Maqsood Yaqub

Relationship of Cerebrospinal Fluid Markers to 11C-PiB and 18F-FDDNP Binding

The purpose of this study was to investigate the potential relationships between cerebrospinal fluid (CSF) measurements of β-amyloid-1–42 (Aβ1-42) and total tau to 11C-Pittsburgh compound B (11C-PiB) and 2-(1-{6-[(2-18F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene) malononitrile (18F-FDDNP) binding as measured using PET. Methods: A total of 37 subjects were included, consisting of 15 patients with Alzheimer disease (AD), 12 patients with mild cognitive impairment, and 10 healthy controls. All subjects underwent a lumbar puncture and PET using both 11C-PiB and 18F-FDDNP. For both PET tracers, parametric images of binding potential were generated. Potential associations of CSF levels of Aβ1-42 and tau with 11C-PiB and 18F-FDDNP binding were assessed using Pearson correlation coefficients and linear regression analyses. Results: For both global 11C-PiB and 18F-FDDNP binding, significant correlations with CSF levels of Aβ1-42 (r = −0.72 and −0.37, respectively) and tau (r = 0.58 and 0.56, respectively) were found across groups (all P < 0.001, except P < 0.05 for correlation between 18F-FDDNP and Aβ1-42). Linear regression analyses showed that, adjusted for regional volume, age, sex, and diagnosis, global 11C-PiB uptake had an inverse association with Aβ1-42 CSF levels (standardized β = −0.50, P < 0.001), whereas there was a positive association between global 18F-FDDNP binding and tau CSF levels (standardized β = 0.62, P < 0.01). Conclusion: The good agreement between these 2 different types of biomarkers (i.e., CSF and PET) provides converging evidence for their validity. The inverse association between 11C-PiB and CSF tau Aβ1-42 confirms that 11C-PiB measures amyloid load in the brain. The positive association between 18F-FDDNP and CSF tau suggests that at least part of the specific signal of 18F-FDDNP in AD patients is due to tangle formation.

Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies

PurposeStandardized uptake values (SUV) are commonly used for quantification of whole-body [18F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) studies. Changes in SUV following therapy, however, only provide a proper measure of response in case of homogeneous FDG uptake in the tumour. The purpose of this study was therefore to implement and characterize a method that enables quantification of heterogeneity in tumour FDG uptake.MethodsCumulative SUV-volume histograms (CSH), describing % of total tumour volume above % threshold of maximum SUV (SUVmax), were calculated. The area under a CSH curve (AUC) is a quantitative index of tumour uptake heterogeneity, with lower AUC corresponding to higher degrees of heterogeneity. Simulations of homogeneous and heterogeneous responses were performed to assess the value of AUC-CSH for measuring uptake and/or response heterogeneity. In addition, partial volume correction and image denoising was applied prior to calculating AUC-CSH. Finally, the method was applied to a number of human FDG scans.ResultsPartial volume correction and noise reduction improved CSH curves. Both simulations and clinical examples showed that AUC-CSH values corresponded with level of tumour heterogeneity and/or heterogeneity in response. In contrast, this correspondence was not seen with SUVmax alone. The results indicate that the main advantage of AUC-CSH above other measures, such as 1/COV (coefficient of variation), is the possibility to measure or normalize AUC-CSH in different ways.ConclusionAUC-CSH might be used as a quantitative index of heterogeneity in tracer uptake. In response monitoring studies it can be used to address heterogeneity in response.

