Quantification of myocardial blood flow by CZT-SPECT with motion correction and comparison with 15O-water PET.

BACKGROUND: We compared quantification of MBF and myocardial flow reserve (MFR) with a 99mTc-sestamibi CZT-SPECT to 15O-water PET. METHODS: SPECT MBF for thirty patients in the WATERDAY study was re-analyzed by QPET software with motion correction and optimal placement of the arterial input function. 15O-water PET MBF was re-quantified using dedicated software. Inter-operator variability was assessed using repeatability coefficients (RPC). RESULTS: Significant correlations were observed between global (r = 0.91, P < 0.001) and regional MBF (r = 0.86, P < 0.001) with SPECT compared to PET. Global MBF (rest 0.95 vs 1.05 ml/min/g, P = 0.07; stress 2.62 vs 2.68 mL/min/g, P = 0.17) and MFR (2.65 vs 2.75, P = 0.86) were similar between SPECT and PET. Rest (0.81 vs 0.98 mL/min/g, P = 0.03) and stress MBF (1.98 vs 2.61 mL/min/g, P = 0.01) in right coronary artery (RCA) were lower with SPECT compared to PET. However, MFR in the RCA territory was similar (2.54 vs 2.77, P = 0.21). The SPECT-PET RPC for global MBFs and MFR were 0.95 mL/min/g and 0.94, with inter-observer RPC of 0.59 mL/min/g and 0.74, respectively. CONCLUSIONS: MBF and MFR derived from CZT-SPECT with motion correction and optimal placement of the arterial input function showed good agreement with 15O-water PET, as well as low inter-operator variability.

Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT).

BACKGROUND: We aim to establish a multicenter registry collecting clinical, imaging, and follow-up data for patients who undergo myocardial perfusion imaging (MPI) with the latest generation SPECT scanners. METHODS: REFINE SPECT (REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT) uses a collaborative design with multicenter contribution of clinical data and images into a comprehensive clinical-imaging database. All images are processed by quantitative software. Over 290 individual imaging variables are automatically extracted from each image dataset and merged with clinical variables. In the prognostic cohort, patient follow-up is performed for major adverse cardiac events. In the diagnostic cohort (patients with correlating invasive angiography), angiography and revascularization results within 6 months are obtained. RESULTS: To date, collected prognostic data include scans from 20,418 patients in 5 centers (57% male, 64.0 ± 12.1 years) who underwent exercise (48%) or pharmacologic stress (52%). Diagnostic data include 2079 patients in 9 centers (67% male, 64.7 ± 11.2 years) who underwent exercise (39%) or pharmacologic stress (61%). CONCLUSION: The REFINE SPECT registry will provide a resource for collaborative projects related to the latest generation SPECT-MPI. It will aid in the development of new artificial intelligence tools for automated diagnosis and prediction of prognostic outcomes.

Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry.

BACKGROUND: Upper reference limits for transient ischemic dilation (TID) have not been rigorously established for cadmium-zinc-telluride (CZT) camera systems. We aimed to derive TID limits for common myocardial perfusion imaging protocols utilizing a large, multicenter registry (REFINE SPECT). METHODS: One thousand six hundred and seventy-two patients with low likelihood of coronary artery disease with normal perfusion findings were identified. Images were processed with Quantitative Perfusion SPECT software (Cedars-Sinai Medical Center, Los Angeles, CA). Non-attenuation-corrected, camera-, radiotracer-, and stress protocol-specific TID limits in supine position were derived from 97.5th percentile and mean + 2 standard deviations (SD). Reference limits were compared for different solid-state cameras (D-SPECT vs. Discovery), radiotracers (technetium-99m-sestamibi vs. tetrofosmin), different types of stress (exercise vs. four different vasodilator-based protocols), and different vasodilator-based protocols. RESULTS: TID measurements did not follow Gaussian distribution in six out of eight subgroups. TID limits ranged from 1.18 to 1.52 (97.5th percentile) and 1.18 to 1.39 (mean + 2SD). No difference was noted between D-SPECT and Discovery cameras (P = 0.71) while differences between exercise and vasodilator-based protocols (adenosine, regadenoson, or regadenoson-walk) were noted (all P < 0.05). CONCLUSIONS: We used a multicenter registry to establish camera-, radiotracer-, and protocol-specific upper reference limits of TID for supine position on CZT camera systems. Reference limits did not differ between D-SPECT and Discovery camera.

