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The introduction of wire-free microcirculatory resistance index from functional angiography (angio-IMR) promises swift detection of coronary microvascular dysfunction, however it has not been properly validated. We sought to validate angio-IMR against invasive IMR and PET derived microvascular resistance (MVR). Moreover, we studied if angio-IMR could aid in the detection of ischemia with non-obstructive coronary arteries (INOCA). In this investigator-initiated study symptomatic patients underwent [ 15 O]H 2 O positron emission tomography (PET) and invasive angiography with 3-vessel fractional flow reserve (FFR). Invasive IMR was measured in 40 patients. Angio-IMR and QFR were computed retrospectively. MVR was defined as the ratio of mean distal coronary pressure to PET derived coronary flow. PET and QFR/angio-IMR analyses were performed by blinded core labs. The right coronary artery was excluded. A total of 211 patients (mean age 61 ± 9, 148 (70%) male) with 312 vessels with successful angio-IMR analyses were included. Angio-IMR correlated moderately with invasive IMR (r = 0.48, p < 0.01), whereas no correlation was found between angio-IMR and MVR (r=-0.07, p = 0.25). Angio-IMR did not differ for vessels without obstructive coronary artery disease (CAD) (FFR-) but with reduced stress perfusion (PET+) compared to vessels without obstructive CAD (FFR-) with normal stress perfusion (PET-) (median 28.19 IQR 20.42-38.99 vs. 31.67 IQR 23.47-40.63, p = 0.40). Angio-IMR correlated moderately with invasively measured IMR, whereas angio-IMR did not correlate with PET derived MVR. Moreover, angio-IMR did not reliably identify patients with INOCA., Competing Interests: Declarations. Competing interests: RK, JT and JH are employees of Medis Medical Imaging. Disclosures: RK, JT and JH are employees of Medis Medical Imaging. JK has received consultancy fees from GE Healthcare and AstraZeneca and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer and Merck, outside of the submitted work. TvdH has received speaker fees and institutional research grants from Abbott and Philips. PK received research grants from HeartFlow Inc. The remaining authors have nothing to disclose., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Aims: The diagnostic performance of quantitative perfusion cardiac magnetic resonance (QP-CMR) imaging has scarcely been evaluated in patients with a history of coronary artery disease (CAD) and new onset chest pain. The present study compared the diagnostic performance of automated QP-CMR for detection of fractional flow reserve (FFR) defined hemodynamically significant CAD with visual assessment of first-pass stress perfusion CMR (v-CMR) and quantitative [15O]H2O positron emission tomography (PET) imaging in a true head-to-head fashion in patients with prior CAD., Methods and Results: This PACIFIC-2 substudy included 145 symptomatic chronic coronary symptom patients with prior myocardial infarction (MI) and/or percutaneous coronary intervention (PCI). All patients underwent dual-sequence, single bolus perfusion CMR and [15O]H2O PET perfusion imaging followed by invasive coronary angiography with three-vessel FFR. Hemodynamically significant CAD was defined as an FFR ≤0.80. QP-CMR, v-CMR and PET exhibited a sensitivity of 66%, 67%, and 80%, respectively, whereas specificity was 60%, 62%, and 63%. Sensitivity of QP-CMR was lower than PET (P=0.015), whereas specificity of QP-CMR and PET was comparable. Diagnostic accuracy and area under the curve (AUC) of QP-CMR (64% and 0.66) was comparable to both v-CMR (66% [P=NS] and 0.67 (P=NS]) and PET (74% [P=NS] and 0.78 [P=NS])., Conclusions: In patients with prior MI and/or PCI, the diagnostic performance of QP-CMR was comparable to visual assessment of first-pass stress perfusion CMR and quantitative [15O]H2O PET for the detection of hemodynamically significant CAD as defined by FFR., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

The heart depends critically on continuous blood supply, but it is unknown whether cancer itself affects myocardial blood flow (MBF). This study investigated MBF in cancer patients and cardiac morphology in a cancer mice model. MBF was quantified with [ 15 O]H 2 O positron emission tomography at rest in recently diagnosed breast cancer patients and age-matched female controls, and additionally during 10-min exercise in the cancer patients. Cardiac morphological changes were analyzed with a breast cancer mouse model and control mice without tumors. Resting MBF was similar in cancer patients and controls. MBF increased significantly during exercise in cancer patients, and exercising MBF correlated positively with cancer grade. In the mouse model, cancer did not affect heart weight, cardiomyocyte size, myocardial capillary density, or capillary-to-myocyte size ratio. Thus, resting MBF in humans or myocardial capillarity in mice appears not to be affected by breast cancer. The exercise-induced MBF increase in cancer patients with higher histologic grade requires further investigations., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

