Scientific Computing and Imaging Institute

About: Scientific Computing and Imaging Institute is a based out in . It is known for research contribution in the topics: Visualization & Population. The organization has 359 authors who have published 847 publications receiving 28106 citations.

A Structural MRI Study of Human Brain Development from Birth to 2 Years

Abstract: Brain development in the first 2 years after birth is extremely dynamic and likely plays an important role in neurodevelopmental disorders, including autism and schizophrenia Knowledge regarding this period is currently quite limited We studied structural brain development in healthy subjects from birth to 2 Ninety-eight children received structural MRI scans on a Siemens head-only 3T scanner with magnetization prepared rapid gradient echo T1-weighted, and turbo spin echo, dual-echo (proton density and T2 weighted) sequences: 84 children at 2–4 weeks, 35 at 1 year and 26 at 2 years of age Tissue segmentation was accomplished using a novel automated approach Lateral ventricle, caudate, and hippocampal volumes were also determined Total brain volume increased 101% in the first year, with a 15% increase in the second The majority of hemispheric growth was accounted for by gray matter, which increased 149% in the first year; hemispheric white matter volume increased by only 11% Cerebellum volume increased 240% in the first year Lateral ventricle volume increased 280% in the first year, with a small decrease in the second The caudate increased 19% and the hippocampus 13% from age 1 to age 2 There was robust growth of the human brain in the first two years of life, driven mainly by gray matter growth In contrast, white matter growth was much slower Cerebellum volume also increased substantially in the first year of life These results suggest the structural underpinnings of cognitive and motor development in early childhood, as well as the potential pathogenesis of neurodevelopmental disorders

FEBio: finite elements for biomechanics.

Abstract: In the field of computational biomechanics, investigators have primarily used commercial software that is neither geared toward biological applications nor sufficiently flexible to follow the latest developments in the field This lack of a tailored software environment has hampered research progress, as well as dissemination of models and results To address these issues, we developed the FEBio software suite (http://mrlsciutahedu/software/febio), a nonlinear implicit finite element (FE) framework, designed specifically for analysis in computational solid biomechanics This paper provides an overview of the theoretical basis of FEBio and its main features FEBio offers modeling scenarios, constitutive models, and boundary conditions, which are relevant to numerous applications in biomechanics The open-source FEBio software is written in C++, with particular attention to scalar and parallel performance on modern computer architectures Software verification is a large part of the development and maintenance of FEBio, and to demonstrate the general approach, the description and results of several problems from the FEBio Verification Suite are presented and compared to analytical solutions or results from other established and verified FE codes An additional simulation is described that illustrates the application of FEBio to a research problem in biomechanics Together with the pre- and postprocessing software PREVIEW and POSTVIEW, FEBio provides a tailored solution for research and development in computational biomechanics

Left Atrial Strain and Strain Rate in Patients With Paroxysmal and Persistent Atrial Fibrillation Relationship to Left Atrial Structural Remodeling Detected by Delayed-Enhancement MRI

Abstract: Background— Atrial fibrillation (AF) is a progressive condition that begins with hemodynamic and/or structural changes in the left atrium (LA) and evolves through paroxysmal and persistent stages. Because of limitations with current noninvasive imaging techniques, the relationship between LA structure and function is not well understood. Methods and Results— Sixty-five patients (age, 61.2±14.2 years; 67% men) with paroxysmal (44%) or persistent (56%) AF underwent 3D delayed-enhancement MRI. Segmentation of the LA wall was performed and degree of enhancement (fibrosis) was determined using a semiautomated quantification algorithm. Two-dimensional echocardiography and longitudinal LA strain and strain rate during ventricular systole with velocity vector imaging were obtained. Mean fibrosis was 17.8±14.5%. Log-transformed fibrosis values correlated inversely with LA midlateral strain ( r =−0.5, P =0.003) and strain rate ( r =−0.4, P <0.005). Patients with persistent AF as compared with paroxysmal AF had more fibrosis (22±17% versus 14±9%, P =0.04) and lower midseptal (27±14% versus 38±16%, P =0.01) and midlateral (35±16% versus 45±14% P =0.03) strains. Multivariable stepwise regression showed that midlateral strain ( r =−0.5, P =0.006) and strain rate ( r =−0.4, P =0.01) inversely predicted the extent of fibrosis independent of other echocardiographic parameters and the rhythm during imaging. Conclusions— LA wall fibrosis by delayed-enhancement MRI is inversely related to LA strain and strain rate, and these are related to the AF burden. Echocardiographic assessment of LA structural and functional remodeling is quick and feasible and may be helpful in predicting outcomes in AF. Received March 17, 2009; accepted January 15, 2010. # CLINICAL PERSPECTIVE {#article-title-2}

Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

Abstract: Objective: The benefit of deep brain stimulation (DBS) for Parkinson's disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remains unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods: A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of Unified Parkinson's Disease Rating Scale). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results: In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease-matched to our DBS patients. Interpretation: Effective STN-DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. This article is protected by copyright. All rights reserved.

The ALPS project release 2.0: open source software for strongly correlated systems

Abstract: We present release 2.0 of the ALPS (Algorithms and Libraries for Physics Simulations) project, an open source software project to develop libraries and application programs for the simulation of strongly correlated quantum lattice models such as quantum magnets, lattice bosons, and strongly correlated fermion systems. The code development is centered on common XML and HDF5 data formats, libraries to simplify and speed up code development, common evaluation and plotting tools, and simulation programs. The programs enable non-experts to start carrying out serial or parallel numerical simulations by providing basic implementations of the important algorithms for quantum lattice models: classical and quantum Monte Carlo (QMC) using non-local updates, extended ensemble simulations, exact and full diagonalization (ED), the density matrix renormalization group (DMRG) both in a static version and a dynamic time-evolving block decimation (TEBD) code, and quantum Monte Carlo solvers for dynamical mean field theory (DMFT). The ALPS libraries provide a powerful framework for programmers to develop their own applications, which, for instance, greatly simplify the steps of porting a serial code onto a parallel, distributed memory machine. Major changes in release 2.0 include the use of HDF5 for binary data, evaluation tools in Python, support for the Windows operating system, the use of CMake as build system and binary installation packages for Mac OS X and Windows, and integration with the VisTrails workflow provenance tool. The software is available from our web server at http://alps.comp-phys.org/.