LAUSR

Cardiovascular diseases represent, to date, the major cause of mortality worldwide. Diagnosis of the most frequent of such disease, acute myocardial infarction (AMI), requires the evaluation of time-series measurement of specific cardiac biomarkers concentration. The aim of this paper is to provide the clinicians with a quantitative tool to analyze such time-series, with the final goal of enhancing the diagnostic and prognostic procedures. The proposed approach is based on a novel dynamical model, which synthetically describes the basic mechanisms underlying cardiac troponin (cTnT) release into the plasma after the onset of AMI. Leveraging tools of system identification and a data set of AMI patients treated at our University Hospital, the model has been assessed as an effective tool to quantify the characteristic release curves observed under different conditions. Furthermore, it has been shown how the devised approach is also suitable in those cases where only partial measurements are available to the clinician to recover important clinical information. Finally, an optimal experimental design analysis has been performed in order to gain insights on how to optimize the experimental data collection phase with potentially relevant implications on both the quality and cost of the diagnosis procedure.