological patterns consistent with models of concussion wherein brainstem white matter tracts undergo early axonal damage and cumulative axonal injuries along subcortical, limbic, and cortical brain circuitries supporting mood, emotions, and behavior. This deposition pattern is distinctively different from the progressive pattern of neuropathology [paired helical filament (PHF)-tau and amyloid-β] in AD, which typically begins in the medial temporal lobe progressing along the cortical default mode network, with no or minimal involvement of subcortical structures. This particular [F-18]FDDNP PET imaging pattern in cases of suspected CTE also is primarily consistent with PHF-tau distribution observed at autopsy in subjects with a history of mild TBI and autopsy-confirmed diagnosis of CTE.

Simultaneous estimation of physiological parameters and the input function - in vivo PET data

Dynamic imaging with positron emission tomography (PET) is widely used for the in-vivo measurement of the regional cerebral metabolic rate for glucose (rCMRGlc) with [/sup 18/F]fluorodeoxy-D-glucose (FDG), and is used for the clinical evaluation of neurological diseases. However, in addition to the acquisition of dynamic images, continuous arterial blood sampling is the conventional method of obtaining the tracer time-activity curve in blood (or plasma) for the numerical estimation of rCMRGlc in mg glucose/100 g tissue/min. The insertion of arterial lines and the subsequent collection and processing of multiple blood samples are impractical for clinical PET studies because it is invasive, it has the remote (but real) potential for producing limb ischemia, and it exposes personnel to additional radiation and the risks associated with handling blood. Based on a method for extracting kinetic parameters from dynamic PET images, we developed a modified version (post-estimation method) to improve the numerical identifiability of the parameter estimates when we deal with data obtained from clinical studies. We applied both methods to dynamic neurological FDG PET studies in three adults. We found that the input function and parameter estimates obtained with our noninvasive methods agreed well with those estimated from the gold-standard method of arterial blood sampling and that rCMRGlc estimates were highly correlated. No significant difference was found between rCMRGlc estimated by our methods and the gold-standard method. We suggest that our proposed noninvasive methods may offer an advance over existing methods.

Effects of Administration Route, Dietary Condition, and Blood Glucose Level on Kinetics and Uptake of 18F-FDG in Mice

The effects of dietary condition and blood glucose level on the kinetics and uptake of 18F-FDG in mice were systematically investigated using intraperitoneal and tail-vein injection. Methods: Dynamic PET was performed for 60 min on 23 isoflurane-anesthetized male C57BL/6 mice after intravenous (n = 11) or intraperitoneal (n = 12) injection of 18F-FDG. Five and 6 mice in the intravenous and intraperitoneal groups, respectively, were kept fasting overnight (18 ± 2 h), and the others were fed ad libitum. Serial blood samples were collected from the femoral artery to measure 18F-FDG and glucose concentrations. Image data were reconstructed using filtered backprojection with CT-based attenuation correction. The standardized uptake value (SUV) was estimated from the 45- to 60-min image. The metabolic rate of glucose (MRGlu) and 18F-FDG uptake constant (Ki) were derived by Patlak graphical analysis. Results: In the brain, SUV and Ki were significantly higher in fasting mice with intraperitoneal injection, but MRGlu did not differ significantly under different dietary states and administration routes. Cerebral Ki was inversely related to elevated blood glucose levels, irrespective of administration route or dietary state. In myocardium, SUV, Ki, and MRGlu were significantly lower in fasting than in nonfasting mice for both routes of injection. Myocardial SUV and Ki were strongly dependent on the dietary state, and Ki did not correlate with the blood glucose level. Similar results were obtained for skeletal muscle, although the differences were not as pronounced. Conclusion: Intraperitoneal injection is a valid alternative route, providing pharmacokinetic data equivalent to data from tail-vein injection for small-animal 18F-FDG PET. Cerebral Ki varies inversely with blood glucose level, but the measured cerebral MRGlu does not correlate with blood glucose level or dietary condition. Conversely, the Ki values of the myocardium and skeletal muscle are strongly dependent on dietary condition but not on blood glucose level. In tissue in which 18F-FDG uptake declines with increasing blood glucose, correction for blood glucose level will make SUV a more robust outcome measure of MRGlu.

PET of Brain Prion Protein Amyloid in Gerstmann–Sträussler–Scheinker Disease

In vivo amyloid PET imaging was carried out on six symptomatic and asymptomatic carriers of PRNP mutations associated with the Gerstmann–Sträussler–Scheinker (GSS) disease, a rare familial neurodegenerative brain disorder demonstrating prion amyloid neuropathology, using 2‐(1‐{6‐[(2‐[F‐18]fluoroethyl)(methyl)amino]‐2‐naphthyl}ethylidene)malononitrile ([F‐18]FDDNP). 2‐Deoxy‐2‐[F‐18]fluoro‐d‐glucose PET ([F‐18]FDG) and magnetic resonance imaging (MRI) scans were also performed in each subject.

Estimation of input function and kinetic parameters using simulated annealing: application in a flow model

Accurate determination of the input function is essential for absolute quantification of physiological parameters in positron emission tomography and single-photon emission computed tomography imaging, but it requires an invasive and tedious procedure of blood sampling that is impractical in clinical studies. We previously proposed a technique that estimates simultaneously kinetic parameters and the input function from the tissue impulse response functions and requires two blood samples. A nonlinear least squares method estimated all the parameters in the impulse response functions and the input function but failed occasionally due to high noise levels in the data, causing an ill-conditioned cost function. This paper investigates the feasibility of applying a Monte Carlo method called simulated annealing to estimate kinetic parameters in the impulse response functions and the input function. Time-activity curves of teboroxime, which is very sensitive to changes in the input function, were simulated based on published data obtained from a canine model. The equations describing the tracer kinetics in different regions were minimized simultaneously by simulated annealing and nonlinear least squares. We found that the physiological parameters obtained with simulated annealing are accurate, and the estimated input function more closely resembled the simulated curve. We conclude that simulated annealing reduces bias in the estimation of physiological parameters and determination of the input function.

