Hybrid Imaging: Calcium Score and Myocardial Perfusion Imaging

Coronary heart disease (CHD) remains the top cause of death due to cardiovascular conditions worldwide, with someone suffering a myocardial infarction every 40 seconds. This highlights the importance of non-invasive imaging technologies like myocardial perfusion imaging (MPI), which are crucial for detecting coronary artery disease (CAD) early, even before symptoms appear. However, the reliance solely on MPI has shifted due to its limitations in definitively ruling out atherosclerosis, leading to the adoption of hybrid imaging techniques. Hybrid imaging combines computed tomography (CT) with MPI techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT). This integration, often within a single gantry system, enhances the diagnostic accuracy by allowing for attenuation correction (AC), acquisition of the coronary artery calcium score (CACS), and more precise tracing of radiotracer uptake. The built-in CT in modern MPI systems assists in these functions, which is essential for better diagnosis and risk assessment in patients. The addition of CACS to MPI, a method involving the assessment of calcified plaque in coronary arteries, notably enhances diagnostic and prognostic capabilities. CACS helps in identifying atherosclerosis and predicting potential cardiac events, facilitating personalized risk management and the initiation of tailored interventions like statins and aspirin. Such comprehensive imaging strategies not only improve the accuracy of detecting CAD but also help in stratifying patient risk more effectively. In this paper, we discuss how the incorporation of CAC into MPI protocols enhances the diagnostic sensitivity for detecting obstructive CAD, as evidenced by several studies where the addition of CAC to MPI has led to improved outcomes in diagnosing CAD. Moreover, CAC has been shown to unmask silent coronary atherosclerosis in patients with normal MPI results, highlighting its incremental diagnostic value. We will discuss the evolving role of hybrid imaging in guiding therapeutic decisions, particularly the use of statins for cardiovascular prevention. The integration of CAC assessment with MPI not only aids in the early detection and management of CAD but also optimizes therapeutic strategies, enhancing patient care through a more accurate and personalized approach. Such advancements underscore the need for further research to fully establish the benefits of combining CAC with MPI in the clinical assessment of cardiovascular risk.

The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[15O]-water positron emission tomography

AIMS

The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE).

METHODS AND RESULTS

Five hundred seventy-two consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0, 1-100, 101-400, 401-1000, >1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62-0.70] and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC > 100 and CAC > 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [15O]-water-PET scan.

CONCLUSION

There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.

PET myocardial perfusion imaging: Trends, challenges, and opportunities

Various non-invasive images are used in clinical practice for the diagnosis and prognostication of chronic coronary syndromes. Notably, quantitative myocardial perfusion imaging (MPI) through positron emission tomography (PET) has seen significant technical advancements and a substantial increase in its use over the past two decades. This progress has generated an unprecedented wealth of clinical information, which, when properly applied, can diagnose and fine-tune the management of patients with different types of ischemic syndromes. This state-of-art review focuses on quantitative PET MPI, its integration into clinical practice, and how it holds up at the eyes of modern cardiac imaging and revascularization clinical trials, along with future perspectives.

Downward myocardial creep during stress PET imaging is inversely associated with mortality

PURPOSE

The myocardial creep is a phenomenon in which the heart moves from its original position during stress-dynamic PET myocardial perfusion imaging (MPI) that can confound myocardial blood flow measurements. Therefore, myocardial motion correction is important to obtain reliable myocardial flow quantification. However, the clinical importance of the magnitude of myocardial creep has not been explored. We aimed to explore the prognostic value of myocardial creep quantified by an automated motion correction algorithm beyond traditional PET-MPI imaging variables.

METHODS

Consecutive patients undergoing regadenoson rest-stress [82Rb]Cl PET-MPI were included. A newly developed 3D motion correction algorithm quantified myocardial creep, the maximum motion at stress during the first pass (60 s), in each direction. All-cause mortality (ACM) served as the primary endpoint.

