Clovis Tauber

Molecular Imaging of Microglial Activation in Amyotrophic Lateral Sclerosis

There is growing evidence of activated microglia and inflammatory processes in the cerebral cortex in amyotrophic lateral sclerosis (ALS). Activated microglia is characterized by increased expression of the 18 kDa translocator protein (TSPO) in the brain and may be a useful biomarker of inflammation. In this study, we evaluated neuroinflammation in ALS patients using a radioligand of TSPO, 18F-DPA-714. Ten patients with probable or definite ALS (all right-handed, without dementia, and untreated by riluzole or other medication that might bias the binding on the TSPO), were enrolled prospectively and eight healthy controls matched for age underwent a PET study. Comparison of the distribution volume ratios between both groups were performed using a Mann-Whitney’s test. Significant increase of distribution of volume ratios values corresponding to microglial activation was found in the ALS sample in primary motor, supplementary motor and temporal cortex (p = 0.009, p = 0.001 and p = 0.004, respectively). These results suggested that the cortical uptake of 18F-DPA-714 was increased in ALS patients during the “time of diagnosis” phase of the disease. This finding might improve our understanding of the pathophysiology of ALS and might be a surrogate marker of efficacy of treatment on microglial activation.

Initial evaluation in healthy humans of [18F]DPA-714, a potential PET biomarker for neuroinflammation

INTRODUCTION The translocator protein 18 kDa (TSPO), although minimally expressed in healthy brain, is up-regulated in pathological conditions, coinciding with microglial activation. It is thereby a suitable in vivo biomarker of neuroinflammation for detection, evaluation and therapeutic monitoring of brain diseases. We aimed to estimate the radiation dosimetry of the positron emission tomography (PET) TSPO radioligand [(18)F]DPA-714, and we evaluated in healthy volunteers its whole-body uptake and cerebral kinetics. METHODS Biodistribution data from mice were used for the prediction of radiation dosimetry. In human studies, a 90-min dynamic PET scan was performed in seven healthy volunteers after injection of [(18)F]DPA-714 (245±45 MBq). Arterial and venous samples were collected from two subjects, and two additional subjects were submitted to whole-body acquisition. Regions of interest were defined over cerebral structures to obtain mean time-activity curves and to estimate the distribution volume ratios by Logan graphical analysis, and over peripheral organs to obtain standard uptake values. RESULTS The effective dose estimated from biodistribution in mice was 17.2 μSv/MBq. Modeling of regional brain and plasma data showed good in vivo stability of [(18)F]DPA-714 in humans, with only 20% of blood metabolites 20 min postinjection (p.i.). Maximum cerebral uptake was observed 5 min p.i., followed by two decreasing phases: a rapid washout (5-30 min) followed by a slower phase for the remainder of PET acquisition. Whole-body images demonstrate high activity in the gallbladder, heart, spleen and kidneys. CONCLUSIONS This initial study in humans shows that [(18)F]DPA-714 is a promising PET radioligand with excellent in vivo stability and biodistribution, and acceptable effective dose estimation. Therefore, [(18)F]DPA-714 could provide a sensitive measure of neuroinflammatory changes in subsequent clinical investigations.

Robust B-spline snakes for ultrasound image segmentation

Snake-based methods are commonly used to segment ultrasound images. However, their performance is generally limited because of the specific properties of this kind of images. This paper addresses the sensitivity of parametric active contours to speckle within ultrasound images. We propose a new B-spline snake model, founded on two original external energies specifically tailored for the segmentation of biomedical speckled images. First, the curve is attracted from a wide capture range with an expansion energy that facilitates the snake initialization. Then, it is accurately fitted on the region boundaries with an energy that allows precise positioning of the curve along edges in ultrasound images. A mutual inhibition function is designed to control the two energies. Results on real ultrasound images are presented and quantitatively compared to the boundaries manually outlined by experts. Our method improves the precision of heart cavities segmentation.

A robust speckle reducing anisotropic diffusion

This paper deals with anisotropic diffusion in images affected by speckle. Two existing methods are reviewed. The first is a robust diffusion technique, non adapted to speckle, based on the Tukey function. The second applies an isotropic diffusion to speckle but lacks robustness. The contribution of this paper is to create a robust anisotropic diffusion filter adapted to speckle. The proposed approach is based on the two reviewed methods and introduces an original diffusion tensor Experimentation results are presented and the performance of the three methods compared. The proposed algorithm shows significant enhancement.

Quasi-automatic initialization for parametric active contours

Active contour is a well-known image segmentation technique, commonly used to find object boundaries in images. Its main benefit is its ability to retrieve an ordered collection of points. However, fitting precisely a deformable contour to actual boundaries depends strongly on its initialization and requires adjusting various parameters. This paper presents an original method to initialize quasi-automatically explicit deformable models when segmenting regions that require no change of topology. The proposed method relies on a careful study of the gradient vector flow. Two original concepts are introduced, namely strong and weak divergence centers. The analysis of the properties of these centers leads to establishing a quasi-automatic method to setup an initial curve that will reach all the boundaries of a target region. Results using synthetic and real images are presented, showing the validity of our approach.

A general quasi-automatic initialization for snakes: application to ultrasound images

Segmentation with active contours is heavily dependent on the initialization. In this paper we propose a novel method for a quasi-automatic initialization of deformable models. Our method relies on the use of an additional energy based on the gradient vector flow. We define the centers of strong and weak divergence and use them to set up the initial curve. As our goal is the segmentation of the heart cavities, we also propose a new gradient vector field for ultrasound images based on the coefficient of variation. Results on real ultra-sound images are presented and compared to the boundaries manually outlined by an expert. They confirm the potential of the method.

