OBJECTIVES: Mild cognitive impairment (MCI) is recognized as a predementia state, but its definition is inconsistent and only 20%-30% develop dementia after 2 years. Biomarkers may help identify individuals at greatest risk of progressive decline. The authors examine a novel neuroimaging technique, diffusion tensor imaging (DTI) as a potential biomarker of MCI. DESIGN: Cross-sectional prospective study. SETTING: Subjects were recruited randomly using the electoral roll from two electorates in East Sydney, Australia. PARTICIPANTS: A community-dwelling sample (N = 249) and age 70-90 years. MEASUREMENTS: Screening to exclude dementia, comprehensive neuropsychiatric assessment, cognitive test battery, structural magnetic resonance imaging and DTI to obtain measures of fractional anisotropy (FA) and mean diffusivity (MD). MCI was diagnosed by standard criteria. RESULTS: After controlling for age, sex, and years of education, the amnestic MCI (aMCI) group demonstrated microstructural pathology in the parahippocampal white matter, frontal white matter, splenium of corpus callosum, and posterior cingulate region. The nonamnestic MCI (naMCI) group demonstrated microstructural pathology in the frontal white matter, internal capsule, occipital white matter, and the posterior cingulate region. A binary logistic regression model showed that DTI of the left posterior cingulate was significant in identifying persons with aMCI to an accuracy of 85.1%. Receiver operating characteristics curve analysis yielded a sensitivity of 80% and specificity of 60.3% in distinguishing aMCI from naMCI and the normal comparison group. CONCLUSION: DTI of the posterior cingulate region discriminates MCI from cognitively normal individuals with accuracy and has the potential to be used as a biomarker of MCI, in particular aMCI.
OBJECTIVES: Mild cognitive impairment (MCI) is recognized as a predementia state, but its definition is inconsistent and only 20%-30% develop dementia after 2 years. Biomarkers may help identify individuals at greatest risk of progressive decline. The authors examine a novel neuroimaging technique, diffusion tensor imaging (DTI) as a potential biomarker of MCI. DESIGN: Cross-sectional prospective study. SETTING: Subjects were recruited randomly using the electoral roll from two electorates in East Sydney, Australia. PARTICIPANTS: A community-dwelling sample (N = 249) and age 70-90 years. MEASUREMENTS: Screening to exclude dementia, comprehensive neuropsychiatric assessment, cognitive test battery, structural magnetic resonance imaging and DTI to obtain measures of fractional anisotropy (FA) and mean diffusivity (MD). MCI was diagnosed by standard criteria. RESULTS: After controlling for age, sex, and years of education, the amnestic MCI (aMCI) group demonstrated microstructural pathology in the parahippocampal white matter, frontal white matter, splenium of corpus callosum, and posterior cingulate region. The nonamnestic MCI (naMCI) group demonstrated microstructural pathology in the frontal white matter, internal capsule, occipital white matter, and the posterior cingulate region. A binary logistic regression model showed that DTI of the left posterior cingulate was significant in identifying persons with aMCI to an accuracy of 85.1%. Receiver operating characteristics curve analysis yielded a sensitivity of 80% and specificity of 60.3% in distinguishing aMCI from naMCI and the normal comparison group. CONCLUSION: DTI of the posterior cingulate region discriminates MCI from cognitively normal individuals with accuracy and has the potential to be used as a biomarker of MCI, in particular aMCI.
Authors: Nikki H Stricker; David H Salat; Jessica M Foley; Tyler A Zink; Ida L Kellison; Craig P McFarland; Laura J Grande; Regina E McGlinchey; William P Milberg; Elizabeth C Leritz Journal: J Int Neuropsychol Soc Date: 2013-07-01 Impact factor: 2.892
Authors: Michael Ewers; Giovanni B Frisoni; Stefan J Teipel; Lea T Grinberg; Edson Amaro; Helmut Heinsen; Paul M Thompson; Harald Hampel Journal: Prog Neurobiol Date: 2011-06-22 Impact factor: 11.685
Authors: Mohammad-Reza Nazem-Zadeh; Christopher H Chapman; Theodore L Lawrence; Christina I Tsien; Yue Cao Journal: Med Phys Date: 2012-09 Impact factor: 4.071
Authors: Janne M Papma; Marius de Groot; Inge de Koning; Francesco U Mattace-Raso; Aad van der Lugt; Meike W Vernooij; Wiro J Niessen; John C van Swieten; Peter J Koudstaal; Niels D Prins; Marion Smits Journal: Hum Brain Mapp Date: 2013-09-23 Impact factor: 5.038
Authors: Christopher H Chapman; Tong Zhu; Mohamad Nazem-Zadeh; Yebin Tao; Henry A Buchtel; Christina I Tsien; Theodore S Lawrence; Yue Cao Journal: Radiother Oncol Date: 2016-07-11 Impact factor: 6.280
Authors: Christopher H Chapman; Vijaya Nagesh; Pia C Sundgren; Henry Buchtel; Thomas L Chenevert; Larry Junck; Theodore S Lawrence; Christina I Tsien; Yue Cao Journal: Int J Radiat Oncol Biol Phys Date: 2011-05-11 Impact factor: 7.038