Transient ischaemic dilation and post-stress wall motion abnormality increase risk in patients with less than moderate ischaemia: analysis of the REFINE SPECT registry.

AIMS: Ischaemia on single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is strongly associated with cardiovascular risk. Transient ischaemic dilation (TID) and post-stress wall motion abnormalities (WMA) are non-perfusion markers of ischaemia with incremental prognostic utility. Using a large, multicentre SPECT MPI registry, we assessed the degree to which these features increased the risk of major adverse cardiovascular events (MACE) in patients with less than moderate ischaemia. METHODS AND RESULTS: Ischaemia was quantified with total perfusion deficit using semiautomated software and classified as: none (<1%), minimal (1 to <5%), mild (5 to <10%), moderate (10 to <15%), and severe (≥15%). Univariable and multivariable Cox proportional hazard analyses were used to assess associations between high-risk imaging features and MACE. We included 16 578 patients, mean age 64.2 and median follow-up 4.7 years. During follow-up, 1842 patients experienced at least one event. Patients with mild ischaemia and TID were more likely to experience MACE compared with patients without TID [adjusted hazard ratio (HR) 1.42, P = 0.023], with outcomes not significantly different from patients with moderate ischaemia without other high-risk features (unadjusted HR 1.15, P = 0.556). There were similar findings in patients with post-stress WMA. However, in multivariable analysis of patients with mild ischaemia, TID (adjusted HR 1.50, P = 0.037), but not WMA, was independently associated with increased MACE. CONCLUSION: In patients with mild ischaemia, TID or post-stress WMA identify groups of patients with outcomes similar to patients with moderate ischaemia. Whether these combinations identify patients who may derive benefit from revascularization deserves further investigation.

5-Year Prognostic Value of Quantitative Versus Visual MPI in Subtle Perfusion Defects: Results From REFINE SPECT.

OBJECTIVES: This study compared the ability of automated myocardial perfusion imaging analysis to predict major adverse cardiac events (MACE) to that of visual analysis. BACKGROUND: Quantitative analysis has not been compared with clinical visual analysis in prognostic studies. METHODS: A total of 19,495 patients from the multicenter REFINE SPECT (REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT) study (64 ± 12 years of age, 56% males) undergoing stress Tc-99m-labeled single-photon emission computed tomography (SPECT) myocardial perfusion imaging were followed for 4.5 ± 1.7 years for MACE. Perfusion abnormalities were assessed visually and categorized as normal, probably normal, equivocal, or abnormal. Stress total perfusion deficit (TPD), quantified automatically, was categorized as TPD = 0%, TPD >0% to <1%, ≤1% to <3%, ≤3% to <5%, ≤5% to ≤10%, or TPD >10%. MACE consisted of death, nonfatal myocardial infarction, unstable angina, or late revascularization (>90 days). Kaplan-Meier and Cox proportional hazards analyses were performed to test the performance of visual and quantitative assessments in predicting MACE. RESULTS: During follow-up examinations, 2,760 (14.2%) MACE occurred. MACE rates increased with worsening of visual assessments, that is, the rate for normal MACE was 2.0%, 3.2% for probably normal, 4.2% for equivocal, and 7.4% for abnormal (all p < 0.001). MACE rates increased with increasing stress TPD from 1.3% for the TPD category of 0% to 7.8% for the TPD category of >10% (p < 0.0001). The adjusted hazard ratio (HR) for MACE increased even in equivocal assessment (HR: 1.56; 95% confidence interval [CI]: 1.37 to 1.78) and in the TPD category of ≤3% to <5% (HR: 1.74; 95% CI: 1.41 to 2.14; all p < 0.001). The rate of MACE in patients visually assessed as normal still increased from 1.3% (TPD = 0%) to 3.4% (TPD ≥5%) (p < 0.0001). CONCLUSIONS: Quantitative analysis allows precise granular risk stratification in comparison to visual reading, even for cases with normal clinical reading.

Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry.

AIMS: To optimize per-vessel prediction of early coronary revascularization (ECR) within 90 days after fast single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) using machine learning (ML) and introduce a method for a patient-specific explanation of ML results in a clinical setting. METHODS AND RESULTS: A total of 1980 patients with suspected coronary artery disease (CAD) underwent stress/rest 99mTc-sestamibi/tetrofosmin MPI with new-generation SPECT scanners were included. All patients had invasive coronary angiography within 6 months after SPECT MPI. ML utilized 18 clinical, 9 stress test, and 28 imaging variables to predict per-vessel and per-patient ECR with 10-fold cross-validation. Area under the receiver operator characteristics curve (AUC) of ML was compared with standard quantitative analysis [total perfusion deficit (TPD)] and expert interpretation. ECR was performed in 958 patients (48%). Per-vessel, the AUC of ECR prediction by ML (AUC 0.79, 95% confidence interval (CI) [0.77, 0.80]) was higher than by regional stress TPD (0.71, [0.70, 0.73]), combined-view stress TPD (AUC 0.71, 95% CI [0.69, 0.72]), or ischaemic TPD (AUC 0.72, 95% CI [0.71, 0.74]), all P < 0.001. Per-patient, the AUC of ECR prediction by ML (AUC 0.81, 95% CI [0.79, 0.83]) was higher than that of stress TPD, combined-view TPD, and ischaemic TPD, all P < 0.001. ML also outperformed nuclear cardiologists' expert interpretation of MPI for the prediction of early revascularization performance. A method to explain ML prediction for an individual patient was also developed. CONCLUSION: In patients with suspected CAD, the prediction of ECR by ML outperformed automatic MPI quantitation by TPDs (per-vessel and per-patient) or nuclear cardiologists' expert interpretation (per-patient).

Quantitative Clinical Nuclear Cardiology, Part 1: Established Applications.

Single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has attained widespread clinical acceptance as a standard of care for patients with known or suspected coronary artery disease (CAD). A significant contribution to this success has been the use of computer techniques to provide objective quantitative assessment in the standardization of the interpretation of these studies. Software platforms have been developed as a pipeline to provide the quantitative algorithms researched, developed and validated to be clinically useful so diagnosticians everywhere can benefit from these tools. The goal of this CME article (PART 1) is to describe the many quantitative tools that are clinically established and more importantly how clinicians should use them routinely in the interpretation, clinical management and therapy guidance of patients with CAD.

Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT Registry.

OBJECTIVE: Prevalence and prognostic impact of cardiovascular disease differ between patients with or without diabetes. We aimed to explore differences in the prevalence and prognosis of myocardial ischemia by automated quantification of total perfusion deficit (TPD) among patients with and without diabetes. RESEARCH DESIGN AND METHODS: Of 20,418 individuals who underwent single-photon emission computed tomography myocardial perfusion imaging, 2,951 patients with diabetes were matched to 2,951 patients without diabetes based on risk factors using propensity score. TPD was categorized as TPD = 0%, 0% < TPD < 1%, 1% ≤ TPD < 5%, 5% ≤ TPD ≤ 10%, and TPD >10%. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause mortality, myocardial infarction, unstable angina, or late revascularization. RESULTS: MACE risk was increased in patients with diabetes compared with patients without diabetes at each level of TPD above 0 (P < 0.001 for interaction). In patients with TPD >10%, patients with diabetes had greater than twice the MACE risk compared with patients without diabetes (annualized MACE rate 9.4 [95% CI 6.7-11.6] and 3.9 [95% CI 2.8-5.6], respectively, P < 0.001). Patients with diabetes with even very minimal TPD (0% < TPD < 1%) experienced a higher risk for MACE than those with 0% TPD (hazard ratio 2.05 [95% CI 1.21-3.47], P = 0.007). Patients with diabetes with a TPD of 0.5% had a similar MACE risk as patients without diabetes with a TPD of 8%. CONCLUSIONS: For every level of TPD >0%, even a very minimal deficit of 0% < TPD < 1%, the MACE risk was higher in the patients with diabetes compared with patients without diabetes. Patients with diabetes with minimal ischemia had comparable MACE risk as patients without diabetes with significant ischemia.

