title: Spatial patterns of structural brain changes in type 2 diabetic patients and their longitudinal progression with intensive control of blood glucose.
abstract: OBJECTIVE
  Understanding the effect of diabetes as well as of alternative treatment strategies on cerebral structure is critical for the development of targeted interventions against accelerated neurodegeneration in type 2 diabetes. We investigated whether diabetes characteristics were associated with spatially specific patterns of brain changes and whether those patterns were affected by intensive versus standard glycemic treatment.
  
  
  METHODS
  Using baseline MRIs of 488 participants with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes-Memory in Diabetes (ACCORD-MIND) study, we applied a new voxel-based analysis methodology to identify spatially specific patterns of gray matter and white matter volume loss related to diabetes duration and HbA1c. The longitudinal analysis used 40-month follow-up data to evaluate differences in progression of volume loss between intensive and standard glycemic treatment arms.
  
  
  RESULTS
  Participants with longer diabetes duration had significantly lower gray matter volumes, primarily in certain regions in the frontal and temporal lobes. The longitudinal analysis of treatment effects revealed a heterogeneous pattern of decelerated loss of gray matter volume associated with intensive glycemic treatment. Intensive treatment decelerated volume loss, particularly in regions adjacent to those cross-sectionally associated with diabetes duration. No significant relationship between low versus high baseline HbA1c levels and brain changes was found. Finally, regions in which cognitive change was associated with longitudinal volume loss had only small overlap with regions related to diabetes duration and to treatment effects.
  
  
  CONCLUSIONS
  Applying advanced quantitative image pattern analysis methods on longitudinal MRI data of a large sample of patients with type 2 diabetes, we demonstrate that there are spatially specific patterns of brain changes that vary by diabetes characteristics and that the progression of gray matter volume loss is slowed by intensive glycemic treatment, particularly in regions adjacent to areas affected by diabetes.
authors.affiliation: Center for Biomedical Image Computing and Analytics (CBICA) and Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA guray.erus@uphs.upenn.edu christos.davatzikos@uphs.upenn.edu.
authors.forename: Guray
authors.initials: G
authors.lastname: Erus
authors.affiliation: Center for Biomedical Image Computing and Analytics (CBICA) and Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA.
authors.forename: Harsha
authors.initials: H
authors.lastname: Battapady
authors.affiliation: Center for Biomedical Image Computing and Analytics (CBICA) and Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA.
authors.forename: Tianhao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.
authors.forename: James
authors.initials: J
authors.lastname: Lovato
authors.affiliation: Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.
authors.forename: Michael E
authors.initials: ME
authors.lastname: Miller
authors.affiliation: Roena B. Kulynych Center for Memory and Cognition Research, Department of Internal Medicine, Wake Forest Baptist Medical Center, Winston-Salem, NC.
authors.forename: Jeff D
authors.initials: JD
authors.lastname: Williamson
authors.affiliation: Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD.
authors.forename: Lenore J
authors.initials: LJ
authors.lastname: Launer
authors.affiliation: Center for Biomedical Image Computing and Analytics (CBICA) and Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA.
authors.forename: R Nick
authors.initials: RN
authors.lastname: Bryan
authors.affiliation: Center for Biomedical Image Computing and Analytics (CBICA) and Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA guray.erus@uphs.upenn.edu christos.davatzikos@uphs.upenn.edu.
authors.forename: Christos
authors.initials: C
authors.lastname: Davatzikos
mesh_terms: D000368:Aged; D001786:Blood Glucose / Q000378:metabolism*; D015992:Body Mass Index; D001921:Brain / Q000473:pathology*; D002318:Cardiovascular Diseases / Q000503:physiopathology; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D059906:Neuroimaging; D012307:Risk Factors; D013997:Time Factors
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin