The analysis of intravascular indicator dynamics is important for cardiovascular diagnostics as well as for the assessment of tissue perfusion, aimed at the detection of ischemic regions or cancer hypervascularization. To this end, indicator dilution curves are measured after the intravenous injection of an indicator bolus and fitted by parametric models for the estimation of the hemodynamic parameters of interest. Based on heuristic reasoning, the dilution process is often modeled by a gamma variate. In this paper, we provide both a physical and stochastic interpretation of the gamma variate model. The accuracy of the model is compared with the local density random walk model, a known model based on physics principles. Dilution curves were measured by contrast ultrasonography both in vitro and in vivo (20 patients). Blood volume measurements were used to test the accuracy and clinical relevance of the estimated parameters. Both models provided accurate curve fits and volume estimates. In conclusion, the proposed interpretations of the gamma variate model describe physics aspects of the dilution process and lead to a better understanding of the observed parameters, increasing the value and credibility of the model, and possibly expanding its diagnostic applications.

The intra-thoracic blood volume (ITBV) is a cardiovascular parameter related to the cardiac preload and left ventricular function. Its assessment is, therefore, important for diagnosis and follow-up of several cardiovascular dysfunctions. Nowadays, the ITBV can be accurately measured only by invasive indicator dilution techniques, which require a double catheterization of the patient. In this study, a novel technique is presented for ITBV assessment by dynamic magnetic resonance imaging after intravenous injection of a small bolus of gadolinium chelate.

Despite intensive monitoring of patients in the ICU, dosage adjustment of antimicrobials is often omitted. Implementing this clinical rule has the potential to contribute to a significant improvement in medication safety and is expected to generate substantial savings.