Detection of substantia nigra echogenicities in 3D transcranial ultrasound for early diagnosis of Parkinson disease

Abstract

Parkinson’s disease (PD) is a neurodegenerative movement disorder caused by decay of dopaminergic cells in the substantia nigra (SN), which are basal ganglia residing within the midbrain area. In the past two decades, transcranial B-mode sonography (TCUS) has emerged as a viable tool in differential diagnosis of PD and recently has been shown to have promising potential as a screening technique for early detection of PD, even before onset of motor symptoms. In TCUS imaging, the degeneration of SN cells becomes visible as bright and hyper-echogenic speckle patches (SNE) in the midbrain. Recent research proposes the usage of 3D ultrasound imaging in order to make the application of the TCUS technique easier and more objective. In this work, for the first time, we propose an automatic 3D SNE detection approach based on random forests, with a novel formulation of SNE probability that relies on visual context and anatomical priors. On a 3D-TCUS dataset of 11 PD patients and 11 healthy controls, we demonstrate that our SNE detection approach yields promising results with a sensitivity and specificity of around 83%.