Optimally Stabilized PET Image Denoising Using Trilateral Filtering

Low-resolution and signal-dependent noise distribution in positron emission tomography (PET) images makes denoising process an inevitable step prior to qualitative and quantitative image analysis tasks. Conventional PET denoising methods either over-smooth small-sized structures due to resolution limitation or make incorrect assumptions about the noise characteristics. Therefore, clinically important quantitative information may be corrupted. To address these challenges, we introduced a novel approach to remove signal-dependent noise in the PET images where the noise distribution was considered as Poisson-Gaussian mixed. Meanwhile, the generalized Anscombe's transformation (GAT) was used to stabilize varying nature of the PET noise. Other than noise stabilization, it is also desirable for the noise removal filter to preserve the boundaries of the structures while smoothing the noisy regions. Indeed, it is important to avoid significant loss of quantitative information such as standard uptake value (SUV)-based metrics as well as metabolic lesion volume. To satisfy all these properties, we extended bilateral filtering method into trilateral filtering through multiscaling and optimal Gaussianization process. The proposed method was tested on more than 50 PET-CT images from various patients having different cancers and achieved the superior performance compared to the widely used denoising techniques in the literature.Comment: 8 pages, 3 figures; to appear in the Lecture Notes in Computer Science (MICCAI 2014

A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging

Introduction: Recent evidence suggests the blood-to-brain influx rate (K1) in TSPO PET imaging as a promising biomarker of blood–brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test–retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03–0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers’ unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal

The translocator protein (TSPO) is prodromal to mitophagy loss in neurotoxicity

Dysfunctional mitochondria characterise Parkinson’s Disease (PD). Uncovering etiological molecules, which harm the homeostasis of mitochondria in response to pathological cues, is therefore pivotal to inform early diagnosis and therapy in the condition, especially in its idiopathic forms. This study proposes the 18 kDa Translocator Protein (TSPO) to be one of those. Both in vitro and in vivo data show that neurotoxins, which phenotypically mimic PD, increase TSPO to enhance cellular redox-stress, susceptibility to dopamine-induced cell death, and repression of ubiquitin-dependent mitophagy. TSPO amplifies the extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) signalling, forming positive feedback, which represses the transcription factor EB (TFEB) and the controlled production of lysosomes. Finally, genetic variances in the transcriptome confirm that TSPO is required to alter the autophagy–lysosomal pathway during neurotoxicity

Positron emission tomography compartmental models: A basis pursuit strategy for kinetic modelling

A kinetic modelling approach for the quantification of in vivo tracer studies with dynamic positron emission tomography (PET) is presented. The approach is based on a general compartmental description of the tracer’s fate in vivo and determines a parsimonious model consistent with the measured data. The technique involves the determination of a sparse selection of kinetic basis functions from an overcomplete dictionary using the method of basis pursuit denoising. This enables the characterization of the systems impulse response function from which values of the systems macro parameters can be estimated. These parameter estimates can be obtained from a region of interest analysis or as parametric images from a voxel based analysis. In addition, model order estimates are returned which correspond to the number of compartments in the estimated compartmental model. Validation studies evaluate the methods performance against two pre-existing data led techniques, namely graphical analysis and spectral analysis. Application of this technique to measured PET data is demonstrated using [ 11 C]diprenorphine (opiate receptor) and [ 11 C]WAY-100635 (5-HT1A receptor). Whilst, the method is presented in the context of PET neuroreceptor binding studies, it has general applicability to the quantification of PET/SPET radiotracer studies in neurology, oncology and cardiology

Wavelet analysis of gene expression (WAGE)

The wavelet transform (WT) is the mathematical operator of choice for the analysis of nonstationary signals. At the same time, it is also a modelling operator that may be used to impose functional constraints on data to unveil hidden groupings and relationships. In this work, we apply the WT to the chromosomal sequences of gene expression values measured with microarray technology. The application of the wavelet operator aims to uncover clusters of genes that interact by vicinity, either because of a shared regulatory mechanism or because of common susceptibility to environmental factors. Application of the method to data on the expression of human brain genes in neuro-degeneration validates the technique and, at the same time, illustrates the potential of the method

Wavelet analysis of gene expression (WAGE)