Aims: Pericoronary adipose tissue (PCAT) attenuation obtained by coronary computed tomography angiography (CCTA) has been associated with coronary inflammation and outcomes. Whether PCAT attenuation is predictive of major adverse cardiac events (MACE) during long-term follow-up is unknown., Methods and Results: Symptomatic patients with coronary artery disease (CAD) who underwent CCTA were included, and clinical outcomes were evaluated. PCAT was measured at all lesions for all three major coronary arteries using semi-automated software. A comparison between patients with and without MACE was made on both a per-lesion and a per-patient level. The predictive value of PCAT attenuation for MACE was assessed in Cox regression models. In 483 patients (63.3 ± 8.5 years, 54.9% men), 1561 lesions were analysed over a median follow-up duration of 9.5 years. The mean PCAT attenuation was not significantly different between patients with and without MACE. At a per-patient level, the adjusted hazard ratio (HR) and 95% confidence interval (CI) for MACE were 0.970 (95% CI: 0.933-1.008, P = 0.121) when the average of all lesions per patient was analysed, 0.992 (95% CI: 0.961-1.024, P = 0.622) when only the most obstructive lesion was evaluated, and 0.981 (95% CI: 0.946-1.016, P = 0.285) when only the lesion with the highest PCAT attenuation per individual was evaluated. Adjusted HRs for vessel-specific PCAT attenuation in the right coronary artery, left anterior descending artery, and left circumflex artery were 0.957 (95% CI: 0.830-1.104, P = 0.548), 0.989 (95% CI: 0.954-1.025, P = 0.550), and 0.739 (95% CI: 0.293-1.865, P = 0.522), respectively, in predicting long-term MACE., Conclusion: In patients referred to CCTA for clinically suspected CAD, PCAT attenuation did not predict MACE during long-term follow-up., Competing Interests: Conflict of interest: The Department of Cardiology of Leiden University Medical Center received research grants from Abbott Vascular, Bayer, Biotronik, Boston Scientific, Edwards Lifesciences, GE Healthcare and Medtronic. J.J.B. received speaker fees from Abbott Vascular, Edwards Lifesciences, and Omron. J.W.J. received research grants from and/or was speaker (with or without lecture fees) on a.o.(CME accredited) meetings sponsored by Amarin, Amgen, Athera, Biotronik, Boston Scientific, Dalcor, Daiichi Sankyo, Lilly, Medtronic, Merck-Schering-Plough, Novartis, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, the Netherlands Heart Foundation, CardioVascular Research the Netherlands (CVON), the Netherlands Heart Institute, and the European Community Framework KP7 Programme. J.K. received consultancy fees from GE Healthcare and Synektik Pharma and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer, and Merck, outside of the submitted work. A.S. received consultancy fees from Astra Zeneca and Pfizer and speaker fees from Abbott, Astra Zeneca, BMS, Janssen, Novartis, and Pfizer. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: To investigate the location-specific prognostic significance of plaque burden, diameter stenosis and plaque morphology., Methods and Results: Patients without a documented cardiac history who underwent coronary computed tomography angiography (CCTA) for suspected coronary artery disease were included. Percentage atheroma volume (PAV), maximum diameter stenosis, and plaque morphology were assessed and classified into proximal, mid, or distal segments of the coronary tree. Major adverse cardiac events (MACE) were defined as death or non-fatal myocardial infarction. Among 2819 patients 267 events (9.5%) occurred during a median follow-up of 6.9 years. When adjusted for traditional risk factors and presence of PAV on other locations, only proximal PAV was independently associated with MACE. However, PAV of the proximal segments was strongly correlated to PAV localized at the mid (R= 0.76) and distal segments (R=0.74, p<0.01 for both). When only adjusted for cardiovascular risk factors, the area under the curve (AUC) to predict MACE for proximal PAV was 0.73 (95%CI 0.69-0.76), which was similar compared to mid PAV (AUC 0.72, 95%CI 0.68-0.76) and distal PAV (AUC 0.72, 95%CI 0.68-0.76). Similar results were obtained using diameter stenosis instead of PAV. The presence of proximal low-attenuation plaque had borderline additional prognostic value., Conclusions: Proximal PAV was the strongest predictor of MACE when adjusted for cardiovascular risk factors and plaque at other locations. However, when presence of plaque was only adjusted for cardiovascular risk factors, proximal, mid, and distal plaque localization showed a similar predictive ability for MACE., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Anatomical and functional imaging identify different phenotypes of coronary artery disease (CAD) that may have implications for lipid-lowering medication (LLM)., Objectives: The aim of this study was to assess the associations between LLM and long-term outcomes after combined anatomical and functional imaging in patients with suspected obstructive CAD., Methods: Consecutive patients (n = 1,973; 41% men; median age: 63 years) underwent coronary computed tomography angiography (CTA) because of suspected CAD. Patients in whom obstructive CAD was not ruled out by CTA underwent ischemia testing by positron emission tomography. Data on LLM purchases were collected until 2 years, and the combined endpoints of death, myocardial infarction, and unstable angina pectoris were assessed at a median of 6.7 years., Results: After imaging, LLM was used by 24% of patients with no CAD, 51% of patients with nonobstructive CAD, 72% of patients with obstructive CAD on CTA without myocardial ischemia, and 91% of patients with myocardial ischemia. The use of LLM decreased during follow-up, with 77% of patients with myocardial ischemia using LLM for 2 years. The use of LLM was associated with a lower annual rate of adverse events in patients with myocardial ischemia (6.1% vs 2.8%; P = 0.032) or obstructive CAD without myocardial ischemia (2.9% vs 1.4%; P = 0.004) but not in patients with nonobstructive CAD (1.5% vs 1.4%; P = 0.89) or no CAD (0.3% vs 0.3%; P = 0.68)., Conclusions: The CAD phenotype defined by anatomical and functional imaging guides the use of LLM. The presence of myocardial ischemia and anatomical obstructive coronary lesions were associated with a long-term outcome benefit from LLM., Competing Interests: Funding Support and Author Disclosures This study was funded by research grants from the Academy of Finland, the Finnish Foundation for Cardiovascular Research, and Turku University Hospital, as a financial support for the submitted work. The funders had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The authors are independent from the funders. The Turku PET Centre has received an unrestricted research grant from Cleerly, Inc. Dr Saraste has received institutional research contracts from AstraZeneca and Precordior; has received speaker fees from Abbott, Novartis, Bayer, AstraZeneca, and Amgen; has participated in Advisory Boards for AstraZeneca, Amgen, Pfizer, and Boehringer Ingelheim; has a membership of the scientific advisory committee for the Finnish Foundation for Cardiovascular Research; and has a board membership for the European Society of Cardiology. Dr Knuuti has received consulting fees from AstraZeneca and GE Healthcare; has received speaker fees from GE Healthcare, Merck, Lundbeck, Bayer, Boehringer-Ingelheim, Pfizer, and Siemens; and has participated on data safety monitoring or advisory boards. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Among patients with obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CTA), downstream positron emission tomography (PET) perfusion imaging can be performed to assess the presence of myocardial ischemia. A novel artificial-intelligence-guided quantitative computed tomography ischemia algorithm (AI-QCT ischemia ) aims to predict ischemia directly from coronary CTA images. We aimed to study the prognostic value of AI-QCT ischemia among patients with obstructive CAD on coronary CTA and normal or abnormal downstream PET perfusion., Methods: AI-QCT ischemia was calculated by blinded analysts among patients from the retrospective coronary CTA cohort at Turku University Hospital, Finland, with obstructive CAD on initial visual reading (diameter stenosis ≥50%) being referred for downstream 15 O-H 2 O-PET adenosine stress perfusion imaging. All coronary arteries with their side branches were assessed by AI-QCT ischemia . Absolute stress myocardial blood flow ≤2.3 ​ml/g/min in ≥2 adjacent segments was considered abnormal. The primary endpoint was death, myocardial