RESULTS

A total of 4,276 patients (median age 71 years; 60% male) were analyzed, and 1,007 ACM events were documented during a 5-year median follow-up. Processing time for automatic motion correction was < 12 s per patient. Myocardial creep in the superior to inferior (downward) direction was greater than the other directions (median, 4.2 mm vs. 1.3-1.7 mm). Annual mortality rates adjusted for age and sex were reduced with a larger downward creep, with a 4.2-fold ratio between the first (0 mm motion) and 10th decile (11 mm motion) (mortality, 7.9% vs. 1.9%/year). Downward creep was associated with lower ACM after full adjustment for clinical and imaging parameters (adjusted hazard ratio, 0.93; 95%CI, 0.91-0.95; p < 0.001). Adding downward creep to the standard PET-MPI imaging model significantly improved ACM prediction (area under the receiver operating characteristics curve, 0.790 vs. 0.775; p < 0.001), but other directions did not (p > 0.5).

CONCLUSIONS

Downward myocardial creep during regadenoson stress carries additional information for the prediction of ACM beyond conventional flow and perfusion PET-MPI. This novel imaging biomarker is quantified automatically and rapidly from stress dynamic PET-MPI.

A fully automated deep learning approach for coronary artery segmentation and comprehensive characterization

Coronary computed tomography angiography (CCTA) allows detailed assessment of early markers associated with coronary artery disease (CAD), such as coronary artery calcium (CAC) and tortuosity (CorT). However, their analysis can be time-demanding and biased. We present a fully automated pipeline that performs (i) coronary artery segmentation and (ii) CAC and CorT objective analysis. Our method exploits supervised learning for the segmentation of the lumen, and then, CAC and CorT are automatically quantified. 281 manually annotated CCTA images were used to train a two-stage U-Net-based architecture. The first stage employed a 2.5D U-Net trained on axial, coronal, and sagittal slices for preliminary segmentation, while the second stage utilized a multichannel 3D U-Net for refinement. Then, a geometric post-processing was implemented: vessel centerlines were extracted, and tortuosity score was quantified as the count of branches with three or more bends with change in direction forming an angle >45°. CAC scoring relied on image attenuation. CAC was detected by setting a patient specific threshold, then a region growing algorithm was applied for refinement. The application of the complete pipeline required <5 min per patient. The model trained for coronary segmentation yielded a Dice score of 0.896 and a mean surface distance of 1.027 mm compared to the reference ground truth. Tracts that presented stenosis were correctly segmented. The vessel tortuosity significantly increased locally, moving from proximal, to distal regions (p < 0.001). Calcium volume score exhibited an opposite trend (p < 0.001), with larger plaques in the proximal regions. Volume score was lower in patients with a higher tortuosity score (p < 0.001). Our results suggest a linked negative correlation between tortuosity and calcific plaque formation. We implemented a fast and objective tool, suitable for population studies, that can help clinician in the quantification of CAC and various coronary morphological parameters, which is helpful for CAD risk assessment.

Coronary artery calcium (CAC) score for cardiovascular risk stratification in a Thai clinical cohort: A comparison of absolute scores and age-sex-specific percentiles

Purposes

Coronary artery calcium (CAC) score provides a quantification of atherosclerotic plaque within the coronary arteries. This study aimed to examine the prevalence and CAC score distribution and to evaluate the association of each CAC score classifications with major adverse cardiovascular events (MACE) in a Thai clinical cohort.

Methods

This study was a retrospective observational cohort. We included patients aged above 35 years who underwent CAC score testing. The absolute and age-sex specific percentile classifications were categorized as 0, 1 to 10, 11 to 100, 101 to 400, and >400 and 0, <75th, 75th - 90th, and >90th, respectively. The endpoint was MACE, including cardiovascular death, myocardial infarction, heart failure hospitalization, coronary artery revascularization procedure, and stroke. Multivariable Cox regression was used to estimate the hazard ratios. The discriminative performance between classifications were compared using Harrell's C-statistics. The agreement was assessed via Cohen's Kappa.

Results

This study included 440 patients, with approximately 70% of Thai patients exhibiting a CAC score. CAC score distributed higher in male than female and increased with age. Both CAC score classification demonstrated the acceptable predictive performance. However, fair agreement was observed between classifications (Cohen's kappa 0.51, 95%CI 0.42-0.59). Within the absolute classification, a higher CAC score was associated with increased hazard ratios for MACE across stratified age-sex-specific percentile levels. In contrast, the hazard ratios for MACE did not consistently rise with higher age-sex-specific percentile CAC score when stratified by absolute CAC score levels.

