Beschreibung: The aim of this study was to explore the feasibility of attenuation correction (AC) of myocardial perfusion imaging (MPI) with a virtual unenhanced cardiac CT scan synthesized from contrast-enhanced single-source dual-energy coronary CT angiography. Methods: Segmental myocardial percentage uptake values obtained with AC were analyzed by use of correlation analysis and Bland–Altman limits of agreement (20-segment model), and clinical agreement was evaluated in 30 patients. Results: The 2 methods showed an excellent correlation for segmental myocardial percentage uptake at stress ( r = 0.93; P 〈 0.001; low dose) and at rest ( r = 0.90; P 〈 0.001; high dose) with narrow Bland–Altman limits of agreement (–6.8% to 7.8% and –7.8% to 7.4%, respectively). The levels of clinical agreement of SPECT MPI corrected with standard versus virtual unenhanced CT AC were 99% per coronary territory and 97% per patient. Conclusion: Our results suggest that AC of SPECT MPI with a virtual unenhanced CT scan synthesized from contrast-enhanced coronary CT angiography is feasible and reliable.

Beschreibung: We have evaluated the impact of increased body mass on the quality of myocardial perfusion imaging using a latest-generation -camera with cadmium-zinc-telluride semiconductor detectors in patients with high (≥40 kg/m 2 ) or very high (≥45 kg/m 2 ) body mass index (BMI). Methods: We enrolled 81 patients, including 18 with no obesity (BMI 〈 30 kg/m 2 ), 17 in World Health Organization obese class I (BMI, 30–34.9 kg/m 2 ), 15 in class II (BMI, 35–39.9 kg/m 2 ), and 31 in class III (BMI ≥ 40 kg/m 2 ), including 15 with BMI ≥ 45 kg/m 2 . Image quality was scored as poor (1), moderate (2), good (3), or excellent (4). Patients with BMI ≥ 45 kg/m 2 and nondiagnostic image quality (≤2) were rescanned after repositioning to better center the heart in the field of view. Receiver-operating-curve analysis was applied to determine the BMI cutoff required to obtain diagnostic image quality (≥3). Results: Receiver-operating-curve analysis resulted in a cutoff BMI of 39 kg/m 2 ( P 〈 0.001) for diagnostic image quality. In patients with BMI ≥ 40 kg/m 2 , image quality was nondiagnostic in 81%; after CT-based attenuation correction this decreased to 55%. Repositioning further improved image quality. Rescanning on a conventional SPECT camera resulted in diagnostic image quality in all patients with BMI ≥ 45 kg/m 2 . Conclusion: Patients with BMI ≥ 40 kg/m 2 should be scheduled for myocardial perfusion imaging on a conventional SPECT camera, as it is difficult to obtain diagnostic image quality on a cadmium-zinc-telluride camera.

Beschreibung: The purpose of this study was to evaluate the added value of coronary artery calcium score (CACS) as an adjunct to myocardial perfusion imaging (MPI) with SPECT for cardiac risk stratification before noncardiac surgery. SPECT MPI is a well-established and widely used tool for preoperative risk stratification before noncardiac surgery. The potential added value of combining SPECT MPI with CACS is unknown. Methods: We included 326 consecutive patients who were referred for SPECT MPI for preoperative cardiac risk assessment before elective noncardiac surgery. All patients underwent an additional low-dose CT scan for CACS and SPECT MPI. Patients were followed up for 40 d after their index surgical procedure, and the occurrence of major adverse cardiovascular events (MACE), including death, myocardial infarction, revascularization, stroke, and sudden cardiac death, was registered. Results: Postoperative MACE occurred in 30 patients (9%). Cumulative MACE rate was highest in patients with abnormal SPECT and high CACS (22%), defined by a cutoff value CACS of 1,314 or more, and lowest in patients with normal SPECT MPI findings and low CACS (5%) (CACS 〈 1,314). A CACS score of 1,314 or more was independently associated with a higher MACE rate in patients with normal (12% vs. 5%) or abnormal perfusion (22% vs. 12%, P 〈 0.05 for all intergroup comparisons). Conclusion: SPECT MPI findings and CACS are strong preoperative risk predictors. CACS allows further risk stratification, indicating very low risk when CACS less than 1,314 is associated with normal SPECT MPI findings. Conversely, in patients with abnormal SPECT MPI findings, a CACS of 1,314 or more confers an added value for predicting adverse outcomes.

Beschreibung: The ability to obtain quantitative values of flow and myocardial flow reserve (MFR) has been perceived as an important advantage of PET over conventional nuclear myocardial perfusion imaging (MPI). We evaluated the added diagnostic value of MFR over MPI alone as assessed with 13 N-ammonia and PET/CT to predict angiographic coronary artery disease (CAD). Methods: Seventy-three patients underwent 1-d adenosine stress–rest 13 N-ammonia PET/CT MPI, and MFR was calculated. The added value of MFR as an adjunct to MPI for predicting CAD (luminal narrowing ≥ 50%) was evaluated using invasive coronary angiography as a standard of reference. Results: Per patient, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MPI for detecting significant CAD were 79%, 80%, 91%, 59%, and 79%, respectively. Adding a cutoff of less than 2.0 for global MFR to MPI findings improved the values to 96% ( P 〈 0.005), 80%, 93%, 89% ( P 〈 0.005), and 92% ( P 〈 0.005), respectively. Conclusion: The quantification of MFR in 13 N-ammonia PET/CT MPI provides a substantial added diagnostic value for detection of CAD. Particularly in patients with normal MPI results, quantification of MFR helps to unmask clinically significant CAD.