infarction, or unstable angina pectoris. The median follow-up was 6.2 [IQR 4.4-8.3] years., Results: 662 of 768 (86%) patients had conclusive AI-QCT ischemia result. In patients with normal 15 O-H 2 O-PET perfusion, an abnormal AI-QCT ischemia result (n ​= ​147/331) vs. normal AI-QCT ischemia result (n ​= ​184/331) was associated with a significantly higher crude and adjusted rates of the primary endpoint (adjusted HR 2.47, 95% CI 1.17-5.21, p ​= ​0.018). This did not pertain to patients with abnormal 15 O-H 2 O-PET perfusion (abnormal AI-QCT ischemia result (n ​= ​269/331) vs. normal AI-QCT ischemia result (n ​= ​62/331); adjusted HR 1.09, 95% CI 0.58-2.02, p ​= ​0.794) (p-interaction ​= ​0.039)., Conclusion: Among patients with obstructive CAD on coronary CTA referred for downstream 15 O-H 2 O-PET perfusion imaging, AI-QCT ischemia showed incremental prognostic value among patients with preserved perfusion by 15 O-H 2 O-PET imaging, but not among those with reduced perfusion., Competing Interests: Declaration of competing interest Dr. Bär received research grants to the institution from Medis Medical Imaging Systems, Bangerter-Rhyner Stiftung (Basel, Switzerland) and Abbott, outside the submitted work. Dr. Saraste received consultancy fees from Astra Zeneca and Pfizer, and speaker fees from Abbott, Astra Zeneca, Janssen, Novartis and Pfizer. Dr. Bax received speaker fees from Abbott. Drs Earls and Min are employees of and hold equity in Cleerly Inc. Dr. Knuuti received consultancy fees from GE Healthcare and Synektik and speaker fees from Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer and Siemens, outside of the submitted work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Aim: Clinical risk scores for coronary artery disease (CAD) are used in clinical practice to select patients for diagnostic testing and therapy. Several studies have proposed that polygenic risk scores (PRSs) can improve the prediction of CAD, but the scores need to be validated in clinical populations with accurately characterized phenotypes. We assessed the predictive power of the three most promising PRSs for the prediction of coronary atherosclerosis and obstructive CAD., Methods: This study was conducted on 943 symptomatic patients with suspected CAD for whom the phenotype was accurately characterized using anatomic and functional imaging. Previously published genome-wide polygenic scores were generated to compare a genetic model based on PRSs with a model based on clinical data. The test and PRS cohorts were predominantly Caucasian of northern European ancestry., Results: All three PRSs predicted coronary atherosclerosis and obstructive CAD statistically significantly. The predictive accuracy of the models combining clinical data and different PRSs varied between 0.778 and 0.805 in terms of the area under the receiver operating characteristic (AUROC), being close to the model including only clinical variables (AUROC 0.769). The difference between the clinical model and combined clinical + PRS model was not significant for PRS1 (p=0.627) and PRS3 (p=0.061). Only PRS2 slightly improved the predictive power of the model (p=0.04). The likelihood ratios showed the very weak diagnostic power of all PRSs., Conclusion: The addition of PRSs to conventional risk factors did not clinically significantly improve the predictive accuracy for either coronary atherosclerosis or obstructive CAD, showing that current PRSs are not justified for routine clinical use in CAD.

Aims: Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims to identify myocardial ischaemia directly from CTA images and may be helpful to improve risk stratification. The aims were to investigate (i) the prognostic value of AI-QCTischaemia amongst symptomatic patients with suspected CAD entering diagnostic imaging with coronary CTA and (ii) the prognostic value of AI-QCTischaemia separately amongst patients with no/non-obstructive CAD (≤50% visual diameter stenosis) and obstructive CAD (>50% visual diameter stenosis)., Methods and Results: For this cohort study, AI-QCTischaemia was calculated by blinded analysts amongst patients with suspected CAD undergoing coronary CTA. The primary endpoint was the composite of death, myocardial infarction (MI), or unstable angina pectoris (uAP) (median follow-up 6.9 years). A total of 1880/2271 (83%) patients had conclusive AI-QCTischaemia result. Patients with an abnormal AI-QCTischaemia result (n = 509/1880) vs. patients with a normal AI-QCTischaemia result (n = 1371/1880) had significantly higher crude and adjusted rates of the primary endpoint [adjusted hazard