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Multi-parametric representation of voxel-based quantitative magnetic resonance imaging.

Engström M, Warntjes JB, Tisell A, Landtblom AM, Lundberg P - PLoS ONE (2014)

Bottom Line: The resulting parameter images were normalized to a standard template.The results were visualized by conventional geometric representations and also by multi-parametric representations.In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes.

View Article: PubMed Central - PubMed

Affiliation: Division of Radiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.

ABSTRACT
The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R(1) and R(2), and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R(1) and R(2), and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.

No MeSH data available.


Related in: MedlinePlus

Effect of regions of interest (ROI) size on tissue parameters.The figure shows R–R plots in ROIs for the Multiple Sclerosis (MS) and the reference group, respectively. A) Caudate nucleus; B) Thalamus; C) Total white matter. The color bar shows within-ROI distance from the ROI surface. The circles show mean R and R values in 0, 2, 4, 6, and 8 mm reduced ROIs. Black circles represent 0 mm reduction and white circles represent 8 mm reduction.
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pone-0111688-g006: Effect of regions of interest (ROI) size on tissue parameters.The figure shows R–R plots in ROIs for the Multiple Sclerosis (MS) and the reference group, respectively. A) Caudate nucleus; B) Thalamus; C) Total white matter. The color bar shows within-ROI distance from the ROI surface. The circles show mean R and R values in 0, 2, 4, 6, and 8 mm reduced ROIs. Black circles represent 0 mm reduction and white circles represent 8 mm reduction.

Mentions: In Figure 6 the trends regarding changes in –R values due to ROI reduction are visualized. The mean –R values in each ROI changed towards the –R values in the voxels most distant from the ROI surface upon ROI reduction. This feature is clearly seen for the thalamus (Figure 6B) and WM (Figure 6C).


Multi-parametric representation of voxel-based quantitative magnetic resonance imaging.

Engström M, Warntjes JB, Tisell A, Landtblom AM, Lundberg P - PLoS ONE (2014)

Effect of regions of interest (ROI) size on tissue parameters.The figure shows R–R plots in ROIs for the Multiple Sclerosis (MS) and the reference group, respectively. A) Caudate nucleus; B) Thalamus; C) Total white matter. The color bar shows within-ROI distance from the ROI surface. The circles show mean R and R values in 0, 2, 4, 6, and 8 mm reduced ROIs. Black circles represent 0 mm reduction and white circles represent 8 mm reduction.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230947&req=5

pone-0111688-g006: Effect of regions of interest (ROI) size on tissue parameters.The figure shows R–R plots in ROIs for the Multiple Sclerosis (MS) and the reference group, respectively. A) Caudate nucleus; B) Thalamus; C) Total white matter. The color bar shows within-ROI distance from the ROI surface. The circles show mean R and R values in 0, 2, 4, 6, and 8 mm reduced ROIs. Black circles represent 0 mm reduction and white circles represent 8 mm reduction.
Mentions: In Figure 6 the trends regarding changes in –R values due to ROI reduction are visualized. The mean –R values in each ROI changed towards the –R values in the voxels most distant from the ROI surface upon ROI reduction. This feature is clearly seen for the thalamus (Figure 6B) and WM (Figure 6C).

Bottom Line: The resulting parameter images were normalized to a standard template.The results were visualized by conventional geometric representations and also by multi-parametric representations.In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes.

View Article: PubMed Central - PubMed

Affiliation: Division of Radiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.

ABSTRACT
The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R(1) and R(2), and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R(1) and R(2), and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.

No MeSH data available.


Related in: MedlinePlus