Macrophage mannose receptor CD206 targeting of fluoride-18 labeled mannosylated dextran: A validation study in mice.

PURPOSE: Aluminum fluoride-18-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid-conjugated mannosylated dextran derivative (Al[18F]F-NOTA-D10CM) is a new tracer for PET imaging. We report here on in vitro and in vivo validation of the tracer's ability to target the macrophage mannose receptor CD206. METHODS: First, the uptake of intravenously (i.v.) administered Al[18F]F-NOTA-D10CM was compared between wild-type (WT) and CD206-/- knockout (KO) mice. C57BL/6N mice were injected with complete Freund's adjuvant (CFA) in the left hind leg and the uptake of Al[18F]F-NOTA-D10CM after i.v. or intradermal (i.d.) injection was studied at 5 and 14 days after CFA induction of inflammation. Healthy C57BL/6N mice were studied as controls. Mice underwent PET/CT on consecutive days with [18F]FDG, i.v. Al[18F]F-NOTA-D10CM, and i.d. Al[18F]F-NOTA-D10CM. After the last imaging, Al[18F]F-NOTA-D10CM was i.v. injected for an ex vivo biodistribution study and autoradiography of inflamed tissues. Blood plasma samples were analyzed using high-performance liquid chromatography. To evaluate the specificity of Al[18F]F-NOTA-D10CM binding, an in vitro competitive displacement study was performed on inflamed tissue sections using autoradiography. CD206 expression was assessed by immunohistochemical staining. RESULTS: Compared with WT mice, the uptake of Al[18F]F-NOTA-D10CM was significantly lower in several CD206-/- KO mice tissues, including liver (SUV 8.21 ± 2.51 vs. 1.06 ± 0.16, P < 0.001) and bone marrow (SUV 1.63 ± 0.37 vs. 0.22 ± 0.05, P < 0.0001). The uptake of i.v. injected Al[18F]F-NOTA-D10CM was significantly higher in inflamed ankle joint (SUV 0.48 ± 0.13 vs. 0.18 ± 0.05, P < 0.0001) and inflamed foot pad skin (SUV 0.41 ± 0.10 vs. 0.04 ± 0.01, P < 0.0001) than in the corresponding tissues in healthy mice. The i.d.-injected Al[18F]F-NOTA-D10CM revealed differences between CFA-induced lymph node activation and lymph nodes in healthy mice. Ex vivo γ-counting, autoradiography, and immunohistochemistry supported the results, and a decrease of ~ 80% in the binding of Al[18F]F-NOTA-D10CM in the displacement study with excess NOTA-D10CM confirmed that tracer binding was specific. At 60 min after i.v. injection, an average 96.70% of plasma radioactivity was derived from intact Al[18F]F-NOTA-D10CM, indicating good in vivo stability. The uptake of Al[18F]F-NOTA-D10CM into inflamed tissues was positively associated with the area percentage of CD206-positive staining. CONCLUSION: The uptake of mannosylated dextran derivative Al[18F]F-NOTA-D10CM correlated with CD206 expression and the tracer appears promising for inflammation imaging.

A systematic review for the evidence of recommendations and guidelines in hybrid nuclear cardiovascular imaging.

OBJECTIVES: This study aimed to evaluate the level of evidence of expert recommendations and guidelines for clinical indications and procedurals in hybrid nuclear cardiovascular imaging. METHODS: From inception to August 2023, a PubMed literature analysis of the latest version of guidelines for clinical hybrid cardiovascular imaging techniques including SPECT(/CT), PET(/CT), and PET(/MRI) was performed in two categories: (1) for clinical indications for all-in primary diagnosis; subgroup in prognosis and therapy evaluation; and for (2) imaging procedurals. We surveyed to what degree these followed a standard methodology to collect the data and provide levels of evidence, and for which topic systematic review evidence was executed. RESULTS: A total of 76 guidelines, published between 2013 and 2023, were included. The evidence of guidelines was based on systematic reviews in 7.9% of cases, non-systematic reviews in 47.4% of cases, a mix of systematic and non-systematic reviews in 19.7%, and 25% of guidelines did not report any evidence. Search strategy was reported in 36.8% of cases. Strengths of recommendation were clearly reported in 25% of guidelines. The notion of external review was explicitly reported in 23.7% of cases. Finally, the support of a methodologist was reported in 11.8% of the included guidelines. CONCLUSION: The use of evidence procedures for developing for evidence-based cardiovascular hybrid imaging recommendations and guidelines is currently suboptimal, highlighting the need for more standardized methodological procedures.