ratio (HRadj) 1.96, 95% confidence interval (CI) 1.46-2.63, P < 0.001; covariates: age/sex/hypertension/diabetes/smoking/typical angina]. An abnormal AI-QCTischaemia result was associated with significantly higher crude and adjusted rates of the primary endpoint amongst patients with no/non-obstructive CAD (n = 1373/1847) (HRadj 1.81, 95% CI 1.09-3.00, P = 0.022), but not amongst those with obstructive CAD (n = 474/1847) (HRadj 1.26, 95% CI 0.75-2.12, P = 0.386) (P-interaction = 0.032)., Conclusion: Amongst patients with suspected CAD, an abnormal AI-QCTischaemia result was associated with a two-fold increased adjusted rate of long-term death, MI, or uAP. AI-QCTischaemia may be useful to improve risk stratification, especially amongst patients with no/non-obstructive CAD on coronary CTA., Competing Interests: Conflict of interest: S.B. reports research grants to the institution from Medis Medical Imaging Systems, Bangerter-Rhyner Stiftung (Basel, Switzerland), and Abbott, outside the submitted work. A.S. received consultancy fees from Astra Zeneca and Pfizer, and speaker fees from Abbott, Astra Zeneca, and Novartis. J.J.B. received speaker fees from Abbott. J.P.E. and J.K.M. are employees of and hold equity in Cleerly Inc. J.K. received consultancy fees from GE Healthcare and Synektik Pharma and speaker fees from Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer, and Siemens, outside of the submitted work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: To evaluate the incremental value of positron emission tomography (PET) myocardial perfusion imaging (MPI) over coronary computed tomography angiography (CCTA) in predicting short- and long-term outcome using machine learning (ML) approaches., Methods and Results: A total of 2411 patients with clinically suspected coronary artery disease (CAD) underwent CCTA, out of whom 891 patients were admitted to downstream PET MPI for haemodynamic evaluation of obstructive coronary stenosis. Two sets of Extreme Gradient Boosting (XGBoost) ML models were trained, one with all the clinical and imaging variables (including PET) and the other with only clinical and CCTA-based variables. Difference in the performance of the two sets was analysed by means of area under the receiver operating characteristic curve (AUC). After the removal of incomplete data entries, 2284 patients remained for further analysis. During the 8-year follow-up, 210 adverse events occurred including 59 myocardial infarctions, 35 unstable angina pectoris, and 116 deaths. The PET MPI data improved the outcome prediction over CCTA during the first 4 years of the observation time and the highest AUC was at the observation time of Year 1 (0.82, 95% confidence interval 0.804-0.827). After that, there was no significant incremental prognostic value by PET MPI., Conclusion: PET MPI variables improve the prediction of adverse events beyond CCTA imaging alone for the first 4 years of follow-up. This illustrates the complementary nature of anatomic and functional information in predicting the outcome of patients with suspected CAD., Competing Interests: Conflict of interest: J.K. received consultancy fees from GE Healthcare and AstraZeneca and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer, and Merck, outside of the submitted work. A.S. received consultancy fees from Amgen and Astra Zeneca, Boehringer-Ingelheim, and Pfizer, and speaker fees from Abbott, Astra Zeneca, and Bayer. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: We sought to evaluate the mechanism of angiotensin receptor-neprilysin inhibitor (ARNI) sacubitril/valsartan therapy and compare it with a valsartan-only control group in patients with heart failure with reduced ejection fraction (HFrEF)., Methods and Results: The study was a phase IV, prospective, randomized, double-blind, parallel-group study in patients with New York Heart Association class II-III heart failure and left ventricular ejection fraction (LVEF) ≤35%. During a 6-week run-in period, all patients received valsartan therapy, which was up-titrated to the highest tolerated dose level (80 mg bid or 160 mg bid) and then randomized to either valsartan or sacubitril/valsartan. Myocardial oxygen consumption, energetic efficiency of cardiac work, cardiac and systemic haemodynamics were quantified using echocardiography and 11 C-acetate positron emission tomography before and after 6 weeks of therapy (on stable dose) in 55 patients (ARNI group: n = 27, mean age 63 ± 10 years, LVEF 29.2 ± 10.4%; and valsartan-only control group: n = 28, mean age 64 ± 8 years, LVEF 29.0 ± 7.3%; all p = NS). The energetic