Carotid artery wall motion analysis from B-mode ultrasound using adaptive block matching: in silico evaluation and in vivo application.

Valid risk stratification for carotid atherosclerotic plaques represents a crucial public health issue toward preventing fatal cerebrovascular events. Although motion analysis (MA) provides useful information about arterial wall dynamics, the identification of motion-based risk markers remains a significant challenge. Considering that the ability of a motion estimator (ME) to handle changes in the appearance of motion targets has a major effect on accuracy in MA, we investigated the potential of adaptive block matching (ABM) MEs, which consider changes in image intensities over time. To assure the validity in MA, we optimized and evaluated the ABM MEs in the context of a specially designed in silico framework. ABM(FIRF2), which takes advantage of the periodicity characterizing the arterial wall motion, was the most effective ABM algorithm, yielding a 47% accuracy increase with respect to the conventional block matching. The in vivo application of ABM(FIRF2) revealed five potential risk markers: low movement amplitude of the normal part of the wall adjacent to the plaques in the radial (RMA(PWL)) and longitudinal (LMA(PWL)) directions, high radial motion amplitude of the plaque top surface (RMA(PTS)), and high relative movement, expressed in terms of radial strain (RSI(PL)) and longitudinal shear strain (LSSI(PL)), between plaque top and bottom surfaces. The in vivo results were reproduced by OF(LK(WLS)) and ABM(KF-K2), MEs previously proposed by the authors and with remarkable in silico performances, thereby reinforcing the clinical values of the markers and the potential of those MEs. Future in vivo studies will elucidate with confidence the full potential of the markers.

Automated detection of the carotid artery wall in longitudinal B-mode images using active contours initialized by the Hough transform.

In this paper, a fully automatic active-contour-based segmentation method is presented, for detecting the carotid artery wall in longitudinal B-mode ultrasound images. A Hough-transform-based methodology is used for the definition of the initial snake, followed by a gradient vector flow (GVF) snake deformation for the final contour detection. The GVF snake is based on the calculation of the image edge map and the calculation of GVF field which guides its deformation for the estimation of the real arterial wall boundaries. In twenty cases there was no significant difference between the automated segmentation and the manual diameter measurements. The sensitivity, specificity and accuracy were 0.97, 0.99 and 0.98, respectively, for both diastolic and systolic cases. In conclusion, the proposed methodology provides an accurate and reliable way to segment ultrasound images of the carotid artery.

Time-frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?

The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies and can be quantified with a number of techniques. In this paper, real and simulated sleep spindles were regarded as AM/FM signals modeled by six parameters that define the instantaneous envelope (IE) and instantaneous frequency (IF) waveforms for a sleep spindle. These parameters were estimated using four different methods, namely the Hilbert transform (HT), complex demodulation (CD), matching pursuit (MP) and wavelet transform (WT). The average error in estimating these parameters was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT. The signal distortion induced by the use of a given method was greatest in the case of HT and MP. These two techniques would necessitate the removal of about 0.4s from the spindle data, which is an important limitation for the case of spindles with duration less than 1s. Although the CD method may lead to a higher error than HT and MP, it requires a removal of only about 0.23s of data. An application of this sleep spindle parameterization via the CD method is proposed, in search of efficient EEG-based biomarkers in dementia. Preliminary results indicate that the proposed parameterization may be promising, since it can quantify specific differences in IE and IF characteristics between sleep spindles from dementia subjects and those from aged controls.

Chest wall volume regulation during exercise in COPD patients with GOLD stages II to IV.

The present study investigated how end-expiratory ribcage and abdominal volume regulation during exercise is related to the degree of dynamic chest wall hyperinflation in patients with different spirometric severity of chronic obstructive pulmonary disease (COPD) based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. In total, 42 COPD patients and 11 age-matched healthy subjects were studied during a ramp-incremental cycling test to the limit of tolerance (W(peak)). Volume variations of the chest wall (at end expiration (EEV(cw)) and end inspiration) and its compartments (ribcage (V(rc)) and abdominal (V(ab))) were computed by optoelectronic plethysmography. At W(peak), only patients in GOLD stages III and IV exhibited a significant increase in EEV(cw) (increase of 454+/-509 and 562+/-363 mL, respectively). These patients did not significantly reduce end-expiratory V(ab), whereas patients in GOLD stage II resembled healthy subjects with significantly reduced end-expiratory V(ab) (decrease of 287+/-350 mL). In patients, the greater the increase in EEV(cw) at W(peak), the smaller the reductions in end-expiratory V(ab) and the greater the increase in end-expiratory V(rc). In chronic obstructive pulmonary disease patients with different spirometric disease severity, greater degrees of exercise-induced dynamic chest wall hyperinflation were accompanied by lower degrees of end-expiratory abdominal volume displacement and larger increases in end-expiratory ribcage volume.