Explainable deep-learning-based ischemia detection using hybrid O-15 H2O perfusion positron emission tomography and computed tomography imaging with clinical data.

BACKGROUND: We developed an explainable deep-learning (DL)-based classifier to identify flow-limiting coronary artery disease (CAD) by O-15 H2O perfusion positron emission tomography computed tomography (PET/CT) and coronary CT angiography (CTA) imaging. The classifier uses polar map images with numerical data and visualizes data findings. METHODS: A DLmodel was implemented and evaluated on 138 individuals, consisting of a combined image-and data-based classifier considering 35 clinical, CTA, and PET variables. Data from invasive coronary angiography were used as reference. Performance was evaluated with clinical classification using accuracy (ACC), area under the receiver operating characteristic curve (AUC), F1 score (F1S), sensitivity (SEN), specificity (SPE), precision (PRE), net benefit, and Cohen's Kappa. Statistical testing was conducted using McNemar's test. RESULTS: The DL model had a median ACC = 0.8478, AUC = 0.8481, F1S = 0.8293, SEN = 0.8500, SPE = 0.8846, and PRE = 0.8500. Improved detection of true-positive and false-negative cases, increased net benefit in thresholds up to 34%, and comparable Cohen's kappa was seen, reaching similar performance to clinical reading. Statistical testing revealed no significant differences between DL model and clinical reading. CONCLUSIONS: The combined DL model is a feasible and an effective method in detection of CAD, allowing to highlight important data findings individually in interpretable manner.

Molecular Imaging of Heart Failure: An Update and Future Trends.

Molecular imaging can detect and quantify pathophysiological processes underlying heart failure, complementing evaluation of cardiac structure and function with other imaging modalities. Targeted tracers have enabled assessment of various cellular and subcellular mechanisms of heart failure aiming for improved phenotyping, risk stratification, and personalized therapy. This review outlines the current status of molecular imaging in heart failure, accompanied with discussion on novel developments. The focus is on radionuclide methods with data from clinical studies. Imaging of myocardial metabolism can identify left ventricle dysfunction caused by myocardial ischemia that may be reversible after revascularization in the presence of viable myocardium. In vivo imaging of active inflammation and amyloid deposition have an established role in the detection of cardiac sarcoidosis and transthyretin amyloidosis. Innervation imaging has well documented prognostic value in predicting heart failure progression and arrhythmias. Tracers specific for inflammation, angiogenesis and myocardial fibrotic activity are in earlier stages of development, but have demonstrated potential value in early characterization of the response to myocardial injury and prediction of cardiac function over time. Early detection of disease activity is a key for transition from medical treatment of clinically overt heart failure towards a personalized approach aimed at supporting repair and preventing progressive cardiac dysfunction.

Polygenic Risk Scores in Predicting Coronary Artery Disease in Symptomatic Patients. A Validation Study.

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.

Deep generative denoising networks enhance quality and accuracy of gated cardiac PET data.

