PURPOSE: Dopamine transporter (DaT) imaging is an adjunct diagnostic tool in parkinsonian disorders. Interpretation of DaT scans is based on visual reads. SBRquant is an automated method that measures the striatal binding ratio (SBR) in DaT scans, but has yet to be optimized. We aimed to (1) optimize SBRquant parameters to distinguish between patients with Parkinson disease (PD) and healthy controls using the Parkinson's Progression Markers Initiative (PPMI) database and (2) test the validity of these parameters in an outpatient cohort. METHODS: For optimization, 336 DaT scans (215 PD patients and 121 healthy controls) from the PPMI database were used. Striatal binding ratio was calculated varying the number of summed transverse slices (N) and positions of the striatal regions of interest (d). The resulting SBRs were evaluated using area under the receiver operating characteristic curve. The optimized parameters were then applied to 77 test patients (35 PD and 42 non-PD patients). Striatal binding ratios were also correlated with clinical measures in the PPMI-PD group. RESULTS: The optimal parameters discriminated the training groups in the PPMI cohort with 95.8% sensitivity and 98.3% specificity (lowest putamen SBR threshold, 1.037). The same parameters discriminated the groups in the test cohort with 97.1% sensitivity and 100% specificity (lowest putamen SBR threshold, 0.875). A significant negative correlation (r = -0.24, P = 0.0004) was found between putamen SBRs and motor severity in the PPMI-PD group. CONCLUSIONS: SBRquant discriminates DaT scans with high sensitivity and specificity. It has a high potential for use as a quantitative diagnostic aid in clinical and research settings.
PURPOSE:Dopamine transporter (DaT) imaging is an adjunct diagnostic tool in parkinsonian disorders. Interpretation of DaT scans is based on visual reads. SBRquant is an automated method that measures the striatal binding ratio (SBR) in DaT scans, but has yet to be optimized. We aimed to (1) optimize SBRquant parameters to distinguish between patients with Parkinson disease (PD) and healthy controls using the Parkinson's Progression Markers Initiative (PPMI) database and (2) test the validity of these parameters in an outpatient cohort. METHODS: For optimization, 336 DaT scans (215 PDpatients and 121 healthy controls) from the PPMI database were used. Striatal binding ratio was calculated varying the number of summed transverse slices (N) and positions of the striatal regions of interest (d). The resulting SBRs were evaluated using area under the receiver operating characteristic curve. The optimized parameters were then applied to 77 test patients (35 PD and 42 non-PDpatients). Striatal binding ratios were also correlated with clinical measures in the PPMI-PD group. RESULTS: The optimal parameters discriminated the training groups in the PPMI cohort with 95.8% sensitivity and 98.3% specificity (lowest putamen SBR threshold, 1.037). The same parameters discriminated the groups in the test cohort with 97.1% sensitivity and 100% specificity (lowest putamen SBR threshold, 0.875). A significant negative correlation (r = -0.24, P = 0.0004) was found between putamen SBRs and motor severity in the PPMI-PD group. CONCLUSIONS: SBRquant discriminates DaT scans with high sensitivity and specificity. It has a high potential for use as a quantitative diagnostic aid in clinical and research settings.
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