Abstract

Motivation: A kind of perfusion biomarker capable of effectively distinguishing Parkinson's disease (PD) from normal subjects and reflecting motor dysfunction and levodopa reactivity is under research. Goal(s): To construct a stable PD-related perfusion pattern based on arterial spin labelling (ASL), and to explore levodopa reactivity of motor symptoms with the pattern. Approach: Principal component analysis and the scaled sub-profile model (PCA-SSM) was used to construct and validate PD-related perfusion pattern, with correlation and predictive analysis. Results: The PD-related perfusion pattern was constructed to predict the severity of motor symptoms and assess levodopa reactivity in PD patients with axial symptom. Impact: The PD-related perfusion pattern could serve as a potential biomarker for evaluating the severity of motor symptoms and the prognosis of levodopa therapy in PD patients with axial symptom.