Myocardial flow reserve recovery in patients with Takotsubo syndrome: Insights from positron emission tomography.

BACKGROUND: Coronary microvascular dysfunction (CMD) has been implicated in the pathogenesis of Takotsubo syndrome (TTS). Positron emission tomography (PET) plays a key role in the assessment of CMD through myocardial flow reserve (MFR). However, there is limited information on the temporal progression of MFR and its relationship to coronary artery disease (CAD) in TTS patients. METHODS: This study evaluated patients with TTS who underwent cardiac catheterization and PET within one year of hospitalization. Patients were categorized into acute (≤10 days), subacute (11-30 days), and chronic (≥31 days) stages based on post-onset time of PET assessment. MFR values and prevalence of abnormal MFR (<2.0) were compared between stages. Temporal MFR changes in patients with obstructive CAD (≥70% stenosis by coronary angiography), non-obstructive CAD, and normal coronaries were compared. RESULTS: Of the 88 patients studied (mean age 70; 96% female), 52 (59%) were in the acute, 17 (19%) in the subacute, and 19 (22%) in the chronic stage. Median MFR in the acute stage was 2.0 (1.5-2.3), with 58% of patients showing abnormal MFR. A significant time-dependent improvement in MFR was observed (P = 0.002), accompanied by a decreased prevalence of abnormal MFR (P = 0.016). While patients with normal coronaries showed significant MFR improvement over time (P = 0.045), patients with obstructive or non-obstructive CAD demonstrated no improvement across three stages (P = 0.346 and 0.174, respectively). CONCLUSION: PET-derived MFR was impaired in TTS patients during the acute phase, with improvement suggesting potential recovery from CMD over time. The concurrent presence of obstructive CAD might impede this recovery process.

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the disease probability can be overestimated due to selection bias. We evaluated different strategies for training AI models to improve the calibration (accurate estimate of disease probability), using external testing. METHODS: Deep learning was trained using 828 patients from 3 sites, with MPI and invasive angiography within 6 months. Perfusion was assessed using upright (U-TPD) and supine total perfusion deficit (S-TPD). AI training without data augmentation (model 1) was compared to training with augmentation (increased sampling) of patients without obstructive CAD (model 2), and patients without CAD and TPD < 2% (model 3). All models were tested in an external population of patients with invasive angiography within 6 months (n = 332) or low likelihood of CAD (n = 179). RESULTS: Model 3 achieved the best calibration (Brier score 0.104 vs 0.121, p < 0.01). Improvement in calibration was particularly evident in women (Brier score 0.084 vs 0.124, p < 0.01). In external testing (n = 511), the area under the receiver operating characteristic curve (AUC) was higher for model 3 (0.930), compared to U-TPD (AUC 0.897) and S-TPD (AUC 0.900, p < 0.01 for both). CONCLUSION: Training AI models with augmentation of low-risk patients can improve calibration of AI models developed to identify patients with CAD, allowing more accurate assignment of disease probability. This is particularly important in lower-risk populations and in women, where overestimation of disease probability could significantly influence down-stream patient management.

Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging.

PURPOSE: Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS: From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%). RESULTS: Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference). CONCLUSIONS: Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone.

Role of nuclear cardiology in diagnosis and risk stratification of coronary microvascular disease.

Coronary flow reserve (CFR) with positron emission tomography/computed tomography (PET/CT) has an important role in the diagnosis of coronary microvascular disease (CMD), aids risk stratification and may be useful in monitoring therapy. CMD contributes to symptoms and a worse prognosis in patients with coronary artery disease (CAD), nonischemic cardiomyopathies, and heart failure. CFR measurements may improve our understanding of the role of CMD in symptoms and prognosis in CAD and other cardiovascular diseases. The clinical presentation of CAD has changed. The prevalence of nonobstructive CAD has increased to about 50% of patients with angina undergoing angiography. Ischemia with nonobstructive arteries (INOCA) is recognized as an important cause of symptoms and has an adverse prognosis. Patients with INOCA may have ischemia due to CMD, epicardial vasospasm or diffuse nonobstructive CAD. Reduced CFR in patients with INOCA identifies a high-risk group that may benefit from management strategies specific for CMD. Although measurement of CFR by PET/CT has excellent accuracy and repeatability, use is limited by cost and availability. CFR measurement with single-photon emission tomography (SPECT) is feasible, validated, and would increase availability and use of CFR. Patients with CMD can be identified by reduced CFR and selected for specific therapies.

