Cardiovascular magnetic resonance feature tracking in small animals – a preliminary study on reproducibility and sample size calculation

Background Cardiovascular magnetic resonance feature tracking (CMR-FT) is a novel tissue tracking technique developed for noninvasive assessment of myocardial motion and deformation. This preliminary study aimed to evaluate the observer’s reproducibility of CMR-FT in a small animal (mouse) model and define sample size calculation for future trials. Methods Six C57BL/6 J mice were selected from the ongoing experimental mouse model onsite and underwent CMR with a 3 Tesla small animal MRI scanner. Myocardial deformation was analyzed using dedicated software (TomTec, Germany) by two observers. Left ventricular (LV) longitudinal, circumferential and radial strain (EllLAX, EccSAX and ErrSAX) were calculated. To assess intra-observer agreement data analysis was repeated after 4 weeks. The sample size required to detect a relative change in strain was calculated. Results In general, EccSAX and EllLAX demonstrated highest inter-observer reproducibility (ICC 0.79 (0.46–0.91) and 0.73 (0.56–0.83) EccSAX and EllLAX respectively). In contrast, at the intra-observer level EllLAX was more reproducible than EccSAX (ICC 0.83 (0.73–0.90) and 0.74 (0.49–0.87) EllLAX and EccSAX respectively). The reproducibility of ErrSAX was weak at both observer levels. Preliminary sample size calculation showed that a small study sample (e.g. ten animals to detect a relative 10% change in EccSAX) could be sufficient to detect changes if parameter variability is low. Conclusions This pilot study demonstrates good to excellent inter- and intra-observer reproducibility of CMR-FT technique in small animal model. The most reproducible measures are global circumferential and global longitudinal strain, whereas reproducibility of radial strain is weak. Furthermore, sample size calculation demonstrates that a small number of animals could be sufficient for future trials

Methods for monitoring and prognosis of clinical status of patients in acute phase of myocardial infarction for computer network based clinical decision support system

a b s t r a c t The methods for evaluation of crucial factors describing status of cardiologic patients in intensive care units based on advanced signal processing methods were incorporated into prototype network based clinical decision support system. The methods realize: (a) evaluation of heart rate variability in aim to predict clinical outcome; (b) evaluation of central hemodynamics in non-invasive way by means of chest impedance signal analysis; (c) automatic detection and evaluation of ECG T-wave alternans -predictor of sudden cardiac death. Modern standard monitoring equipment has connection to the computer network and possibility to transfer registered signals and clinical data what could be processed and evaluated with such clinical decision system. The remotely accessed methods of the system can significantly improve the quality of monitoring of patient status using standard equipment