Mohit Gupta1, Kevin S King1, Rajiv Srinivasa1, Myron F Weiner2, Keith Hulsey1, Colby R Ayers3, Anthony Whittemore1, Roderick W McColl1, Heidi C Rossetti2, Ronald M Peshock4. 1. Department of Radiology, The University of Texas Southwestern Medical Center, Dallas. 2. Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas. 3. Donald W. Reynolds Cardiovascular Clinical Research Center, The University of Texas Southwestern Medical Center, Dallas. 4. Department of Radiology, The University of Texas Southwestern Medical Center, Dallas3Donald W. Reynolds Cardiovascular Clinical Research Center, The University of Texas Southwestern Medical Center, Dallas4Department of Internal Medicine, The University of.
Abstract
IMPORTANCE: Understanding the relationships between age-related changes in brain structure and cognitive function has been limited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnically homogeneous cohorts with biased selection based on risk factors. These limitations have prevented the generalizability of results from brain morphology studies. OBJECTIVE: To determine the association of 3.0-T structural brain magnetic resonance (MR) imaging measurements with cognitive function in the multiracial/multiethnic, population-based Dallas Heart Study. DESIGN, SETTING, AND PARTICIPANTS: Whole-brain, 2-dimensional, fluid-attenuated inversion recovery and 3-dimensional, magnetization-prepared, rapid acquisition with gradient echo MR imaging at 3.0 T was performed in 1645 Dallas Heart Study participants (mean [SD] age, 49.9 [10.5] years; age range, 19-85 years) who received both brain MR imaging and cognitive screening with the Montreal Cognitive Assessment between September 18, 2007, and December 28, 2009. Measurements were obtained for white matter hyperintensity volume, total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume. Linear regression and a best predictive model were developed to determine the association of MR imaging biomarkers with the Montreal Cognitive Assessment total score and domain-specific questions. MAIN OUTCOMES AND MEASURES: High-resolution anatomical MR imaging was used to quantify brain volumes. Scores on the screening Montreal Cognitive Assessment were used for cognitive assessment in participants. RESULTS: After adjustment for demographic variables, total brain volume (P < .0001, standardized estimate [SE] = .1069), gray matter volume (P < .0001, SE = .1156), white matter volume (P = .008, SE = .0687), cerebrospinal fluid volume (P = .012, SE = -.0667), and hippocampal volume (P < .0001) were significantly associated with cognitive performance. A best predictive model identified gray matter volume (P < .001, SE = .0021), cerebrospinal fluid volume (P = .01, SE = .0024), and hippocampal volume (P = .004, SE = .1017) as 3 brain MR imaging biomarkers significantly associated with the Montreal Cognitive Assessment total score. Questions specific to the visuospatial domain were associated with the most brain MR imaging biomarkers (total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume), while questions specific to the orientation domain were associated with the least brain MR imaging biomarkers (only hippocampal volume). CONCLUSIONS AND RELEVANCE: Brain MR imaging volumes, including total brain volume, gray matter volume, cerebrospinal fluid volume, and hippocampal volume, were independently associated with cognitive function and may be important early biomarkers of risk for cognitive insult in a young multiracial/multiethnic population. A best predictive model indicated that a combination of multiple neuroimaging biomarkers may be more effective than a single brain MR imaging volume measurement.
IMPORTANCE: Understanding the relationships between age-related changes in brain structure and cognitive function has been limited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnically homogeneous cohorts with biased selection based on risk factors. These limitations have prevented the generalizability of results from brain morphology studies. OBJECTIVE: To determine the association of 3.0-T structural brain magnetic resonance (MR) imaging measurements with cognitive function in the multiracial/multiethnic, population-based Dallas Heart Study. DESIGN, SETTING, AND PARTICIPANTS: Whole-brain, 2-dimensional, fluid-attenuated inversion recovery and 3-dimensional, magnetization-prepared, rapid acquisition with gradient echo MR imaging at 3.0 T was performed in 1645 Dallas Heart Study participants (mean [SD] age, 49.9 [10.5] years; age range, 19-85 years) who received both brain MR imaging and cognitive screening with the Montreal Cognitive Assessment between September 18, 2007, and December 28, 2009. Measurements were obtained for white matter hyperintensity volume, total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume. Linear regression and a best predictive model were developed to determine the association of MR imaging biomarkers with the Montreal Cognitive Assessment total score and domain-specific questions. MAIN OUTCOMES AND MEASURES: High-resolution anatomical MR imaging was used to quantify brain volumes. Scores on the screening Montreal Cognitive Assessment were used for cognitive assessment in participants. RESULTS: After adjustment for demographic variables, total brain volume (P < .0001, standardized estimate [SE] = .1069), gray matter volume (P < .0001, SE = .1156), white matter volume (P = .008, SE = .0687), cerebrospinal fluid volume (P = .012, SE = -.0667), and hippocampal volume (P < .0001) were significantly associated with cognitive performance. A best predictive model identified gray matter volume (P < .001, SE = .0021), cerebrospinal fluid volume (P = .01, SE = .0024), and hippocampal volume (P = .004, SE = .1017) as 3 brain MR imaging biomarkers significantly associated with the Montreal Cognitive Assessment total score. Questions specific to the visuospatial domain were associated with the most brain MR imaging biomarkers (total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume), while questions specific to the orientation domain were associated with the least brain MR imaging biomarkers (only hippocampal volume). CONCLUSIONS AND RELEVANCE: Brain MR imaging volumes, including total brain volume, gray matter volume, cerebrospinal fluid volume, and hippocampal volume, were independently associated with cognitive function and may be important early biomarkers of risk for cognitive insult in a young multiracial/multiethnic population. A best predictive model indicated that a combination of multiple neuroimaging biomarkers may be more effective than a single brain MR imaging volume measurement.
Authors: Anna C van Loenhoud; Alle Meije Wink; Colin Groot; Sander C J Verfaillie; Jos Twisk; Frederik Barkhof; Bart van Berckel; Philip Scheltens; Wiesje M van der Flier; Rik Ossenkoppele Journal: Hum Brain Mapp Date: 2017-06-20 Impact factor: 5.038
Authors: Rajiv N Srinivasa; Heidi C Rossetti; Mohit K Gupta; Roger N Rosenberg; Myron F Weiner; Ronald M Peshock; Roderick W McColl; Linda S Hynan; Richard T Lucarelli; Kevin S King Journal: Radiology Date: 2015-07-28 Impact factor: 11.105
Authors: Scott M Carlson; Julie Kim; David A Khan; Kevin King; Richard T Lucarelli; Roderick McColl; Ronald Peshock; E Sherwood Brown Journal: J Asthma Date: 2016-05-17 Impact factor: 2.515
Authors: Megan K Lowther; Jarrod P Tunnell; Jayme M Palka; Darlene R King; Damilola C Salako; Dimitri G Macris; Jay B Italiya; Justin L Grodin; Carol S North; E Sherwood Brown Journal: J Neuroimmunol Date: 2020-09-08 Impact factor: 3.478