FDG an Myocardial Infarction: The PIAF Trial

History of Myocardial Infarction

In order to define distinct and reliable arterial 18Fluorodeoxyglucose (FDG) thresholds identifying patients at risk for cardiovascular events, patients with a history of myocardial infarction will be included in this international multicenter trial. Non-enhanced whole-body FDG PET/CT will be performed in all patients and the arterial FDG uptake in the carotid arteries as well as the aorta will be quantified by calculating different uptake parameters. In addition, FDG uptake in hematopoietic tissues (spleen, bone marrow), visceral adipose tissue (VAT) and different brain regions (e. g. amygdala) will be measured. Furthermore, specific blood biomarkers including genetic biomarkers, which are linked to atherosclerotic disease with predictive power for future cardiovascular events, will be analyzed in a subgroup of patients. In part 2 of the trial, a 4-year follow-up period will be analyzed with a focus on the prediction of cardiovascular events (acute coronary syndrome, non-fatal ischemic stroke, ischemic cardiac death, other causes of death, coronary/vascular revascularization, new-onset of angina, symptomatic peripheral arterial disease and heart failure). The predictive value of the arterial, hematopoietic and cerebral FDG uptake parameters as well as of the specific blood and genetic biomarkers will be determined.

From a clinical perspective, atherosclerosis leading to arterial plaque rupture is one of the most important causes of death that still misses a personalized, reliable and quantitative assessment of risk. This is particularly true for patients who suffered from a non-fatal coronary syndrome, were recent studies described severe CVD event rates of up to 5 % per year despite the use of aggressive secondary prevention strategies. While in previous clinical interventional trials inflammatory atherosclerotic activity was mainly determined by the surrogate marker high-sensitivity C-reactive protein, other studies have shown superiority of FDG PET/CT in the stratification of patients in high versus low risk groups, where risk in the highest (vs. lowest) TBR tertile was approximately 3-fold greater compared with what has been historically observed for the inflammatory blood biomarker, hsCRP. It is, thus, expected that imaging (vs. blood) biomarkers provide additional prognostic information that is more relevant to the artery wall per se, whereas currently used blood biomarkers carry information from vascular as well as nonvascular sources. The current research aims at identifying distinct and reliable FDG PET threshold values, which specify the individual risk of a distinct patient. For this purpose, a well-designed and well-powered multicenter trial is needed. Fundamentally, the research project aims at evaluating the prognostic value of arterial FDG PET/CT imaging of individuals with known cardiovascular disease (CVD). Specifically, we will: * Test the hypothesis that the baseline measures of arterial inflammation (as assessed by FDG PET/CT) independently predict the risk of CVD events (as coronary death, myocardial infarction, coronary insufficiency, angina, ischemic stroke, hemorrhagic stroke, transient ischemic attack, peripheral artery disease, revascularization, or heart failure) in a large cohort of individuals with prior MI. * Evaluate the incremental prognostic value of arterial inflammation (PET) over circulating blood biomarkers * Evaluate the prognostic value of inflammation data derived from various arterial locations (e.g. aorta, carotids, or other locations) for their ability to predict severe cardiovascular events * Identify cut-off values that indicate higher risk * Evaluate the predicted value of specific brain uptake, hematopoietic tissue (spleen, bone marrow) and visceral adipose tissue on emerging CV events. Evaluate the added value of combining those uptake values with arterial uptake * Evaluate the different established arterial FDG uptake parameters with regards to standardization and scanner type/variability * Apply deep-learning algorithms for detection of organ/tissue interactions and CV event hypothesis generation * Evaluate a subset of patients for inter-observer variability * Evaluate the detection rate of incidental PET/CT findings in the study cohort (suspected malignancies, other diseases) * Suggest novel diagnostic algorithms and clinical protocols accordingly * Evaluate the prognostic value of additionally derived genetic markers. * Specifically, we propose that patients with higher GRS have increased FDG PET/CT based inflammatory atherosclerotic activity and are prone to more MACE

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