Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR. (21st July 2014)

• Record Type: Journal Article
• Authors: Zhong, Yi; Utriainen, David; Wang, Ying; Kang, Yan; Haacke, E. Mark
• Other Names: Agaian Sos Academic Editor.
• Is Part Of: International journal of biomedical imaging. Volume 2014(2014)
• Publication Date: 2014-07-21
• Subjects: Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Imagerie pour le diagnostic; Imagerie médicale; Diagnostic imaging; Imaging systems in medicine; Diagnostic Imaging -- Periodicals; Electronic journals; Periodicals; 616.0754
• DOI: 10.1155/2014/239123
• Languages: English
• ISSNs: 1687-4188

Abstract

Abstract : White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR) MR images provided good contrast between the lesions and other tissue; however the signal intensity of gray matter tissue was close to the lesions in FLAIR images that may cause more false positives in the segment result. We developed and evaluated a tool for automated WMH detection only using high resolution 3D T2 fluid attenuated inversion recovery (FLAIR) MR images. We use a high spatial frequency suppression method to reduce the gray matter area signal intensity. We evaluate our method in 26 MS patients and 26 age matched health controls. The data from the automated algorithm showed good agreement with that from the manual segmentation. The linear correlation between these two approaches in comparing WMH volumes was found to beY = 1.04 X + 1.74 ( R 2 = 0.96 ) . The automated algorithm estimates the number, volume, and category of WMH.