Machine learning to predict abnormal myocardial perfusion from pre-test features.

BACKGROUND: Accurately predicting which patients will have abnormal perfusion on MPI based on pre-test clinical information may help physicians make test selection decisions. We developed and validated a machine learning (ML) model for predicting abnormal perfusion using pre-test features. METHODS: We included consecutive patients who underwent SPECT MPI, with 20,418 patients from a multi-center (5 sites) international registry in the training population and 9019 patients (from 2 separate sites) in the external testing population. The ML (extreme gradient boosting) model utilized 30 pre-test features to predict the presence of abnormal myocardial perfusion by expert visual interpretation. RESULTS: In external testing, the ML model had higher prediction performance for abnormal perfusion (area under receiver-operating characteristic curve [AUC] 0.762, 95% CI 0.750-0.774) compared to the clinical CAD consortium (AUC 0.689) basic CAD consortium (AUC 0.657), and updated Diamond-Forrester models (AUC 0.658, p < 0.001 for all). Calibration (validation of the continuous risk prediction) was superior for the ML model (Brier score 0.149) compared to the other models (Brier score 0.165 to 0.198, all p < 0.001). CONCLUSION: ML can predict abnormal myocardial perfusion using readily available pre-test information. This model could be used to help guide physician decisions regarding non-invasive test selection.

Prevalence and predictors of automatically quantified myocardial ischemia within a multicenter international registry.

BACKGROUND: The utility of cardiac stress testing depends on the prevalence of myocardial ischemia within candidate populations. However, a comprehensive assessment of the factors influencing frequency of myocardial ischemia within contemporary populations referred for stress testing has not been performed. METHODS: We assessed 19,690 patients undergoing nuclear stress testing from a multicenter registry. The chi-square test was used to assess the relative importance of features for predicting myocardial ischemia. RESULTS: In the overall cohort, LVEF, male gender, and rest total perfusion deficit (TPD) were the top three predictors of ischemia, followed by CAD status, age, typical angina, and CAD risk factors. Myocardial ischemia was observed in 13.6 % of patients with LVEF > 55 %, in 26.2 % of patients with LVEF 45 %-54 %, and in 48.3% among patients with LVEF < 45 % (P < 0.001). A similar pattern was noted for rest TPD (P < 0.001). Men had a threefold higher frequency of ischemia versus women (25.8 % vs. 8.4%, P < 0.001). Although the relative ranking of ischemia predictors varied among centers, LVEF and/or rest TPD were among the two most potent predictors of myocardial ischemia within each center. CONCLUSION: The prevalence of myocardial ischemia varied markedly according to clinical and imaging characteristics. LVEF and rest TPD are robust predictors of myocardial ischemia.

Automated quantitative analysis of CZT SPECT stratifies cardiovascular risk in the obese population: Analysis of the REFINE SPECT registry.

