Luis Jiménez-Ángeles

Factorial phase analysis of ventricular contraction using equilibrium radionuclide angiography images

Abstract Factorial phase analysis (FaPI) represents an alternative method to Fourier phase analysis (FoPI) in the evaluation and detection of abnormalities on cardiac contraction patterns, but it has limitations in representing the sequence in abnormal contraction patterns. In this work we propose a modified factorial phase image (FaPIm) that incorporates more complete information regarding the ventricular contraction sequence. In particular, we analyze and evaluate the contribution of the third eigenimage, in the presence of ventricular dyssynchrony, which has not been sufficiently explored in the literature. We have validated the proposed FaPIm using two Equilibrium Radionuclide Angiography (ERNA) sets of images obtained with a dynamic cardiac phantom and with a numerically simulated phantom. Also, we have tested the proposed representation for a control group of 23 normal subjects and for a sample of 15 patients with Complete Left Bundle Branch Block (LBBB). Whereas FoPI allows us to obtain an image that synthesizes ventricular contraction with the smallest dispersion around the mean values, FaPI and FaPIm show that external areas surrounding ventricular cavities present more dephasing than the rest of the ventricular region and contain more detailed information about the progression of contraction. Also, in the presence of an abnormal contraction pattern, the magnitude of the third eigenvalue was greater than the corresponding eigenvalue obtained for normal simulations. The dispersion plots obtained for a normal contraction pattern show that left ventricle (LV) and right ventricle (RV) information overlap. Therefore, when there is a dyssynchrony between LV and RV contraction it becomes necessary to incorporate the information corresponding to the third factor to achieve a clear separation between regions. In the comparison of the indices of control and LBBB populations, FaPIm shows significant differences in five out of six contraction indices, showing its promising value as a clinical tool.

Factor analysis of ventricular contraction using SPECT-ERNA images

Equilibrium radionuclide angiography images (ERNA) has been established as a useful modality for clinical evaluation of the ventricular function. Tomographic acquisition of ERNA (SPECT-ERNA) improves the quantification of ventricular function with planar ERNA, avoiding both the overlap of structures and the need of defining the best septal view which can be difficult in dilated ventricles. In this work we analyze the contribution and distribution of the most significant factors of dynamic structures (FADS), and propose an index based on the characterization of the normal contraction pattern, to quantify the ventricular contraction normality in a set of patients with clinical diagnosis of pulmonary arterial hypertension (PAH) using SPECT-ERNA. The statistical analysis shows significant differences between normal and PAH subjects in the models of left ventricle (LV) contraction pattern. This comparison shows that the LV has an abnormal contraction as a consequence of the pulmonary arterial hypertension.

Automated Classification of Severity in Cardiac Dyssynchrony Merging Clinical Data and Mechanical Descriptors

Cardiac resynchronization therapy (CRT) improves functional classification among patients with left ventricle malfunction and ventricular electric conduction disorders. However, a high percentage of subjects under CRT (20%–30%) do not show any improvement. Nonetheless the presence of mechanical contraction dyssynchrony in ventricles has been proposed as an indicator of CRT response. This work proposes an automated classification model of severity in ventricular contraction dyssynchrony. The model includes clinical data such as left ventricular ejection fraction (LVEF), QRS and P-R intervals, and the 3 most significant factors extracted from the factor analysis of dynamic structures applied to a set of equilibrium radionuclide angiography images representing the mechanical behavior of cardiac contraction. A control group of 33 normal volunteers (28 ± 5 years, LVEF of 59.7% ± 5.8%) and a HF group of 42 subjects (53.12 ± 15.05 years, LVEF < 35%) were studied. The proposed classifiers had hit rates of 90%, 50%, and 80% to distinguish between absent, mild, and moderate-severe interventricular dyssynchrony, respectively. For intraventricular dyssynchrony, hit rates of 100%, 50%, and 90% were observed distinguishing between absent, mild, and moderate-severe, respectively. These results seem promising in using this automated method for clinical follow-up of patients undergoing CRT.

The Effects of Sleep Deprivation in Working Memory Using the N-back Task

Sleep is important for body restitution and memory consolidation. Sleep loss can lead to heart attacks, diabetes and high blood pressure. Several studies report a decline in cognitive performance after sleep deprivation, spe-cially on working memory. The objective of this study was to evaluate the effects of sleep deprivation in working memory using the N-back task with three load levels (0-back, 1-back and 2-back). Twelve healthy volunteers (male and female) underwent 24 hours of sleep deprivation. A decline in accuracy was observed while reaction times increased after deprivation. Decreased activation was found in post sleep deprivation main-ly in the frontal lobe, Wernicke’s area and in some other areas located in occipital lobe, parietal lobe and temporal lobes. We also found increased activation in the cingulate gyus, insular cortex and some other areas located in temporal lobe and parietal lobes. These results confirm the previous evidence that frontal lobes are seriously compromised after sleep depriva-tion.