Movement Correction Method for Human Brain PET Images: Application to Quantitative Analysis of Dynamic [18F]-FDDNP Scans

Head movement during a PET scan (especially a dynamic scan) can affect both the qualitative and the quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic 2-(1-{6-[(2-18F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (18F-FDDNP) PET images of cognitively intact controls and patients with Alzheimers disease (AD). Methods: Dynamic 18F-FDDNP PET images, used for in vivo imaging of β-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD patients and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission–emission and emission–emission misalignments was applied to all studies. No restriction was assumed for zero movement between the transmission scan and the first emission scan. Logan analysis, with the cerebellum as the reference region, was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC. Results: MC improved the image quality and quantitative values in 18F-FDDNP PET images. In this subject population, no significant difference in DVR value was observed in the medial temporal (MTL) region of controls and patients with AD before MC. However, after MC, significant differences in DVR values in the frontal, parietal, posterior cingulate, MTL, lateral temporal (LTL), and global regions were seen between the 2 groups (P < 0.05). In controls and patients with AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by more than 18% after MC. Mean DVR separation between controls and patients with AD was higher in frontal, MTL, LTL, and global regions after MC. Group classification by discriminant analysis based on 18F-FDDNP DVR values was markedly improved after MC. Conclusion: The streamlined and easy-to-use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of 18F-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinsons disease) and to brain PET scans with other molecular imaging probes.

Unexpected Expression Pattern for Glycosylphosphatidylinositol-anchored HDL-binding Protein 1 (GPIHBP1) in Mouse Tissues Revealed by Positron Emission Tomography Scanning

Glycosylphosphatidylinositol-anchored high density lipoprotein-binding protein 1 (GPIHBP1), a GPI-anchored endothelial cell protein, binds lipoprotein lipase (LPL) and transports it into the lumen of capillaries where it hydrolyzes triglycerides in lipoproteins. GPIHBP1 is assumed to be expressed mainly within the heart, skeletal muscle, and adipose tissue, the sites where most lipolysis occurs, but the tissue pattern of GPIHBP1 expression has never been evaluated systematically. Because GPIHBP1 is found on the luminal face of capillaries, we predicted that it would be possible to define GPIHBP1 expression patterns with radiolabeled GPIHBP1-specific antibodies and positron emission tomography (PET) scanning. In Gpihbp1−/− mice, GPIHBP1-specific antibodies were cleared slowly from the blood, and PET imaging showed retention of the antibodies in the blood pools (heart and great vessels). In Gpihbp1+/+ mice, the antibodies were cleared extremely rapidly from the blood and, to our surprise, were taken up mainly by lung and liver. Immunofluorescence microscopy confirmed the presence of GPIHBP1 in the capillary endothelium of both lung and liver. In most tissues with high levels of Gpihbp1 expression, Lpl expression was also high, but the lung was an exception (very high Gpihbp1 expression and extremely low Lpl expression). Despite low Lpl transcript levels, however, LPL protein was readily detectable in the lung, suggesting that some of that LPL originates elsewhere and then is captured by GPIHBP1 in the lung. In support of this concept, lung LPL levels were significantly lower in Gpihbp1−/− mice than in Gpihbp1+/+ mice. In addition, Lpl−/− mice expressing human LPL exclusively in muscle contained high levels of human LPL in the lung.

Postmortem 3-D brain hemisphere cortical tau and amyloid-β pathology mapping and quantification as a validation method of neuropathology imaging.

This work is aimed at correlating pre-mortem [18F]FDDNP positron emission tomography (PET) scan results in a patient with dementia with Lewy bodies (DLB), with cortical neuropathology distribution determined postmortem in three physical dimensions in whole brain coronal sections. Analysis of total amyloid-β (Aβ) distribution in frontal cortex and posterior cingulate gyrus confirmed its statistically significant correlation with cortical [18F]FDDNP PET binding values (distribution volume ratios, DVR) (p < 0.001, R = 0.97, R2 = 0.94). Neurofibrillary tangle (NFT) distribution correlated significantly with cortical [18F]FDDNP PET DVR in the temporal lobe (p < 0.001, R = 0.87, R2 = 0.76). Linear combination of Aβ and NFT densities was highly predictive of [18F]FDDNP PET DVR through all analyzed regions of interest (p < 0.0001, R = 0.92, R2 = 0.85), and both densities contributed significantly to the model. Lewy bodies were present at a much lower level than either Aβ or NFTs and did not significantly contribute to the in vivo signal. [18F]FDG PET scan results in this patient were consistent with the distinctive DLB pattern of hypometabolism. This work offers a mapping brain model applicable to all imaging probes for verification of imaging results with Aβ and/or tau neuropathology brain distribution using immunohistochemistry, fluorescence microscopy, and autoradiography.

Medical Image Segmentation: Methods and Applications in Functional Imaging

Detection, localization, diagnosis, staging, and monitoring treatment responses are the most important aspects and crucial procedures in diagnostic medicine and clinical oncology. Early detection and localization of the diseases and accurate disease staging can improve the survival and change management in patients prior to planned surgery or therapy. Therefore, current medical practice has been directed toward early but efficient localization and staging of diseases, while ensuring that patients would receive the most effective treatment.