Machine Learning in the Evaluation of Myocardial Ischemia Through Nuclear Cardiology

Purpose of ReviewTo summarize the advances achieved in the detection and characterization of myocardial ischemia and prediction of related outcomes through machine learning (ML)-based artificial intelligence (AI) workflows in both single-photon emission computed tomography (SPECT) and positron emission tomography (PET).Recent FindingsIn the field of cardiology, the implementation of ML algorithms has recently gravitated around image processing for characterization, diagnostic, and prognostic purposes. Nuclear cardiology represents a particular niche for AI as it deals with complex images of semi-quantitative and quantitative nature acquired with SPECT and PET.SummaryAI is revolutionizing clinical research. Since the recent convergence of powerful ML algorithms and increasing computational power, the study of very large datasets has demonstrated that clinical classification and prediction can be optimized by exploring very high-dimensional non-linear patterns. In the evaluation of myocardial ischemia, ML is optimizing the recognition of perfusion abnormalities beyond traditional measures and refining prediction of adverse cardiovascular events at the individual-patient level.</div

Improving patient identification for advanced cardiac imaging through machine learning-integration of clinical and coronary CT angiography data

Background: Standard computed tomography angiography (CTA) outputs a myriad of interrelated variables in the evaluation of suspected coronary artery disease (CAD). But an important proportion of obstructive lesions does not cause significant myocardial ischemia. Nowadays, machine learning (ML) allows integration of numerous variables through complex interdependencies that optimize classification and prediction at the individual level. We evaluated ML performance in integrating CTA and clinical variables to identify patients that demonstrate myocardial ischemia through PET and those who ultimately underwent early revascularization. Methods and results: 830 patients with CTA and selective PET were analyzed. Nine clinical and 58 CTA variables were integrated through ensemble-boosting ML to identify patients with ischemia and those who underwent early revascularization. ML performance was compared against expert CTA interpretation, calcium score and clinical variables. While ML using all CTA variables achieved an AUC = 0.85, it was outperformed by expert CTA interpretation (AUC = 0.87, p < 0.01 for comparison), comparable to ML integration of CTA variables with clinical variables. However, the best performance was achieved by ML integration of expert CTA interpretation and clinical variables for both dependent variables (AUCs = 0.91 and 0.90, p < 0.001). Conclusions: Machine learning integration of diagnostic CTA and clinical data may improve identification of patients with myocardial ischemia and those requiring early revascularization at the individual level. This could potentially aid in sparing the need for subsequent advanced imaging and better identifying patients in ultimate need for revascularization. While ML integrating all CTA variables did not outperform expert CTA interpretation, ML data integration from different sources consistently improves diagnostic performance. (C) 2021 The Authors. Published by Elsevier B.V

Phase analysis of gated PET in the evaluation of mechanical ventricular synchrony:A narrative overview

Noninvasive imaging modalities offer the possibility to dynamically evaluate cardiac motion during the cardiac cycle by means of ECG-gated acquisitions. Such motion characterization along with orientation, segmentation preprocessing, and ultimately, phase analysis, can provide quantitative estimates of ventricular mechanical synchrony. Current evidence on the role of mechanical synchrony evaluation is mainly available for echocardiography and gated single-photon emission computed tomography, but less is known about the utilization of gated positron emission tomography (PET). Although data available are sparse, there is indication that mechanical synchrony evaluation can be of diagnostic and prognostic values in patients with known or suspected coronary artery disease-related myocardial ischemia, prediction of response to cardiac resynchronization therapy, and estimation of risk for adverse cardiac events in patients’ heart failure. As such, the evaluation of mechanical ventricular synchrony through phase analysis of gated acquisitions represents a value addition to modern cardiac PET imaging modality, which warrants further research and development in the evaluation of patients with cardiovascular disease

Ventricular synchrony is not significantly determined by absolute myocardial perfusion in patients with chronic heart failure:A N-13-ammonia PET study

Background It is thought that heart failure (HF) patients may benefit from the evaluation of mechanical (dys)synchrony, and an independent inverse relationship between myocardial perfusion and ventricular synchrony has been suggested. We explore the relationship between quantitative myocardial perfusion and synchrony parameters when accounting for the presence and extent of fixed perfusion defects in patients with chronic HF. Methods We studied 98 patients with chronic HF who underwent rest and stress Nitrogen-13 ammonia PET. Multivariate analyses of covariance were performed to determine relevant predictors of synchrony (measured as bandwidth, standard deviation, and entropy). Results In our population, there were 43 (44%) women and 55 men with a mean age of 71 +/- 9.6 years. The SRS was the strongest independent predictor of mechanical synchrony variables (p <.01), among other considered predictors including: age, sex, body mass index, smoking, diabetes mellitus, dyslipidemia, hypertension, rest myocardial blood flow (MBF), and myocardial perfusion reserve (MPR). Results were similar when considering stress MBF instead of MPR. Conclusions The existence and extent of fixed perfusion defects, but not the quantitative PET myocardial perfusion parameters (sMBF and MPR), constitute a significant independent predictor of ventricular mechanical synchrony in patients with chronic HF