Detection of Alzheimer Pathology In Vivo Using Both 11C-PIB and 18F-FDDNP PET

11C-Pittsburgh Compound-B (11C-PIB) and 18F-(2-(1-{6-[(2-[18F]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene) (18F-FDDNP) have been developed as PET tracers for in vivo imaging of pathology in Alzheimers disease (AD). The purpose of this study was to directly compare these tracers in patients with AD, patients with mild cognitive impairment (MCI), and healthy controls. Methods: Paired 11C-PIB and 18F-FDDNP scans were acquired in 14 patients with AD, 11 patients with amnestic MCI, and 13 controls. For both tracers, parametric images of binding potential (BPND) were generated. Global cortical BPND was assessed using ANOVA. In addition, regional patterns of BPND were compared between diagnostic groups using ANOVA for repeated measures. Results: Global cortical BPND of 11C-PIB showed higher binding in patients with AD than in controls and patients with MCI. 18F-FDDNP uptake was higher in patients with AD than in controls, but MCI could not be distinguished from AD or from controls. Global BPND values of both tracers were moderately correlated (r = 0.45; P = 0.005). In MCI, BPND of 11C-PIB showed a bimodal distribution, whereas values for 18F-FDDNP were more widespread, with more MCI patients demonstrating increased uptake. Regional 11C-PIB binding showed different patterns across diagnostic groups, as AD patients showed an overall increase in binding, with the lowest binding in the medial temporal lobe. With 18F-FDDNP, patterns were similar across diagnostic groups. For all groups, highest values were observed in the medial temporal lobe. Conclusion: Differences in BPND between patients with AD, patients with MCI, and controls were more pronounced for 11C-PIB. The difference in regional binding, the moderate correlation, and the discrepant findings in MCI suggest that they measure related, but different, characteristics of the disease.

Microglial activation in healthy aging.

Healthy brain aging is characterized by neuronal loss and decline of cognitive function. Neuronal loss is closely associated with microglial activation and postmortem studies have indeed suggested that activated microglia may be present in the aging brain. Microglial activation can be quantified in vivo using (R)-[(11)C]PK11195 and positron emission tomography. The purpose of this study was to measure specific binding of (R)-[(11)C]PK11195 in healthy subjects over a wide age range. Thirty-five healthy subjects (age range 19-79 years) were included. In all subjects 60-minute dynamic (R)-[(11)C]PK11195 scans were acquired. Specific binding of (R)-[(11)C]PK11195 was calculated using receptor parametric mapping in combination with supervised cluster analysis to extract the reference tissue input function. Increased binding of (R)-[(11)C]PK11195 with aging was found in frontal lobe, anterior and posterior cingulate cortex, medial inferior temporal lobe, insula, hippocampus, entorhinal cortex, thalamus, parietal and occipital lobes, and cerebellum. This indicates that activated microglia appear in several cortical and subcortical areas during healthy aging, suggesting widespread neuronal loss.

Development of [11C]erlotinib Positron Emission Tomography for In Vivo Evaluation of EGF Receptor Mutational Status

Purpose: To evaluate whether, in patients with non–small cell lung carcinoma (NSCLC), tumor uptake of [11C]erlotinib can be quantified and imaged using positron emission tomography and to assess whether the level of tracer uptake corresponds with the presence of activating tumor EGF receptor (EGFR) mutations. Experimental Design: Ten patients with NSCLCs, five with an EGFR exon 19 deletion, and five without were scanned twice (test retest) on the same day with an interval of at least 4 hours. Each scanning procedure included a low-dose computed tomographic scan, a 10-minute dynamic [15O]H2O scan, and a 1-hour dynamic [11C]erlotinib scan. Data were analyzed using full tracer kinetic modeling. EGFR expression was evaluated using immunohistochemistry. Results: The quantitative measure of [11C]erlotinib uptake, that is, volume of distribution (VT), was significantly higher in tumors with activating mutations, that is, all with exon 19 deletions (median VT, 1.76; range, 1.25–2.93), than in those without activating mutations (median VT, 1.06; range, 0.67–1.22) for both test and retest data (P = 0.014 and P = 0.009, respectively). Good reproducibility of [11C]erlotinib VT was seen (intraclass correlation coefficient = 0.88). Intergroup differences in [11C]erlotinib uptake were not correlated with EGFR expression levels, nor tumor blood flow. Conclusion: [11C]erlotinib VT was significantly higher in NSCLCs tumors with EGFR exon 19 deletions. Clin Cancer Res; 19(1); 183–93. ©2012 AACR.

