Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study.

BACKGROUND: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal results. We evaluated whether unsupervised machine learning could identify unique phenotypes among patients with normal scans and whether those phenotypes were associated with risk of death or myocardial infarction. METHODS: Patients from a large international multicenter MPI registry (10 sites) with normal perfusion by expert visual interpretation were included in this cohort analysis. The training population included 9849 patients, and external testing population 12,528 patients. Unsupervised cluster analysis was performed, with separate training and external testing cohorts, to identify clusters, with four distinct phenotypes. We evaluated the clinical and imaging features of clusters and their associations with death or myocardial infarction. FINDINGS: Patients in Clusters 1 and 2 almost exclusively underwent exercise stress, while patients in Clusters 3 and 4 mostly required pharmacologic stress. In external testing, the risk for Cluster 4 patients (20.2% of population, unadjusted hazard ratio [HR] 6.17, 95% confidence interval [CI] 4.64-8.20) was higher than the risk associated with pharmacologic stress (HR 3.03, 95% CI 2.53-3.63), or previous myocardial infarction (HR 1.82, 95% CI 1.40-2.36). INTERPRETATION: Unsupervised learning identified four distinct phenotypes of patients with normal perfusion scans, with a significant proportion of patients at very high risk of myocardial infarction or death. Our results suggest a potential role for patient phenotyping to improve risk stratification of patients with normal imaging results. FUNDING: This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R35HL161195 to PS]. The REFINE SPECT database was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R01HL089765 to PS]. MCW was supported by the British Heart Foundation [FS/ICRF/20/26002].

Impact on cardiovascular outcome of coronary revascularization-induced changes in ischemic perfusion defect and myocardial flow reserve.

PURPOSE: We evaluated the impact on cardiovascular outcome of coronary revascularization-induced changes in ischemic total perfusion defect (ITPD) and myocardial flow reserve (MFR) as assessed by 82Rb positron emission tomography (PET)/computed tomography (CT) imaging. METHODS: The study included 102 patients referred to 82Rb PET/CT myocardial perfusion imaging before and after coronary revascularization. All patients were followed for the occurrence of cardiovascular events (cardiac death, nonfatal myocardial infarction, repeated revascularization, and heart failure) after the second imaging study. RESULTS: During a median follow-up of 20 months, 21 events occurred. The clinical characteristics were comparable between patients with and without events. In the overall study population, after revascularization, there was a significant reduction (P < 0.001) of ITPD, while hyperemic myocardial blood flow (MBF) (P < 0.01) and MFR (P < 0.05) significantly improved. Event rate was higher in patients with ITPD (P < 0.005) or MFR (P < 0.001) worsening compared to those with unchanged or improved ITPD or MFR. At Cox univariable analysis, ITPD and MFR worsening resulted in predictors of events (both P < 0.05). Patients with worsening of both ITPD and MFR had the worst event-free survival (log-rank 32.9, P for trend < 0.001). CONCLUSIONS: In patients with stable CAD, worsening of ITPD and MFR after revascularization procedures is associated with higher risk of cardiovascular events. Follow-up MPI with 82Rb PET/CT may improve risk stratification in patients submitted to coronary revascularization.

Cancer care pathways across seven countries in Europe: What are the current obstacles? And how can artificial intelligence help?

