CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.
Meera SrikrishnaNicholas J AshtonAlexis MoscosoJoana B PereiraRolf A HeckemannDanielle van WestenGiovanni VolpeJoel SimrénAnna ZettergrenSilke KernLars-Olof WahlundBibek GyanwaliSaima HilalJoyce Chong RuifenHenrik ZetterbergKaj BlennowEric WestmanChristopher ChenIngmar SkoogMichael SchöllPublished in: Alzheimer's & dementia : the journal of the Alzheimer's Association (2023)
Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.