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Diffusion tensor magnetic resonance imaging as molecular diagnostic tool for leukoaraiosis
228
1st International Conference on Molecular Diagnostic and Biomarker Discovery/Asian Pac J Trop Dis 2014; 4(3): 223-252
Diffusion
tensor magnetic resonance imaging as molecular diagnostic tool for leukoaraiosis doi: 10.1016/S2222-1808(14)60520-X
襃 2014
by the Asian Pacific Journal of Tropical Disease. All rights reserved.
MohdTaib N. H., Wan Abdullah A. K., Shuaib I. L., Magosso E. and Mat Isa S. Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, KubangKerian, Kelantan, Malaysia Advanced Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas, Pulau Pinang, Malaysia
ABSTRACT
Introduction: Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) technique that measures mobility of water in biological tissues at molecular level. Useful quantitative parameters offered by DTI include mean diffusivity (MD) which indicates the diffusivity of water molecules in tissues, as well as fractional anisotropy (FA) which quantifies the degree of anisotropy in that particular region. DTI also allows for reconstruction of cerebral nerve fibre tracts through method called fibre tractography. Leukoaraiosis is a brain white-matter change detected as hyperintensity area on T2-weighted image of MRI. It is associated with age and various vascular risk factors, e.g. hypertension and diabetes mellitus. Its aetiology is thought to be related to ischaemia. DTI is expected to provide useful information for characterisation of leukoaraiosis. Objective: To compare MD and FA values as well as fibre tractography between healthy and leukoaraiosis areas in the brain white-matter. Methods: Twelve volunteers with leukoaraiosis (5 male, 7 female; age: 57.0 依 7.3) underwent brain scan using 1.5T MRI. Only two of them had hypertension, while none had diabetes. MD and FA values were measured for normal and leukoaraiosis areas in three different brain regions, namely the frontal, occipital, and parietal lobes. Fibre tractography was also performed. Comparison of obtained data for leukoaraiosis areas and healthy tissue in the corresponding lobe were performed. p<0.05 was considered statistically significant. Results & Discussion: Significantly higher MD and reduced FA were observed in leukoaraiosis area compared to normal tissues in all lobes. Fibre tractography exhibits an obvious discontinuity of several nerve fibre tracts at the area of leukoaraiosis. Conclusion: Relatively higher MD and reduced FA values seem to distinguish leukoaraiosis from normal tissues. Conventional MRI does not supply any quantitative value, whereas DTI provides molecular information for both healthy and leukoaraiosis areas.
Identification
of diagnostic and prognostic biomarkers to improve the management of diabetes-related ulcers
doi: 10.1016/S2222-1808(14)60521-1
襃 2014
by the Asian Pacific Journal of Tropical Disease. All rights reserved.
Sharma,Srihari; Gupta, Rajesh; Compay, Arnulf; Sampson, Dayle; Fernandez, Melissa;Upton, Zee and Shooter, Gary Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
ABSTRACT
Introduction: Diabetes-related ulcers are a common and severe complication of diabetes which is expected to increase in prevalence in line with projected global growth in rates of diabetes. Caring for these chronic wounds imposes a multi-billion dollar burden on the health care systems. These ulcers can prove lethal if untreated or not recognised and can lead to critical health complications. Methods: To investigate underlying causes of wound chronicity, proteomic analyses of swab samples collected weekly from healing and non-healing diabetic foot ulcers was performed. Protein profiling was conducted based on Surface Enhanced Laser Desorption Ionisation Time of Flight (SELDI-TOF) mass spectrometry and statistical softwares were used to short list potential biomarkers. In addition, bottom-up proteomics was performed on healing and non-healing samples by SDS-PAGE and LC-MS/MS analysis using an AB SCIEX Triple TOF® 5600 System. Trans-proteomic pipeline was used for data analyses and X! Tandem was used to search the database. Label-free quantitative proteomic analyses were performed using a computational tool called Abacus. Results: (1) Statistical analyses of healing and non healing samples analysed on SELDI-TOF revealed 5 and 7 potential biomarkers (m/z) for samples with Texas score A1 and C1 respectively. (2) Bottom-up proteomics approach from both healing and non-healing samples identified 15 unique (healing) and 16 unique (non-healing) potential biomarkers. (3) Quantitative proteomic analyses resulted in 24 and 45 up-regulated healing candidates and 67 and 43 up-regulated nonhealing candidates for Texas score A1 and C1 wounds. (4) Relative quantification of 23 proteins related to oxidative stress has been identified through Abacus and 5/23 proteins have been validated using ELISA. Conclusions: We are investigating these potential biomarkers using various biochemical, bioinformatics and statistical tools. A thorough investigation and study of the patterns may generate new protein candidates that can be used as potential prognostic and diagnostic biomarkers to improve the management of diabetic ulcers.