Conclusions

Both absolute and age-sex-specific percentile CAC score demonstrated acceptable performance in predicting MACE. However, the absolute CAC score classification may be more suitable for risk stratification within the Thai clinical cohort. Our findings offer supportive information that could inform future recommendations for CAC score testing criteria within national clinical practice guidelines.

Automated Motion Correction for Myocardial Blood Flow Measurements and Diagnostic Performance of 82Rb PET Myocardial Perfusion Imaging

Motion correction (MC) affects myocardial blood flow (MBF) measurements in 82Rb PET myocardial perfusion imaging (MPI); however, frame-by-frame manual MC of dynamic frames is time-consuming. This study aims to develop an automated MC algorithm for time-activity curves used in compartmental modeling and compare the predictive value of MBF with and without automated MC for significant coronary artery disease (CAD). Methods: In total, 565 patients who underwent PET-MPI were considered. Patients without angiographic findings were split into training (n = 112) and validation (n = 112) groups. The automated MC algorithm used simplex iterative optimization of a count-based cost function and was developed using the training group. MBF measurements with automated MC were compared with those with manual MC in the validation group. In a separate cohort, 341 patients who underwent PET-MPI and invasive coronary angiography were enrolled in the angiographic group. The predictive performance in patients with significant CAD (≥70% stenosis) was compared between MBF measurements with and without automated MC. Results: In the validation group (n = 112), MBF measurements with automated and manual MC showed strong correlations (r = 0.98 for stress MBF and r = 0.99 for rest MBF). The automatic MC took less time than the manual MC (<12 s vs. 10 min per case). In the angiographic group (n = 341), MBF measurements with automated MC decreased significantly compared with those without (stress MBF, 2.16 vs. 2.26 mL/g/min; rest MBF, 1.12 vs. 1.14 mL/g/min; MFR, 2.02 vs. 2.10; all P < 0.05). The area under the curve (AUC) for the detection of significant CAD by stress MBF with automated MC was higher than that without (AUC, 95% CI, 0.76 [0.71-0.80] vs. 0.73 [0.68-0.78]; P < 0.05). The addition of stress MBF with automated MC to the model with ischemic total perfusion deficit showed higher diagnostic performance for detection of significant CAD (AUC, 95% CI, 0.82 [0.77-0.86] vs. 0.78 [0.74-0.83]; P = 0.022), but the addition of stress MBF without MC to the model with ischemic total perfusion deficit did not reach significance (AUC, 95% CI, 0.81 [0.76-0.85] vs. 0.78 [0.74-0.83]; P = 0.067). Conclusion: Automated MC on 82Rb PET-MPI can be performed rapidly with excellent agreement with experienced operators. Stress MBF with automated MC showed significantly higher diagnostic performance than without MC.

Economic and healthcare resource utilization assessments of PET imaging in Coronary Artery Disease diagnosis: a systematic review and discussion of opportunities for future economic evaluations

AIMS

This systematic literature review (SLR) consolidated economic and healthcare resource utilization (HCRU) evidence for positron emission tomography (PET) and single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) to inform future economic evaluations.

MATERIALS AND METHODS

An electronic search was conducted in MEDLINE, Embase, and Cochrane databases from 2012-2022. Economic and HCRU studies in adults who underwent PET- or SPECT-MPI for coronary artery disease (CAD) diagnosis were eligible. A qualitative methodological assessment of existing economic evaluations, HCRU, and downstream cardiac outcomes was completed. Exploratory meta-analyses of clinical outcomes were performed.

RESULTS

The search yielded 13,439 results, with 71 records included. Economic evaluations and comparative clinical trials were limited in number and outcome types (HCRU, downstream cardiac outcomes, and diagnostic performance) assessed. No studies included all outcome types and only one economic evaluation linked diagnostic performance to HCRU. The meta-analyses of comparative studies demonstrated significantly higher rates of early- and late-invasive coronary angiography and revascularization for PET- compared to SPECT-MPI; however, the rate of repeat testing was lower with PET-MPI. The rate of acute myocardial infarction was lower, albeit non-significant with PET- vs. SPECT-MPI.

LIMITATIONS AND CONCLUSIONS

This SLR identified economic and HCRU evaluations following PET- and SPECT-MPI for CAD diagnosis and determined that existing studies do not capture all pertinent outcome parameters or link diagnostic performance to downstream HCRU and cardiac outcomes, thus, resulting in simplified assessments of CAD burden. A limitation of this work relates to heterogeneity in study designs, patient populations, and follow-up times of existing studies. Resultingly, it was challenging to pool data in meta-analyses. Overall, this work provides a foundation for the development of comprehensive economic models for PET- and SPECT-MPI in CAD diagnosis, which should link diagnostic outcomes to HCRU and downstream cardiac events to capture the full CAD scope.

Coronary artery calcium score and pre-test probabilities as gatekeepers to predict and rule out perfusion defects in positron emission tomography

BACKGROUND

Little is known about the gatekeeper performance of coronary artery calcium score (CACS) before myocardial perfusion positron emission tomography (PET), compared with updated pre-test probabilities from American and European guidelines (pre-test-AHA/ACC, pre-test-ESC).

METHODS

We enrolled participants without known coronary artery disease undergoing CACS and Rubidium-82 PET. Abnormal perfusion was defined as summed stress score ≥ 4. Using Bayes' formula, pre-test probabilities and CACS were combined into post-test probabilities.

RESULTS

We included 2050 participants (54% male, mean age 64.6 years) with median CACS 62 (IQR 0-380), pre-test-ESC 17% (11-26), pre-test-AHA/ACC 27% (16-44), and abnormal perfusion in 437 participants (21%). To predict abnormal perfusion, area under the curve of CACS was 0.81, pre-test-AHA/ACC 0.68, pre-test-ESC 0.69, post-test-AHA/ACC 0.80, and post-test-ESC 0.81 (P < 0.001 for CACS vs. each pre-test, and each post-test vs. pre-test). CACS = 0 had 97% negative predictive value (NPV), pre-test-AHA/ACC ≤ 5% 100%, pre-test-ESC ≤ 5% 98%, post-test-AHA/ACC ≤ 5% 98%, and post-test-ESC ≤ 5% 96%. Among participants, 26% had CACS = 0, 2% pre-test-AHA/ACC ≤ 5%, 7% pre-test-ESC ≤ 5%, 23% post-test-AHA/ACC ≤ 5%, and 33% post-test-ESC ≤ 5% (all P < 0.001).

CONCLUSIONS

CACS and post-test probabilities are excellent predictors of abnormal perfusion and can rule it out with very high NPV in a substantial proportion of participants. CACS and post-test probabilities may be used as gatekeepers before advanced imaging. Coronary artery calcium score (CACS) predicted abnormal perfusion (SSS ≥ 4) in myocardial positron emission tomography (PET) better than pre-test probabilities of coronary artery disease (CAD), while pre-test-AHA/ACC and pre-test-ESC performed similarly (left). Using Bayes' formula, pre-test-AHA/ACC or pre-test-ESC were combined with CACS into post-test probabilities (middle). This calculation reclassified a substantial proportion of participants to low probability of CAD (0-5%), not needing further imaging, as shown for AHA/ACC probabilities (2% with pre-test-AHA/ACC to 23% with post-test-AHA/ACC, P < 0.001, right). Very few participants with abnormal perfusion were classified under pre-test or post-test probabilities 0-5%, or under CACS 0. AUC: area under the curve. Pre-test-AHA/ACC: Pre-test probability of the American Heart Association/American College of Cardiology. Post-test-AHA/ACC: Post-test probability combining pre-test-AHA/ACC and CACS. Pre-test-ESC: Pre-test probability of the European Society of Cardiology. SSS: Summed stress score.

Combined evaluation of CAC score and myocardial perfusion imaging in patients at risk of cardiovascular disease: where are we and what do the data say

Advances in the prevention and treatment of cardiovascular disease (CVD) over the last decades have led to a marked reduction in mortality for CVD. Nevertheless, atherosclerosis leading to coronary artery disease and stroke remains one of the most common causes of death in the world. The usefulness of imaging tests in the early identification of disease led to identify subjects at major risk of poor outcomes, suggesting risk factor modification. The aim of this article is to analyze the state of art of combined imaging in patients at risk of CVD referred to MPI evaluation, to highlight the present and potential features able to provide incremental prognostic information to help clinicians in patient management and to reduce adverse events.

