Unsupervised Fiber Bundles Registration using Weighted Measures Geometric Demons

International audienceBrain image registration aims at reducing anatomical variability across subjects to create a common space for group analysis. Multi-modal approaches intend to minimize cortex shape variations along with internal structures, such as fiber bundles. A di ficulty is that it requires a prior identi fication of these structures, which remains a challenging task in the absence of a complete reference atlas. We propose an extension of the log-Geometric Demons for jointly registering images and fi ber bundles without the need of point or ber correspondences. By representing fi ber bundles as Weighted Measures we can register subjects with di fferent numbers of fiber bundles. The ef ficacy of our algorithm is demonstrated by registering simultaneously T1 images and between 37 and 88 ber bundles depending on each of the ten subject used. We compare results with a multi-modal T1 + Fractional Anisotropy (FA) and a tensor-based registration algorithms and obtain superior performance with our approach

Quantification of volumetric morphometry and optical property in the cortex of human cerebellum at micrometer resolution

The surface of the human cerebellar cortex is much more tightly folded than the cerebral cortex. Volumetric analysis of cerebellar morphometry in magnetic resonance imaging studies suffers from insufficient resolution, and therefore has had limited impact on disease assessment. Automatic serial polarization-sensitive optical coherence tomography (as-PSOCT) is an emerging technique that offers the advantages of microscopic resolution and volumetric reconstruction of large-scale samples. In this study, we reconstructed multiple cubic centimeters of ex vivo human cerebellum tissue using as-PSOCT. The morphometric and optical properties of the cerebellar cortex across five subjects were quantified. While the molecular and granular layers exhibited similar mean thickness in the five subjects, the thickness varied greatly in the granular layer within subjects. Layer-specific optical property remained homogenous within individual subjects but showed higher cross-subject variability than layer thickness. High-resolution volumetric morphometry and optical property maps of human cerebellar cortex revealed by as-PSOCT have great potential to advance our understanding of cerebellar function and diseases

Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry

International audienceWe present an extension of the diffeomorphic Geometric Demons algorithm which combines the iconic registration with geometric constraints. Our algorithm works in the log-domain space, so that one can efficiently compute the deformation field of the geometry. We represent the shape of objects of interest in the space of currents which is sensitive to both location and geometric structure of objects. Currents provides a distance between geometric structures that can be defined without specifying explicit point-to-point correspondences. We demonstrate this framework by registering simultaneously T1 images and 65 fiber bundles consistently extracted in 12 subjects and compare it against non-linear T1, tensor, and multi-modal T1+ Fractional Anisotropy (FA) registration algorithms. Results show the superiority of the Log-domain Geometric Demons over their purely iconic counterparts

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14–17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and long-itudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource

Evaluation of in vitro Antifungal Activity of Xylosma prockia (Turcz.) Turcz. (Salicaceae) Leaves Against Cryptococcus spp.

