Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Non-invasive quantification of brain glycogen absolute concentration.

The only currently available method to measure brain glycogen in vivo is 13C NMR spectroscopy. Incorporation of 13C-labeled glucose (Glc) is necessary to allow glycogen measurement, but might be affected by turnover changes. Our aim was to measure glycogen absolute concentration in the rat brain by eliminating label turnover as variable. The approach is based on establishing an increased, constant 13C isotopic enrichment (IE). 13C-Glc infusion is then performed at the IE of brain glycogen. As glycogen IE cannot be assessed in vivo, we validated that it can be inferred from that of N-acetyl-aspartate IE in vivo: After [1-13C]-Glc ingestion, glycogen IE was 2.2 +/- 0.1 fold that of N-acetyl-aspartate (n = 11, R(2) = 0.77). After subsequent Glc infusion, glycogen IE equaled brain Glc IE (n = 6, paired t-test, p = 0.37), implying isotopic steady-state achievement and complete turnover of the glycogen molecule. Glycogen concentration measured in vivo by 13C NMR (mean +/- SD: 5.8 +/- 0.7 micromol/g) was in excellent agreement with that in vitro (6.4 +/- 0.6 micromol/g, n = 5). When insulin was administered, the stability of glycogen concentration was analogous to previous biochemical measurements implying that glycogen turnover is activated by insulin. We conclude that the entire glycogen molecule is turned over and that insulin activates glycogen turnover.

Differential transgene expression profiles in rat brain, using rAAV2/1 vectors with tetracycline-inducible and cytomegalovirus promoters.

The biodistribution of transgene expression in the CNS after localized stereotaxic vector delivery is an important issue for the safety of gene therapy for neurological diseases. The cellular specificity of transgene expression from rAAV2/1 vectors (recombinant adeno-associated viral vectors pseudotyped with viral capsids from serotype 1) using the tetracycline-inducible (TetON) expression cassette in comparison with the cytomegalovirus (CMV) promoter was investigated in the rat nigrostriatal pathway. After intrastriatal injection, although green fluorescent protein (GFP) was expressed mainly in neurons with both vectors, the relative proportions of DARPP-32-positive projection neurons and parvalbumin-positive interneurons were, respectively, 13:1 and 2:1 for the CMV and TetON vectors. DARP32-positive neurons projecting to the globus pallidus were strongly GFP positive with both vectors, whereas those projecting to the substantia nigra pars reticulata (SNpr) were efficiently labeled by the CMV vector but poorly by the TetON vector. Numerous GFP-positive cells were evidenced in the subventricular zone with both vectors. However, in the olfactory bulb (OB), GFP-positive neurons were observed with the CMV vector but not the TetON vector. We conclude that the absence of significant amounts of transgene product in distant regions (SN and OB) constitutes a safety advantage of the AAV2/1-TetON vector for striatal gene therapy. Midbrain injections resulted in selective GFP expression in tyrosine hydroxylase-positive neurons by the TetON vector whereas with the CMV vector, GFP-positive cells covered a widespread area of the midbrain. The biodistribution of GFP protein corresponded to that of the transcripts and not of the viral genomes. We conclude that the rAAV2/1-TetON vector constitutes an interesting tool for specific transgene expression in midbrain dopaminergic neurons.

The gene MAPK8IP1, encoding islet-brain-1, is a candidate for type 2 diabetes.

Type 2 diabetes is a polygenic and genetically heterogeneous disease . The age of onset of the disease is usually late and environmental factors may be required to induce the complete diabetic phenotype. Susceptibility genes for diabetes have not yet been identified. Islet-brain-1 (IB1, encoded by MAPK8IP1), a novel DNA-binding transactivator of the glucose transporter GLUT2 (encoded by SLC2A2), is the homologue of the c-Jun amino-terminal kinase-interacting protein-1 (JIP-1; refs 2-5). We evaluated the role of IBi in beta-cells by expression of a MAPK8IP1 antisense RNA in a stable insulinoma beta-cell line. A 38% decrease in IB1 protein content resulted in a 49% and a 41% reduction in SLC2A2 and INS (encoding insulin) mRNA expression, respectively. In addition, we detected MAPK8IP1 transcripts and IBi protein in human pancreatic islets. These data establish MAPK8IP1 as a candidate gene for human diabetes. Sibpair analyses performed on i49 multiplex French families with type 2 diabetes excluded MAPK8IP1 as a major diabetogenic locus. We did, however, identify in one family a missense mutation located in the coding region of MAPK8IP1 (559N) that segregated with diabetes. In vitro, this mutation was associated with an inability of IB1 to prevent apoptosis induced by MAPK/ERK kinase kinase 1 (MEKK1) and a reduced ability to counteract the inhibitory action of the activated c-JUN amino-terminal kinase (JNK) pathway on INS transcriptional activity. Identification of this novel non-maturity onset diabetes of the young (MODY) form of diabetes demonstrates that IB1 is a key regulator of 3-cell function.