Towards consensus in acquisition and image analysis of PET and SPECT in the assessment of cardiac sympathetic innervation: a mini-review:a mini-review

In the rapidly evolving field of nuclear medicine, imaging cardiac sympathetic innervation using both conventional nuclear medicine and PET tracers is a small but growing field of interest. Recent larger clinical trials have underlined the importance of imaging cardiac sympathetic innervation as well as the consequences of low regional tracer accumulation for patient outcomes. New developments have resulted in the introduction of novel PET tracers with high clinical potential, especially for imaging centers without an on-site cyclotron. Despite the generated guidelines, especially on MIBG scintigraphy, widespread compliance with standardization efforts for cardiac sympathetic innervation imaging has not been yet achieved. Compliance with standardization of imaging acquisition and data analysis is crucial to move forward towards refinement of clinical guidelines

Towards consensus in acquisition and image analysis of PET and SPECT in the assessment of cardiac sympathetic innervation: a mini-review

In the rapidly evolving field of nuclear medicine, imaging cardiac sympathetic innervation using both conventional nuclear medicine and PET tracers is a small but growing field of interest. Recent larger clinical trials have underlined the importance of imaging cardiac sympathetic innervation as well as the consequences of low regional tracer accumulation for patient outcomes. New developments have resulted in the introduction of novel PET tracers with high clinical potential, especially for imaging centers without an on-site cyclotron. Despite the generated guidelines, especially on MIBG scintigraphy, widespread compliance with standardization efforts for cardiac sympathetic innervation imaging has not been yet achieved. Compliance with standardization of imaging acquisition and data analysis is crucial to move forward towards refinement of clinical guidelines

The utilization of positron emission tomography in the evaluation of renal health and disease

PurposePositron emission tomography (PET) is a nuclear imaging technique that uses radiotracers to visualize metabolic processes of interest across different organs, to diagnose and manage diseases, and monitor therapeutic response. This systematic review aimed to characterize the value of PET for the assessment of renal metabolism and function in subjects with non-oncological metabolic disorders.MethodsThis review was conducted and reported in accordance with the PRISMA statement. Research articles reporting “kidney” or “renal” metabolism evaluated with PET imaging between 1980 and 2021 were systematically searched in Medline/PubMed, Science Direct, and the Cochrane Library. Search results were exported and stored in RefWorks, the duplicates were removed, and eligible studies were identified, evaluated, and summarized.ResultsThirty reports met the inclusion criteria. The majority of the studies were prospective (73.33%, n = 22) in nature. The most utilized PET radiotracers were 15O-labeled radio water (H215O, n = 14) and 18F-fluorodeoxyglucose (18F-FDG, n = 8). Other radiotracers used in at least one study were 14(R,S)-(18)F-fluoro-6-thia-heptadecanoic acid (18F-FTHA), 18F-Sodium Fluoride (18F-NaF), 11C-acetate, 68-Gallium (68Ga), 13N-ammonia (13N-NH3), Rubidium-82 (82Rb), radiolabeled cationic ferritin (RadioCF), 11C‐para-aminobenzoic acid (11C-PABA), Gallium-68 pentixafor (68Ga-Pentixafor), 2-deoxy-2-F-fluoro-D-sorbitol (F-FDS) and 55Co-ethylene diamine tetra acetic acid (55Co-EDTA).ConclusionPET imaging provides an effective modality for evaluating a range of metabolic functions including glucose and fatty acid uptake, oxygen consumption and renal perfusion. Multiple positron emitting radiolabeled racers can be used for renal imaging in clinical settings. PET imaging thus holds the potential to improve the diagnosis of renal disorders, and to monitor disease progression and treatment response.</p

Genomic insights in ascending aortic size and distensibility

BACKGROUND: Alterations in the anatomic and biomechanical properties of the ascending aorta (AAo) can give rise to various vascular pathologies. The aim of the current study is to gain additional insights in the biology of the AAo size and function. METHODS: We developed an AI based analysis pipeline for the segmentation of the AAo, and the extraction of AAO parameters. We then performed genome-wide association studies of AAo maximum area, AAo minimum area and AAo distensibility in up to 37,910 individuals from the UK Biobank. Variants that were significantly associated with AAo phenotypes were used as instrumental variables in Mendelian randomization analyses to investigate potential causal relationships with coronary artery disease, myocardial infarction, stroke and aneurysms. FINDINGS: Genome-wide association studies revealed a total of 107 SNPs in 78 loci. We annotated 101 candidate genes involved in various biological processes, including connective tissue development (THSD4 and COL6A3). Mendelian randomization analyses showed a causal association with aneurysm development, but not with other vascular diseases. INTERPRETATION: We identified 78 loci that provide insights into mechanisms underlying AAo size and function in the general population and provide genetic evidence for their role in aortic aneurysm development