Cryptococcus species are responsible for important systemic mycosis and are estimated to cause millions of new cases annually. The available therapy is limited due to the high toxicity and the increasing rates of yeast resistance to antifungal drugs. Popularly known as “sucará,” Xylosma prockia (Turcz.) Turcz. (Salicaceae) is a native plant from Brazil with little information on its pharmacological potential. In this work, we evaluated in vitro anticryptococcal effects of the leaf ethanolic extract of X. prockia and its fractions against Cryptococcus gattii and Cryptococcus neoformans. We also evaluated phenotypic alterations caused by ethyl acetate fraction (EAF) (chosen according to its biological results). The liquid chromatography–mass spectrometry (LC-MS) analysis of EAF demonstrated the presence of phenolic metabolites that belong to three structurally related groups as majority compounds: caffeoylquinic acid, coumaroyl-glucoside, and caffeoyl-glucoside/deoxyhexosyl-caffeoyl glucoside derivatives. The minimum inhibitory concentration (MIC) values against C. gattii and C. neoformans ranged from 8 to 64 mg/L and from 0.5 to 8 mg/L, for ethanolic extract and EAF, respectively. The EAF triggered an oxidative burst and promoted lipid peroxidation. EAF also induced a reduction of ergosterol content in the pathogen cell membrane. These effects were not associated with alterations in the cell surface charge or in the thermodynamic fingerprint of the molecular interaction between EAF and the yeasts evaluated. Cytotoxic experiments with peripheral blood mononuclear cells (PBMCs) demonstrated that EAF was more selective for yeasts than was PBMCs. The results may provide evidence that X. prockia leaf extract might indeed be a potential source of antifungal agents.Fil: Folly, Mariany L. C.. Universidade Federal de Juiz de Fora; BrasilFil: Ferreira, Gabriella F.. Universidade Federal de Juiz de Fora; BrasilFil: Salvador, Maiara R.. Universidade Federal de Juiz de Fora; BrasilFil: Sathler, Ana A.. Universidade Federal de Juiz de Fora; BrasilFil: da Silva, Guilherme F.. Universidade Federal de Juiz de Fora; BrasilFil: Santos, Joice Castelo Branco. Ceuma University; BrasilFil: Santos, Julliana R. A. dos. Ceuma University; BrasilFil: Nunes Neto, Wallace Ribeiro. Ceuma University; BrasilFil: Rodrigues, João Francisco Silva. Ceuma University; BrasilFil: Fernandes, Elizabeth Soares. Ceuma University; BrasilFil: da Silva, Luís Cláudio Nascimento. Ceuma University; BrasilFil: de Freitas, Gustavo José Cota. Universidade Federal de Minas Gerais; BrasilFil: Denadai, Ângelo M.. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; BrasilFil: Rodrigues, Ivanildes V.. Universidade Federal de Juiz de Fora; BrasilFil: Mendonça, Leonardo M.. Universidade Federal de Juiz de Fora; BrasilFil: Monteiro, Andrea Souza. Ceuma University; BrasilFil: Santos, Daniel Assis. Universidade Federal de Minas Gerais; BrasilFil: Cabrera, Gabriela Myriam. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad de Microanálisis y Métodos Físicos en Química Orgánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Unidad de Microanálisis y Métodos Físicos en Química Orgánica; ArgentinaFil: Siless, Gastón Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad de Microanálisis y Métodos Físicos en Química Orgánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Unidad de Microanálisis y Métodos Físicos en Química Orgánica; ArgentinaFil: Lang, Karen L.. Universidade Federal de Juiz de Fora; Brasi

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14-17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and longitudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource.R01 MH101521 - NIMH NIH HHS; R01 EB021265 - NIBIB NIH HHS; S10 RR019307 - NCRR NIH HHS; R01 AT007257 - NCCIH NIH HHS; U01 MH108168 - NIMH NIH HHS; R37 MH068376 - NIMH NIH HHS; P41 EB019936 - NIBIB NIH HHS; U01 EB026996 - NIBIB NIH HHS; R01 EB020740 - NIBIB NIH HHS; F32 MH114525 - NIMH NIH HHS; S10 RR023043 - NCRR NIH HHS; R01 MH099021 - NIMH NIH HHS; R01 MH096987 - NIMH NIH HHS; S10 RR023401 - NCRR NIH HHSPublished versio

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14–17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and long-itudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource

Supervised classification of white matter fibers based on neighborhood fiber orientation distributions using an ensemble of neural networks

White matter fibers constitute the main information transfer network of the brain and their accurate digital representation and classification is an important goal of neuroscience image computing. In current clinical practice, the reconstruction of desired fibers generally involves manual selection of regions of interest by an expert, which is time-consuming and subject to user bias, expertise and fatigue. Hence, automation of the process is desired. To that end, we propose a supervised classification approach that utilizes an ensemble of neural networks. Each streamline is represented by the fiber orientation distributions in its neighborhood, while the resolved fiber orientations are obtained by generalized q-sampling imaging (GQI) and a subsequent diffusion decomposition method. In order to make the supervised fiber classification succeed in a real scenario where a substantial portion of reconstructed fiber tracts contain spurious fibers, we present a way to create an “invalid” class label through a dedicated training set creation scheme with an ensemble of networks. The performance of the proposed classification method is demonstrated on major fiber pathways in the brainstem. 30 subjects from Human Connectome Project (HCP)’s publicly available “WU-Minn 500 Subjects + MEG2 dataset” are used as the dataset

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

© 2020 We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14–17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and longitudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource