A fully automated method for accurate measurement of geometrical distortion in magnetic resonance imaging of a 3D-lattice phantom

Objective: Adolescence is a critical period for the maturation of neurobiological processes that underlie higher cognitive functions and social and emotional behaviour. However, there are limited studies that investigated brain volumes in healthy adolescents and young persons. The aim of this study was to compare the Grey Matter (GM), White Matter (WM) and some specific brain subcortical volumes such as hippocampus and amygdala between healthy adolescents and young groups by using VolBrain. Material and Methods: Magnetic resonance imaging brain scans were retrospectively obtained from 20 healthy adolescent and young subjects. The mean ages of the adolescent and young persons were 13±1 and 24±2, respectively. Brain parenchyma (BP), GM, WM and asymmetry features were calculated using VolBrain, and the GM and WM volumes of each subjects were compared with those of the both groups. The current study to examine whether regional gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), some brain subcortical structures volumes differed between healthy adolescent and young groups. Also, of the whole brain, hemispheres, and hippocampus, amigdala of adolescent and young subject volumes were measured with an automated method. Results: We have observed that the young group was found to have a 4 % less in volume of GM, when compared with adolescent groups. Conclusion: Our data indicate that quantitative structural Magnetic Resonance Imaging (MRI) data of the adolescent brain is important in understanding the age-related human morphological changes.

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Anatomical phenotyping in the brain and skull of a mutant mouse by magnetic resonance imaging and computed tomography

Physiological Genomics ◽

10.1152/physiolgenomics.00217.2005 ◽

2006 ◽

Vol 24 (2) ◽

pp. 154-162 ◽

Cited By ~ 80

Author(s):

Brian J. Nieman ◽

Ann M. Flenniken ◽

S. Lee Adamson ◽

R. Mark Henkelman ◽

John G. Sled

Keyword(s):

Magnetic Resonance Imaging ◽

Computed Tomography ◽

Magnetic Resonance ◽

Connexin 43 ◽

Quantitative Methods ◽

Imaging Techniques ◽

Point Mutations ◽

Nondestructive Method ◽

Resonance Imaging ◽

Automated Method

Since genetically modified mice have become more common in biomedical research as models of human disease, a need has also grown for efficient and quantitative methods to assess mouse phenotype. One powerful means of phenotyping is characterization of anatomy in mutant vs. normal populations. Anatomical phenotyping requires visualization of structures in situ, quantification of complex shape differences between mouse populations, and detection of subtle or diffuse abnormalities during high-throughput survey work. These aims can be achieved with imaging techniques adapted from clinical radiology, such as magnetic resonance imaging and computed tomography. These imaging technologies provide an excellent nondestructive method for visualization of anatomy in live individuals or specimens. The computer-based analysis of these images then allows thorough anatomical characterizations. We present an automated method for analyzing multiple-image data sets. This method uses image registration to identify corresponding anatomy between control and mutant groups. Within- and between-group shape differences are used to map regions of significantly differing anatomy. These regions are highlighted and represented quantitatively by displacements and volume changes. This methodology is demonstrated for a partially characterized mouse mutation generated by N-ethyl- N-nitrosourea mutagenesis that is a putative model of the human syndrome oculodentodigital dysplasia, caused by point mutations in the gene encoding connexin 43.

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Automated volumetry of hippocampus is useful to confirm unilateral mesial temporal sclerosis in patients with radiologically positive findings

The Neuroradiology Journal ◽

10.1177/1971400917709627 ◽

2017 ◽

Vol 30 (4) ◽

pp. 318-323 ◽

Cited By ~ 4

Author(s):

Guilherme Silva ◽

Cristina Martins ◽

Nádia Moreira da Silva ◽

Duarte Vieira ◽

Dias Costa ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Statistical Tests ◽