Triple-gated motion and blood pool clearance corrections improve reproducibility of coronary 18F-NaF PET.

PURPOSE: To improve the test-retest reproducibility of coronary plaque 18F-sodium fluoride (18F-NaF) positron emission tomography (PET) uptake measurements. METHODS: We recruited 20 patients with coronary artery disease who underwent repeated hybrid PET/CT angiography (CTA) imaging within 3 weeks. All patients had 30-min PET acquisition and CTA during a single imaging session. Five PET image-sets with progressive motion correction were reconstructed: (i) a static dataset (no-MC), (ii) end-diastolic PET (standard), (iii) cardiac motion corrected (MC), (iv) combined cardiac and gross patient motion corrected (2 × MC) and, (v) cardiorespiratory and gross patient motion corrected (3 × MC). In addition to motion correction, all datasets were corrected for variations in the background activities which are introduced by variations in the injection-to-scan delays (background blood pool clearance correction, BC). Test-retest reproducibility of PET target-to-background ratio (TBR) was assessed by Bland-Altman analysis and coefficient of reproducibility. RESULTS: A total of 47 unique coronary lesions were identified on CTA. Motion correction in combination with BC improved the PET TBR test-retest reproducibility for all lesions (coefficient of reproducibility: standard = 0.437, no-MC = 0.345 (27% improvement), standard + BC = 0.365 (20% improvement), no-MC + BC = 0.341 (27% improvement), MC + BC = 0.288 (52% improvement), 2 × MC + BC = 0.278 (57% improvement) and 3 × C + BC = 0.254 (72% improvement), all p < 0.001). Importantly, in a sub-analysis of 18F-NaF-avid lesions with gross patient motion > 10 mm following corrections, reproducibility was improved by 133% (coefficient of reproducibility: standard = 0.745, 3 × MC = 0.320). CONCLUSION: Joint corrections for cardiac, respiratory, and gross patient motion in combination with background blood pool corrections markedly improve test-retest reproducibility of coronary 18F-NaF PET.

Quantitative Clinical Nuclear Cardiology, Part 1: Established Applications.

SPECT myocardial perfusion imaging has attained widespread clinical acceptance as a standard of care for patients with known or suspected coronary artery disease. A significant contribution to this success has been the use of computer techniques to provide objective quantitative assessment in the standardization of the interpretation of these studies. Software platforms have been developed as a pipeline to provide the quantitative algorithms researched, developed and validated to be clinically useful so diagnosticians everywhere can benefit from these tools. The goal of this continuing medical education article (part 1) is to describe the many quantitative tools that are clinically established and, more importantly, how clinicians should use them routinely in interpretation, clinical management, and therapy guidance for patients with coronary artery disease.

Solid-State Detector SPECT Myocardial Perfusion Imaging.

