A multi-input, single output imaging model may predict the extent of glioma invasion with significant correlation with histopathology.

Precise focusing is essential for transcranial MRI-guided focused ultrasound (TcMRgFUS) to minimize collateral damage to non-diseased tissues and to achieve temperatures capable of inducing coagulative necrosis at acceptable power deposition levels. CT is usually used for this refocusing but requires a separate study (CT) ahead of the TcMRgFUS procedure. The goal of this study was to determine whether MRI using an appropriate sequence would be a viable alternative to CT for planning ultrasound refocusing in TcMRgFUS. We tested three MRI pulse sequences (3D T1 weighted 3D volume interpolated breath hold examination (VIBE), proton density weighted 3D sampling perfection with applications optimized contrasts using different flip angle evolution and 3D true fast imaging with steady state precision T2-weighted imaging) on patients who have already had a CT scan performed. We made detailed measurements of the calvarial structure based on the MRI data and compared those so-called 'virtual CT' to detailed measurements of the calvarial structure based on the CT data, used as a reference standard. We then loaded both standard and virtual CT in a TcMRgFUS device and compared the calculated phase correction values, as well as the temperature elevation in a phantom. A series of Bland-Altman measurement agreement analyses showed T1 3D VIBE as the optimal MRI sequence, with respect to minimizing the measurement discrepancy between the MRI derived total skull thickness measurement and the CT derived total skull thickness measurement (mean measurement discrepancy: 0.025; 95% CL (-0.22-0.27); p = 0.825). The T1-weighted sequence was also optimal in estimating skull CT density and skull layer thickness. The mean difference between the phase shifts calculated with the standard CT and the virtual CT reconstructed from the T1 dataset was 0.08 ± 1.2 rad on patients and 0.1 ± 0.9 rad on phantom. Compared to the real CT, the MR-based correction showed a 1 °C drop on the maximum temperature elevation in the phantom (7% relative drop). Without any correction, the maximum temperature was down 6 °C (43% relative drop). We have developed an approach that allows for a reconstruction of a virtual CT dataset from MRI to perform phase correction in TcMRgFUS.

Introduction Diffusion-MRI is a rapidly evolving research field that has produced a wealth of algorithms for the analysis of white matter fibre architecture and disorders in the brain. Camino is a free, open-source toolkit designed to make a selection of this technology available and convenient to use for the diffusion MRI research community. Camino implements a data processing pipeline, which allows for easy scripting and flexible integration with other software. This abstract summarises the features of Camino at each stage of the pipeline from the raw data to the statistics used by clinicians and researchers.Design Camino is written in Java, and designed for a Unix-style interface. The user documentation is in the form of Unix manual pages, and each program has a shell wrapper, so users do not require any knowledge of Java. The data pipeline provides flexibility, by allowing data to be imported and exported to other software, and transparency, because the output of each Camino program can be analyzed in detail. Fig. 1 illustrates the pipeline. Camino processes all data in voxel order, where the measurements for each voxel are stored together. This ordering facilitates the data pipeline model and allows each voxel to be processed independently, which simplifies parallel processing. All of Camino's output is in a documented raw binary format. The tractography module optionally outputs Analyze images for easy integration with visualisation software. DataThe data source for Camino can be raw data from a scanner or from Camino's data synthesiser. The data synthesiser emulates scanner sequences and provides synthetic data from a range of customisable test functions. Data from scanners is not typically in voxel order, so Camino contains tools for rearranging data into the correct format. Associated with each data file is the scheme file, which is a text file that describes the acquisition parameters for each measurement.Reconstruction The reconstruction stage takes as input raw data and reconstructs information about the diffusion in each voxel. Camino supports a range of standard and advanced reconstruction algorithms. The simplest and fastest inversion is the linear diffusion tensor fit, in which the elements of the diffusion tensor are calculated from a standard linear least-squares fit to the log of the measurements. With the dtfit program, a linear diffusion tensor fit takes about two minutes for a 128 × 128 × 60 voxel data set, on a standard Pentium IV 2.4 GHz workstation. Nonlinear fitting is slower but potentially more accurate. Camino supports nonlinear least-squares diffusion tensor fitting and the RESTORE method [1]. Camino also supports non-tensor based diffusion reconstruction, including mixture modelling [2], PAS-MRI [3], Q-ball [4] and spherical deconvolution [5]. Spherical harmonic voxel classification [6] detects non-Gaussian diffusion. The thresholds used in classification can be set interactively (Fig. 2) and the classification can be used to drive reconstruction, fitting multi-fibre models only wh...

Chitosan polymers (Cs), from which microparticles (CsM) may be precipitated to deliver various intracellular payloads, are generally considered biologically inert. We examined the impact of cell culture conditions on CsM size and the effect of chitosan on CD59 expression in primary human smooth muscle cells. We found that particle concentration and incubation time in biological buffers augmented particle size. Between pH 7.0 and pH 7.5, CsM size increased abruptly. We utilized CsM containing a plasmid with a gene for CD59 (pCsM) to transfect cells. Both CD59 mRNA and the number of CD59-positive cells were increased after pCsM treatment. Unexpectedly, CsM also augmented the number of CD59-positive cells. Cs alone enhanced CD59 expression more potently than either pCSM or CsM. This observation strongly suggests that chitosan is in fact bioactive and that chitosan-only controls should be included to avoid misattributing the activity of the delivery agent with that of the payload.

Introduction The effects of omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFA) on cerebrovascular disease remain unsettled. However, most studies have focused on marine sourced n-3 PUFA rather than total n-3 PUFA, of which the majority in the American diet is plant derived. This study therefore intended to investigate these effects in a cohort for which the vegetarian diet was more prevalent than the general public. Methods Cox proportional hazards with fatal stroke as the outcome was performed on the approximately 96,000 subject Adventist Health Study 2 prospective cohort. Stratification by race and sex was performed on models with a priori covariables, comparing 90th to 10th percentile daily intakes of energy-adjusted total n-3 PUFA, total n-6 PUFA, and the n-6 / n-3 PUFA ratio as variables of interest. Results For the main analytical group (78,335 subjects), the hazard ratio (95% confidence interval) for total n-3 PUFA was 0.65 (0.51–0.83), and for total n-6 PUFA was 1.37 (1.02–1.82), while adjusting for both fatty acids in the model. The n-6 / n-3 PUFA ratio was harmful with a HR of 1.40 (1.16–1.69), whereas the inclusion of total n-3 PUFA slightly attenuated the HR to 1.33(1.02–1.74). Effects were similar for the non-black sex-combined and sex-specific analyses. Conclusion In most analytic groups, subjects with greater total n-3 PUFA intakes have lower risk of fatal stroke, and those with a higher n-6 / n-3 PUFA ratio had higher risk. However, the n-6 / n-3 PUFA ratio remains statistically significant even after adjusting for total n-3 PUFA or total n-6 PUFA, suggesting that the ratio is of epidemiologic interest for cerebrovascular disease research.