The relative brain signal variability increases in the behavioral variant of frontotemporal dementia and Alzheimer's disease but not in schizophrenia.
Timo TuovinenJani HäkliRiikka RyttyJohanna KrügerVesa KorhonenMatti JärveläHeta HelakariJanne KananenJuha NikkinenJuha VeijolaAnne M RemesVesa Kivinieminull nullPublished in: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism (2024)
Overlapping symptoms between Alzheimer's disease (AD), behavioral variant of frontotemporal dementia (bvFTD), and schizophrenia (SZ) can lead to misdiagnosis and delays in appropriate treatment, especially in cases of early-onset dementia. To determine the potential of brain signal variability as a diagnostic tool, we assessed the coefficient of variation of the BOLD signal (CV BOLD ) in 234 participants spanning bvFTD (n = 53), AD (n = 17), SZ (n = 23), and controls (n = 141). All underwent functional and structural MRI scans. Data unveiled a notable increase in CV BOLD in bvFTD patients across both datasets (local and international, p < 0.05), revealing an association with clinical scores (CDR and MMSE, r = 0.46 and r = -0.48, p < 0.0001). While SZ and control group demonstrated no significant differences, a comparative analysis between AD and bvFTD patients spotlighted elevated CV BOLD in the frontopolar cortices for the latter (p < 0.05). Furthermore, CV BOLD not only presented excellent diagnostic accuracy for bvFTD (AUC 0.78-0.95) but also showcased longitudinal repeatability. During a one-year follow-up, the CV BOLD levels increased by an average of 35% in the bvFTD group, compared to a 2% increase in the control group (p < 0.05). Our findings suggest that CV BOLD holds promise as a biomarker for bvFTD, offering potential for monitoring disease progression and differentiating bvFTD from AD and SZ.
Keyphrases
- resting state
- functional connectivity
- early onset
- end stage renal disease
- newly diagnosed
- ejection fraction
- white matter
- late onset
- peritoneal dialysis
- big data
- contrast enhanced
- cognitive decline
- machine learning
- electronic health record
- mild cognitive impairment
- artificial intelligence
- cerebral ischemia
- climate change
- multiple sclerosis
- brain injury
- deep learning
- replacement therapy
- sleep quality