efficiency of cardiac work remained unchanged in both treatment arms. However, both diastolic (-4.5 mmHg; p = 0.026) and systolic blood pressure (-9.8 mmHg; p = 0.0007), myocardial perfusion (-0.054 ml/g/min; p = 0.045), and left ventricular mechanical work (-296; p = 0.038) decreased significantly in the ARNI group compared to the control group. Although myocardial oxygen consumption decreased in the ARNI group (-5.4%) compared with the run-in period and remained unchanged in the control group (+0.5%), the between-treatment group difference was not significant (p = 0.088)., Conclusions: We found no differences in the energetic efficiency of cardiac work between ARNI and valsartan-only groups in HFrEF patients. However, ARNI appears to have haemodynamic and cardiac mechanical effects over valsartan in heart failure patients., (© 2023 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: In chronic coronary syndrome (CCS) patients with documented coronary artery disease (CAD), ischaemia detection by myocardial perfusion imaging (MPI) and an invasive approach are viable diagnostic strategies. We compared the diagnostic performance of quantitative flow ratio (QFR) with single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance imaging (CMR) in patients with prior CAD [previous percutaneous coronary intervention (PCI) and/or myocardial infarction (MI)]., Methods and Results: This PACIFIC-2 sub-study evaluated 189 CCS patients with prior CAD for inclusion. Patients underwent SPECT, PET, and CMR followed by invasive coronary angiography with fractional flow reserve (FFR) measurements of all major coronary arteries (N = 567), except for vessels with a sub-total or chronic total occlusion. Quantitative flow ratio computation was attempted in 488 (86%) vessels with measured FFR available (FFR ≤0.80 defined haemodynamically significant CAD). Quantitative flow ratio analysis was successful in 334 (68%) vessels among 166 patients and demonstrated a higher accuracy (84%) and sensitivity (72%) compared with SPECT (66%, P < 0.001 and 46%, P = 0.001), PET (65%, P < 0.001 and 58%, P = 0.032), and CMR (72%, P < 0.001 and 33%, P < 0.001). The specificity of QFR (87%) was similar to that of CMR (83%, P = 0.123) but higher than that of SPECT (71%, P < 0.001) and PET (67%, P < 0.001). Lastly, QFR exhibited a higher area under the receiver operating characteristic curve (0.89) than SPECT (0.57, P < 0.001), PET (0.66, P < 0.001), and CMR (0.60, P < 0.001)., Conclusion: QFR correlated better with FFR in patients with prior CAD than MPI, as reflected in the higher diagnostic performance measures for detecting FFR-defined, vessel-specific, significant CAD., Competing Interests: Conflict of interests: J.H.R., R.A.K., and J.T. are employees of Medis Medical Imaging. J.K. received consultancy fees from GE Healthcare and AstraZeneca and speaker fees from GE Healthcare, Bayer, Lundbeck, and Merck. P.K. received research grants from HeartFlow Inc. All others have no conflict of interests to disclose., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Machine Learning (ML) allows integration of the numerous variables delivered by cardiac PET/CT, while traditional survival analysis can provide explainable prognostic estimates from a restricted number of input variables. We implemented a hybrid ML-and-survival analysis of multimodal PET/CT data to identify patients who developed myocardial infarction (MI) or death in long-term follow up., Methods: Data from 739 intermediate risk patients who underwent coronary CT and selectively stress 15 O-water-PET perfusion were analyzed for the occurrence of MI and all-cause mortality. Images were evaluated segmentally for atherosclerosis and absolute myocardial perfusion through 75 variables that were integrated through ML into an ML-CCTA and an ML-PET score. These scores were then modeled along with clinical variables through Cox regression. This hybridized model was compared against an expert interpretation-based and a calcium score-based model., Results: Compared with expert- and calcium score-based models, the hybridized ML-survival model showed the highest performance (CI .81 vs .71 and .64). The strongest predictor for outcomes was the ML-CCTA score., Conclusion: Prognostic modeling of PET/CT data for the long-term occurrence of adverse events may be improved through ML imaging score integration and subsequent traditional survival analysis with clinical variables. This hybridization of methods offers an alternative to traditional survival modeling of conventional expert image scoring and interpretation., (© 2023. The Author(s).)