BACKGROUND: Obese patients constitute a substantial proportion of patients referred for SPECT myocardial perfusion imaging (MPI), presenting a challenge of increased soft tissue attenuation. We investigated whether automated quantitative perfusion analysis can stratify risk among different obesity categories and whether two-view acquisition adds to prognostic assessment. METHODS: Participants were categorized according to body mass index (BMI). SPECT MPI was assessed visually and quantified automatically; combined total perfusion deficit (TPD) was evaluated. Kaplan-Meier and Cox proportional hazard analyses were used to assess major adverse cardiac event (MACE) risk. Prognostic accuracy for MACE was also compared. RESULTS: Patients were classified according to BMI: BMI < 30, 30 ≤ BMI < 35, BMI ≥ 35. In adjusted analysis, each category of increasing stress TPD was associated with increased MACE risk, except for 1% ≤ TPD < 5% and 5% ≤ TPD < 10% in patients with BMI ≥ 35. Compared to visual analysis, single-position stress TPD had higher prognostic accuracy in patients with BMI < 30 (AUC .652 vs .631, P < .001) and 30 ≤ BMI < 35 (AUC .660 vs .636, P = .027). Combined TPD had better discrimination than visual analysis in patients with BMI ≥ 35 (AUC .662 vs .615, P = .003). CONCLUSIONS: Automated quantitative methods for SPECT MPI interpretation provide robust risk stratification in the obese population. Combined stress TPD provides additional prognostic accuracy in patients with more significant obesity.

Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT.

BACKGROUND: Stress-only myocardial perfusion imaging (MPI) markedly reduces radiation dose, scanning time, and cost. We developed an automated clinical algorithm to safely cancel unnecessary rest imaging with high sensitivity for obstructive coronary artery disease (CAD). METHODS AND RESULTS: Patients without known CAD undergoing both MPI and invasive coronary angiography from REFINE SPECT were studied. A machine learning score (MLS) for prediction of obstructive CAD was generated using stress-only MPI and pre-test clinical variables. An MLS threshold with a pre-defined sensitivity of 95% was applied to the automated patient selection algorithm. Obstructive CAD was present in 1309/2079 (63%) patients. MLS had higher area under the receiver operator characteristic curve (AUC) for prediction of CAD than reader diagnosis and TPD (0.84 vs 0.70 vs 0.78, P < .01). An MLS threshold of 0.29 had superior sensitivity than reader diagnosis and TPD for obstructive CAD (95% vs 87% vs 87%, P < .01) and high-risk CAD, defined as stenosis of the left main, proximal left anterior descending, or triple-vessel CAD (sensitivity 96% vs 89% vs 90%, P < .01). CONCLUSIONS: The MLS is highly sensitive for prediction of both obstructive and high-risk CAD from stress-only MPI and can be applied to a stress-first protocol for automatic cancellation of unnecessary rest imaging.

Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT Registry.

BACKGROUND: Diabetes mellitus (DM) is increasingly prevalent among contemporary populations referred for cardiac stress testing, but its potency as a predictor for major adverse cardiovascular events (MACE) vs other clinical variables is not well delineated. METHODS AND RESULTS: From 19,658 patients who underwent SPECT-MPI, we identified 3122 patients with DM without known coronary artery disease (CAD) (DM+/CAD-) and 3564 without DM with known CAD (DM-/CAD+). Propensity score matching was used to control for the differences in characteristics between DM+/CAD- and DM-/CAD+ groups. There was comparable MACE in the matched DM+/CAD- and DM-/CAD+ groups (HR 1.15, 95% CI 0.97-1.37). By Chi-square analysis, type of stress (exercise or pharmacologic), total perfusion deficit (TPD), and left ventricular function were the most potent predictors of MACE, followed by CAD and DM status. The combined consideration of mode of stress, TPD, and DM provided synergistic stratification, an 8.87-fold (HR 8.87, 95% CI 7.27-10.82) increase in MACE among pharmacologically stressed patients with DM and TPD > 10% (vs non-ischemic, exercised stressed patients without DM). CONCLUSIONS: Propensity-matched patients with DM and no known CAD have similar MACE risk compared to patients with known CAD and no DM. DM is synergistic with mode of stress testing and TPD in predicting the risk of cardiac stress test patients.

Radiolabeled Thioflavin-T Derivative PET Imaging for the Assessment of Cardiac Amyloidosis.