BACKGROUND: Cardiac positron emission tomography (PET) can visualize and quantify the molecular and physiological pathways of cardiac function. However, cardiac and respiratory motion can introduce blurring that reduces PET image quality and quantitative accuracy. Dual cardiac- and respiratory-gated PET reconstruction can mitigate motion artifacts but increases noise as only a subset of data are used for each time frame of the cardiac cycle. AIM: The objective of this study is to create a zero-shot image denoising framework using a conditional generative adversarial networks (cGANs) for improving image quality and quantitative accuracy in non-gated and dual-gated cardiac PET images. METHODS: Our study included retrospective list-mode data from 40 patients who underwent an 18F-fluorodeoxyglucose (18F-FDG) cardiac PET study. We initially trained and evaluated a 3D cGAN-known as Pix2Pix-on simulated non-gated low-count PET data paired with corresponding full-count target data, and then deployed the model on an unseen test set acquired on the same PET/CT system including both non-gated and dual-gated PET data. RESULTS: Quantitative analysis demonstrated that the 3D Pix2Pix network architecture achieved significantly (p value<0.05) enhanced image quality and accuracy in both non-gated and gated cardiac PET images. At 5%, 10%, and 15% preserved count statistics, the model increased peak signal-to-noise ratio (PSNR) by 33.7%, 21.2%, and 15.5%, structural similarity index (SSIM) by 7.1%, 3.3%, and 2.2%, and reduced mean absolute error (MAE) by 61.4%, 54.3%, and 49.7%, respectively. When tested on dual-gated PET data, the model consistently reduced noise, irrespective of cardiac/respiratory motion phases, while maintaining image resolution and accuracy. Significant improvements were observed across all gates, including a 34.7% increase in PSNR, a 7.8% improvement in SSIM, and a 60.3% reduction in MAE. CONCLUSION: The findings of this study indicate that dual-gated cardiac PET images, which often have post-reconstruction artifacts potentially affecting diagnostic performance, can be effectively improved using a generative pre-trained denoising network.

PET imaging of unruptured intracranial aneurysm inflammation (PET-IA) study: a feasibility study protocol.

INTRODUCTION: Positron emission tomography (PET) imaging can be used to evaluate arterial wall inflammation in extracranial vascular diseases. However, the application of PET imaging in unruptured intracranial aneurysms (UIA) remains unexplored. Our objective is to investigate feasibility of PET imaging using 18F-FDG and 68Ga-DOTANOC tracers to evaluate arterial wall inflammation in UIA. METHODS AND ANALYSIS: This PET imaging feasibility study will enrol patients scheduled for surgical treatment of UIA. The study subjects will undergo PET imaging of the intracranial arteries within 1 month before planned surgery. The imaging protocol includes 18F-FDG PET MRI, MRA with gadolinium enhancement, and 68Ga-DOTANOC PET CT. The study will also involve preoperative blood samples, intraoperative cerebrospinal fluid (CSF) samples, and aneurysm sac biopsy. Planned sample size is at least 18 patients. Primary outcome is uptake of 18F-FDG or 68Ga-DOTANOC in intracranial arterial aneurysms compared with contralateral normal vessel as maximum standardised uptake value or target-to-blood pool ratio and correlation of uptake of 18F-FDG or 68Ga-DOTANOC to aneurysm histological findings. Secondary outcomes include estimating the correlations between uptake of 18F-FDG or 68Ga-DOTANOC and histological findings with blood and CSF miRNA-levels, arterial wall enhancement in gadolinium enhanced MRA, aneurysm size and shape, smoking, hypertension, and location of the aneurysm. ETHICS AND DISSEMINATION: This study is approved by the Human Research Ethics Committee of the Hospital District of Southwest Finland, Finnish Medicines Agency Fimea, and Turku University Hospital. Findings will be disseminated through peer-reviewed journal articles and presentations at national and international conferences. TRIAL REGISTRATION NUMBER: NCT04715503.

Prognostic value of a novel artificial intelligence-based coronary CTA-derived ischemia algorithm among patients with normal or abnormal myocardial perfusion.

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-QCTischemia) aims to predict ischemia directly from coronary CTA images. We aimed to study the prognostic value of AI-QCTischemia among patients with obstructive CAD on coronary CTA and normal or abnormal downstream PET perfusion. METHODS: AI-QCTischemia 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 15O-H2O-PET adenosine stress perfusion imaging. All coronary arteries with their side branches were assessed by AI-QCTischemia. Absolute stress myocardial blood flow ≤2.3 â€‹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-QCTischemia result. In patients with normal 15O-H2O-PET perfusion, an abnormal AI-QCTischemia result (n â€‹= â€‹147/331) vs. normal AI-QCTischemia result (n â€‹= â€‹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 â€‹= â€‹0.018). This did not pertain to patients with abnormal 15O-H2O-PET perfusion (abnormal AI-QCTischemia result (n â€‹= â€‹269/331) vs. normal AI-QCTischemia result (n â€‹= â€‹62/331); adjusted HR 1.09, 95% CI 0.58-2.02, p â€‹= â€‹0.794) (p-interaction â€‹= â€‹0.039). CONCLUSION: Among patients with obstructive CAD on coronary CTA referred for downstream 15O-H2O-PET perfusion imaging, AI-QCTischemia showed incremental prognostic value among patients with preserved perfusion by 15O-H2O-PET imaging, but not among those with reduced perfusion.

Preliminary protocol for measuring the reproducibility and accuracy of flow values on digital PET/CT systems in [15O]H2O myocardial perfusion imaging using a flow phantom.

BACKGROUND: Several factors may decrease the accuracy of quantitative PET myocardial perfusion imaging (MPI). It is therefore essential to ensure that myocardial blood flow (MBF) values are reproducible and accurate, and to design systematic protocols to achieve this. Until now, no systematic phantom protocols have been available to assess the technical factors affecting measurement accuracy and reproducibility in MPI. MATERIALS AND METHODS: We implemented a standard measurement protocol, which applies a flow phantom in order to compare image-derived flow values with respect to a ground truth flow value with [15O]H2O MPI performed on both a Discovery MI (DMI-20, GE Healthcare) and a Biograph Vision 600 (Vision-600, Siemens Healthineers) system. Both systems have automatic [15O]H2O radio water generators (Hidex Oy) individually installed, allowing us to also study the differences occurring due to two different bolus delivery systems. To investigate the technical factors contributing to the modelled flow values, we extracted the [15O]H2O bolus profiles, the flow values from the kinetic modeling (Qin and Qout), and finally calculated their differences between test-retest measurements on both systems. RESULTS: The measurements performed on the DMI-20 system produced Qin and Qout values corresponging to each other as well as to the reference flow value across all test-retest measurements. The repeatability differences on DMI-20 were 2.1% ± 2.6% and 3.3% ± 4.1% for Qin and Qout, respectively. On Vision-600 they were 10% ± 8.4% and 11% ± 10% for Qin and Qout, respectively. The measurements performed on the Vision-600 system showed more variation between Qin and Qout values across test-retest measurements and exceeded 15% difference in 7/24 of the measurements. CONCLUSIONS: A preliminary protocol for measuring the accuracy and reproducibility of flow values in [15O]H2O MPI between digital PET/CT systems was assessed. The test-retest reproducibility falls below 15% in majority of the measurements conducted between two individual injector systems and two digital PET/CT systems. This study highlights the importance of implementing a standardized bolus injection and delivery protocol and importance of assessing technical factors affecting flow value reproducibility, which should be carefully investigated in a multi-center setting.

Natural History of Myocardial αvß3 Integrin Expression After Acute Myocardial Infarction: Correlation with Changes in Myocardial Blood Flow.

Angiogenesis is an essential part of the cardiac repair process after myocardial infarction, but its spatiotemporal dynamics remain to be fully deciphered.68Ga-NODAGA-Arg-Gly-Asp (RGD) is a PET tracer targeting αvß3 integrin expression, which is a marker of angiogenesis. Methods: In this prospective single-center trial, we aimed to monitor angiogenesis through myocardial integrin αvß3 expression in 20 patients with ST-segment elevation myocardial infarction (STEMI). In addition, the correlations between the expression levels of myocardial αvß3 integrin and the subsequent changes in 82Rb PET/CT parameters, including rest and stress myocardial blood flow (MBF), myocardial flow reserve (MFR), and wall motion abnormalities, were assessed. The patients underwent 68Ga-NODAGA-RGD PET/CT and rest and stress 82Rb-PET/CT at 1 wk, 1 mo, and 3 mo after STEMI. To assess 68Ga-NODAGA-RGD uptake, the summed rest 82Rb and 68Ga-NODAGA-RGD images were coregistered, and segmental SUVs were calculated (RGD SUV). Results: At 1 wk after STEMI, 19 participants (95%) presented increased 68Ga-NODAGA-RGD uptake in the infarcted myocardium. Seventeen participants completed the full imaging series. The values of the RGD SUV in the infarcted myocardium were stable 1 mo after STEMI (1 wk vs. 1 mo, 1.47 g/mL [interquartile range (IQR), 1.37-1.64 g/mL] vs. 1.47 g/mL [IQR, 1.30-1.66 g/mL]; P = 0.9), followed by a significant partial decrease at 3 mo (1.32 g/mL [IQR, 1.12-1.71 g/mL]; P = 0.011 vs. 1 wk and 0.018 vs. 1 mo). In segment-based analysis, positive correlations were found between RGD SUV at 1 wk and the subsequent changes in stress MBF (Spearman ρ: r = 0.17, P = 0.0033) and MFR (Spearman ρ: r = 0.31, P < 0.0001) at 1 mo. A negative correlation was found between RGD SUV at 1 wk and the subsequent changes in wall motion abnormalities at 3 mo (Spearman ρ: r = -0.12, P = 0.035). Conclusion: The present study found that αvß3 integrin expression is significantly increased in the infarcted myocardium 1 wk after STEMI. This expression remains stable after 1 mo and partially decreases after 3 mo. Initial αvß3 integrin expression at 1 wk is significantly weakly correlated with subsequent improvements in stress MBF, MFR, and wall motion analysis.

Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors.

BACKGROUND: Heart failure (HF) is the leading cause of hospitalization in individuals over 65 years of age. Identifying noninvasive methods to detect HF may address the epidemic of HF. Seismocardiography which measures cardiac vibrations transmitted to the chest wall has recently emerged as a promising technology to detect HF. OBJECTIVES: In this multicenter study, the authors examined whether seismocardiography using commercially available smartphones can differentiate control subjects from patients with stage C HF. METHODS: Both inpatients and outpatients with HF were enrolled from Finland and the United States. Inpatients with HF were assessed within 2 days of admission, and outpatients were assessed in the ambulatory setting. In a prespecified pooled data analysis, algorithms were derived using logistic regression and then validated using a bootstrap aggregation method. RESULTS: A total of 217 participants with HF (174 inpatients and 172 outpatients) and 786 control subjects from cardiovascular clinics were enrolled. The mean age of participants with acute HF was 64 ± 13 years, 64.9% were male, left ventricular ejection fraction was 39% ± 15%, and median N-terminal pro-B-type natriuretic peptide was 5,778 ng/L (Q1-Q3: 1,933-6,703). The majority (74%) of participants with HF had reduced EF, and 38% had atrial fibrillation. Across both HF cohorts, the algorithms had an area under the receiver operating characteristic curve of 0.95 with a sensitivity of 85%, specificity of 90%, and accuracy of 89% for the detection of HF, with a decision threshold of 0.5. The positive and negative likelihood ratios were 8.50 and 0.17, respectively. The accuracy of the algorithms was not significantly different in subgroups based on age, sex, body mass index, and atrial fibrillation. CONCLUSIONS: Smartphone-based assessment of cardiac function using seismocardiography is feasible and differentiates patients with HF from control subjects with high diagnostic accuracy. (Recognition of Heart Failure With Micro Electro-mechanical Sensors FI; NCT04444583; Recognition of Heart Failure With Micro Electro-mechanical Sensors [NCT04378179]; Detection of Coronary Artery Disease With Micro Electro-mechanical Sensors; NCT04290091).

Location-Specific Prognostic Significance of Plaque Burden, Stenosis, and Plaque Morphology in Coronary Artery Disease.

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.

Pericoronary adipose tissue for predicting long-term outcome.

AIMS: The 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. Comparison between patients with versus without MACE were performed both on per lesion and per patient basis. 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 analyzed over a median follow-up duration of 9.5 years. The mean PCAT attenuation was not significantly different between patients with versus without MACE. At a patient level, the adjusted hazard ratio (HR) and 95% confidence interval (CI) for MACE was 0.970 (CI:0.933-1.008, p=0.121) when analyzing the average of all lesions per patient, 0.992 (CI:0.961-1.024, p=0.622) when only the most obstructive lesion was evaluated, and 0.981 (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 (CI:0.830-1.104, p=0.548), 0.989 (CI:0.954-1.025, p=0.550) and 0.739 (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.

Total-Body PET/CT Applications in Cardiovascular Diseases: A Perspective Document of the SNMMI Cardiovascular Council.

Digital PET/CT systems with a long axial field of view have become available and are emerging as the current state of the art. These new camera systems provide wider anatomic coverage, leading to major increases in system sensitivity. Preliminary results have demonstrated improvements in image quality and quantification, as well as substantial advantages in tracer kinetic modeling from dynamic imaging. These systems also potentially allow for low-dose examinations and major reductions in acquisition time. Thereby, they hold great promise to improve PET-based interrogation of cardiac physiology and biology. Additionally, the whole-body coverage enables simultaneous assessment of multiple organs and the large vascular structures of the body, opening new opportunities for imaging systemic mechanisms, disorders, or treatments and their interactions with the cardiovascular system as a whole. The aim of this perspective document is to debate the potential applications, challenges, opportunities, and remaining challenges of applying PET/CT with a long axial field of view to the field of cardiovascular disease.

Determining Hemodynamically Significant Coronary Artery Disease: Patient-Specific Cutoffs in Quantitative Myocardial Blood Flow Using [15O]H2O PET Imaging.

Currently, cutoffs of quantitative [15O]H2O PET to detect fractional flow reserve (FFR)-defined coronary artery disease (CAD) were derived from a single cohort that included patients without prior CAD. However, prior CAD, sex, and age can influence myocardial blood flow (MBF). Therefore, the present study determined the influence of prior CAD, sex, and age on optimal cutoffs of hyperemic MBF (hMBF) and coronary flow reserve (CFR) and evaluated whether cutoff optimization enhanced diagnostic performance of quantitative [15O]H2O PET against an FFR reference standard. Methods: Patients with chronic coronary symptoms underwent [15O]H2O PET and invasive coronary angiography with FFR. Optimal cutoffs for patients with and without prior CAD and subpopulations based on sex and age were determined. Results: This multicenter study included 560 patients. Optimal cutoffs were similar for patients with (n = 186) and without prior CAD (hMBF, 2.3 vs. 2.3 mL·min-1·g-1; CFR, 2.7 vs. 2.6). Females (n = 190) had higher hMBF cutoffs than males (2.8 vs. 2.3 mL·min-1·g-1), whereas CFRs were comparable (2.6 vs. 2.7). However, female sex-specific hMBF cutoff implementation decreased diagnostic accuracy as compared with the cutoff of 2.3 mL·min-1·g-1 (72% vs. 82%, P < 0.001). Patients aged more than 70 y (n = 79) had lower hMBF (1.7 mL·min-1·g-1) and CFR (2.3) cutoffs than did patients aged 50 y or less, 51-60 y, and 61-70 y (hMBF, 2.3-2.4 mL·min-1·g-1; CFR, 2.7). Age-specific cutoffs in patients aged more than 70 y yielded comparable accuracy to the previously established cutoffs (hMBF, 72% vs. 76%, P = 0.664; CFR, 80% vs. 75%, P = 0.289). Conclusion: Patients with and without prior CAD had similar [15O]H2O PET cutoffs for detecting FFR-defined significant CAD. Stratifying patients according to sex and age led to different optimal cutoffs; however, these values did not translate into an increased overall accuracy as compared with previously established thresholds for MBF.

External validation of a deep learning algorithm for automated echocardiographic strain measurements.

Aims: Echocardiographic strain imaging reflects myocardial deformation and is a sensitive measure of cardiac function and wall-motion abnormalities. Deep learning (DL) algorithms could automate the interpretation of echocardiographic strain imaging. Methods and results: We developed and trained an automated DL-based algorithm for left ventricular (LV) strain measurements in an internal dataset. Global longitudinal strain (GLS) was validated externally in (i) a real-world Taiwanese cohort of participants with and without heart failure (HF), (ii) a core-lab measured dataset from the multinational prevalence of microvascular dysfunction-HF and preserved ejection fraction (PROMIS-HFpEF) study, and regional strain in (iii) the HMC-QU-MI study of patients with suspected myocardial infarction. Outcomes included measures of agreement [bias, mean absolute difference (MAD), root-mean-squared-error (RMSE), and Pearson's correlation (R)] and area under the curve (AUC) to identify HF and regional wall-motion abnormalities. The DL workflow successfully analysed 3741 (89%) studies in the Taiwanese cohort, 176 (96%) in PROMIS-HFpEF, and 158 (98%) in HMC-QU-MI. Automated GLS showed good agreement with manual measurements (mean ± SD): -18.9 ± 4.5% vs. -18.2 ± 4.4%, respectively, bias 0.68 ± 2.52%, MAD 2.0 ± 1.67, RMSE = 2.61, R = 0.84 in the Taiwanese cohort; and -15.4 ± 4.1% vs. -15.9 ± 3.6%, respectively, bias -0.65 ± 2.71%, MAD 2.19 ± 1.71, RMSE = 2.78, R = 0.76 in PROMIS-HFpEF. In the Taiwanese cohort, automated GLS accurately identified patients with HF (AUC = 0.89 for total HF and AUC = 0.98 for HF with reduced ejection fraction). In HMC-QU-MI, automated regional strain identified regional wall-motion abnormalities with an average AUC = 0.80. Conclusion: DL algorithms can interpret echocardiographic strain images with similar accuracy as conventional measurements. These results highlight the potential of DL algorithms to democratize the use of cardiac strain measurements and reduce time-spent and costs for echo labs globally.

Plasma lipidomics and coronary plaque changes: a substudy of the SMARTool clinical trial.

AIMS: To date, no studies have investigated the association between lipid species and coronary plaque changes over time, quantitatively assessed by serial imaging. We aimed to prospectively determine the association between lipid species quantified by a plasma lipidomic analysis and coronary plaque changes according to composition assessed by a quantitative serial analysis of coronary computed tomography angiography (CTA). METHODS AND RESULTS: Patients with suspected coronary artery disease (CAD) undergoing baseline coronary CTA were prospectively enrolled by seven EU centres in the SMARTool study and submitted to clinical, molecular, and coronary CTA re-evaluation at follow-up (an inter-scan period of 6.39 ± 1.17 years). Out of 202 patients who were analysed in the SMARTool main clinical study, a lipidomic analysis was performed in 154 patients before the baseline coronary CTA, and this group was included in the present study. A quantitative CTA analysis was performed by using a separate core laboratory blinded from clinical data. In the univariable analysis, it was found that no lipid species were significantly associated with annual total and calcified plaque changes. After adjusting for clinical variables at baseline and statin use, it was found that three lipid species were significantly associated with non-calcified plaque progression. In detail, cholesteryl ester(20:3), sphingomyelin (SM)(40:3), and SM(41:1) were found to be positively related to non-calcified plaque progression (Bonferroni-adjusted P-values = 0.005, 0.016, and 0.004, respectively). CONCLUSION: The current study showed an independent relationship between specific lipid species determined by a plasma lipidomic analysis and non-calcified coronary plaque progression assessed by a serial, quantitative coronary CTA analysis.