There has been an evolutionary leap in SPECT imaging with the advent of camera systems that use solid-state crystals and novel collimator designs configured specifically for cardiac imaging. Solid-state SPECT camera systems have facilitated dramatic reductions in both imaging time and radiation dose while maintaining high diagnostic accuracy. These advances are related to simultaneous improvement in photon sensitivity due to the collimator and imaging geometry, as well as image resolution due to the improved energy resolution of the new crystals. Improved photon sensitivity has facilitated fast or low-dose myocardial perfusion imaging (MPI), and early dynamic imaging has emerged as a technique for assessing myocardial blood flow with SPECT. Lastly, general-purpose solid-state camera systems and hybrid SPECT/CT systems have also been developed that may have important clinical roles in cardiac imaging. This review summarizes state-of-the-art solid-state SPECT MPI technology and clinical applications, including emerging techniques for SPECT MPI flow estimation. We also discuss imaging protocols used with the new cameras, potential imaging pitfalls, and the latest data providing large-scale validation of the diagnostic and prognostic value of this new technology.

Added prognostic value of left ventricular shape by gated SPECT imaging in patients with suspected coronary artery disease and normal myocardial perfusion.

BACKGROUND: Left ventricular (LV) remodeling is associated with adverse cardiovascular events. We evaluated the added prognostic value of LV shape index (SI) assessed by gated single-photon emission tomography (SPECT) in patients without known coronary artery disease (CAD). METHODS AND RESULTS: We studied 674 patients with normal myocardial perfusion and normal LV ejection fraction (EF) on stress gated SPECT imaging. An automated software program was used to calculate end-diastolic and end-systolic LVSI. An LVSI ≤ 0.54 at end-systole was considered normal. Follow-up was 96% complete with a median follow-up of 37 months. During follow-up, 25 events occurred (3.8% cumulative event rate). Event-free survival was lower in patients with abnormal end-systolic LVSI (P < .001). Age (P = .021), diabetes (P = .048), and end-systolic LVSI (P < .001) were independent predictors of events. LVSI added prognostic information increasing the global chi-square of the model including age and diabetes from 15.15 to 25.97 (P < .001). The effect of diabetes on hazard ratio increased with increasing values of end-systolic LVSI. The probability of events at 48 months predicted by Weibull analysis progressively increased with increasing values of end-systolic LVSI and was higher in patients with diabetes as compared to those without. Decision curve analyses indicate that the model including end-systolic LVSI resulted in an increased net benefit between 5% and 30% threshold probability, indicating superior estimation of outcomes at low threshold probability levels. CONCLUSIONS: The evaluation of LVSI may identify patients with early-stage LV remodeling and at higher risk of adverse cardiac events, even in the presence of normal myocardial perfusion.

Detection and quantitation of right ventricular reversible perfusion defects by stress SPECT myocardial perfusion imaging: A proof-of-principle study.

BACKGROUND: In patients with right dominant coronary circulation, the right ventricular (RV) myocardium and the inferior region of the left ventricular (LV) myocardium share a common source of blood flow. We hypothesized that stress/rest SPECT myocardial perfusion imaging (MPI) could detect reversible perfusion defects in the RV in some patients with LV inferior wall perfusion abnormalities. MATERIAL AND METHODS: We identified 2 groups of patients with LV inferior wall perfusion defects (with or without defects in other regions of LV myocardium) from our database. Patients in group 1 (n = 17) had reversible perfusion defects in the RV free wall by visual analysis, while patients in group 2 (n = 17) did not. The images were processed with filtered back projection and, separately, with iterative reconstruction. The images were then re-processed using an automated quantitative software that is specifically designed to include the RV in the region of interest. RESULTS: There were 76% men in group 1 and 94% in group 2 (P <0.05). The mean age was 65±20 in group 1 vs. 63±18 years in group 2 (P < 0.05). The stress type was exercise in 30% in group 1 and 35% in group 2, with the remaining patients studied with pharmacological stress testing (P = NS). The presence of RV reversible perfusion defects using filtered back projection was more evident in 13 patients (75%), while it was better seen with iterative reconstruction in 4 patients (25%). By automated analysis, the RV reversible perfusion defect size was 19 ± 14% of RV myocardium. CONCLUSION: This proof-of-principle study demonstrates that reversible RV perfusion defects suggestive of ischemia can be detected by SPECT myocardial perfusion imaging in some patients with LV inferior ischemia by visual analysis and can be quantitated by automated programs. Further studies on the diagnostic and prognostic relevance of assessing RV ischemia on SPECT MPI are needed.