Optimization of supervised cluster analysis for extracting reference tissue input curves in (R)-[11C]PK11195 brain PET studies

Performance of two supervised cluster analysis (SVCA) algorithms for extracting reference tissue curves was evaluated to improve quantification of dynamic (R)-[11C]PK11195 brain positron emission tomography (PET) studies. Reference tissues were extracted from images using both a manually defined cerebellum and SVCA algorithms based on either four (SVCA4) or six (SVCA6) kinetic classes. Data from controls, mild cognitive impairment patients, and patients with Alzheimers disease were analyzed using various kinetic models including plasma input, the simplified reference tissue model (RPM) and RPM with vascular correction (RPMV b ). In all subject groups, SVCA-based reference tissue curves showed lower blood volume fractions (V b ) and volume of distributions than those based on cerebellum time-activity curve. Probably resulting from the presence of specific signal from the vessel walls that contains in normal condition a significant concentration of the 18 kDa translocation protein. Best contrast between subject groups was seen using SVCA4-based reference tissues as the result of a lower number of kinetic classes and the prior removal of extracerebral tissues. In addition, incorporation of V b in RPM improved both parametric images and binding potential contrast between groups. Incorporation of V b within RPM, together with SVCA4, appears to be the method of choice for analyzing cerebral (R)-[11C]PK11195 neurodegeneration studies.

Optimization algorithms and weighting factors for analysis of dynamic PET studies

Positron emission tomography (PET) pharmacokinetic analysis involves fitting of measured PET data to a PET pharmacokinetic model. The fitted parameters may, however, suffer from bias or be unrealistic, especially in the case of noisy data. There are many optimization algorithms, each having different characteristics. The purpose of the present study was to evaluate (1) the performance of different optimization algorithms and (2) the effects of using incorrect weighting factors during optimization in terms of both accuracy and reproducibility of fitted PET pharmacokinetic parameters. In this study, the performance of commonly used optimization algorithms (i.e. interior-reflective Newton methods) and a simulated annealing (SA) method was evaluated. This SA algorithm, known as basin hopping, was modified for the present application. In addition, optimization was performed using various weighting factors. Algorithms and effects of using incorrect weighting factors were studied using both simulated and clinical time-activity curves (TACs). Input data, taken from [(15)O]H(2)O, [(11)C]flumazenil and [(11)C](R)-PK11195 studies, were used to simulate time-activity curves at various variance levels (0-15% COV). Clinical evaluation was based on studies with the same three tracers. SA was able to produce accurate results without the need for selecting appropriate starting values for (kinetic) parameters, in contrast to the interior-reflective Newton method. The latter gave biased results unless it was modified to allow for a range of starting values for the different parameters. For patient studies, where large variability is expected, both SA and the extended Newton method provided accurate results. Simulations and clinical assessment showed similar results for the evaluation of different weighting models in that small to intermediate mismatches between data variance and weighting factors did not significantly affect the outcome of the fits. Large errors were observed only when the mismatch between weighting model and data variance was large. It is concluded that selection of specific optimization algorithms and weighting factors can have a large effect on the accuracy and precision of PET pharmacokinetic analysis. Apart from carefully selecting appropriate algorithms and variance models, further improvement in accuracy might be obtained by using noise reducing strategies, such as wavelet filtering, provided that these methods do not introduce significant bias.

