Computer-Aided Diagnosis of Parkinson's Disease, Based on SPECT Scans of the Dopamine Transporter

Abstract

Computer-aided diagnosis (CAD) tools have been, more and more frequently, proposed as a complement to the visual evaluation of dopamine transporter (DaT) single-photon emission computed tomography (SPECT) scans. Classification accuracies up to 98% have been reported in the differentiation between healthy control (HC) subjects and patients with Parkinson's disease (PD) based on DaT SPECT. CAD systems have also been used to differentiate between different types of Parkinsonism, but the accuracies are not as high as for the classification of PD patients versus HC subjects. When compared with cutoff-based classification techniques or visual classification, the CAD originated higher accuracy. The works reported in the literature on CAD systems of DaT SPECT have some limitations, with the lack of postmortem diagnosis the most important of them. The lack of consistency in the definition of the groups of patients and overlap of datasets used are also significant limitations. Despite all limitations and inconsistencies found in the published works, there is evidence that CAD based on DaT SPECT can effectively help in the clinics and is surely a better solution than the cutoff-based techniques only. Therefore, we believe CAD should be used in clinics as a complement to the visual and quantitative evaluation.