A Hybrid Model for Cardiac Perfusion: Coupling a Discrete Coronary Arterial Tree Model with a Continuous Porous-Media Flow Model of the Myocardium.

This paper presents a novel hybrid approach for the computational modeling of cardiac perfusion, combining a discrete model of the coronary arterial tree with a continuous porous-media flow model of the myocardium. The constructive constrained optimization (CCO) algorithm captures the detailed topology and geometry of the coronary arterial tree network, while Poiseuille's law governs blood flow within this network. Contrast agent dynamics, crucial for cardiac MRI perfusion assessment, are modeled using reaction-advection-diffusion equations within the porous-media framework. The model incorporates fibrosis-contrast agent interactions and considers contrast agent recirculation to simulate myocardial infarction and Gadolinium-based late-enhancement MRI findings. Numerical experiments simulate various scenarios, including normal perfusion, endocardial ischemia resulting from stenosis, and myocardial infarction. The results demonstrate the model's efficacy in establishing the relationship between blood flow and stenosis in the coronary arterial tree and contrast agent dynamics and perfusion in the myocardial tissue. The hybrid model enables the integration of information from two different exams: computational fractional flow reserve (cFFR) measurements of the heart coronaries obtained from CT scans and heart perfusion and anatomy derived from MRI scans. The cFFR data can be integrated with the discrete arterial tree, while cardiac perfusion MRI data can be incorporated into the continuum part of the model. This integration enhances clinical understanding and treatment strategies for managing cardiovascular disease.

Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification.

This work presents a new mathematical model to describe cardiac perfusion in the myocardium as acquired by cardiac magnetic resonance (CMR) perfusion exams. The combination of first pass (or contrast-enhanced CMR) and late enhancement CMR is a widely used non-invasive exam that can identify abnormal perfused regions of the heart via the use of a contrast agent (CA). The exam provides important information to the diagnosis, management, and prognosis of ischemia and infarct: perfusion on different regions, the status of microvascular structures, the presence of fibrosis, and the relative volume of extracellular space. This information is obtained by inferring the spatiotemporal dynamics of the contrast in the myocardial tissue from the acquired images. The evaluation of these physiological parameters plays an important role in the assessment of myocardial viability. However, the nature of cardiac physiology poses great challenges in the estimation of these parameters. Briefly, these are currently estimated qualitatively via visual inspection of images and comparison of relative brightness between different regions of the heart. Therefore, there is a great urge for techniques that can help to quantify cardiac perfusion. In this work, we propose a new mathematical model based on multidomain flow in porous media. The model is based on a system of partial differential equations. Darcy's law is used to obtain the pressure and velocity distribution. CA dynamics is described by reaction-diffusion-advection equations in the intravascular space and in the interstitial space. The interaction of fibrosis and the CA is also considered. The new model treats the domains as anisotropic media and imposes a closed loop of intravascular flow, which is necessary to reproduce the recirculation of the CA. The model parameters were adjusted to reproduce clinical data. In addition, the model was used to simulate different scenarios: normal perfusion; endocardial ischemia due to stenosis in a coronary artery in the epicardium; and myocardial infarct. Therefore, the computational model was able to correlate anatomical features, stenosis and the presence of fibrosis, with functional ones, cardiac perfusion. Altogether, the results suggest that the model can support the process of non-invasive cardiac perfusion quantification.

An Optimization-Based Algorithm for the Construction of Cardiac Purkinje Network Models.

OBJECTIVE: This work presents a new algorithm for the construction of a model for the Purkinje network (PN) of the heart. METHODS: The algorithm is based on a method called constructive constrained optimization (CCO), which was reformulated for the specific case of automatic PN generation. The proposed optimization-based algorithm is referred to as constructive optimization (CO). The CO method iteratively constructs the PN by minimizing the total length of the generated PN tree. In addition, it can take into account some important topological information of the PN, such as the location of the Purkinje-muscle junctions and the average bifurcation angle found in the literature. RESULTS: To validate the model, the new method was compared with the classical L-system method for generating PN models and to a recently proposed image-based technique. CONCLUSION: The results show that the CO is able to construct PNs with geometric features and activation times that are in good agreement with those reported in the literature and to those obtained by the other aforementioned alternatives.

Trypanosoma brucei PUF9 regulates mRNAs for proteins involved in replicative processes over the cell cycle.

Many genes that are required at specific points in the cell cycle exhibit cell cycle-dependent expression. In the early-diverging model eukaryote and important human pathogen Trypanosoma brucei, regulation of gene expression in the cell cycle and other processes is almost entirely post-transcriptional. Here, we show that the T. brucei RNA-binding protein PUF9 stabilizes certain transcripts during S-phase. Target transcripts of PUF9--LIGKA, PNT1 and PNT2--were identified by affinity purification with TAP-tagged PUF9. RNAi against PUF9 caused an accumulation of cells in G2/M phase and unexpectedly destabilized the PUF9 target mRNAs, despite the fact that most known Puf-domain proteins promote degradation of their target mRNAs. The levels of the PUF9-regulated transcripts were cell cycle dependent, peaking in mid- to late- S-phase, and this effect was abolished when PUF9 was targeted by RNAi. The sequence UUGUACC was over-represented in the 3' UTRs of PUF9 targets; a point mutation in this motif abolished PUF9-dependent stabilization of a reporter transcript carrying the PNT1 3' UTR. LIGKA is involved in replication of the kinetoplast, and here we show that PNT1 is also kinetoplast-associated and its over-expression causes kinetoplast-related defects, while PNT2 is localized to the nucleus in G1 phase and redistributes to the mitotic spindle during mitosis. PUF9 targets may constitute a post-transcriptional regulon, encoding proteins involved in temporally coordinated replicative processes in early G2 phase.