Beschreibung: Precise definition of the mitral valve plane (VP) during segmentation of the left ventricle for SPECT myocardial perfusion imaging (MPI) quantification often requires manual adjustment, which affects the quantification of perfusion. We developed a machine learning approach using support vector machines (SVM) for automatic VP placement. Methods: A total of 392 consecutive patients undergoing 99m Tc-tetrofosmin stress (5 min; mean ± SD, 350 ± 54 MBq) and rest (5 min; 1,024 ± 153 MBq) fast SPECT MPI attenuation corrected (AC) by CT and same-day coronary CT angiography were studied; included in the 392 patients were 48 patients who underwent invasive coronary angiography and had no known coronary artery disease. The left ventricle was segmented with standard clinical software (quantitative perfusion SPECT) by 2 experts, adjusting the VP if needed. Two-class SVM models were computed from the expert placements with 10-fold cross validation to separate the patients used for training and those used for validation. SVM probability estimates were used to compute the best VP position. Automatic VP localizations on AC and non-AC images were compared with expert placement on coronary CT angiography. Stress and rest total perfusion deficits and detection of per-vessel obstructive stenosis by invasive coronary angiography were also compared. Results: Bland–Altman 95% confidence intervals (CIs) for VP localization by SVM and experts for AC stress images (bias, 1; 95% CI, –5 to 7 mm) and AC rest images (bias, 1; 95% CI, –7 to 10 mm) were narrower than interexpert 95% CIs for AC stress images (bias, 0; 95% CI, –8 to 8 mm) and AC rest images (bias, 0; 95% CI, –10 to 10 mm) ( P 〈 0.01). Bland–Altman 95% CIs for VP localization by SVM and experts for non-AC stress images (bias, 1; 95% CI, –4 to 6 mm) and non-AC rest images (bias, 2; 95% CI, –7 to 10 mm) were similar to interexpert 95% CIs for non-AC stress images (bias, 0; 95% CI, –6 to 5 mm) and non-AC rest images (bias, –1; 95% CI, –9 to 7 mm) ( P was not significant [NS]). For regional detection of obstructive stenosis, ischemic total perfusion deficit areas under the receiver operating characteristic curve for the 2 experts (AUC, 0.79 [95% CI, 0.7–0.87]; AUC, 0.81 [95% CI, 0.73–0.89]) and the SVM (0.82 [0.74–0.9]) for AC data were the same ( P = NS) and were higher than those for the unadjusted VP (0.63 [0.53–0.73]) ( P 〈 0.01). Similarly, for non-AC data, areas under the receiver operating characteristic curve for the experts (AUC, 0.77 [95% CI, 0.69–0.89]; AUC, 0.8 [95% CI, 0.72–0.88]) and the SVM (0.79 [0.71–0.87]) were the same ( P = NS) and were higher than those for the unadjusted VP (0.65 [0.56–0.75]) ( P 〈 0.01). Conclusion: Machine learning with SVM allows automatic and accurate VP localization, decreasing user dependence in SPECT MPI quantification.

Beschreibung: Recent advances in SPECT technology including cadmium–zinc–telluride (CZT) semiconductor detector material may pave the way for absolute myocardial blood flow (MBF) measurements by SPECT. The aim of the present study was to compare K 1 uptake rate constants as surrogates of absolute MBF and myocardial flow reserve index (MFRi) in humans as assessed with a CZT SPECT camera versus PET. Methods: Absolute MBF was assessed in 28 consecutive patients undergoing adenosine stress–rest myocardial perfusion imaging (MPI) by 99m Tc-tetrofosmin CZT SPECT and 13 N-ammonia PET, and MFR was calculated as a ratio of hyperemic over resting MBF. Results from both MPI methods were compared, and correlation coefficients were calculated. The diagnostic accuracy of CZT MFRi to predict an abnormal MFR defined as PET MFR less than 2 was assessed using a receiver-operator-characteristic curve. Results: Median MBF at rest was comparable between CZT and PET (0.89 [interquartile range (IQR), 0.77–1.00] vs. 0.92 [IQR, 0.78–1.06] mL/g/min; P = not significant) whereas it was significantly lower at stress in CZT than PET (1.11 [IQR, 1.00–1.26] vs. 2.06 [IQR, 1.48–2.56] mL/g/min; P 〈 0.001). This resulted in median MFRi values of 1.32 (IQR, 1.13–1.52) by CZT and 2.36 (IQR, 1.57–2.71) by PET ( P 〈 0.001). The receiver-operator-characteristic curve revealed a cutoff for CZT MFRi at 1.26 to predict an abnormal PET MFR yielding an accuracy of 75%. Conclusion: The estimation of absolute MBF index values by CZT SPECT MPI with 99m Tc-tetrofosmin is technically feasible, although hyperemic values are significantly lower than from PET with 13 N-ammonia, resulting in a substantial underestimation of MFR. Nevertheless, CZT MFRi may confer diagnostic value.