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BACKGROUND: The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. METHODS: 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). RESULTS: FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). CONCLUSIONS: FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.

BACKGROUND: The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. METHODS: 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). RESULTS: FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). CONCLUSIONS: FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.

BACKGROUND: The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. METHODS: 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). RESULTS: FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). CONCLUSIONS: FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.

BACKGROUND: The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. METHODS: 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). RESULTS: FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). CONCLUSIONS: FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.

BACKGROUND: The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. METHODS: 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). RESULTS: FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). CONCLUSIONS: FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.