Personalized prediction of mode of cardiac death in heart failure using supervised machine learning in the context of cardiac innervation imaging

Growth of molecular imaging bears potential to transform nuclear cardiology from a primarily diagnostic method to a precision medicine tool. Molecular targets amenable for imaging and therapeutic intervention are particularly promising to facilitate risk stratification, patient selection and exquisite guidance of novel therapies, and interrogation of systems-based interorgan communication. Non-invasive visualization of pathobiology provides valuable insights into the progression of disease and response to treatment. Specifically, inflammation, fibrosis, and neurohormonal signaling, central to the progression of cardiovascular disease and emerging therapeutic strategies, have been investigated by molecular imaging. As the number of radioligands grows, careful investigation of the binding properties and added-value of imaging should be prioritized to identify high-potential probes and facilitate translation to clinical applications. In this review, we discuss the current state of molecular imaging in cardiovascular medicine, and the challenges and opportunities ahead for cardiovascular molecular imaging to navigate the path from diagnosis to prognosis to personalized medicine.