Incremental prognostic value of stress phase entropy over standard PET myocardial perfusion imaging variables

PURPOSE

Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables.

METHODS

Consecutive patients who underwent pharmacological stress-rest 82Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM).

RESULTS

In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1).

CONCLUSION

Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction.

Myocardial Flow Reserve, an Independent Prognostic Marker of All-Cause Mortality Assessed by 82Rb PET Myocardial Perfusion Imaging: A Danish Multicenter Study

BACKGROUND

Rubidium-82 positron emission tomography (82Rb PET) myocardial perfusion imaging is used in clinical practice to quantify regional perfusion defects. Additionally, 82Rb PET provides a measure of absolute myocardial flow reserve (MFR), describing the vasculature state of health. We assessed whether 82Rb PET-derived MFR is associated with all-cause mortality independently of the extent of perfusion defects.

METHODS

We conducted a multicenter clinical registry-based study of patients undergoing 82Rb PET myocardial perfusion imaging on suspicion of chronic coronary syndromes. Patients were followed up in national registries for the primary outcome of all-cause mortality. Global MFR ≤2 was considered reduced.

RESULTS

Among 7169 patients studied, 38.1% were women, the median age was 69 (IQR, 61-76) years, and 39.0% had MFR ≤2. A total of 667 (9.3%) patients died during a median follow-up of 3.1 (IQR, 2.6-4.0) years, more in patients with MFR ≤2 versus MFR >2 (15.7% versus 5.2%; P<0.001). MFR ≤2 was associated with all-cause mortality across subgroups defined by the extent of perfusion defects (all P<0.05). In a Cox survival regression model adjusting for sex, age, comorbidities, kidney function, left ventricular ejection fraction, and perfusion defects, MFR ≤2 was a robust predictor of mortality with a hazard ratio of 1.62 (95% CI, 1.31-2.02; P<0.001). Among patients with no reversible perfusion defects (n=3101), MFR ≤2 remained strongly associated with mortality (hazard ratio, 1.86 [95% CI, 1.26-2.73]; P<0.01). The prognostic value of impaired MFR was similar for cardiac and noncardiac death.

CONCLUSIONS

MFR ≤2 predicts all-cause mortality independently of the extent of perfusion defects. Our results support the inclusion of MFR when assessing the prognosis of patients suspected of chronic coronary syndromes.

Coronary artery calcium among patients with heterozygous familial hypercholesterolaemia

Aims

We aimed to determine if coronary artery calcium (CAC) is associated with cardiovascular disease (CVD) events, defined as CVD-related death, unstable angina, myocardial infarction, or staged revascularization among patients with heterozygous familial hypercholesterolaemia (HeFH) under primary prevention settings.

Methods and results

Data of patients with FH admitted to Kanazawa University Hospital between 2000 and 2020, who underwent CAC measurement and were followed up (n = 622, male = 306, mean age = 54 years), were retrospectively reviewed. Risk factors for CVD events were determined using the Cox proportional hazard model. The median follow-up duration was 13.2 years (interquartile range: 9.8-18.4 years). We observed 132 CVD events during the follow-up period. The event rate per 1000 person-years for CAC scores of 0 [n = 283 (45.5%)], 1-100 [n = 260 (41.8%)], and >100 [n = 79 (12.7%)] was 1.2, 17.0, and 78.8, respectively. Log (CAC score + 1) was a significant predictor of the occurrence of CVD events (hazard ratio: 3.24; 95% confidence interval: 1.68-4.80; P < 0.0001) in the multivariate Cox regression analysis, independent of other factors. The risk discrimination of CVD events was enhanced by adding CAC information to other conventional risk factors (C-statistics: 0.833-0.934; P < 0.0001).

Conclusion

The CAC score helps in further risk stratification in patients with HeFH.

Obtaining a Coronary Artery Calcium Score with Myocardial Perfusion Imaging

A coronary artery calcium score adds diagnostic and prognostic information to myocardial perfusion imaging and has been shown to alter management. Whenever feasible, coronary calcium assessment should be performed routinely in patients without known coronary artery disease at the time of myocardial perfusion imaging.