Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging

• Published in: Psychiatry research. Neuroimaging Vol. 290; pp. 1 - 4
• Main Authors: Besteher, Bianca, Gaser, Christian, Nenadić, Igor
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 30.08.2019
• Subjects: Adult; Aged; Ageing; Aging, Premature - diagnostic imaging; Aging, Premature - etiology; Brain - diagnostic imaging; Brain - pathology; Case-Control Studies; Depressive Disorder, Major - complications; Depressive Disorder, Major - diagnostic imaging; Depressive Disorder, Major - pathology; Female; Humans; Machine Learning; Magnetic resonance imaging (MRI); Magnetic Resonance Imaging - methods; Major depression; Male; Middle Aged; Pilot Projects; Statistics as Topic - methods; Young Adult; Magnetic resonance imaging (MRI); Major depression; Ageing; Machine learning

•Use of a novel brain structural parameter, the BrainAGE score (brain age estimation gap), based on a machine-learning approach to estimate subjects’ age based on T1 MRIs.•No evidence for accelerated brain aging in MDD patients.•Pilot cohort as a reference for further studies on brain-ageing in MDD....