Recently, PET systems with a long axial field of view have become the current state of the art. Total-body PET scanners enable unique possibilities for scientific research and clinical diagnostics, but this new technology also raises numerous challenges. A key advantage of total-body imaging is that having all the organs in the field of view allows studying biologic interaction of all organs simultaneously. One of the new, promising imaging techniques is total-body quantitative perfusion imaging. Currently, 15 O-labeled water provides a feasible option for quantitation of tissue perfusion at the total-body level. This review summarizes the status of the methodology and the analysis and provides examples of preliminary findings on applications of quantitative parametric perfusion images for research and clinical work. We also describe the opportunities and challenges arising from moving from single-organ studies to modeling of a multisystem approach with total-body PET, and we discuss future directions for total-body imaging., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Coronary flow capacity (CFC) is a measure that integrates hyperemic myocardial blood flow and coronary flow reserve to quantify the pathophysiological impact of coronary artery disease on vasodilator capacity. This study explores the prognostic value of modified CFC derived from [ 15 O]H 2 O positron emission tomography perfusion imaging., Methods: Quantitative rest/stress perfusion measurements were obtained from 1300 patients with known or suspected coronary artery disease. Patients were classified as having myocardial steal (n=38), severely reduced CFC (n=141), moderately reduced CFC (n=394), minimally reduced CFC (n=245), or normal flow (n=482) using previously defined thresholds. The end point was a composite of death and nonfatal myocardial infarction., Results: During a median follow-up of 5.5 (interquartile range, 3.7-7.8) years, the end point occurred in 153 (12%) patients. Myocardial steal (hazard ratio [HR], 6.70 [95% CI, 3.21-13.99]; P <0.001), severely reduced CFC (HR, 2.35 [95% CI, 1.16-4.78]; P =0.018), and moderately reduced CFC (HR, 1.95 [95% CI, 1.11-3.41]; P =0.020) were associated with worse prognosis compared with normal flow, after adjusting for clinical characteristics. Similarly, in the overall population, increased resting myocardial blood flow (HR, 3.05 [95% CI, 1.68-5.54]; P <0.001), decreased hyperemic myocardial blood flow (HR, 0.68 [95% CI, 0.52-0.90]; P =0.007) and decreased coronary flow reserve (HR, 0.55 [95% CI, 0.42-0.71]; P <0.001) were independently associated with adverse outcome. In a model adjusted for the combined use of perfusion metrics, modified CFC demonstrated independent prognostic value (overall P =0.017)., Conclusions: [ 15 O]H 2 O positron emission tomography-derived resting myocardial blood flow, hyperemic myocardial blood flow, coronary flow reserve, and CFC are prognostic factors for death and nonfatal myocardial infarction in patients with known or suspected coronary artery disease. Importantly, after adjustment for clinical characteristics and the combined use of [ 15 O]H 2 O positron emission tomography perfusion metrics, modified CFC remained independently associated with adverse outcome., Competing Interests: Disclosures None.

Aims: Combined anatomical and functional imaging enables detection of non-obstructive and obstructive coronary artery disease (CAD) as well as myocardial ischaemia. We evaluated sex differences in disease profile and outcomes after combined computed tomography angiography (CTA) and positron emission tomography (PET) perfusion imaging in patients with suspected obstructive CAD., Methods and Results: We retrospectively evaluated 1948 patients (59% women) referred for coronary CTA due to suspected CAD during the years 2008-2016. Patients with a suspected obstructive lesion on coronary CTA (n = 657) underwent 15O-water PET to assess stress myocardial blood flow (MBF). During a mean follow-up of 6.8 years, 182 adverse events (all-cause death, myocardial infarction, or unstable angina) occurred. Women had more often normal coronary arteries (42% vs. 22%, P < 0.001) and less often abnormal stress MBF (9% vs. 28%, P < 0.001) than men. The annual adverse event rate was lower in women vs. men (1.2% vs. 1.7%, P = 0.02). Both in women and men, coronary calcification, non-obstructive CAD, and abnormal stress MBF were independent predictors of events. Abnormal stress MBF was associated with 5.0- and 5.6-fold adverse event rates in women and men, respectively. There was no interaction between sex and coronary calcification, non-obstructive CAD, or abnormal stress MBF in terms of predicting adverse events., Conclusion: Among patients evaluated for chronic chest pain, women have a lower prevalence of ischaemic CAD and a lower rate of adverse events. Combined coronary CTA and PET myocardial perfusion imaging predict outcomes equally in women and men., Competing Interests: Conflict of interest: Dr. Knuuti received consultancy fees from GE Healthcare and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer-Ingelheim, Pfizer, Siemens, and Merck, outside of the submitted work. Dr. Saraste received consultancy fees from Amgen and Astra Zeneca, Boehringer Ingelheim and Pfizer, and speaker fees from Abbott, Astra Zeneca, and Bayer outside of the submitted work. Dr. Bax received speaker fees from Abbot Vascular. The Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands has received unrestricted research grants from Bayer, Abbott Vascular, Medtronic, Biotronik, Boston Scientific, GE Healthcare, and Edwards Lifesciences. Other authors have no conflicts of interest to declare., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)