Quantitative analysis of biochemical parameters is crucial for a correct diagnosis and prognosis of patients subject to acute myocardial infarction (AMI). In order to achieve a quantitative understanding of the dynamics of cardiac biomarkers, we have developed a mathematical model that can be exploited to extrapolate the release curve of cardiac troponin T (cTnT) into the plasma from few experimental acquisitions. The present work introduces a novel approach, based on the cTnT-release model, aimed at the identification of the infarct onset time. Indeed, in spite of the clinical importance of such information, in many cases, it is not easy to establish the exact time of occurrence of the ischemic event. We show that using a model-based optimization approach, the infarct onset time can be reliably estimated using the cTnT concentration acquisitions taken in the first few hours post-AMI. The assessment of the proposed approach is conducted on an experimental dataset, in which the infarct has been artificially induced and, therefore, the onset time is exactly known. In particular, the effectiveness of the devised estimation algorithm has been tested under several scenarios, with the first cTnT acquisition taken up to 12 h after AMI. Altogether, the proposed model-based approach provides a useful tool to help the clinicians in the quantitative estimation of important clinical parameters from the release curves of the cardiac biomarkers.
Keywords: Acute myocardial infarction; Biological models; Cardiac biomarkers; Identifiability; Infarct time; System identification.