1st International Conference on Molecular Diagnostic and Biomarker Discovery/Asian Pac J Trop Dis 2014; 4(3): 223-252
Diffusion
tensor magnetic resonance imaging as molecular diagnostic tool for leukoaraiosis doi: 10.1016/S2222-1808(14)60520-X
襃 2014
by the Asian Pacific Journal of Tropical Disease. All rights reserved.
MohdTaib N. H., Wan Abdullah A. K., Shuaib I. L., Magosso E. and Mat Isa S. Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, KubangKerian, Kelantan, Malaysia Advanced Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas, Pulau Pinang, Malaysia
ABSTRACT
Introduction: Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) technique that measures mobility of water in biological tissues at molecular level. Useful quantitative parameters offered by DTI include mean diffusivity (MD) which indicates the diffusivity of water molecules in tissues, as well as fractional anisotropy (FA) which quantifies the degree of anisotropy in that particular region. DTI also allows for reconstruction of cerebral nerve fibre tracts through method called fibre tractography. Leukoaraiosis is a brain white-matter change detected as hyperintensity area on T2-weighted image of MRI. It is associated with age and various vascular risk factors, e.g. hypertension and diabetes mellitus. Its aetiology is thought to be related to ischaemia. DTI is expected to provide useful information for characterisation of leukoaraiosis. Objective: To compare MD and FA values as well as fibre tractography between healthy and leukoaraiosis areas in the brain white-matter. Methods: Twelve volunteers with leukoaraiosis (5 male, 7 female; age: 57.0 依 7.3) underwent brain scan using 1.5T MRI. Only two of them had hypertension, while none had diabetes. MD and FA values were measured for normal and leukoaraiosis areas in three different brain regions, namely the frontal, occipital, and parietal lobes. Fibre tractography was also performed. Comparison of obtained data for leukoaraiosis areas and healthy tissue in the corresponding lobe were performed. p<0.05 was considered statistically significant. Results & Discussion: Significantly higher MD and reduced FA were observed in leukoaraiosis area compared to normal tissues in all lobes. Fibre tractography exhibits an obvious discontinuity of several nerve fibre tracts at the area of leukoaraiosis. Conclusion: Relatively higher MD and reduced FA values seem to distinguish leukoaraiosis from normal tissues. Conventional MRI does not supply any quantitative value, whereas DTI provides molecular information for both healthy and leukoaraiosis areas.
Identification
of diagnostic and prognostic biomarkers to improve the management of diabetes-related ulcers
doi: 10.1016/S2222-1808(14)60521-1
襃 2014
by the Asian Pacific Journal of Tropical Disease. All rights reserved.
Sharma,Srihari; Gupta, Rajesh; Compay, Arnulf; Sampson, Dayle; Fernandez, Melissa;Upton, Zee and Shooter, Gary Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
ABSTRACT
Introduction: Diabetes-related ulcers are a common and severe complication of diabetes which is expected to increase in prevalence in line with projected global growth in rates of diabetes. Caring for these chronic wounds imposes a multi-billion dollar burden on the health care systems. These ulcers can prove lethal if untreated or not recognised and can lead to critical health complications. Methods: To investigate underlying causes of wound chronicity, proteomic analyses of swab samples collected weekly from healing and non-healing diabetic foot ulcers was performed. Protein profiling was conducted based on Surface Enhanced Laser Desorption Ionisation Time of Flight (SELDI-TOF) mass spectrometry and statistical softwares were used to short list potential biomarkers. In addition, bottom-up proteomics was performed on healing and non-healing samples by SDS-PAGE and LC-MS/MS analysis using an AB SCIEX Triple TOF® 5600 System. Trans-proteomic pipeline was used for data analyses and X! Tandem was used to search the database. Label-free quantitative proteomic analyses were performed using a computational tool called Abacus. Results: (1) Statistical analyses of healing and non healing samples analysed on SELDI-TOF revealed 5 and 7 potential biomarkers (m/z) for samples with Texas score A1 and C1 respectively. (2) Bottom-up proteomics approach from both healing and non-healing samples identified 15 unique (healing) and 16 unique (non-healing) potential biomarkers. (3) Quantitative proteomic analyses resulted in 24 and 45 up-regulated healing candidates and 67 and 43 up-regulated nonhealing candidates for Texas score A1 and C1 wounds. (4) Relative quantification of 23 proteins related to oxidative stress has been identified through Abacus and 5/23 proteins have been validated using ELISA. Conclusions: We are investigating these potential biomarkers using various biochemical, bioinformatics and statistical tools. A thorough investigation and study of the patterns may generate new protein candidates that can be used as potential prognostic and diagnostic biomarkers to improve the management of diabetic ulcers.