Unsupervised clustering analysis-based characterization of spatial profiles of inaccuracy in apparent diffusion coefficient values with varying acquisition plan orientation and diffusion weighting gradient direction - a large multicenter phantom study.

This large multicenter study of 37 magnetic resonance imaging scanners aimed at characterizing, for the first time, spatial profiles of inaccuracy (namely, Δ-profiles) in apparent diffusion coefficient (ADC) values with varying acquisition plan orientation and diffusion weighting gradient direction, using a statistical approach exploiting unsupervised clustering analysis. A diffusion-weighted imaging (DWI) protocol (b-value: 0-200-400-600-800-1000 s mm) with different combinations of acquisition plan orientation (axial/sagittal/coronal) and diffusion weighting gradient direction (anterior-posterior/left-right/feet-head) was acquired on a standard water phantom. For each acquisition setup, Δ-profiles along the 3 main orthogonal directions were characterized by fitting data with a second order polynomial function ().

Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A comparison of derived brain volume measurements.

Purpose: T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a quantitative 3D anatomical image coupled with T1-map. Here we investigated the agreement between FreeSurfer-derived volume measurements obtained from MPRAGE and CS MP2RAGE acquisitions.

Methods: MPRAGE and CS MP2RAGE images of 37 subjects (14 patients with neurodegenerative disorders and 23 healthy controls) were acquired on a 3 T MR scanner and grey matter volumes were extracted using standard FreeSurfer parcellation.

On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis.

Purpose: The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation.

Methods: Water phantom acquisitions were carried out on 39 scanners.

Author Correction: Faithful animal modelling of human glioma by using primary initiating cells and its implications for radiosensitization therapy.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Dependence of apparent diffusion coefficient measurement on diffusion gradient direction and spatial position - A quality assurance intercomparison study of forty-four scanners for quantitative diffusion-weighted imaging.

Purpose: To propose an MRI quality assurance procedure that can be used for routine controls and multi-centre comparison of different MR-scanners for quantitative diffusion-weighted imaging (DWI).

Materials And Methods: 44 MR-scanners with different field strengths (1 T, 1.5 T and 3 T) were included in the study.

A straightforward multiparametric quality control protocol for proton magnetic resonance spectroscopy: Validation and comparison of various 1.5 T and 3 T clinical scanner systems.

Purpose: The aim of this study was to propose and validate across various clinical scanner systems a straightforward multiparametric quality assurance procedure for proton magnetic resonance spectroscopy (MRS).

Methods: Eighteen clinical 1.5 T and 3 T scanner systems for MRS, from 16 centres and 3 different manufacturers, were enrolled in the study.

Growing Region Segmentation Software (GRES) for quantitative magnetic resonance imaging of multiple sclerosis: intra- and inter-observer agreement variability: a comparison with manual contouring method.

Lesion area measurement in multiple sclerosis (MS) is one of the key points in evaluating the natural history and in monitoring the efficacy of treatments. This study was performed to check the intra- and inter-observer agreement variability of a locally developed Growing Region Segmentation Software (GRES), comparing them to those obtained using manual contouring (MC). From routine 1.