Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.
Audrey KatakoPaul SheltonAndrew L GoertzenDaniel LevinBohdan BybelMaram AljuaidHyun Jin YoonDo Young KangSeok Min KimChong Sik LeeJi Hyun KoPublished in: Scientific reports (2018)
Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). General linear model, scaled subprofile modeling and support vector machines were examined. Among the tested classification methods, support vector machine with Iterative Single Data Algorithm produced the best performance, i.e., sensitivity (0.84) × specificity (0.95), by 10-fold cross-validation. We have applied the same classification algorithm to four different datasets from ADNI, Health Science Centre (Winnipeg, Canada), Dong-A University Hospital (Busan, S. Korea) and Asan Medical Centre (Seoul, S. Korea). Our data analyses confirmed that the support vector machine with Iterative Single Data Algorithm showed the best performance in prediction of future development of AD from the prodromal stage (mild cognitive impairment), and that it was also sensitive to other types of dementia such as Parkinson's Disease Dementia and Dementia with Lewy Bodies, and that perfusion imaging using single photon emission computed tomography may achieve a similar accuracy to that of FDG-PET.
Keyphrases
- positron emission tomography
- mild cognitive impairment
- machine learning
- computed tomography
- deep learning
- cognitive decline
- pet ct
- big data
- pet imaging
- artificial intelligence
- cognitive impairment
- image quality
- public health
- electronic health record
- healthcare
- contrast enhanced
- parkinson disease
- dual energy
- magnetic resonance imaging
- risk assessment
- emergency department
- high resolution
- high throughput
- quality improvement
- current status
- photodynamic therapy
- mental health
- data analysis
- rna seq