PURPOSE OF REVIEW: Cardiac amyloidosis (CA) is an often under-recognized cause of heart failure with preserved ejection fraction. The goal of the current paper was to review imaging modalities available for detecting cardiac amyloidosis. We wished to determine what modalities are available for the diagnosis of cardiac amyloidosis and what modalities could be utilized in the future. RECENT FINDINGS: Early and delayed planar imaging of the chest currently plays a central role in the workup and diagnosis of CA. However, novel positron emission tomography (PET) tracers could play a large role in CA imaging in the future. There is an increasing body of literature supporting the use of targeted amyloid-binding PET radiotracers such as 11C-Pittsburgh compound B (11C-PIB), 18F-florbetapir, -flutemetamol, and -florbetaben for the detection of cardiac amyloid. While planar imaging currently plays a large role in the workup of CA, PET imaging could play an increasing important role in the future. The quantitative abilities of novel PET tracers could theoretically allow for the serial monitoring of patients and detection of response to therapy, and the sensitive nature of the tracers could allow for even earlier disease detection. Further work with large randomized controlled trial data is needed in the development and validation of PET tracers for cardiac amyloid and represents an exciting development within the realm of nuclear cardiology.

Reduced acquisition times for measurement of myocardial blood flow with 99mTc-tetrofosmin and solid-state detector SPECT.

BACKGROUND: Measurement of myocardial blood flow (MBF) is feasible using SPECT imaging but the acquisition requires more time than usual. Our study assessed the impact of reducing acquisition times on the accuracy and repeatability of the uptake rate constant (K1). METHODS: Twenty-nine patients underwent two rest/stress studies with Tc-99m-tetrofosmin 18 ± 13 days apart, using a one-day rest/stress dynamic SPECT imaging protocol with a solid-state cardiac camera. A 5-minute static image was acquired prior to tracer injection for subtraction of residual activity, followed immediately by 11-minute of list-mode data collection. Static image acquisition times of 0.5, 1, and 3 minutes and dynamic imaging times of 5, 7, and 9 minutes were simulated by truncating list-mode data. Images were reconstructed with/without attenuation correction and with/without motion correction. Kinetic parameters were calculated using a 1-tissue-compartment model. RESULTS: K1 increased with reduced dynamic but not static imaging time (P < 0.001). The increase in K1 for a 9-minute scan was small (4.7 ± 5.3%) compared with full-length studies. The repeatability of K1 did not change significantly (13 ± 12%, P > 0.17). CONCLUSIONS: A shortened imaging protocol of 3-minute (rest) or 30-second (stress) static image acquisition and 9 minutes of dynamic image acquisition altered K1 by less than 5% compared to a previously validated 11-minute acquisition.

Comparison of myocardial blood flow and flow reserve with dobutamine and dipyridamole stress using rubidium-82 positron emission tomography.

BACKGROUND: The objective of this study was to compare the hyperemic myocardial blood flow (MBF) and myocardial flow reserve (MFR) obtained with dobutamine to those of dipyridamole in patients referred for myocardial perfusion imaging (MPI) using 82Rb positron emission tomography. METHODS: One hundred and fifty-six patients who underwent a 82Rb PET MPI study with dobutamine stress were included. A matching cohort of patients who underwent a 82Rb PET MPI study with dipyridamole stress was created, accounting for sex, age, history of coronary artery disease (CAD), prior revascularization, CAD risk factors, body mass index, and MPI interpretation. RESULTS: Global rest MBF (median [interquartile range] 0.84 [0.64-1.00] vs 0.69 [0.59-0.85]), stress MBF (2.36 [1.73-3.08] vs 1.66 [1.25-2.06]), MFR (2.75 [2.19-3.64] vs 2.29 [1.78-2.84]), and corrected MFR (2.85 [2.14-3.64] vs 2.20 [1.65-2.75]) were all significantly higher (P < 0.0001) in the dobutamine cohort compared to the dipyridamole cohort. CONCLUSION: The results of this study suggest that dobutamine produces higher MBF compared to dipyridamole in a representative population referred to nuclear cardiology laboratories.

Internal validation of myocardial flow reserve PET imaging using stress/rest myocardial activity ratios with Rb-82 and N-13-ammonia.