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR). We demonstrated an approach to visually convey the reasoning behind a patient's risk to provide insight to clinicians beyond that of a "black box." METHODS: We trained multiple models using 122 potential clinical predictors (features) for 8321 patients, including 551 cases of subsequent cardiac death. Accuracy was measured by area under the ROC curve (AUC), computed within a cross-validation framework. We developed a method to display the model's rationale to facilitate clinical interpretation. RESULTS: The baseline LR (AUC = 0.76; 14 features) was outperformed by all other methods. A least absolute shrinkage and selection operator (LASSO) model (AUC = 0.77; p = .045; 6 features) required the fewest features. A support vector machine (SVM) model (AUC = 0.83; p < .0001; 49 features) provided the highest accuracy. CONCLUSIONS: LASSO outperformed LR in both accuracy and simplicity (number of features), with SVM yielding best AUC for prediction of cardiac death in patients undergoing MPS. Combined with presenting the reasoning behind the risk scores, our results suggest that ML can be more effective than LR for this application.

Data-Driven Gross Patient Motion Detection and Compensation: Implications for Coronary 18F-NaF PET Imaging.

Patient motion degrades image quality, affecting the quantitative assessment of PET images. This problem affects studies of coronary lesions in which microcalcification processes are targeted. Coronary PET imaging protocols require scans of up to 30 min, introducing the risk of gross patient motion (GPM) during the acquisition. Here, we investigate the feasibility of an automated data-driven method for the detection of GPM during PET acquisition. Methods: Twenty-eight patients with stable coronary disease underwent a 30-min PET acquisition 1 h after the injection of 18F-sodium fluoride (18F-NaF) at 248 ± 10 MBq (mean ± SD) and then a coronary CT angiography scan. An automated data-driven GPM detection technique tracking the center of mass of the count rates for every 200 ms in the PET list-mode data was devised and evaluated. Two patient motion patterns were considered: sudden repositioning (motion of >0.5 mm within 3 s) and general repositioning (motion of >0.3 mm over 15 s or more). After the reconstruction of diastolic images, individual GPM frames with focal coronary uptake were coregistered in 3 dimensions, creating a GPM-compensated (GPMC) image series. Lesion motion was reported for all lesions with focal uptake. Relative differences in SUVmax and target-to-background ratio (TBR) between GPMC and non-GPMC (standard electrocardiogram-gated data) diastolic PET images were compared in 3 separate groups defined by the maximum motion observed in the lesion (<5, 5-10, and >10 mm). Results: A total of 35 18F-NaF-avid lesions were identified in 28 patients. An average of 3.5 ± 1.5 GPM frames were considered for each patient, resulting in an average frame duration of 7 ± 4 (range, 3-21) min. The mean per-patient motion was: 7 ± 3 mm (maximum, 13.7 mm). GPM correction increased SUVmax and TBR in all lesions with greater than 5 mm of motion. In lesions with 5-10 mm of motion (n = 15), SUVmax and TBR increased by 4.6% ± 5.6% (P = 0.02) and 5.8% ± 6.4% (P < 0.002), respectively. In lesions with greater than 10 mm of motion (n = 15), the SUVmax and TBR increased by 5.0% ± 5.3% (P = 0.009) and 11.5% ± 10.1% (P = 0.001), respectively. GPM correction led to the diagnostic reclassification of 3 patients (11%). Conclusion: GPM during coronary 18F-NaF PET imaging is common and may affect quantitative accuracy. Automated retrospective compensation of this motion is feasible and should be considered for coronary PET imaging.

Three-Hour Delayed Imaging Improves Assessment of Coronary 18F-Sodium Fluoride PET.

