Publication date: Apr 11, 2019
The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed to detect the stages of Parkinson’s disease (PD). In this retrospective study, a total of 202 Tc-TRODAT-1 SPECT imaging were collected. All of the PD patient cases were separated into mild (HYS Stage 1 to Stage 3) and severe (HYS Stage 4 and Stage 5) PD, according to the Hoehn and Yahr Scale (HYS) standard. A three-dimensional method was used to estimate six features of activity distribution and striatal activity volume in the images. These features were skewness, kurtosis, Cyhelsky’s skewness coefficient, Pearson’s median skewness, dopamine transporter activity volume, and dopamine transporter activity maximum. Finally, the data were modeled using logistic regression (LR) and support vector machine (SVM) for PD classification. The results showed that SVM classifier method produced a higher accuracy than LR. The sensitivity, specificity, PPV, NPV, accuracy, and AUC with SVM method were 0.82, 1.00, 0.84, 0.67, 0.83, and 0.85, respectively. Additionally, the Kappa value was shown to reach 0.68. This claimed that the SVM-based model could provide further reference for PD stage classification in medical diagnosis. In the future, more healthy cases will be expected to clarify the false positive rate in this classification model.
Hsu, S.Y., Lin, H.C., Chen, T.B., Du, W.C., Hsu, Y.H., Wu, Y.C., Tu, P.W., Huang, Y.H., and Chen, H.Y. Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging. 20455. 2019 Sensors (Basel) (19):7.
- Radiotracers for imaging of Parkinson’s disease.
- Correlation of 99mTc-TRODAT-1 SPECT Imaging Findings and Clinical Staging of Parkinson Disease.
- Dopamine transporter imaging for the diagnosis of multiple system atrophy cerebellar type.
- Revision of Diagnosis in Early Parkinsonism with Abnormal Dopamine Transporter Imaging.