BACKGROUND: Myocardial flow reserve (MFR) measurement provides incremental diagnostic and prognostic information. The objective of the current study was to investigate the application of a simplified model for the estimation of MFR using only the stress/rest myocardial activity ratio (MAR) in patients undergoing rest-stress cardiac PET MPI. METHODS AND RESULTS: Rest and dipyridamole stress dynamic PET imaging was performed in consecutive patients using 82Rb or 13NH3 (n = 250 each). Reference standard MFR was quantified using a standard one-tissue compartment model. Stress/rest myocardial activity ratio (MAR) was calculated using the LV-mean activity from 2 to 6 minutes post-injection. Simplified estimates of MFR (MFREST) were then calculated using an inverse power function. For 13NH3, there was good correlation between MFR and MFREST values (R = 0.63), with similar results for 82Rb (R = 0.73). There was no bias in the MFREST values with either tracer. The overall diagnostic performance of MFREST for detection of MFR < 2 was good with ROC area under the curve (AUC) = 83.2 ± 1.2% for 13NH3 and AUC = 90.4 ± 0.7% for 82Rb. CONCLUSION: MFR was estimated with good accuracy using 82Rb and 13NH3 with a simplified method that relies only on stress/rest activity ratios. This novel approach does not require dynamic imaging or tracer kinetic modeling. It may be useful for routine quality assurance of PET MFR measurements, or in scanners where full dynamic imaging and tracer kinetic modeling is not feasible for technical or logistical reasons.

Site qualification and clinical interpretation standards for 99mTc-SPECT perfusion imaging in a multi-center study of MITNEC (Medical Imaging Trials Network of Canada).

BACKGROUND: Qualification and interpretation standards are essential for establishing 99mTc-SPECT MPI accuracy vs. alternative modalities. METHODS: Rest-stress 99mTc-SPECT phantom scans were acquired on 35 cameras. LV defects were quantified with summed stress (SSS) and difference scores (SDS) at 2 core labs. SDS ≥ 2 in the right coronary artery (RCA) was the qualifying standard. Twenty rest (R)-stress (S) patient images were acquired on qualified cameras and interpreted by core labs. Global scoring differences > 3 between labs or discordant clinical interpretations underwent review. Scoring, interpretation, image quality, and diagnostic parameter agreement were assessed. RESULTS: Phantom scans: visual scoring confirmed RCA-ischemia on all cameras. Regional SSS, SDS agreement was moderate to very good: ICC-r = 0.57, 0.84. Patient scans: 90% of global SSS, 85% of SDS differences were ≤ 3. Regional SSS, SDS agreement: ICC-r = 0.87, 0.86, and global abnormal (SSS ≥ 4) and ischemic (SDS ≥ 2) interpretation: ICC-r = 0.90 were excellent. Clinical interpretation agreement was 100% following review. Image quality agreement was 70%. Automated metrics also agreed: ischemic total perfusion deficit ICC-r = 0.75, reversible perfusion defect, transient ischemic dilation, and S-R LV ejection fraction ICC-r ≥ 0.90. CONCLUSION: Quantitative scoring and interpretation of scans were highly repeatable with site qualification and clinical interpretation standardization, indicating that dual-core lab interpretation is appropriate to determine 99mTc-SPECT MPI accuracy.

Acquisition, Processing, and Interpretation of PET 18F-FDG Viability and Inflammation Studies.

PURPOSE OF REVIEW: This article reviews the acquisition protocols and image interpretation for 18F-fluorodeoxyglucose (18F-FDG) imaging with positron emission tomography (PET) applied to the evaluation of myocardial viability and inflammation. RECENT FINDINGS: Cardiac PET with 18F-FDG provides essential information for the assessment of myocardial viability and inflammation and is usually combined with PET perfusion imaging using 82Rb or 13N-ammonia. Viable myocardium maintains glucose metabolism which can be detected via the uptake of 18F-FDG by PET imaging. The patient is prepared for viability imaging by shifting the metabolism of the heart to maximize the uptake of glucose and hence of 18F-FDG. Comparison of the 18F-FDG and myocardial perfusion images allows distinction between regions of the myocardium that are hibernating and thus may recover function with intervention, from those that are infarcted. Increased glucose utilization in the inflammatory cells also makes 18F-FDG a useful imaging technique in conditions such as cardiac sarcoidosis. Here, suppression of normal myocardial uptake is essential for accurate image interpretation. 18F-FDG PET broadens the scope of information potentially available through a cardiac PET study. With careful patient preparation, it provides valuable insights into myocardial viability and inflammatory processes such as sarcoidosis.