Software Phantom for the Synthesis of Equilibrium Radionuclide Ventriculography Images

This paper presents the novel design of a software phantom for the evaluation of equilibrium radionuclide ventriculography systems. Through singular value decomposition, the data matrix corresponding to an equilibrium image series is decomposed into both spatial and temporal fundamental components that can be parametrized. This parametric model allows for the application of user-controlled conditions related to a desired dynamic behavior. Being invertible, the decomposition is used to regenerate the radionuclide image series, which is then translated into a DICOM ventriculography file that can be read by commercial equipment

Effects of high frequency rTMS on sleep deprivation: A pilot study

Transcranial magnetic stimulation is a neurostimulation technique which has the potential to serve as a unique research tool for investigating a wide variety of fields in cognitive neuroscience. TMS has been approved by the FDA to serve as a treatment to depression and has also been used to evaluate its effects among several conditions such as Alzheimer, Parkinson disease, chronic pain and stroke. High frequency TMS has been previously used with the intention to measure and modulate the negative effects of sleep deprivation in cognitive performance, but there is no consensus about the ideal protocol yet. In this pilot study, we attempt to test high frequency rTMS in different brain targets in order to determine the effects in remediation of working memory due to sleep deprivation. These results provide preliminary evidence of the potential effectiveness of TMS for the treatment of cognitive impairment.

Neural Modulation in Aversive Emotion Processing: An Independent Component Analysis Study

Emotional processing has an important role in social interaction. We report the findings about the Independent Component Analysis carried out on a fMRI set obtained with a paradigm of face emotional processing. The results showed that an independent component, mainly cerebellar-medial-frontal, had a positive modulation associated with fear processing. Also, another independent component, mainly parahippocampal-prefrontal, showed a negative modulation that could be associated with implicit reappraisal of emotional stimuli. Independent Component Analysis could serve as a method to understand complex cognitive processes and their underlying neural dynamics.

Neural Activity of Cues Associated with Smoking after 24-Hour Smoking Abstinence and After 7-Days of Treatment and Smoking Abstinence

More than five million of worldwide deaths are the result of direct tobacco use. Nicotine dependence, usually maintained by tobacco smoking, is a psychiatric disorder that is characterized by compulsive drug-taking and withdrawal upon abrupt cessation of intake. Although most of the smokers express a desire to quit only about 14-49% of those who initiate smoking cessation achieve abstinence after receiving nicotine replacement. Social and environmental cues associated with drug intake play a substantial role in the maintenance of habits and contribute to relapse. The objective of this work was to evaluate how cues associated with smoking affect the brain after 24-hour smoking abstinence and after 7-days of treatment with transdermal nicotine and smoking abstinence (7-days). Five adult smokers underwent 2 similar sessions, on both, 24-hour and 7-days, of a cue-viewing task during functional Magnetic Resonance Image acquisitions. After 24-hour smoking cues not only activated central cortical regions involved in motor planning but also execution and cingulate gyrus associated with emotional and social cognitions. However, greater brain activation was observed after 7-days treatment in brain regions responsible for primary visual sensory processing, higher visual attention level and right prefrontal cortex responsible for sustained attention, memory, and decision-making processes. Results of this study suggest that a period of 7-days of treatment and smoking abstinence is not the enough time to inhibit or diminish the activation of areas involved in the processing of smoking-related sensory information and the planning/selection of relevant actions.

Normality Index of Ventricular Contraction Based on a Statistical Model from FADS

Radionuclide-based imaging is an alternative to evaluate ventricular function and synchrony and may be used as a tool for the identification of patients that could benefit from cardiac resynchronization therapy (CRT). In a previous work, we used Factor Analysis of Dynamic Structures (FADS) to analyze the contribution and spatial distribution of the 3 most significant factors (3-MSF) present in a dynamic series of equilibrium radionuclide angiography images. In this work, a probability density function model of the 3-MSF extracted from FADS for a control group is presented; also an index, based on the likelihood between the control groups contraction model and a sample of normal subjects is proposed. This normality index was compared with those computed for two cardiopathic populations, satisfying the clinical criteria to be considered as candidates for a CRT. The proposed normality index provides a measure, consistent with the phase analysis currently used in clinical environment, sensitive enough to show contraction differences between normal and abnormal groups, which suggests that it can be related to the degree of severity in the ventricular contraction dyssynchrony, and therefore shows promise as a follow-up procedure for patients under CRT.