Coronary 18F-sodium fluoride (18F-NaF) PET identifies ruptured plaques in patients with recent myocardial infarction and localizes to atherosclerotic lesions with active calcification. Most studies to date have performed the PET acquisition 1 h after injection. Although qualitative and semiquantitative analysis is feasible with 1-h images, residual blood-pool activity often makes it difficult to discriminate plaques with 18F-NaF uptake from noise. We aimed to assess whether delayed PET performed 3 h after injection improves image quality and uptake measurements. Methods: Twenty patients (67 ± 7 y old, 55% male) with stable coronary artery disease underwent coronary CT angiography (CTA) and PET/CT both 1 h and 3 h after the injection of 266.2 ± 13.3 MBq of 18F-NaF. We compared the visual pattern of coronary uptake, maximal background (blood pool) activity, noise, SUVmax, corrected SUVmax (cSUVmax), and target-to-background (TBR) ratio in lesions defined by CTA on 1-h versus 3-h 18F-NaF PET. Results: On 1-h PET, 26 CTA lesions with 18F-NaF PET uptake were identified in 12 (60%) patients. On 3-h PET, we detected 18F-NaF PET uptake in 7 lesions that were not identified on 1-h PET. The median cSUVmax and TBRs of these lesions were 0.48 (interquartile range [IQR], 0.44-0.51) and 1.45 (IQR, 1.39-1.52), respectively, compared with -0.01 (IQR, -0.03-0.001) and 0.95 (IQR, 0.90-0.98), respectively, on 1-h PET (both P < 0.001). Across the entire cohort, 3-h PET SUVmax was similar to 1-h PET measurements (1.63 [IQR, 1.37-1.98] vs. 1.55 [IQR, 1.43-1.89], P = 0.30), and the background activity was lower (0.71 [IQR, 0.65-0.81] vs. 1.24 [IQR, 1.05-1.31], P < 0.001). On 3-h PET, TBR, cSUVmax, and noise were significantly higher (respectively: 2.30 [IQR, 1.70-2.68] vs. 1.28 [IQR, 0.98-1.56], P < 0.001; 0.38 [IQR, 0.27-0.70] vs. 0.90 [IQR, 0.64-1.17], P < 0.001; and 0.10 [IQR, 0.09-0.12] vs. 0.07 [IQR, 0.06-0.09], P = 0.02). Median cSUVmax and TBR increased by 92% (range, 33%-225%) and 80% (range, 20%-177%), respectively. Conclusion: Blood-pool activity decreases on delayed imaging, facilitating the assessment of 18F-NaF uptake in coronary plaques. Median TBR increases by 80%, leading to the detection of more plaques with significant uptake than are detected using the standard 1-h protocol. A greater than 1-h delay may improve the detection of 18F-NaF uptake in coronary artery plaques.

Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.

Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease from combined analysis of semiupright and supine stress MPI by deep learning (DL) as compared with standard combined total perfusion deficit (TPD). Methods: 1,160 patients without known coronary artery disease (64% male) were studied. Patients underwent stress 99mTc-sestamibi MPI with new-generation solid-state SPECT scanners in 4 different centers. All patients had on-site clinical reads and invasive coronary angiography correlations within 6 mo of MPI. Obstructive disease was defined as at least 70% narrowing of the 3 major coronary arteries and at least 50% for the left main coronary artery. Images were quantified at Cedars-Sinai. The left ventricular myocardium was segmented using standard clinical nuclear cardiology software. The contour placement was verified by an experienced technologist. Combined stress TPD was computed using sex- and camera-specific normal limits. DL was trained using polar distributions of normalized radiotracer counts, hypoperfusion defects, and hypoperfusion severities and was evaluated for prediction of obstructive disease in a novel leave-one-center-out cross-validation procedure equivalent to external validation. During the validation procedure, 4 DL models were trained using data from 3 centers and then evaluated on the 1 center left aside. Predictions for each center were merged to have an overall estimation of the multicenter performance. Results: 718 (62%) patients and 1,272 of 3,480 (37%) arteries had obstructive disease. The area under the receiver operating characteristics curve for prediction of disease on a per-patient and per-vessel basis by DL was higher than for combined TPD (per-patient, 0.81 vs. 0.78; per-vessel, 0.77 vs. 0.73; P < 0.001). With the DL cutoff set to exhibit the same specificity as the standard cutoff for combined TPD, per-patient sensitivity improved from 61.8% (TPD) to 65.6% (DL) (P < 0.05), and per-vessel sensitivity improved from 54.6% (TPD) to 59.1% (DL) (P < 0.01). With the threshold matched to the specificity of a normal clinical read (56.3%), DL had a sensitivity of 84.8%, versus 82.6% for an on-site clinical read (P = 0.3). Conclusion: DL improves automatic interpretation of MPI as compared with current quantitative methods.