The CatLet score and outcome prediction in acute myocardial infarction for patients undergoing primary percutaneous intervention: A proof-of-concept study.

BACKGROUND: The Coronary Artery Tree description and Lesion EvaluaTion (CatLet) score accommodating the variability in coronary anatomy is a recently developed and comprehensive angiographic scoring system aimed at assisting in risk-stratification of patients with coronary artery disease. However, a validation of this angiographic scoring system is lacking. METHODS: The CatLet score was calculated retrospectively in 308 consecutively enrolled patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention. The primary endpoint, major adverse cardiac or cerebrovascular events (MACCEs), was stratified according to CatLet tertiles: CatLetlow ≤14 (n = 124), CatLetmid 15-21 (n = 82) and CatLettop ≥22 (n = 102). RESULTS: The CatLet score alone or after adjusting for a broad spectrum of risk factors, significantly predicted clinical outcomes at a median 4.3-year follow-up. Multivariable-adjusted hazard ratios (95%CI)/unit higher score were 1.05 (1.04-1.07) for MACCE, 1.06 (1.04-1.07) for cardiac death, and 1.05 (1.04-1.07) for all-cause death. When compared to the SYNTAX score, improved discrimination and better calibration of this CatLet score resulted in a significantly refined risk stratification. The overall category-free net reclassification improvement afforded by this CatLet score was as follows: 37.2% (p = .008) for MACCEs, 35.5% (p = .0249) for cardiac death, and 31.8% (p = .0316) for all-cause death. CONCLUSIONS: The ability to integrate the variability in coronary anatomy into angiographic scoring makes the CatLet score a more specific tool for outcome predictions in AMI. (http://www.chictr.org.cn. Unique identifiers: ChiCTR-POC-17013536).

Effect of proton pump inhibitors on Rubidium-82 gastric uptake using positron emission tomography myocardial perfusion imaging.

BACKGROUND: Rb-82 positron emission tomography (PET) myocardial perfusion imaging (MPI) is a robust tool for the evaluation of coronary artery disease (CAD). However, gastric uptake and spillover can be seen in 10% of Rb-82 PET MPI studies, commonly affecting the inferior wall, and can preclude the accurate identification of myocardial ischemia. We sought to understand the relationship between Rb-82 gastric uptake and the use of proton pump inhibitors (PPI). METHODS: 600 consecutive patients who presented for a clinically indicated Rb-82 PET MPI study were prospectively enrolled. In addition to the clinical history, PPI use was ascertained (medication, dose, frequency and duration of use, and time of last dose). Patients were categorized as PPI and non-PPI users. Rb-82 uptake in the gastrium, myocardium, and liver were measured at rest. Absolute uptake values and gastric:hepatic ratios were compared in PPI and non-PPI users. RESULT: Of 600 enrolled patients, 181 (30.2%) patients were using PPI. The gastric Rb-82 uptake in PPI users was 23% higher than non-PPI users (146 ± 52 kBq/cc vs 119 ± 40 kBq/cc, respectively; P < 0.001). The resting gastric:hepatic Rb-82 uptake ratio was also 23% higher in PPI vs non-PPI users (2.7 ± 1.0 vs 2.2 ± 0.8, respectively; P < 0.001). CONCLUSION: The gastric uptake of Rb-82 appears to be greater in patients actively using PPI and may identify a group who might be at greater risk of non-diagnostic Rb-82 PET MPI.

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.