Cardiovascular magnetic resonance feature-tracking assessment of myocardial mechanics: Intervendor agreement and considerations regarding reproducibility.

AIM: To assess intervendor agreement of cardiovascular magnetic resonance feature tracking (CMR-FT) and to study the impact of repeated measures on reproducibility. MATERIALS AND METHODS: Ten healthy volunteers underwent cine imaging in short-axis orientation at rest and with dobutamine stimulation (10 and 20 µg/kg/min). All images were analysed three times using two types of software (TomTec, Unterschleissheim, Germany and Circle, cvi(42), Calgary, Canada) to assess global left ventricular circumferential (Ecc) and radial (Err) strains and torsion. Differences in intra- and interobserver variability within and between software types were assessed based on single and averaged measurements (two and three repetitions with subsequent averaging of results, respectively) as determined by Bland-Altman analysis, intraclass correlation coefficients (ICC), and coefficient of variation (CoV). RESULTS: Myocardial strains and torsion significantly increased on dobutamine stimulation with both types of software (p<0.05). Resting Ecc and torsion as well as Ecc values during dobutamine stimulation were lower measured with Circle (p<0.05). Intra- and interobserver variability between software types was lowest for Ecc (ICC 0.81 [0.63-0.91], 0.87 [0.72-0.94] and CoV 12.47% and 14.3%, respectively) irrespective of the number of analysis repetitions. Err and torsion showed higher variability that markedly improved for torsion with repeated analyses and to a lesser extent for Err. On an intravendor level TomTec showed better reproducibility for Ecc and torsion and Circle for Err. CONCLUSIONS: CMR-FT strain and torsion measurements are subject to considerable intervendor variability, which can be reduced using three analysis repetitions. For both vendors, Ecc qualifies as the most robust parameter with the best agreement, albeit lower Ecc values obtained using Circle, and warrants further investigation of incremental clinical merit.

Tissue consistency perception in laparoscopy to define the level of fidelity in virtual reality simulation.

BACKGROUND: What degree of fidelity must a laparoscopic simulator have to achieve a training objective? This difficult question is addressed by studying the sensory interaction of surgeons in terms of a surgical skill: tissue consistency perception. METHODS: A method for characterizing surgeon sensory interaction has been defined and applied in an effort to determine the relative importance of three components of perceptual surgical skill: visual cues, haptic information, and previous surgical knowledge and experience. Expert, intermediate, and novel surgeons were enrolled in the study. Users were asked to rank tissue consistency in four different conditions: a description of the tissue alone (Q), visual information alone (VI), tactile information alone (TI), and both visual and tactile information (VTI). Agreement between these stages was assessed by a coefficient of determination (R2). RESULTS: Tissue is a determinant factor (p < 0.001) in the perception of tissue consistency, whereas the expertise of the surgeon is not (p = 0.289). Tissue consistency perception is based mainly on tactile information (TI-VTI agreement is high, R2 = 0.873), although little sensory substitution is present (VI-VTI agreement is low, R2 = 0.509). Agreement of Q-VI increases with experience (R2 = 0.050, 0.290, and 0.573, corresponding with to novel, intermediate, and expert surgeons), which has been associated with the "visual haptics" concept. CONCLUSIONS: Virtual reality simulators need haptic devices with force feedback capability if tissue consistency information is to be delivered. On the other hand, the visual haptics concept has been associated with a kind of tactile memory developed by surgical experience.

Understanding the mechanisms amenable to CRT response: from pre-operative multimodal image data to patient-specific computational models.

This manuscript describes our recent developments towards better understanding of the mechanisms amenable to cardiac resynchronization therapy response. We report the results from a full multimodal dataset corresponding to eight patients from the euHeart project. The datasets include echocardiography, MRI and electrophysiological studies. We investigate two aspects. The first one focuses on pre-operative multimodal image data. From 2D echocardiography and 3D tagged MRI images, we compute atlas based dyssynchrony indices. We complement these indices with presence and extent of scar tissue and correlate them with CRT response. The second one focuses on computational models. We use pre-operative imaging to generate a patient-specific computational model. We show results of a fully automatic personalized electromechanical simulation. By case-per-case discussion of the results, we highlight the potential and key issues of this multimodal pipeline for the understanding of the mechanisms of CRT response and a better patient selection.

Inter-model consistency and complementarity: learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology.

Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.