Stress Myocardial Perfusion PET Provides Incremental Risk Prediction in Patients with and Patients without Diabetes.

PURPOSE: To evaluate the prognostic value of myocardial perfusion PET in patients with and patients without diabetes mellitus. MATERIALS AND METHODS: The authors performed a retrospective analysis of prospectively acquired data from a multicenter registry cohort of 7061 patients, including 1966 with diabetes mellitus, who underwent clinically indicated rest-stress rubidium 82 (82Rb) myocardial perfusion PET. The mean patient age (±standard deviation) was 63.3 years ± 13. Of the 7061 patients, 3348 were women (47.4%), 2296 (32.5%) had known coronary artery disease, and 1895 (26.8%) had previously undergone revascularization. The primary end point was cardiac death (n = 169) assessed at a mean of 2.5 years ± 1.5. The authors used Cox proportional hazards models and risk reclassification measures stratified according to diabetes status. RESULTS: In multivariable models adjusting for established clinical predictors, increasing magnitude of stress myocardial perfusion abnormality was associated with greater risk of cardiac death in patients with diabetes (hazard ratio [HR]: 7.2; 95% confidence interval [CI]: 3.1, 16.8) for severely abnormal myocardium compared with normal myocardium. The addition of stress myocardial perfusion imaging results significantly improved the fit of a clinical model for predicting cardiac death in patients with and patients without diabetes. Myocardial perfusion PET improved risk reclassification for cardiac death in patients with diabetes (category-based net reclassification index: 0.39; 95% CI: 0.15, 0.60, P < .001). Among diabetic patients, an abnormal myocardial perfusion PET scan was associated with increased risk of cardiac death (HR: 4.4; 95% CI: 2.0, 9.7) in all important clinical subgroups based on age, sex, obesity, or prior revascularization. CONCLUSION: In a large cohort of patients referred for clinical 82Rb stress PET, myocardial perfusion imaging results provided incremental risk prediction of cardiac death in patients with and patients without diabetes mellitus.© RSNA, 2019Supplemental material is available for this article.

New Trends in Quantitative Nuclear Cardiology Methods.

PURPOSE OF REVIEW: The use of quantitative analysis in single photon emission computed tomography (SPECT) and positron emission tomography (PET) has become an integral part of current clinical practice and plays a crucial role in the detection and risk stratification of coronary artery disease. Emerging technologies, new protocols, and new quantification methods have had a significant impact on the diagnostic performance and prognostic value of nuclear cardiology imaging, while reducing the need for clinician oversight. In this review, we aim to describe recent advances in automation and quantitative analysis in nuclear cardiology. RECENT FINDINGS: Recent publications have shown that fully automatic processing is feasible, limiting human input to specific cases where aberrancies are detected by the quality control software. Furthermore, there is evidence indicating that fully quantitative analysis of myocardial perfusion imaging is feasible and can achieve at least similar diagnostic accuracy as visual interpretation by an expert clinician. In addition, the use of fully automated quantification in combination with machine learning algorithms can provide incremental diagnostic and prognostic value over the traditional method of expert visual interpretation. SUMMARY: Emerging technologies in nuclear cardiology focus on automation and the use of artificial intelligence as part of the interpretation process. This review highlights the benefits and limitations of these applications, and outlines future directions in the field.