Cardiovascular Risk Factors Predict the Spatial Distribution of White Matter Hyperintensity
| dc.contributor.advisor | McColl, Roderick W. | en |
| dc.contributor.committeeMember | Whittemore, Anthony W. | en |
| dc.contributor.committeeMember | Hulsey, Keith M. | en |
| dc.creator | Banerjee, Soham | en |
| dc.creator.orcid | 0000-0003-3763-9898 | |
| dc.date.accessioned | 2015-06-01T15:41:41Z | |
| dc.date.available | 2015-06-01T15:41:41Z | |
| dc.date.created | 2015-05 | |
| dc.date.issued | 2015-03-24 | |
| dc.date.submitted | May 2015 | |
| dc.date.updated | 2015-06-01T15:40:23Z | |
| dc.description.abstract | OBJECTIVES: To identify the different spatial distribution of white matter hyperintensity (WMH) associated with specific risk factors and use this distribution to estimate the extent of risk factor associated WMH in an individual. MATERIALS AND METHODS: MRI brain images were obtained from 2066 healthy adult participants (858 males, 1208 females; mean age: 50) from a population based sample. An automated algorithm generated each participant’s WMH distribution, registered onto the MNI-152 standard template. For univariate analysis, each risk factor group was compared to the non-risk factor group. Voxels in which WMH frequency was significantly higher (p<0.05) in the risk factor group were mapped. Multivariate analysis consisted of subgroup analysis to minimize confounding of a risk factor on the others. RESULTS: 431891 MNI-space voxels comprised WMH distribution of the entire population. For univariate analysis, 23697 voxels (5.5%) of these voxels were exclusively associated with hypertension and were prevalent in the anterior frontal lobe. Similarly, 24637 voxels (5.7%) were exclusively associated with diabetes and were prevalent at the callososeptal interface. 7315 voxels (1.7%) were only associated with hypercholesterolemia and did not form a discrete spatial distribution. 282115 voxels (65.3%) were not associated with any of the specified risk factors. Multivariate results corroborated the univariate findings. CONCLUSIONS: Each risk factor was associated with a different spatial distribution of WMH. Hypertension was associated with WMH in the anterior frontal lobe and diabetes was associated with WMH in the callososeptal interface. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.oclc | 910559015 | |
| dc.identifier.uri | https://hdl.handle.net/2152.5/1570 | |
| dc.language.iso | en | en |
| dc.subject | Cardiovascular Diseases | en |
| dc.subject | Computational Biology | en |
| dc.subject | Multivariate Analysis | en |
| dc.subject | White Matter | en |
| dc.title | Cardiovascular Risk Factors Predict the Spatial Distribution of White Matter Hyperintensity | en |
| dc.type | Thesis | en |
| dc.type.material | Text | en |
| thesis.degree.department | UT Southwestern Medical School | en |
| thesis.degree.discipline | Research | en |
| thesis.degree.grantor | UT Southwestern Medical Center | en |
| thesis.degree.level | Doctoral | en |
| thesis.degree.name | M.D. with Distinction | en |