Purpose To estimate surface-based wall shear stress (WSS) and evaluate flow patterns in ascending aortic dilatation (AscAD) using a high-resolution, time-resolved, three-dimensional (3D), three-directional velocity encoded, radially undersampled phase contrast magnetic resonance sequence (4D PC-MRI). Materials and Methods 4D PC-MRI was performed in 11 patients with AscAD (46.3±22.0 years) and 10 healthy volunteers (32.9±13.4 years) after written informed consent and IRB-approval. Following manual vessel wall segmentation of the ascending aorta (MATLAB, The Mathworks, Natick, MA), a 3D surface was created using spline interpolation. Spatial WSS variation based on surface division in 12 segments and temporal variation were evaluated in AscAD and normal aortas. Visual analysis of flow patterns was performed based on streamlines and particle traces using EnSight (v9.0, CEI, Apex, NC). Results AscAD was associated with significantly increased diastolic WSS, decreased systolic to diastolic WSS ratio, and delayed onset of peak WSS (all P < 0.001). Temporally averaged WSS was increased and peak systolic WSS was decreased. The maximum WSS in AscAD was on the anterior wall of the ascending aorta. Vortical flow with highest velocities along the anterior wall and increased helical flow during diastole were observed in AscAD compared to controls. Conclusion Changes in WSS in the ascending aorta of AscAD correspond to observed alterations in flow patterns compared to controls.
Objective/Hypothesis Vocal fold vibration is associated with four distinct vibratory patterns: those of the right-upper, right-lower, left-upper, and left-lower vocal fold lips. The purpose of this study was to propose a least squares method to quantify the vibratory properties of each of the four vocal fold lips via videokymography (VKG). Study Design This was a methodological study designed to examine the impact of subglottal pressure and line-scan position on mucosal wave parameters. Methods VKG, a line-scan imaging technique, has proven to be an effective method for studying vocal fold vibratory patterns. This study used VKG images and an automatic mucosal wave extraction method to examine the vibration of each individual vocal fold lip of 17 excised canine larynges under differing subglottal pressures and line-scan positions. Results Varying subglottal pressure led to results consistent with previous studies. Examination of the vocal folds at different line-scan positions along its length revealed that amplitude is greatest at the midpoint of the vocal fold, followed by the anterior portion of the vocal fold, with the posterior portion having the lowest amplitude (P < .001). Frequency and phase delay did not change significantly throughout the length of the vocal fold. Conclusions The method used in this study allows for easy determination of four sets of vibratory parameters, and examination of the effect of biomechanical parameters on vocal fold vibrations.
In this paper, we investigate the biomechanical applications of spatiotemporal analysis and nonlinear dynamic analysis to quantitatively describe regular and irregular vibrations of twelve excised larynges from high-speed image recordings. Regular vibrations show simple spatial symmetry, temporal periodicity, and discrete frequency spectra, while irregular vibrations show complex spatiotemporal plots, aperiodic time series, and broadband spectra. Furthermore, the global entropy and correlation length from spatiotemporal analysis and the correlation dimension from nonlinear dynamic analysis reveal a statistical difference between regular and irregular vibrations. In comparison with regular vibrations, the global entropy and correlation dimension of irregular vibrations are statistically higher, while the correlation length is significantly lower. These findings show that spatiotemporal analysis and nonlinear dynamic analysis are capable of describing the complex dynamics of vocal fold vibrations from high-speed imaging and may potentially be helpful for understanding disordered behaviors in biomedical laryngeal systems.
High-speed digital imaging can provide valuable information on disordered voice production in voice science. However, the large amounts of high-speed image data with limited image resolutions produce significant challenges for computer analysis, and thus effective and efficient image edge extraction methods allowing for the batch analysis of high-speed images of vocal folds is clinically important. In this paper, a novel algorithm for automatic image edge detection is proposed to effectively and efficiently process high-speed images of the vocal folds. The method integrates Lagrange interpolation, differentiation, and Canny edge detection, which allow objective extraction of aperiodic vocal fold vibratory patterns from large numbers of high-speed digital images. This method and two other popular algorithms, histogram and active contour, are performed on 10 sets of high-speed video data from excised larynx experiments to compare their performances in analyzing high-speed images. The accuracy in computing glottal area and the computation time of these methods are investigated. The results show that our proposed method provides the most accurate and efficient detection, and is applicable when processing low-resolution images. In this study, we focus on developing a method to effectively and efficiently process high-speed image data from excised larynges. However, in addition we show the clinical potential of this method by use of example high-speed image data obtained from a patient with vocal nodules.The proposed automatic image-processing algorithm may provide a valuable biomedical application for the clinical assessment of vocal disorders by use of high-speed digital imaging.
Shape change of the left atrium (LA) and LA appendage in atrial fibrillation (AF) patients is hypothesized to be linked to AF pathology and to play a role in thrombogenesis; however, many aspects of shape variation in the heart are poorly understood. To date, studies of the LA shape in AF have been limited to empirical observation and summary metrics, such as volume and its likeness to a sphere. This paper describes a more comprehensive approach to the study of the LA shape through the use of computationally derived statistical shape models. We describe practical approaches that we have developed to extract shape parameters automatically from the three-dimensional MR images of the patient. From these images and our techniques, we can produce a more comprehensive description of LA geometric variability than that has been previously possible. We present the methodology and results from two examples of specific analyses using shape models: (1) we describe statistically significant group differences between the normal control and AF patient populations (n = 137) and (2) we describe characteristic shapes of the LA appendage that are associated with the risk of thrombogenesis determined by transesophageal echocardiography (n = 203).
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