Longitudinal Amyloid Imaging Using 11C-PiB: Methodologic Considerations

Several methods are in use for analyzing 11C-Pittsburgh compound-B (11C-PiB) data. The objective of this study was to identify the method of choice for measuring longitudinal changes in specific 11C-PiB binding. Methods: Dynamic 90-min 11C-PiB baseline and follow-up scans (interval, 30 ± 5 mo) were obtained for 7 Alzheimer disease (AD) patients, 11 patients with mild cognitive impairment (MCI), and 11 healthy controls. Parametric images were generated using reference parametric mapping (RPM2), reference Logan values, and standardized uptake value volume ratios (SUVr), the latter for intervals between 60 and 90 (SUVr60–90) and 40 and 60 (SUVr40–60) minutes after injection. In all analyses, cerebellar gray matter was used as a reference region. A global cortical volume of interest was defined using a probability map–based template. Percentage change between baseline and follow-up was derived for all analytic methods. Results: SUVr60–90 and SUVr40–60 overestimated binding with 13% and 10%, respectively, compared with RPM2. Reference Logan values were on average 6% lower than RPM2. Both SUVr measures showed high intersubject variability. Over time, R1, the delivery of tracer to the cortex relative to that to the cerebellum, decreased in AD patients (P < 0.05) but not in MCI patients and controls. Simulations showed that SUVr, but not RPM2 and reference Logan values, was highly dependent on uptake period and that changes in SUVr over time were sensitive to changes in flow. Conclusion: To reliably assess amyloid binding over time—for example, in drug intervention studies—it is essential to use fully quantitative methods for data acquisition and analysis.

Effects of Image Characteristics on Performance of Tumor Delineation Methods: A Test–Retest Assessment

PET can be used to monitor response during chemotherapy and assess biologic target volumes for radiotherapy. Previous simulation studies have shown that the performance of various automatic or semiautomatic tumor delineation methods depends on image characteristics. The purpose of this study was to assess test–retest variability of tumor delineation methods, with emphasis on the effects of several image characteristics (e.g., resolution and contrast). Methods: Baseline test–retest data from 19 non–small cell lung cancer patients were obtained using 18F-FDG (n = 10) and 3′-deoxy-3′-18F-fluorothymidine (18F-FLT) (n = 9). Images were reconstructed with varying spatial resolution and contrast. Six different types of tumor delineation methods, based on various thresholds or on a gradient, were applied to all datasets. Test–retest variability of metabolic volume and standardized uptake value (SUV) was determined. Results: For both tracers, size of metabolic volume and test–retest variability of both metabolic volume and SUV were affected by the image characteristics and tumor delineation method used. The median volume test–retest variability ranged from 8.3% to 23% and from 7.4% to 29% for 18F-FDG and 18F-FLT, respectively. For all image characteristics studied, larger differences (≤10-fold higher) were seen in test–retest variability of metabolic volume than in SUV. Conclusion: Test–retest variability of both metabolic volume and SUV varied with tumor delineation method, radiotracer, and image characteristics. The results indicate that a careful optimization of imaging and delineation method parameters is needed when metabolic volume is used, for example, as a response assessment parameter.

Comparison of plasma input and reference tissue models for analysing [(11)C]flumazenil studies

A single-tissue compartment model with plasma input is the established method for analysing [11C]flumazenil ([11C]FMZ) studies. However, arterial cannulation and measurement of metabolites are time-consuming. Therefore, a reference tissue approach is appealing, but this approach has not been fully validated for [11C]FMZ. Dynamic [11C]FMZ positron emission tomography scans with arterial blood sampling were performed in nine drug-free depressive patients and eight healthy subjects. Regions of interest were defined on co-registered magnetic resonance imaging scans and projected onto dynamic [11C]FMZ images. Using a Hill-type metabolite function, single (1T) and reversible two-tissue (2T) compartmental models were compared. Simplified reference tissue model (SRTM) and full reference tissue model (FRTM) were investigated using both pons and (centrum semiovale) white matter as reference tissue. The 2T model provided the best fit in 59% of cases. Two-tissue VT values were on average 1.6% higher than 1T VT values. Owing to the higher rejection rate of 2T fits (7.3%), the 1T model was selected as plasma input method of choice. SRTM was superior to FRTM, irrespective whether pons or white matter was used as reference tissue. BPND values obtained with SRTM correlated strongly with 1T VT (r = 0.998 and 0.995 for pons and white matter, respectively). Use of white matter as reference tissue resulted in 5.5% rejected fits, primarily in areas with intermediate receptor density. No fits were rejected using pons as reference tissue. Pons produced 23% higher BPND values than white matter. In conclusion, for most clinical studies, SRTM with pons as reference tissue can be used for quantifying [11C]FMZ binding.