Jei-Yie Huang1,2, Chun-Kai Huang3, Ruoh-Fang Yen1, Hon-Yen Wu2,4, Yu-Kang Tu2, Mei-Fang Cheng1, Ching-Chu Lu1,2, Kai-Yuan Tzen1, Kuo-Liong Chien5,3, Yen-Wen Wu6,3,7,8,9. 1. Department of Nuclear Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan. 2. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan. 3. Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan. 4. Department of Internal Medicine, Far Eastern Memorial Hospital, New Taipei City, Taiwan. 5. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan klchien@ntu.edu.tw wuyw0502@gmail.com. 6. Department of Nuclear Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan klchien@ntu.edu.tw wuyw0502@gmail.com. 7. Department of Nuclear Medicine, Far Eastern Memorial Hospital, New Taipei City, Taiwan. 8. Cardiology Division of Cardiovascular Medical Center, Far Eastern Memorial Hospital, New Taipei City, Taiwan; and. 9. National Yang-Ming University School of Medicine, Taipei, Taiwan.
Abstract
Myocardial perfusion imaging (MPI) with SPECT is a well-established tool for the diagnosis of coronary artery disease (CAD). However, soft-tissue attenuation is a common artifact that limits the diagnostic accuracy of MPI. The aim of this study was to determine whether attenuation correction (AC) improved the diagnostic performance of MPI, using coronary angiography as a reference standard. METHODS: MEDLINE and EMBASE were searched until March 2015 for studies evaluating AC MPI for the diagnosis of CAD. Methodologic quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. For each study, the sensitivity, specificity, and diagnostic odds ratio, along with 95% confidence intervals (CIs), were calculated to determine the diagnostic accuracy of AC versus non-attenuation-corrected (NAC) MPI. A bivariate mixed-effects model was applied for pooling the data. RESULTS: Of 201 articles, 17 studies (1,701 patients) were identified, including 5 studies that used CT AC, 12 studies that used radionuclide source AC (RAC), and 15 studies that reported NAC results. The pooled sensitivities across studies were 0.80 (95% CI, 0.64-0.91), 0.85 (95% CI, 0.81-0.88), 0.84 (95% CI, 0.79-0.88), and 0.80 (95% CI, 0.75-0.85) for CT AC, RAC, all AC, and NAC, respectively. The pooled specificities were 0.83 (95% CI, 0.71-0.91), 0.81 (95% CI, 0.73-0.86), 0.80 (95% CI, 0.74-0.85), and 0.68 (95% CI, 0.61-0.74). Both sensitivities and specificities resulted in a pooled diagnostic odds ratio of 20 (95% CI, 12-34), 24 (95% CI, 13-43), 22 (95% CI, 13-35), and 9 (7-11). Significant differences in specificity and diagnostic odds ratios were noted when AC (including CT AC, RAC, and all AC) was compared with NAC. CONCLUSION: The results from this study suggested that AC should be applied to MPI to improve the diagnosis of CAD, especially the specificity.
Myocardial perfusion imaging (MPI) with SPECT is a well-established tool for the diagnosis of coronary artery disease (CAD). However, soft-tissue attenuation is a common artifact that limits the diagnostic accuracy of MPI. The aim of this study was to determine whether attenuation correction (AC) improved the diagnostic performance of MPI, using coronary angiography as a reference standard. METHODS: MEDLINE and EMBASE were searched until March 2015 for studies evaluating AC MPI for the diagnosis of CAD. Methodologic quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. For each study, the sensitivity, specificity, and diagnostic odds ratio, along with 95% confidence intervals (CIs), were calculated to determine the diagnostic accuracy of AC versus non-attenuation-corrected (NAC) MPI. A bivariate mixed-effects model was applied for pooling the data. RESULTS: Of 201 articles, 17 studies (1,701 patients) were identified, including 5 studies that used CT AC, 12 studies that used radionuclide source AC (RAC), and 15 studies that reported NAC results. The pooled sensitivities across studies were 0.80 (95% CI, 0.64-0.91), 0.85 (95% CI, 0.81-0.88), 0.84 (95% CI, 0.79-0.88), and 0.80 (95% CI, 0.75-0.85) for CT AC, RAC, all AC, and NAC, respectively. The pooled specificities were 0.83 (95% CI, 0.71-0.91), 0.81 (95% CI, 0.73-0.86), 0.80 (95% CI, 0.74-0.85), and 0.68 (95% CI, 0.61-0.74). Both sensitivities and specificities resulted in a pooled diagnostic odds ratio of 20 (95% CI, 12-34), 24 (95% CI, 13-43), 22 (95% CI, 13-35), and 9 (7-11). Significant differences in specificity and diagnostic odds ratios were noted when AC (including CT AC, RAC, and all AC) was compared with NAC. CONCLUSION: The results from this study suggested that AC should be applied to MPI to improve the diagnosis of CAD, especially the specificity.
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