Jan Axelsson

In Vivo Visualization of Amyloid Deposits in the Heart with 11C-PIB and PET

Cardiac amyloidosis is a differential diagnosis in heart failure and is associated with high mortality. There is currently no noninvasive imaging test available for specific diagnosis. N-[methyl-11C]2-(4′-methylamino-phenyl)-6-hydroxybenzothiazole (11C-PIB) PET is used in the evaluation of brain amyloidosis. We evaluated the potential use of 11C-PIB PET in systemic amyloidosis affecting the heart. Methods: Patients (n = 10) diagnosed with systemic amyloidosis—including heart involvement of either monoclonal immunoglobulin light-chain (AL) or transthyretin (ATTR) type—and healthy volunteers (n = 5) were investigated with PET/CT using 11C-PIB to study cardiac amyloid deposits and with 11C-acetate to measure myocardial blood flow to study the impact of global and regional perfusion on PIB retention. Results: Myocardial 11C-PIB uptake was visually evident in all patients 15–25 min after injection and was not seen in any volunteer. A significant difference in 11C-PIB retention in the heart between patients and healthy controls was found. The data indicate that myocardial amyloid deposits in patients diagnosed with systemic amyloidosis could be visualized with 11C-PIB. No correlation between 11C-PIB retention index and myocardial blood flow as measured with 11C-acetate was found on the global level, whereas a positive correlation on the segmental level was seen in a single patient. Conclusion: 11C-PIB and PET could be a method to study systemic amyloidosis of type AL and ATTR affecting the heart and should be investigated further both as a diagnostic tool and as a noninvasive method for treatment follow-up.

A new application of pre-normalized principal component analysis for improvement of image quality and clinical diagnosis in human brain PET studies--clinical brain studies using [11C]-GR205171, [11C]-L-deuterium-deprenyl, [11C]-5-Hydroxy-L-Tryptophan, [11C]-L-DOPA and Pittsburgh Compound-B.

Principal component analysis (PCA) is one of the most applied multivariate image analysis tool on dynamic Positron Emission Tomography (PET). Independent of used reconstruction methodologies, PET images contain correlation in-between pixels, correlations in-between frame and errors caused by the reconstruction algorithm including different corrections, which can affect the performance of the PCA. In this study, we have investigated a new approach of application of PCA on pre-normalized, dynamic human PET images. A range of different tracers have been used for this purpose to explore the performance of the new method as a way to improve detection and visualization of significant changes in tracer kinetics and to enhance the discrimination between pathological and healthy regions in the brain. We compare the new results with the results obtained using other methods. Images generated using the new approach contain more detailed anatomical information with higher quality, precision and visualization, compared with images generated using other methods.

Dopamine D2 receptor availability is linked to hippocampal–caudate functional connectivity and episodic memory

Significance Cognitive functioning depends in part on dopamine neurotransmission in the brain. Research implicates the dopamine D1 receptor family in cognitive functions linked to the prefrontal cortex, such as working memory. The dopamine D2 receptor family has also been linked to cognition, but it remains unclear to which cognitive functions it is specifically related. We examined the relation of D2 receptors to episodic memory, working memory, and speed of processing. D2 receptors in the caudate and hippocampus were related to episodic memory and modulated caudate–hippocampal functional connections. These findings link the dopamine D2 system to hippocampus-based cognitive functions. D1 and D2 dopamine receptors (D1DRs and D2DRs) may contribute differently to various aspects of memory and cognition. The D1DR system has been linked to functions supported by the prefrontal cortex. By contrast, the role of the D2DR system is less clear, although it has been hypothesized that D2DRs make a specific contribution to hippocampus-based cognitive functions. Here we present results from 181 healthy adults between 64 and 68 y of age who underwent comprehensive assessment of episodic memory, working memory, and processing speed, along with MRI and D2DR assessment with [11C]raclopride and PET. Caudate D2DR availability was positively associated with episodic memory but not with working memory or speed. Whole-brain analyses further revealed a relation between hippocampal D2DR availability and episodic memory. Hippocampal and caudate D2DR availability were interrelated, and functional MRI-based resting-state functional connectivity between the ventral caudate and medial temporal cortex increased as a function of caudate D2DR availability. Collectively, these findings indicate that D2DRs make a specific contribution to hippocampus-based cognition by influencing striatal and hippocampal regions, and their interactions.

COBRA: A prospective multimodal imaging study of dopamine, brain structure and function, and cognition

Cognitive decline is a characteristic feature of normal human aging. Previous work has demonstrated marked interindividual variability in onset and rate of decline. Such variability has been linked to factors such as maintenance of functional and structural brain integrity, genetics, and lifestyle. Still, few, if any, studies have combined a longitudinal design with repeated multimodal imaging and a comprehensive assessment of cognition as well as genetic and lifestyle factors. The present paper introduces the Cognition, Brain, and Aging (COBRA) study, in which cognitive performance and brain structure and function are measured in a cohort of 181 older adults aged 64 to 68 years at baseline. Participants will be followed longitudinally over a 10-year period, resulting in a total of three equally spaced measurement occasions. The measurement protocol at each occasion comprises a comprehensive set of behavioral and imaging measures. Cognitive performance is evaluated via computerized testing of working memory, episodic memory, perceptual speed, motor speed, implicit sequence learning, and vocabulary. Brain imaging is performed using positron emission tomography with [(11)C]-raclopride to assess dopamine D2/D3 receptor availability. Structural magnetic resonance imaging (MRI) is used for assessment of white and gray-matter integrity and cerebrovascular perfusion, and functional MRI maps brain activation during rest and active task conditions. Lifestyle descriptives are collected, and blood samples are obtained and stored for future evaluation. Here, we present selected results from the baseline assessment along with a discussion of sample characteristics and methodological considerations that determined the design of the study. This article is part of a Special Issue entitled SI: Memory & Aging.

Dopamine release in nucleus accumbens during rewarded task switching measured by [11C]raclopride

Reward and motivation have positive influences on cognitive-control processes in numerous settings. Models of reward implicate corticostriatal loops and the dopamine (DA) system, with special emphasis on D2 receptors in nucleus accumbens (NAcc). In this study, 11 right-handed males (35-40 years) were scanned with positron emission tomography (PET) in a single [(11)C]raclopride dynamic scan during rewarded and non-rewarded task switching. Rewarded task switching (relative to baseline task switching) decreased [(11)C]raclopride binding in NAcc. Decreasing NAcc [(11)C]raclopride binding was strongly associated with task reaction time measures that reflect individual differences in effort and control strategies. Voxelwise analyses additionally revealed reward-related DA release in anterodorsal caudate, a region previously associated with task-switching. These PET findings provide evidence for striatal DA release during motivated cognitive control, and further suggest that NAcc DA release predicts the task reaction time benefits of reward incentives.

Volume-Wise Application of Principal Component Analysis on Masked Dynamic PET Data in Sinogram Domain

Most of the methods used for analyzing PET data are applied in the spatial domain (image domain), in which reconstructed images contain all different types of effects and errors caused by the reconstruction algorithm such as correlation in-between pixels, correlations in-between frames, and streak-artifacts. In this paper, we have investigated a new, pixel wise, noise prenormalization method used for transformation of input data followed by volume-wise application of principal component analysis (PCA) on masked dynamic PET data in the sinogram domain. We are aiming to improve the performance of PCA and to provide images with improved quality and signal extraction. We compare the performance of PCA and the image quality obtained with the new method with previously published approaches. The results show improvement of performance of PCA with respect to image quality, signal extraction, precision, and visualization

Subcentimeter Tumor Lesion Delineation for High-Resolution 18F-FDG PET Images: Optimizing Correction for Partial-Volume Effects

In PET, partial-volume effects cause errors in estimation of size and activity for small objects with radiopharmaceutical uptake. Recent methods for image reconstruction, compared with traditional reconstruction techniques, include algorithms for resolution recovery that result in images with higher resolution and enable quantification of size and activity of smaller objects. The purpose of this study was to evaluate a combination of 2 algorithms for volume delineation and partial-volume correction on uptake volumes smaller than 0.7 mL using image reconstruction algorithms with and without resolution recovery. Methods: Volumes of interests (VOIs) were delineated using a threshold intensity calculated as a weighted sum of tumor and background intensities. These VOIs were used for calculating correction factors by convolving a tumor mask with the system point-spread function. The methods algorithms were evaluated using a phantom constructed from 5 small different-sized balloons filled with 18F-FDG in background activity. Six different backgrounds were used. Data were acquired using a PET/CT scanner, and the images were reconstructed using 2 iterative algorithms, one of which used a resolution recovery algorithm. Results: For the images reconstructed using the resolution recovery algorithm, the method for volume delineation resulted in VOI sizes that were correct within 1 SD for all balloons of a volume of 0.35 mL (equivalent diameter, 8.8 mm) and larger, in all backgrounds. For the images reconstructed without resolution recovery, the VOI sizes were background-dependent and generally less accurate. Correct volume delineations generally led to accurate activity estimates. Conclusion: The algorithms tested on the phantom developed for this study could, for this PET camera and these reconstruction algorithms, be used for accurate volume delineation and activity quantification of lesions 0.35 mL and larger.

Detecting Small Liver Tumors With

In 111In-pentetreotide single-photon emission computed tomography (SPECT), the tumor-to-background-uptake ratio is generally high. The noise is, however, also usually on a high level, and in combination with the low spatial resolution of SPECT, this may lead to difficulties in the detection of small tumors. This is especially the case in regions with a relatively high background activity, such as in the liver, which is a common region for somatostatin-positive metastases. Visually detecting the small tumors is important for a successful treatment of the cancer disease. In this paper, we compare three different parallel-hole collimators for 111In-pentetreotide SPECT regarding contrast as a function of image noise for a phantom simulating small tumors in liver background. The corresponding contrast-to-noise ratios are also presented. All raw-data projections are produced using Monte Carlo simulations. The collimators are of type low-energy general-purpose (LEGP), extended LEGP (ELEGP), and medium-energy general-purpose (MEGP). Reconstructions were performed with OSEM both with and without model-based compensation. Of the investigated collimators, the ELEGP collimator proved to be the most optimal for the smallest tumors, both with and without model-based compensation included in the reconstruction. It is also shown that model-based compensation outperforms the conventional reconstruction technique.

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Early and persisting response to vismodegib in a patient with bone metastasizing medulloblastoma

In-Pentetreotide SPECT—A Collimator Study Based on Monte Carlo Simulations

BackgroundIn this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence.We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamic time-series. The Scree-plot technique was used to determine which principal components to be rejected in the filter process. This filter was applied to [11C]-acetate on heart and head-neck tumors, [18F]-FDG on liver tumors and brain, and [11C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to real PET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varying parts of a 90-frame [18F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20 MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) were compared.ResultsThe 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manually pick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focal Raclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissue uptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data is reliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior to Patlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dose reduction can be achieved for Patlak slope images without changing image quality or quantitation.ConclusionsThe 2D Hotelling-filtering of dynamic PET data is a computer-efficient method that gives visually improved differentiation of different tissues, which we have observed improve manual or automated region-of-interest delineation of dynamic data. Parametric Patlak images on Hotelling-filtered data display improved clarity, compared to non-filtered Patlak slope images without measurable loss of quantitation, and allow a dramatic decrease in patient injected dose.