A novel marker for heart failure: Cross sectional area assessment in a large vein by conductance catheter.

The present study investigates the feasibility of a new application able to check the heart failure status in a patient through the estimation of the venous distension. In this way it would be possible to follow up patients, avoiding invasive or expensive exams such as cardiac catheterization and echocardiography. Moreover, the devices would also be able to diagnose the decline of the disease, in order to allow a new adaptation to therapy, and vice versa to check the improvement in the patient’s conditions after the CRT device implant. This thesis is essentially divided into three parts: an analytical model was used to obtain an estimation of the error committed for the calculation of the CSA and to understand how the accuracy and sensitivity depend on the different configurations of the electrodes and the catheter position inside the vein; secondly, an in-vitro experiment was carried out in order to verify the practical feasibility for these kinds of measurements, in a very simplified model; in the end, several animal experiments were done to test the in-vivo practicability of the proposed method. The obtained results showed the feasibility of this approach. In fact, the error committed in the estimation of CSA, during the animal experiments, can be considered acceptable (CSAerror_max ≈ -14%). Moreover, it has been demonstrated that the conductance catheter allows assessing, not only the vein CSA, but also the breathing of the animal.

Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking

The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.

A 2-dimensional computational model to analyze the effects of cellular heterogeinity on cardiac pacemaking

The mechanical action of the heart is made possible in response to electrical events that involve the cardiac cells, a property that classifies the heart tissue between the excitable tissues. At the cellular level, the electrical event is the signal that triggers the mechanical contraction, inducing a transient increase in intracellular calcium which, in turn, carries the message of contraction to the contractile proteins of the cell. The primary goal of my project was to implement in CUDA (Compute Unified Device Architecture, an hardware architecture for parallel processing created by NVIDIA) a tissue model of the rabbit sinoatrial node to evaluate the heterogeneity of its structure and how that variability influences the behavior of the cells. In particular, each cell has an intrinsic discharge frequency, thus different from that of every other cell of the tissue and it is interesting to study the process of synchronization of the cells and look at the value of the last discharge frequency if they synchronized.