The wavelet transform (WT) is the mathematical operator of choice for the analysis of nonstationary signals. At the same time, it is also a modelling operator that may be used to impose functional constraints on data to unveil hidden groupings and relationships. In this work, we apply the WT to the chromosomal sequences of gene expression values measured with microarray technology. The application of the wavelet operator aims to uncover clusters of genes that interact by vicinity, either because of a shared regulatory mechanism or because of common susceptibility to environmental factors. Application of the method to data on the expression of human brain genes in neuro-degeneration validates the technique and, at the same time, illustrates the potential of the method

Translating the cellular neuropathology of microglia into neuroimaging results

The brain responds to the challenge of disease with marked changes in the functional state of its glial cells. One of the most rapid and obvious events is the activation of microglia, the brain’s resident tissue macrophages. Microglial activation is increasingly recognised as an important, early step in the pathophysiological response to traumatic, inflammatory and degenerative tissue changes and even to neoplastic transformation that may affect the nervous system. Microglia react rapidly and in a territorially highly confined way to subtle, acute as well as chronic pathological stimuli. Microglia have been aptly called a “sensor” of pathology in the CNS by Kreutzberg [1,2]. This unique behaviour, which may be due to a lack of gap junctions in these cells [3] is of great practical diagnostic use. Thus, detection of microglial activation provides useful information on formal parameters of disease, such as accurate spatial localisation of the disease process, rate of disease progression and insights into secondary neurodegenerative or adaptive alterations which may take place quite remote from the actual lesion site. Part of the remarkable structural and functional plasticity of microglia is the de novo expression of the “peripheral benzodiazepine binding site" (PBBS). PBBS is linked to important functions, such as immune modulation, steroid synthesis and mitochondrial activity. The PBBS is bound by the isoquinoline, PK11195, which labelled with carbon-11 can be used for positron emission tomography (PET). This opens up a unique window to study glial activity in the living human brain

Translating the cellular neuropathology of microglia into neuroimaging results

The brain responds to the challenge of disease with marked changes in the functional state of its glial cells. One of the most rapid and obvious events is the activation of microglia, the brain’s resident tissue macrophages. Microglial activation is increasingly recognised as an important, early step in the pathophysiological response to traumatic, inflammatory and degenerative tissue changes and even to neoplastic transformation that may affect the nervous system. Microglia react rapidly and in a territorially highly confined way to subtle, acute as well as chronic pathological stimuli. Microglia have been aptly called a “sensor” of pathology in the CNS by Kreutzberg [1,2]. This unique behaviour, which may be due to a lack of gap junctions in these cells [3] is of great practical diagnostic use. Thus, detection of microglial activation provides useful information on formal parameters of disease, such as accurate spatial localisation of the disease process, rate of disease progression and insights into secondary neurodegenerative or adaptive alterations which may take place quite remote from the actual lesion site. Part of the remarkable structural and functional plasticity of microglia is the de novo expression of the “peripheral benzodiazepine binding site" (PBBS). PBBS is linked to important functions, such as immune modulation, steroid synthesis and mitochondrial activity. The PBBS is bound by the isoquinoline, PK11195, which labelled with carbon-11 can be used for positron emission tomography (PET). This opens up a unique window to study glial activity in the living human brain

Microglia in Culture: What Genes Do They Express?

The cell culture model utilized in this study represents one of the most widely used paradigms of microglia in vitro. After 14 days, microglia harvested from the neonatal rat brain are considered ‘mature’. However, it is clear that this represents a somewhat arbitrary definition. In this paper, we provide a transcriptome definition of such microglial cells. More than 7,000 known genes and 1,000 expressed sequence tag clusters were analysed. ‘Microglia genes’ were defined as sequences consistently expressed in all microglia samples tested. Accordingly, 388 genes were identified as microglia genes. Another 1,440 sequences were detected in a subset of the cultures. Genes consistently expressed by microglia included genes known to be involved in the cellular immune response, brain tissue surveillance, microglial migration as well as proliferation. The expression profile reported here provides a baseline against which changes of microglia in vitro can be examined. Importantly, expression profiling of normal microglia will help to provide the presently purely operational definition of ‘microglial activation’ with a molecular biological correlate. Furthermore, the data reported here add to our understanding of microglia biology and allow projections as to what functions microglia may exert in vivo, as well as in vitro