4.6 Article

Personalized Computer-Aided Diagnosis for Mild Cognitive Impairment in Alzheimer's Disease Based on sMRI and 11C PiB-PET Analysis

Journal

IEEE ACCESS
Volume 8, Issue -, Pages 218982-218996

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3038723

Keywords

Support vector machines; Positron emission tomography; Magnetic resonance imaging; Task analysis; Pathology; Feature extraction; Alzheimer' s disease; Alzheimer’ s disease; personalized diagnosis; MCI; ¹ ¹ C PiB PET; sMRI

Funding

  1. Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
  2. DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
  3. National Institute on Aging
  4. National Institute of Biomedical Imaging and Bioengineering
  5. AbbVie
  6. Alzheimer's Association
  7. Alzheimer's Drug Discovery Foundation
  8. Araclon Biotech
  9. BioClinica, Inc.
  10. Biogen
  11. Bristol-Myers Squibb Company
  12. CereSpir, Inc.
  13. Cogstate
  14. Eisai Inc.
  15. Elan Pharmaceuticals, Inc.
  16. Eli Lilly and Company
  17. EuroImmun
  18. F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.
  19. Fujirebio
  20. GE Healthcare
  21. IXICO Ltd.
  22. Janssen Alzheimer Immunotherapy Research & Development, LLC.
  23. Johnson & Johnson Pharmaceutical Research & Development LLC.
  24. Lumosity
  25. Lundbeck
  26. Merck Co., Inc.
  27. Meso Scale Diagnostics, LLC.
  28. NeuroRx Research
  29. Neurotrack Technologies
  30. Novartis Pharmaceuticals Corporation
  31. Pfizer Inc.
  32. Piramal Imaging
  33. Servier
  34. Takeda Pharmaceutical Company
  35. Transition Therapeutics
  36. Canadian Institutes of Health Research

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Alzheimer's disease (AD) is a neurodegenerative condition that affects the central nervous system and represents 60% to 70% of all dementia cases. Due to an increased aging population, the number of patients diagnosed with AD is expected to exceed 131 million worldwide by 2050. The disease is characterized by various clinical symptoms and pathological features that define three main sequential decline stages, namely, early/mild, intermediate/moderate and late/severe stages. Although it is considered irreversible, early diagnosis of AD is highly desirable to help preserve cognitive function. However, early diagnosis is difficult due to different factors, including the patient-specific development of AD. The main contribution of the proposed work is to present a personalized (i.e., local/brain regional) computer-aided diagnosis (CAD) system for early diagnosis of AD from two perspectives, functional and structural to assist diagnosis. In other words, the proposed system uniquely yields local/regional diagnosis by combining C-11 PiB positron emission tomography (C-11 PiB PET), which provides functional diagnosis, with structural magnetic resonance imaging (sMRI), which provides structural diagnosis. To the best of our knowledge, this is the first work to combine sMRI and the C-11 PiB PET for local/regional early diagnosis of AD. The system processes the two modalities through a number of steps: pre-processing, brain labeling (parcellation), feature extraction, and diagnosis. A local/regional diagnosis is presented for each modality separately, followed by the final global diagnosis obtained by integrating the results from the two modalities. Evaluation of the proposed system shows average results of 97.5%, 100%, and 96.77% for accuracy, specificity, and sensitivity, respectively. With further development, it is envisioned that this system could contribute to the early diagnosis of AD in the clinical setting.

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