BACKGROUND: Cancer poses significant challenges for healthcare professionals across the disease pathway including cancer imaging. This study constitutes part of the user requirement definition of INCISIVE EU project. The project has been designed to explore the full potential of artificial intelligence (AI)-based technologies in cancer imaging to streamline diagnosis and management. The study aimed to map cancer care pathways (breast, prostate, colorectal and lung cancers) across INCISIVE partner countries, and identify bottle necks within these pathways. METHODS: Email interviews were conducted with ten oncology specialised healthcare professionals representing INCISIVE partner countries: Greece, Cyprus, Spain, Italy, Finland, the United Kingdom (UK) and Serbia. A purposive sampling strategy was employed for recruitment and data was collected between December 2020 and April 2021. Data was entered into Microsoft Excel spreadsheet to allow content examination and comparative analysis. RESULTS: The analysed pathways all shared a common characteristic: inequalities in relation to delays in cancer diagnosis and treatment. All the studied countries, except the UK, lacked official national data about diagnostic and therapeutic delays. Furthermore, a considerable variation was noted regarding the availability of imaging and diagnostic services across the seven countries. Several concerns were also noted for inefficiencies/inequalities with regards to national screening for the four investigated cancer types. CONCLUSIONS: Delays in cancer diagnosis and treatment are an ongoing challenge and a source for inequalities. It is important to have systematic reporting of diagnostic and therapeutic delays in all countries to allow the proper estimation of its magnitude and support needed to address it. Our findings also support the orientation of the current policies towards early detection and wide scale adoption and implementation of cancer screening, through research, innovation, and technology. Technologies involving AI can have a great potential to revolutionise cancer care delivery. POLICY SUMMARY: This study highlights the widespread delay in cancer diagnosis across Europe and supports the need for, systematic reporting of delays, improved availability of imaging services, and optimised national screening programs. The goal is to enhance cancer care delivery, encourage early detection, and implement research, innovation, and AI-based technologies for improved cancer imaging.

Cancer care at the time of the fourth industrial revolution: an insight to healthcare professionals' perspectives on cancer care and artificial intelligence.

BACKGROUND: The integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies. METHODS: A mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO. RESULTS: The survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care. Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations. CONCLUSION: HCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.

Age-Specific Cardiovascular Risk Factors for Major Adverse Cardiac Events in Patients Undergoing Myocardial Perfusion Imaging.

BACKGROUND: The prevalence of traditional cardiovascular risk factors shows different age-specific patterns. It is not known whether the prognostic impact of risk factors is similarly age-specific. We evaluated the profiles of cardiovascular risk factors and their prognostic impact on coronary artery disease (CAD) in relation to age. METHODS: We included 3667 patients with suspected or known CAD undergoing stress myocardial perfusion imaging (MPI). We evaluated the risk for major adverse cardiac events (MACE) within three years from the index MPI in patients belonging to three groups according to age tertile distribution: <59, 59-68, and >68 years. Gender, body mass index, diabetes, hypertension, dyslipidemia, family history of CAD, smoking, angina, dyspnea, previous CAD, and MPI outcome were assessed as risk factors by a multivariable Cox's regression. RESULTS: The three-year risk of MACE increased progressively with age and was 9%, 13%, and 18% for each group, respectively (p < 0.0001). Dyspnea and abnormal MPI outcome were significant risk factors for all age groups. Diabetes and smoking were significant from the age of 59 onwards, while hypertension resulted significant for patients older than 68 years. CONCLUSIONS: The number of risk factors was significantly associated with the occurrence of MACE increase with age. It is noteworthy that a personal history of CAD was not useful for risk stratification, while MPI results were.

Prognostic value of myocardial perfusion imaging by cadmium zinc telluride single-photon emission computed tomography in patients with suspected or known coronary artery disease: a systematic review and meta-analysis.

BACKGROUND: Aim of this study was to define the prognostic value of stress myocardial perfusion imaging by cadmium zinc telluride (CZT) single-photon emission computed tomography (SPECT) for prediction of adverse cardiovascular events in patients with known or suspected coronary artery disease (CAD). METHODS AND RESULTS: Studies published until November 2022 were identified by database search. We included studies using stress myocardial perfusion imaging by CZT-SPECT to evaluate subjects with known or suspected CAD and providing primary data of adverse cardiovascular events. Total of 12 studies were finally included recruiting 36,415 patients. Pooled hazard ratio (HR) for the occurrence of adverse events was 2.17 (95% confidence interval, CI, 1.78-2.65) and heterogeneity was 66.1% (P = 0.001). Five studies reported data on adjusted HR for the occurrence of adverse events. Pooled HR was 1.69 (95% CI, 1.44-1.98) and heterogeneity was 44.9% (P = 0.123). Seven studies reported data on unadjusted HR for the occurrence of adverse events. Pooled HR was 2.72 (95% CI, 2.00-3.70). Nine studies reported data useful to calculate separately the incidence rate of adverse events in patients with abnormal and normal myocardial perfusion. Pooled incidence rate ratio was 2.38 (95% CI, 1.39-4.06) and heterogeneity was 84.6% (P < 0.001). The funnel plot showed no evidence of asymmetry (P = 0.517). At meta-regression analysis, we found an association between HR for adverse events and presence of angina symptoms and family history of CAD. CONCLUSIONS: Stress myocardial perfusion imaging by CZT-SPECT is a valuable noninvasive prognostic indicator for adverse cardiovascular events in patients with known or suspected CAD.

