JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Segmentation and grid generation for numerical simulations of vad connections with patient-specific data

Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.

CD30-positive peripheral T-cell lymphomas share molecular and phenotypic features.

Peripheral T-cell lymphoma, not otherwise specified is a heterogeneous group of aggressive neoplasms with indistinct borders. By gene expression profiling we previously reported unsupervised clusters of peripheral T-cell lymphomas, not otherwise specified correlating with CD30 expression. In this work we extended the analysis of peripheral T-cell lymphoma molecular profiles to prototypical CD30(+) peripheral T-cell lymphomas (anaplastic large cell lymphomas), and validated mRNA expression profiles at the protein level. Existing transcriptomic datasets from peripheral T-cell lymphomas, not otherwise specified and anaplastic large cell lymphomas were reanalyzed. Twenty-one markers were selected for immunohistochemical validation on 80 peripheral T-cell lymphoma samples (not otherwise specified, CD30(+) and CD30(-); anaplastic large cell lymphomas, ALK(+) and ALK(-)), and differences between subgroups were assessed. Clinical follow-up was recorded. Compared to CD30(-) tumors, CD30(+) peripheral T-cell lymphomas, not otherwise specified were significantly enriched in ALK(-) anaplastic large cell lymphoma-related genes. By immunohistochemistry, CD30(+) peripheral T-cell lymphomas, not otherwise specified differed significantly from CD30(-) samples [down-regulated expression of T-cell receptor-associated proximal tyrosine kinases (Lck, Fyn, Itk) and of proteins involved in T-cell differentiation/activation (CD69, ICOS, CD52, NFATc2); upregulation of JunB and MUM1], while overlapping with anaplastic large cell lymphomas. CD30(-) peripheral T-cell lymphomas, not otherwise specified tended to have an inferior clinical outcome compared to the CD30(+) subgroups. In conclusion, we show molecular and phenotypic features common to CD30(+) peripheral T-cell lymphomas, and significant differences between CD30(-) and CD30(+) peripheral T-cell lymphomas, not otherwise specified, suggesting that CD30 expression might delineate two biologically distinct subgroups.

Direct Fourier Tomographic Reconstruction Image-To-Image Filter

We present an open-source ITK implementation of a directFourier method for tomographic reconstruction, applicableto parallel-beam x-ray images. Direct Fourierreconstruction makes use of the central-slice theorem tobuild a polar 2D Fourier space from the 1D transformedprojections of the scanned object, that is resampled intoa Cartesian grid. Inverse 2D Fourier transform eventuallyyields the reconstructed image. Additionally, we providea complex wrapper to the BSplineInterpolateImageFunctionto overcome ITKâeuro?s current lack for image interpolatorsdealing with complex data types. A sample application ispresented and extensively illustrated on the Shepp-Loganhead phantom. We show that appropriate input zeropaddingand 2D-DFT oversampling rates together with radial cubicb-spline interpolation improve 2D-DFT interpolationquality and are efficient remedies to reducereconstruction artifacts.

Exporting Contours to DICOM-RT Structure Set

This paper presents an ITK implementation for exportingthe contours of the automated segmentation results toDICOM-RT Structure Set format. The âeurooeradiotherapystructure setâeuro (RTSTRUCT) object of the DICOM standard isused for the transfer of patient structures and relateddata, between the devices found within and outside theradiotherapy department. It mainly contains theinformation of regions of interest (ROIs) and points ofinterest (E.g. dose reference points). In many cases,rather than manually drawing these ROIs on the CT images,one can indeed benefit from the automated segmentationalgorithms already implemented in ITK. But at present, itis not possible to export the ROIs obtained from ITK toRTSTRUCT format. In order to bridge this gap, we havedeveloped a framework for exporting contour data toRTSTRUCT. We provide here the complete implementation ofRTSTRUCT exporter and present the details of the pipelineused. Results on a 3-D CT image of the Head and Neck(H&N) region are presented.

MBIS: multivariate Bayesian image segmentation tool.

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

New biomarkers in T-cell lymphomas.

Peripheral T-cell lymphomas (PTCLs) are heterogeneous and uncommon malignancies characterized by an aggressive clinical course and a mostly poor outcome with current treatment strategies. The recent genome-wide molecular characterization of several entities has provided novel insights into their pathobiology and led to the identification of new biomarkers with diagnostic, prognostic or therapeutic implications for PTCL patients. Cell lineage and differentiation antigens (markers of γδ or NK lineage, of cytotoxicity, of follicular helper T cells) reflect the tumour's biological behaviour, and their detection in tissue samples may refine the diagnostic and prognostic stratification of the patients. Previously unrecognized gene rearrangements are being discovered (ITK-SYK translocation, IRF4/MUM1 and DUSP22 rearrangements), and may serve as diagnostic genetic markers. Deregulated molecules within oncogenic pathways (NF-κB, Syk, PDGFRα) and immunoreactive cell-surface antigens (CD30, CD52) have been brought to the fore as potential targets for guiding the development of novel therapies.