Brain Magnetic Resonance Imaging ◽

Magnetic Resonance Images ◽

Mesial Temporal Sclerosis ◽

Software Library ◽

Resonance Imaging ◽

Operating Characteristics ◽

Automated Method

Background and purpose We evaluated two methods to identify mesial temporal sclerosis (MTS): visual inspection by experienced epilepsy neuroradiologists based on structural magnetic resonance imaging sequences and automated hippocampal volumetry provided by a processing pipeline based on the FMRIB Software Library. Methods This retrospective study included patients from the epilepsy monitoring unit database of our institution. All patients underwent brain magnetic resonance imaging in 1.5T and 3T scanners with protocols that included thin coronal T2, T1 and fluid-attenuated inversion recovery and isometric T1 acquisitions. Two neuroradiologists with experience in epilepsy and blinded to clinical data evaluated magnetic resonance images for the diagnosis of MTS. The diagnosis of MTS based on an automated method included the calculation of a volumetric asymmetry index between the two hippocampi of each patient and a threshold value to define the presence of MTS obtained through statistical tests (receiver operating characteristics curve). Hippocampi were segmented for volumetric quantification using the FIRST tool and fslstats from the FMRIB Software Library. Results The final cohort included 19 patients with unilateral MTS (14 left side): 14 women and a mean age of 43.4 ± 10.4 years. Neuroradiologists had a sensitivity of 100% and specificity of 73.3% to detect MTS (gold standard, k = 0.755). Automated hippocampal volumetry had a sensitivity of 84.2% and specificity of 86.7% (k = 0.704). Combined, these methods had a sensitivity of 84.2% and a specificity of 100% (k = 0.825). Conclusions Automated volumetry of the hippocampus could play an important role in temporal lobe epilepsy evaluation, namely on confirmation of unilateral MTS diagnosis in patients with radiological suggestive findings.

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A semi-automated method for non-invasive internal organ weight estimation by post-mortem magnetic resonance imaging in fetuses, newborns and children

Yearbook of Diagnostic Radiology ◽

10.1016/s0098-1672(10)79166-9 ◽

2010 ◽

Vol 2010 ◽

pp. 139-140

Author(s):

A.C. Offiah

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Organ Weight ◽

Post Mortem ◽

Weight Estimation ◽

Resonance Imaging ◽

Non Invasive ◽

Automated Method

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A semi-automated method for non-invasive internal organ weight estimation by post-mortem magnetic resonance imaging in fetuses, newborns and children

European Journal of Radiology ◽

10.1016/j.ejrad.2008.07.013 ◽

2009 ◽

Vol 72 (2) ◽

pp. 321-326 ◽

Cited By ~ 33

Author(s):

Sudhin Thayyil ◽

Silvia Schievano ◽

Nicola J. Robertson ◽

Rodney Jones ◽

Lyn S. Chitty ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Organ Weight ◽

Post Mortem ◽

Weight Estimation ◽

Resonance Imaging ◽

Non Invasive ◽

Automated Method

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An Automated Method for Quality Control in MRI Systems: Methods and Considerations

Journal of Imaging ◽

10.3390/jimaging6100111 ◽

2020 ◽

Vol 6 (10) ◽

pp. 111

Author(s):

Angeliki C. Epistatou ◽

Ioannis A. Tsalafoutas ◽

Konstantinos K. Delibasis

Keyword(s):

Magnetic Resonance Imaging ◽

Quality Control ◽

Magnetic Resonance ◽

Signal To Noise Ratio ◽

Selection Criterion ◽

Test Results ◽

Resonance Imaging ◽

Phantom Image ◽

Automated Method ◽

Magnetic Resonance Imaging Mri

Objective: The purpose of this study was to develop an automated method for performing quality control (QC) tests in magnetic resonance imaging (MRI) systems, investigate the effect of different definitions of QC parameters and its sensitivity with respect to variations in regions of interest (ROI) positioning, and validate the reliability of the automated method by comparison with results from manual evaluations. Materials and Methods: Magnetic Resonance imaging MRI used for acceptance and routine QC tests from five MRI systems were selected. All QC tests were performed using the American College of Radiology (ACR) MRI accreditation phantom. The only selection criterion was that in the same QC test, images from two identical sequential sequences should be available. The study was focused on four QC parameters: percent signal ghosting (PSG), percent image uniformity (PIU), signal-to-noise ratio (SNR), and SNR uniformity (SNRU), whose values are calculated using the mean signal and the standard deviation of ROIs defined within the phantom image or in the background. The variability of manual ROIs placement was emulated by the software using random variables that follow appropriate normal distributions. Results: Twenty-one paired sequences were employed. The automated test results for PIU were in good agreement with manual results. However, the PSG values were found to vary depending on the selection of ROIs with respect to the phantom. The values of SNR and SNRU also vary significantly, depending on the combination of the two out of the four standard rectangular ROIs. Furthermore, the methodology used for SNR and SNRU calculation also had significant effect on the results. Conclusions: The automated method standardizes the position of ROIs with respect to the ACR phantom image and allows for reproducible QC results.

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