Left Ventricular Mechano-Energetic Efficiency Identifies an Early Impairment of Myocardial Blood Flow in Arterial Hypertension.

BACKGROUND: Arterial hypertension causes cardiac functional and structural alterations. In hypertensive patients without flow-limiting epicardial coronary artery disease, we investigated possible relationships between positron emission tomography/computed tomography-derived myocardial blood flow (MBF) and echocardiographic parameters of left ventricular (LV) performance, including mechano-energetic efficiency indexed for myocardial mass (MEEi). METHODS: Seventy-eight hypertensive patients without flow-limiting epicardial coronary artery disease underwent echocardiography, including MEEi computation, and cardiac positron emission tomography/computed tomography with assessment of MBF/mass ratio at rest and after stress and myocardial flow reserve. The lowest MEEi tertile (MEEi<0.031 mL/s/g) was compared to the merged second and third tertiles (MEEi≥0.031). RESULTS: Patients in the lowest MEEi tertile were older, had higher systolic blood pressure and body mass index. They also had higher prevalence of LV hypertrophy, whereas lower resting and stress MBF/mass ratio. MEEi was significantly correlated with both resting (r=0.51; P<0.0001) and hyperemic (r=0.54; P<0.0001) MBF/mass ratios, whereas it was not related to myocardial flow reserve. Delta of MBF/mass ratio was lower in the lowest MEEi tertile than in the highest (P<0.0001). In separate multiple linear regression models, after adjusting for sex, systolic blood pressure, body mass index, prevalence of LV hypertrophy, left atrial volume index, and diuretic therapy, the association between LV MEEi and both hyperemic (beta coefficient=0.44; P=0.003) and resting (beta coefficient=0.35; P=0.008) MBF/mass ratio remained significant. CONCLUSIONS: In hypertensive patients without flow-limiting epicardial coronary artery disease, low values of MEEi could detect an early LV dysfunction involving an impairment of both resting and hyperemic MBF/mass ratios. MEEi has the advantage of simpler detection, cheaper costs than positron emission tomography/computed tomography, and a lack of radiation exposure. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02211365.

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.

Computed tomography and nuclear medicine for the assessment of coronary inflammation: clinical applications and perspectives.

There is increasing evidence that in patients with atherosclerotic cardiovascular disease (ASCVD) under optimal medical therapy, a persisting dysregulation of the lipid and glucose metabolism, associated with adipose tissue dysfunction and inflammation, predicts a substantial residual risk of disease progression and cardiovascular events. Despite the inflammatory nature of ASCVD, circulating biomarkers such as high-sensitivity C-reactive protein and interleukins may lack specificity for vascular inflammation. As known, dysfunctional epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) produce pro-inflammatory mediators and promote cellular tissue infiltration triggering further pro-inflammatory mechanisms. The consequent tissue modifications determine the attenuation of PCAT as assessed and measured by coronary computed tomography angiography (CCTA). Recently, relevant studies have demonstrated a correlation between EAT and PCAT and obstructive coronary artery disease, inflammatory plaque status and coronary flow reserve (CFR). In parallel, CFR is well recognized as a marker of coronary vasomotor function that incorporates the haemodynamic effects of epicardial, diffuse and small-vessel disease on myocardial tissue perfusion. An inverse relationship between EAT volume and coronary vascular function and the association of PCAT attenuation and impaired CFR have already been reported. Moreover, many studies demonstrated that 18F-FDG PET is able to detect PCAT inflammation in patients with coronary atherosclerosis. Importantly, the perivascular FAI (fat attenuation index) showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices by providing a quantitative measure of coronary inflammation. As an indicator of increased cardiac mortality, it could guide early targeted primary prevention in a wide spectrum of patients. In this review, we summarize the current evidence regarding the clinical applications and perspectives of EAT and PCAT assessment performed by CCTA and the prognostic information derived by nuclear medicine.

Radionuclide Tracers for Myocardial Perfusion Imaging and Blood Flow Quantification.

Myocardial perfusion imaging by nuclear cardiology is widely validated for the diagnosis, risk stratification, and management of patients with suspected or known coronary artery disease. Numerous radiopharmaceuticals are available for single-photon emission computed tomography and PET modalities. Each tracer shows advantages and limitations that should be taken into account in performing an imaging examination. This review aimed to summarize the state-of-the-art radiotracers used for myocardial perfusion imaging and blood flow quantification, highlighting the new technologic advances and promising possible applications.

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.

Prevalence of cancer therapy cardiotoxicity as assessed by imaging procedures: A scoping review.

BACKGROUND: Advances in treatment and optimization of chemotherapy protocols have greatly improved survival in cancer patients. Unfortunately, treatment can cause a reduction in left ventricular (LV) ejection fraction (EF) leading to cancer therapy-related cardiac dysfunction (CTRCD). We conducted a scoping review of published literature in order to identify and summarize the reported prevalence of cardiotoxicity evaluated by noninvasive imaging procedures in a wide-ranging of patients referred to cancer treatment as chemotherapy and/or radiation therapy. METHODS: Different databases were checked (PubMed, Embase, and Web of Science) to identify studies published from January 2000 to June 2021. Articles were included if they reported data on LVEF evaluation in oncological patients treated with chemotherapeutic agents and/or radiotherapy, measured by echocardiography and/or nuclear or cardiac magnetic resonance imaging test, providing criteria of CTRCD evaluation such as the specific threshold for LVEF decrease. RESULTS: From 963 citations identified, 46 articles, comprising 6841 patients, met the criteria for the inclusion in the scoping review. The summary prevalence of CTRCD as assessed by imaging procedures in the studies reviewed was 17% (95% confidence interval, 14-20). CONCLUSIONS: The results of our scoping review endorse the recommendations regarding imaging modalities to ensure identification of cardiotoxicity in patients undergoing cancer therapies. However, to improve patient management, more homogeneous CTRCD evaluation studies are required, reporting a detailed clinical assessment of the patient before, during and after treatment.

Myocardial blood flow evaluation with dynamic cadmium-zinc-telluride single-photon emission computed tomography: Bright and dark sides.

Myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) assessment with non-invasive techniques represent an important tool to evaluate both coronary artery disease severity and extent. Currently, cardiac positron emission tomography-computed tomography (PET-CT) is the "gold standard" for the assessment of coronary function and provides accurate estimations of baseline and hyperemic MBF and MFR. Nevertheless, due to the high cost and complexity, PET-CT is not widely used in clinical practice. The introduction of cardiac-dedicated cadmium-zinc-telluride (CZT) cameras has renewed researchers' interest on MBF quantitation by single-photon emission computed tomography (SPECT). Indeed, many studies evaluated MPR and MBF measurements by dynamic CZT-SPECT in different cohorts of patients with suspected or overt coronary artery disease. As well, many others have compared the values obtained by CZT-SPECT to the ones by PET-CT, showing good correlations in detecting significant stenosis, although with different and non-standardized cut-off values. Nevertheless, the lack of standardized protocol for acquisition, reconstruction and elaboration makes more difficult to compare different studies and to further assess the real advantages of MBF quantitation by dynamic CZT-SPECT in clinical routine. Many are the issues involved in the bright and dark sides of dynamic CZT-SPECT. They include different type of CZT cameras, different execution protocols, different tracers with different myocardial extraction fraction and distribution, different software packages with different tools and algorithms, often requiring manual post-processing elaboration. This review article provides a clear summary of the state of the art on MBF and MPR evaluation by dynamic CZT-SPECT and outlines the major issues to solve to optimize this technique.

External validation and update of the J-ACCESS model in an Italian cohort of patients undergoing stress myocardial perfusion imaging.

BACKGROUND: Cardiovascular risk models are based on traditional risk factors and investigations such as imaging tests. External validation is important to determine reproducibility and generalizability of a prediction model. We performed an external validation of t the Japanese Assessment of Cardiac Events and Survival Study by Quantitative Gated SPECT (J-ACCESS) model, developed from a cohort of patients undergoing stress myocardial perfusion imaging. METHODS: We included 3623 patients with suspected or known coronary artery disease undergoing stress single-photon emission computer tomography (SPECT) myocardial perfusion imaging at our academic center between January 2001 and December 2019. RESULTS: In our study population, the J-ACCESS model underestimated the risk of major adverse cardiac events (cardiac death, nonfatal myocardial infarction, and severe heart failure requiring hospitalization) within three-year follow-up. The recalibrations and updated of the model slightly improved the initial performance: C-statistics increased from 0.664 to 0.666 and Brier score decreased from 0.075 to 0.073. Hosmer-Lemeshow test indicated a logistic regression fit only for the calibration slope (P = .45) and updated model (P = .22). In the update model, the intercept, diabetes, and severity of myocardial perfusion defects categorized coefficients were comparable with J-ACCESS. CONCLUSION: The external validation of the J-ACCESS model as well as recalibration models have a limited value for predicting of three-year major adverse cardiac events in our patients. The performance in predicting risk of the updated model resulted superimposable to the calibration slope model.

123I-MIBG imaging in heart failure: impact of comorbidities on cardiac sympathetic innervation.

PURPOSE: Heart failure (HF) is a primary cause of morbidity and mortality worldwide, with significant impact on life quality and extensive healthcare costs. Assessment of myocardial sympathetic innervation function plays a central role in prognosis assessment in HF patients. The aim of this review is to summarize the most recent evidence regarding the clinical applications of iodine-123 metaiodobenzylguanidine (123I-MIBG) imaging in patients with HF and related comorbidities. METHODS: A comprehensive literature search was conducted on PubMed and Web of Science databases. Articles describing the impact of 123I-MIBG imaging on HF and related comorbidities were considered eligible for the review. RESULTS: We collected several data reporting that 123I-MIBG imaging is a safe and non-invasive tool to evaluate dysfunction of cardiac sympathetic neuronal function and to assess risk stratification in HF patients. HF is frequently associated with comorbidities that may affect cardiac adrenergic innervation. Furthermore, HF is frequently associated with comorbidities and chronic conditions, such as diabetes, obesity, kidney disease and others, that may affect cardiac adrenergic innervation. CONCLUSION: Comorbidities and chronic conditions lead to more severe impairment of sympathetic nervous system in patients with HF, with a negative impact on disease progression and outcome. Cardiac imaging with 123I-MIBG can be a useful tool to reduce morbidity and prevent adverse events in HF patients.

Prediction of outcome by 82Rb PET/CT in patients with ischemia and nonobstructive coronary arteries.

BACKGROUND: The purpose of this study was to assess the prognostic value of cardiac 82Rb positron emission tomography (PET)/computed tomography (CT) imaging in patients with myocardial ischemia of nonobstructive coronary arteries (INOCA). METHODS: We retrospectively evaluated 311 INOCA patients who underwent rest stress 82Rb PET/CT. Cardiac end points were cardiac death, myocardial infarction, or late coronary revascularization. A parametric survival model was also used to identify how the variables influenced time to event. RESULTS: During a median follow-up of 37 months (range 6-108), 23 (7%) cardiac events occurred. In patients with events total perfusion defect (TPD) was higher and myocardial flow reserve (MFR) lower compared to those without events (both P < .001). At multivariable Cox analysis, increased TPD (i.e., ≥ 5%) and reduced MFR (i.e., < 2) were predictors of events (both P < .001). At Weibull survival analysis, the highest probability of cardiac events and risk acceleration were observed in patients with both increased TPD and reduced MFR. Annualized event rate was higher in patients with reduced MFR compared to those with preserved MFR (P < .001). CONCLUSION: In patients with INOCA, the combined evaluation of myocardial perfusion and coronary vascular function by 82Rb PET/CT is able to identify those at higher risk of cardiac events.