The International Dysphagia Diet Standardisation Initiative (IDDSI) flow test, using a standard 10-mL syringe, is being adopted in many countries for clinical measurement of the consistency of drinks. The working hypothesis is that thickening drinks to retard flow can be advantageous for individuals who struggle to cope with thin drinks. This study assesses how the IDDSI test relates to rheology and clinical knowledge of physiological flows during swallowing. With no pre-existing analytical solution for internal flow through the syringe, a computational model was designed, incorporating rheometry data from a variety of Newtonian and non-Newtonian liquids. The computational model was validated experimentally across the range of liquids but the technique showed limitations in simulating dripping and cohesiveness. Gum-based liquids which were strongly shear-thinning (0.12 < n < 0.25) showed plug-flow characteristics with 90% of the shear occurring in only 22% of the radial dimension. Shear rates were maximal at the nozzle outlet (> 60 times higher than the barrel) and reached 7400/s for the thinnest gum-based liquid. Shear rheology data alone was unable to describe the flow of these drinks. The flow conditions in the test varied according to the type and consistency of liquid, relating to the desired clinical effect.

Electrograms (EGM) recorded from the surface of the myocardium are becoming more and more accessible. T-wave alternans (TWA) is associated with increased vulnerability to ventricular tachycardia/fibrillation and it occurs before the onset of ventricular arrhythmias. Thus, accurate methodologies for time-varying alternans estimation/detection in EGM are needed. In this paper, we perform a simulation study based on epicardial EGM recorded in vivo in humans to compare the accuracy of four methodologies: the spectral method (SM), modified moving average method, laplacian likelihood ratio method (LLR), and a novel method based on time-frequency distributions. A variety of effects are considered, which include the presence of wide band noise, respiration, and impulse artifacts. We found that 1) EGM-TWA can be detected accurately when the standard deviation of wide-band noise is equal or smaller than ten times the magnitude of EGM-TWA. 2) Respiration can be critical for EGM-TWA analysis, even at typical respiratory rates. 3) Impulse noise strongly reduces the accuracy of all methods, except LLR. 4) If depolarization time is used as a fiducial point, the localization of the T-wave is not critical for the accuracy of EGM-TWA detection. 5) According to this study, all methodologies provided accurate EGM-TWA detection/quantification in ideal conditions, while LLR was the most robust, providing better detection-rates in noisy conditions. Application on epicardial mapping of the in vivo human heart shows that EGM-TWA has heterogeneous spatio-temporal distribution.

Identification of targets for ablation of post-infarction ventricular tachycardias (VTs) remains challenging, often requiring arrhythmia induction to delineate the reentrant circuit. This carries a risk for the patient and may not be feasible. Substrate mapping has emerged as a safer strategy to uncover arrhythmogenic regions. However, VT recurrence remains common. To use computer simulations to assess the ability of different substrate mapping approaches to identify VT exit sites. A 3D computational model of the porcine post-infarction heart was constructed to simulate VT and paced rhythm. Electroanatomical maps were constructed based on endocardial electrogram features and the reentry vulnerability index (RVI - a metric combining activation (AT) and repolarization timings to identify tissue susceptibility to reentry). Since scar transmurality in our model was not homogeneous, parameters derived from all signals (including dense scar regions) were used in the analysis. Potential ablation targets obtained from each electroanatomical map during pacing were compared to the exit site detected during VT mapping. Simulation data showed that voltage cut-offs applied to bipolar electrograms could delineate the scar, but not the VT circuit. Electrogram fractionation had the highest correlation with scar transmurality. The RVI identified regions closest to VT exit site but was outperformed by AT gradients combined with voltage cut-offs. The performance of all metrics was affected by pacing location. Substrate mapping could provide information about the infarct, but the directional dependency on activation should be considered. Activation-repolarization metrics have utility in safely identifying VT targets, even with non-transmural scars.