UNLABELLED: The use of myocardial perfusion (82)Rb PET/CT studies continues to increase but its accuracy using database quantification methods for the diagnosis of coronary artery disease (CAD) has not been established. METHODS: A sex-independent normal database and criteria for abnormality for rest-stress (82)Rb PET/CT myocardial perfusion imaging were developed and validated by evaluation of 281 patients (136 females: mean age +/- SD, 63.3 +/- 13.3 y; 145 males: mean age +/- SD, 63.9 +/- 12.8 y) who underwent a rest-adenosine stress (82)Rb PET/CT study. These patients were divided into 3 groups: (a) healthy group: 30 patients, with <5% likelihood of CAD (low likelihood [LLK]) based on sequential Bayesian analysis; these patients were used to generate the normal distribution; (b) pilot group: 174 patients; these patients were used to determine the optimal criteria for detecting and localizing the perfusion abnormality; and (c) validation group: 76 patients (23 with LLK of CAD and 53 who underwent coronary angiography; these patients were used for prospective validation. RESULTS: Of the 53 patients who underwent coronary angiography, 8 had <50% stenosis and 45 patients had at least one stenosis > or =50% in one major artery. Fifteen patients had single-vessel disease, 17 had double-vessel disease, and 13 had triple-vessel disease. The prospective validation shows a normalcy rate of 78% (18/23) for global CAD. The analyses by individual arteries show a normalcy rate of 96% (22/23) for the left anterior descending coronary artery, 96% for the left circumflex coronary artery (22/23), and 100% for the right coronary artery (23/23). The overall sensitivity for detection of CAD (> or =50% stenosis) was 93% (42/45). The overall specificity for detection of the absence of CAD (< or =50% stenosis) was 75% (6/8). Also, the positive predictive value for global CAD was 95% (42/44), the negative predictive value was 67% (6/9), and the accuracy was 91% (48/53). CONCLUSION: The quantitative (82)Rb PET/CT database created and validated in this study is highly accurate for the detection and localization of CAD. Physicians should consider using the quantitative output of these algorithms as decision support tools to aid with image interpretation.
UNLABELLED: The use of myocardial perfusion (82)Rb PET/CT studies continues to increase but its accuracy using database quantification methods for the diagnosis of coronary artery disease (CAD) has not been established. METHODS: A sex-independent normal database and criteria for abnormality for rest-stress (82)Rb PET/CT myocardial perfusion imaging were developed and validated by evaluation of 281 patients (136 females: mean age +/- SD, 63.3 +/- 13.3 y; 145 males: mean age +/- SD, 63.9 +/- 12.8 y) who underwent a rest-adenosine stress (82)Rb PET/CT study. These patients were divided into 3 groups: (a) healthy group: 30 patients, with <5% likelihood of CAD (low likelihood [LLK]) based on sequential Bayesian analysis; these patients were used to generate the normal distribution; (b) pilot group: 174 patients; these patients were used to determine the optimal criteria for detecting and localizing the perfusion abnormality; and (c) validation group: 76 patients (23 with LLK of CAD and 53 who underwent coronary angiography; these patients were used for prospective validation. RESULTS: Of the 53 patients who underwent coronary angiography, 8 had <50% stenosis and 45 patients had at least one stenosis > or =50% in one major artery. Fifteen patients had single-vessel disease, 17 had double-vessel disease, and 13 had triple-vessel disease. The prospective validation shows a normalcy rate of 78% (18/23) for global CAD. The analyses by individual arteries show a normalcy rate of 96% (22/23) for the left anterior descending coronary artery, 96% for the left circumflex coronary artery (22/23), and 100% for the right coronary artery (23/23). The overall sensitivity for detection of CAD (> or =50% stenosis) was 93% (42/45). The overall specificity for detection of the absence of CAD (< or =50% stenosis) was 75% (6/8). Also, the positive predictive value for global CAD was 95% (42/44), the negative predictive value was 67% (6/9), and the accuracy was 91% (48/53). CONCLUSION: The quantitative (82)Rb PET/CT database created and validated in this study is highly accurate for the detection and localization of CAD. Physicians should consider using the quantitative output of these algorithms as decision support tools to aid with image interpretation.
Authors: Ernest V Garcia; Tracy L Faber; C David Cooke; Russell D Folks; Ji Chen; Cesar Santana Journal: J Nucl Cardiol Date: 2007-07 Impact factor: 5.952
Authors: Giovanni Storto; Andrea Soricelli; Teresa Pellegrino; Mario Petretta; Alberto Cuocolo Journal: Eur J Nucl Med Mol Imaging Date: 2009-12 Impact factor: 9.236
Authors: Riikka Lautamäki; Richard T George; Kakuya Kitagawa; Takahiro Higuchi; Jennifer Merrill; Corina Voicu; Anthony DiPaula; Stephan G Nekolla; João A C Lima; Albert C Lardo; Frank M Bengel Journal: Eur J Nucl Med Mol Imaging Date: 2008-11-05 Impact factor: 9.236