Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes.
Jun Pyo KimJeonghun KimYeshin KimSeung Hwan MoonYu Hyun ParkSole YooHyemin JangHee Jin KimDuk L NaSoo Hyun ChoJoon-Kyung SeongPublished in: European journal of nuclear medicine and molecular imaging (2019)
Using a machine learning algorithm, we achieved high accuracy for in vivo amyloid PET staging. The in vivo amyloid stage was associated with cognitive function and cerebral atrophy mostly through the mediation effect of cortical amyloid.