FIBRASCAN: a novel method for 3D white matter tract reconstruction in MR space from cadaveric dissection.

INTRODUCTION Diffusion tractography relies on complex mathematical models that provide anatomical information indirectly, and it needs to be validated. In humans, up to now, tractography has mainly been validated by qualitative comparison with data obtained from dissection. No quantitative comparison was possible because Magnetic Resonance Imaging (MRI) and dissection data are obtained in different reference spaces, and because fiber tracts are progressively destroyed by dissection. Here, we propose a novel method and software (FIBRASCAN) that allow accurate reconstruction of fiber tracts from dissection in MRI reference space. METHOD Five human hemispheres, obtained from four formalin-fixed brains were prepared for Klinglers dissection, placed on a holder with fiducial markers, MR scanned, and then dissected to expose the main association tracts. During dissection, we performed iterative acquisitions of the surface and texture of the specimens using a laser scanner and two digital cameras. Each texture was projected onto the corresponding surface and the resulting set of textured surfaces was coregistered thanks to the fiducial holders. The identified association tracts were then interactively segmented on each textured surface and reconstructed from the pile of surface segments. Finally, the reconstructed tracts were coregistered onto ex vivo MRI space thanks to the fiducials. Each critical step of the process was assessed to measure the precision of the method. RESULTS We reconstructed six fiber tracts (long, anterior and posterior segments of the superior longitudinal fasciculus; Inferior fronto-occipital, Inferior longitudinal and uncinate fasciculi) from cadaveric dissection and ported them into ex vivo MRI reference space. The overall accuracy of the method was of the order of 1mm: surface-to-surface registration=0.138mm (standard deviation (SD)=0.058mm), deformation of the specimen during dissection=0.356mm (SD=0.231mm), and coregistration surface-MRI=0.6mm (SD=0.274mm). The spatial resolution of the method (distance between two consecutive surface acquisitions) was 0.345mm (SD=0.115mm). CONCLUSION This paper presents the robustness of a novel method, FIBRASCAN, for accurate reconstruction of fiber tracts from dissection in the ex vivo MR reference space. This is a major step toward quantitative comparison of MR tractography with dissection results.

Amyloid load and translocator protein 18 kDa in APPswePS1-dE9 mice: a longitudinal study.

We studied concomitantly the level of neuroinflammation and β-amyloid (Aβ) load in the APPswePS1dE9 transgenic mouse model of Alzheimers disease using positron emission tomography. The translocator protein 18 kDa (TSPO) tracer [(18)F]DPA-714 was used to measure neuroinflammation and [(18)F]AV-45 for Aβ load in mice at 6, 9, 12, 15, and 19 months of age. At 19 months, we also analyzed the neuroinflammatory and neuroanatomic status of mice brains. The main affected brain areas were the cortex and hippocampus, with a concomitant progression of neuroinflammation with increased amyloid burden. At 19 months, no increase in TSPO binding was observed in the cerebellum; immunostaining revealed W0-2-positive plaques, indicating that the amyloid deposits seemed not stimulate inflammation. This finding was in agreement with the observed level of microglia and astrocytes staining. Our findings provide a better understanding of the relationships between neuroinflammation and plaque accumulation in the course of the disease in this mouse model. The monitoring of both processes should be of value to validate potential therapeutic approaches.

Brain [18F]FDDNP binding and glucose metabolism in advanced elderly healthy subjects and Alzheimer's disease patients.

BACKGROUND Positron emission tomography (PET) imaging of brain amyloid (Aβ) and neurofibrillary tangle (NFT) load is a candidate biomarker of Alzheimers disease (AD). OBJECTIVES To compare brain Aβ and NFT load and glucose metabolism in advanced elderly (70 years and older) patients with AD and healthy controls (HCs) by PET with [18F]FDDNP and [18F]FDG. METHODS Seven AD patients (mean ± SD age 79.3 ± 3.6 y, Mini-Mental State Examination (MMSE) score 22.1 ± 2.5) and eight HCs (mean age ± SD, 75.7 ± 3.9 y; MMSE score 29.0 ± 1.2) underwent PET with [18F]FDDNP and [18F]FDG. RESULTS Global [18F]FDDNP uptake was significantly higher (p < 0.05) in AD patients (1.15 ± 0.04) than in HCs (1.10 ± 0.06), while global brain metabolism was lower in AD patients than in HCs (AD patients 0.96 ± 0.09; HCs 1.13 ± 0.11; p < 0.05). In HCs, brain glucose metabolism was correlated with age for both the global [18F]FDG SUVr and in the parietal and posterior cingulate regions, while no correlation was found between age and [18F]FDDNP uptake. In AD patients, global [18F]FDDNP uptake and uptake in the frontal and anterior cingulate regions of interest were correlated with MMSE score, while no correlation was observed with brain glucose metabolism. CONCLUSION Imaging Aβ load and NFT with [18F]FDDNP can distinguish AD patients from HCs in an advanced elderly population. It seems to be less sensitive than [18F]FDG to the brain changes observed with normal aging, but more sensitive to cognitive decline in advanced elderly AD patients.

Robust level set for heart cavities detection in ultrasound images

The class of geometric deformable models, also known as level sets, has brought tremendous impact on medical imagery due to its capability of topology preservation and fast shape recovery. Ultrasonic heart images are often characterized by high level of speckle noise causing erroneous detection of cavities. We propose a new stopping term for computing level sets in order to robustly detect the heart cavities in echocardiographic images. Robustness is ensured by the use of the coefficient of variation. Experimental results show significant improvement, especially for images acquired with low frequencies