Body Mass Index Is Independently Associated with the Presence of Ischemia in Myocardial Perfusion Imaging.

Background and Objectives: Obesity has been linked to various cardiovascular risk factors, increased incidence of coronary artery disease, and myocardial perfusion defects. The aim of this study was to investigate if body mass index (BMI) and waist circumference (WC) were associated with myocardial perfusion defects. Materials and Methods: A total of 308 consecutive patients who had myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) and a complete medical record on file were studied retrospectively.

Hybrid bone SPECT/CT reveals spleen calcification in sickle cell mutation and beta-thalassemia.

We present a case of a 65 years-old male with sickle cell mutation and beta-thalassemia (Hb S/β-Thal), who had whole-body bone scan evaluation for osteomyelitis. The examination revealed high radiopharmaceutical uptake in the left abdomen. Further evaluation with hybrid single photon emission computed tomography/computed tomography (SPECT/CT) showed calcification of approximately the entire spleen, in the context of sickle cell anemia.

Estimating topological entropy using ordinal partition networks.

We propose a computationally simple and efficient network-based method for approximating topological entropy of low-dimensional chaotic systems. This approach relies on the notion of an ordinal partition. The proposed methodology is compared to the three existing techniques based on counting ordinal patterns-all of which derive from collecting statistics about the symbolic itinerary-namely (i) the gradient of the logarithm of the number of observed patterns as a function of the pattern length, (ii) direct application of the definition of topological permutation entropy, and (iii) the outgrowth ratio of patterns of increasing length.

Markov modeling via ordinal partitions: An alternative paradigm for network-based time-series analysis.

Mapping time series to complex networks to analyze observables has recently become popular, both at the theoretical and the practitioner's level. The intent is to use network metrics to characterize the dynamics of the underlying system. Applications cover a wide range of problems, from geoscientific measurements to biomedical data and financial time series.

Physiotherapist perceptions of optimal sitting and standing posture.

Background: Assessment of, and advice about, spinal posture is common when people with spinal pain present to physiotherapists. Most descriptions regarding optimal spinal posture have been qualitative in nature.

Objectives: To determine the beliefs of physiotherapists regarding optimal sitting and standing posture.

Regenerating time series from ordinal networks.

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches.

Counting forbidden patterns in irregularly sampled time series. I. The effects of under-sampling, random depletion, and timing jitter.

It has been established that the count of ordinal patterns, which do not occur in a time series, called forbidden patterns, is an effective measure for the detection of determinism in noisy data. A very recent study has shown that this measure is also partially robust against the effects of irregular sampling. In this paper, we extend said research with an emphasis on exploring the parameter space for the method's sole parameter-the length of the ordinal patterns-and find that the measure is more robust to under-sampling and irregular sampling than previously reported.

Counting forbidden patterns in irregularly sampled time series. II. Reliability in the presence of highly irregular sampling.

We are motivated by real-world data that exhibit severe sampling irregularities such as geological or paleoclimate measurements. Counting forbidden patterns has been shown to be a powerful tool towards the detection of determinism in noisy time series. They constitute a set of ordinal symbolic patterns that cannot be realised in time series generated by deterministic systems.