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Yu-quan Shao

Publications and source records attributed to Yu-quan Shao.

2 recordsLinked to original sources

Investigating the role of 99mTc-TRODAT-1 SPECT imaging in idiopathic Parkinson's disease.

OBJECTIVE: To investigate the role of 99mTc-TRODAT-1 SPECT in diagnosis and assessing severity of idiopathic Parkinson's disease (PD). METHODS: Thirty-eight patients with primary, tentative diagnosis of PD and eighteen age-matched normal controls were studied with 99mTc-TRODAT-1 SPECT imaging. The regions of interests (ROIs) were drawn manually on cerebellum (CB), occipital cortex (OC) and three transverse plane slice-views of striatums, the semiquantitative BG (background)/[(OC+CB)/2] were then calculated. RESULTS: A lower uptake of 99mTc-TRODAT-1 in striatums were displayed in thirty-six out of thirty-eight PD patients by visual inspection, compared to controls. In twenty-four PD cases with (Hoehn and Yahr scale) HYS stage I, a greater loss of DAT uptake was found in striatum and its subregions contralateral striatum to the affected limbs than in the same regions of the controls, although the striatal uptake was bilaterally reduced. Using Spearman correlation analysis showed that the reduction of the uptake ratios significantly correlated with the UPDRS in striatum and all its subregions in the PD group (P<0.05), a similar change was also found in the putamen by using the rating scale of Hoehn and Yahr (P<0.05). However, analysis of variance (ANOVA) did not show any relationship between the decreasing uptake of 99mTc-TRODAT-1 and increasing severity of PD patients, although the specific uptake of 99mTc-TRODAT-1 was continuously decreased in the striatum by visual inspection with the progress of PD from HYS stage I to III. CONCLUSION: 99mTc-TRODAT-1 SPECT imaging may serve as a useful method for improving the correct diagnosis of PD. In assessing the role of 99mTc-TRODAT-1 SPECT in disease severity of PD, UPDRS can offer a comprehensive index, although the Hoehn and Yahr assessment may be available in part.

Adult↗

[An algorithm study on telecardiogram diagnosis based on multivariate autoregressive model and two-lead ECG signals].

OBJECTIVE: In view of the time delay caused by reconstruction of signals at remote sites, a direct classification method with high accuracy suitable for telediagnosis of electrocardiogram (ECG) signals is studied. METHOD: The data for analysis and classification was obtained from MIT-BIH database, including 300 samples each of normal sinus rhythm (NSR), atria premature contraction (APC), premature ventricular contraction (PVC), ventricular tachycardia (VT), ventricular fibrillation (VF) and superventricular tachycardia (SVT). An multivariate autoregressive (MAR) model based technique that could combine the signals of two ECG leads was presented to classify the ECGs directly, including MAR modeling performed on ECGs, and quadratic discrimination function (QDF) based classification by using MAR coefficients and K-L MAR coefficients. RESULT: Besides quick and convenient diagnosis, the accuracy of the proposed classification algorithm was as high as 98.3%-100%. CONCLUSION: The MAR modeling based technique is suitable for telecardiogram diagnosis. Comparing with single-lead ECGs, better classification results can be obtained through the combination of two-lead ECG signals.

Algorithms↗