The Role of Attorney Fee Shifting in Public Interest Litigation

BACKGROUND: Brain tissue segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) are important in neuroradiological applications. Quantitative Mri (qMRI) allows segmentation based on physical tissue properties, and the dependencies on MR scanner settings are removed. Brain tissue groups into clusters in the three dimensional space formed by the qMRI parameters R1, R2 and PD, and partial volume voxels are intermediate in this space. The qMRI parameters, however, depend on the main magnetic field strength. Therefore, longitudinal studies can be seriously limited by system upgrades. The aim of this work was to apply one recently described brain tissue segmentation method, based on qMRI, at both 1.5 T and 3.0 T field strengths, and to investigate similarities and differences. METHODS: In vivo qMRI measurements were performed on 10 healthy subjects using both 1.5 T and 3.0 T MR scanners. The brain tissue segmentation method was applied for both 1.5 T and 3.0 T and volumes of WM, GM, CSF and brain parenchymal fraction (BPF) were calculated on both field strengths. Repeatability was calculated for each scanner and a General Linear Model was used to examine the effect of field strength. Voxel-wise t-tests were also performed to evaluate regional differences. RESULTS: Statistically significant differences were found between 1.5 T and 3.0 T for WM, GM, CSF and BPF (p<0.001). Analyses of main effects showed that WM was underestimated, while GM and CSF were overestimated on 1.5 T compared to 3.0 T. The mean differences between 1.5 T and 3.0 T were -66 mL WM, 40 mL GM, 29 mL CSF and -1.99% BPF. Voxel-wise t-tests revealed regional differences of WM and GM in deep brain structures, cerebellum and brain stem. CONCLUSIONS: Most of the brain was identically classified at the two field strengths, although some regional differences were observed

Основы самостоятельной профессионально-прикладной физической подготовки студентов медицинских вузов

ВГМУЛЕЧЕБНАЯ ФИЗКУЛЬТУРАФИЗИЧЕСКАЯ КУЛЬТУРА ЛЕЧЕБНАЯФИЗИЧЕСКАЯ ПОДГОТОВКАРассматриваются вопросы для самостоятельного изучения основ профессионально-прикладной физической подготовки будущих работников в сфере медицинского обслуживания населения

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97964 Brain Characterization Using Normalized Quantitative Magnetic Resonance Imaging

Objectives: To present a method for generating reference maps of typical brain characteristics of groups of subjects using a novel combination of rapid quantitative Magnetic Resonance Imaging (qMRI) and brain normalization. The reference maps can be used to detect significant tissue differences in patients, both locally and globally. Materials and Methods: A rapid qMRI method was used to obtain the longitudinal relaxation rate (R1), the transverse relaxation rate (R 2) and the proton density (PD). These three tissue properties were measured in the brains of 32 healthy subjects and in one patient diagnosed with Multiple Sclerosis (MS). The maps were normalized to a standard brain template using a linear affine registration. The differences of the mean value ofR1, R2 and PD of 31 healthy subjects in comparison to the oldest healthy subject and in comparison to an MS patient were calculated. Larger anatomical structures were characterized using a standard atlas. The vector sum of the normalized differences was used to show significant tissue differences

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97960 Application of Quantitative MRI for Brain Tissue Segmentation at 1.5 T and 3.0 T Field Strengths

Background: Brain tissue segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) are important in neuroradiological applications. Quantitative Mri (qMRI) allows segmentation based on physical tissue properties, and the dependencies on MR scanner settings are removed. Brain tissue groups into clusters in the three dimensional space formed by the qMRI parameters R 1, R 2 and PD, and partial volume voxels are intermediate in this space. The qMRI parameters, however, depend on the main magnetic field strength. Therefore, longitudinal studies can be seriously limited by system upgrades. The aim of this work was to apply one recently described brain tissue segmentation method, based on qMRI, at both 1.5 T and 3.0 T field strengths, and to investigate similarities and differences. Methods: In vivo qMRI measurements were performed on 10 healthy subjects using both 1.5 T and 3.0 T MR scanners. The brain tissue segmentation method was applied for both 1.5 T and 3.0 T and volumes of WM, GM, CS

The mean value and standard deviation of the R1, R2 and PD values in various regions of interest, defined by using the PickAtlas.

<p>Added are the linear regression slopes with subject age. Significant slopes (p<0.05) are displayed in bold face.</p

Example of the normalized qMRI reference maps in a slice through the brain.

<p>The figure shows the reference maps obtained from images pooled across a group of 31 healthy subjects with <b>A</b>: R₁ relaxation rate on a scale 0–3 s⁻¹, <b>B</b>: R₂ relaxation rate on a scale 0–15 s⁻¹ and <b>C</b>: proton density on a scale 50–100%, where 100% corresponds to pure water at 37°C.</p

Schematic overview of the method.

<p>Magnetic Resonance quantification maps of R₁ and R₂ relaxation rates and proton density (PD) are used to synthesize a T2-weighted image. This image is normalized against a standard template T2-weighted image using affine registration. The same transformation is used to normalize the R₁, R₂ and PD maps. The individual quantitative maps from a group of subjects are averaged to obtain reference maps of typical cerebral tissue parameters. Such reference maps can either be compared to an individual brain or with another group.</p

The coefficient of variation (CoV) of the reference maps.

<p>The figure shows CoV in the same slice as visualized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070864#pone-0070864-g002" target="_blank">Fig. 2</a>, with <b>A:</b> CoV map of R₁, <b>B:</b> CoV map of R₂ and <b>C:</b> CoV map of PD. The same scaling of [0–0.5] was used in all CoV maps.</p

Significant deviation of qMRI tissue properties in an elderly subject and an MS patient.

<p>Shown are a FLAIR (<b>A</b>) and T2-weighted image (<b>B</b>) of two axial slices of the head of an elderly subject (female, 72 years old, top two rows) and an MS patient (female, 40 years old, bottom two rows). The color overlay in <b>C</b> corresponds to the normalized difference ΔR₁/σ(R₁) between the subject and the group of healthy controls on the same slices. Only values higher than a threshold of 2.04are shown. Synthetic T2-weighted images are calculated using the R₁, R₂ and PD maps and used as background images. Similar for ΔR₂/σ(R₂) in <b>D</b> and ΔPD/σ(PD) in <b>E</b>. In <b>F</b> the magnitude of the normalized vector sum of ΔR₁/σ(R₁), ΔR₂/σ(R₂) and ΔPD/σ(PD) is shown where voxels that exceed a threshold of 5 are indicated in yellow.</p

Brain tissue segmentation, of one slice in one healthy subject, at both 1.5 T (top panel) and 3.0 T (lower panel).

<p>From left to right: T2-weighted conventional image, white matter (blue), grey matter (green) and CSF (purple). The red lines are the brain intracranial mask calculated automatically by the SyMRI software.</p