Automated detection of the carotid artery wall in B-mode ultrasound images using active contours initialized by the Hough Transform.

Automatic segmentation of the arterial lumen from ultrasound images is an important and often challenging task in clinical diagnosis. We previously used the Hough Transform (HT) to automatically extract circles from sequences of B-mode ultrasound images of transverse sections of the carotid artery. In this paper, an active-contour-based methodology is suggested, initialized by the HT circle, in an attempt to extend previous findings and to accurately detect the arterial wall boundary. The methodology is based on the generation of a gradient vector flow field, an approach attempting to overcome conventional active contours constraints. Contour estimation is then achieved by deforming the initial curve (circle) based on the gradient vector flow field. In ten normal subjects, the specificity and accuracy of the segmentation were on average higher than 0.98, whereas the sensitivity was higher than 0.82. The methodology was also applied to four subjects with atherosclerosis, in which sensitivity, specificity and accuracy were comparable to those of normal subjects. In conclusion, the HT-initialized active contours methodology provides a reliable tool to detect the carotid artery wall in ultrasound images and can be used in clinical practice.

A mathematical model of the mechanical deformation of the carotid artery wall and its application to clinical data.

The study of arterial wall mechanics, including the study of stresses and strains experienced by the vascular wall, is pivotal in our understanding of arterial physiology. In this paper, a mathematical model is provided describing the deformation of the arterial wall in terms of 6 parameters. Actual deformation waveforms were also obtained from the analysis of B-mode ultrasound image sequences of the carotid artery using block-matching. The mathematical model was fitted to the clinical data using nonlinear least squares to determine the 6 parameters for 6 different locations along the posterior and 6 along the anterior walls, on the interface between the lumen and the intima-media complex (L-IM). On the posterior wall, 6 locations were also investigated at the interface between the intima-media complex and the adventitia (IM-A) as well as at the adventitia-surrounding tissue (A-T) boundary. The root mean square error was low for all locations indicating a good fit of the proposed model to the clinical data. The amplitude of the deformation, expressed through parameter alpha, was significantly lower in the A-T interface compared to the other two interfaces. The time when the systolic peak occurs, expressed through parameter t1, was significantly lower in the L-IM interface compared to the other two interfaces. Preliminary findings from a small group of diseased wall locations suggested that the parameters alpha, b and t1 were significantly different than healthy cases. This probably reflects alterations of arterial wall mechanics due to disease. This study showed that the proposed mathematical model is a satisfactory representation of the mechanical deformation of the carotid artery wall in the radial direction and can provide valuable information in the understanding of the mechanical behavior of the arterial wall.

Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles.

The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies. In this work, the sleep spindle is modeled as an AM-FM signal and parameterized in terms of six parameters, three quantifying the instantaneous envelope (IE) and three quantifying the instantaneous frequency (IF) of the spindle model. The IE and IF waveforms of sleep spindles from patients with dementia and normal controls were estimated using the time-frequency technique of Complex Demodulation (CD). Sinusoidal curve-fitting using a matching pursuit (MP) approach was applied to the IE and IF waveforms for the estimation of the six model parameters. Specific differences were found in sleep spindle instantaneous frequency dynamics between spindles from dementia subjects and spindles from controls.

Oxygen kinetics and debt during recovery from expiratory flow-limited exercise in healthy humans.

In healthy subjects expiratory flow limitation (EFL) during exercise can lower O(2) delivery to the working muscles. We hypothesized that if this affects exercise performance it should influence O(2) kinetics at the end of exercise when the O(2) debt is repaid. We performed an incremental exercise test on six healthy males with a Starling resistor in the expiratory line limiting expiratory flow to approximately 1 l s(-1) to determine maximal EFL exercise workload (W (max)). In two more square-wave exercise runs subjects exercised with and without EFL at W (max) for 6 min, while measuring arterial O(2) saturation (% SaO(2)), end-tidal pressure of CO(2) (P (ET)CO(2)) and breath-by-breath O(2) consumption VO2 taking into account changes in O(2) stored in the lungs. Over the last minute of EFL exercise, mean P (ET)CO(2) (54.7 +/- 9.9 mmHg) was significantly higher (P < 0.05) compared to control (41.4 +/- 3.9 mmHg). At the end of EFL exercise %SaO(2) fell significantly by 4 +/- 3%. When exercise stopped, EFL was removed, and we continued to measure VO2. During recovery, there was an immediate step increase in [Formula: see text] so that repayment of EFL O(2) debt started at a higher VO2 than control. Recovery VO2 kinetics after EFL exercise was best characterized by a double-exponential function with fundamental and slow time constants of 27 +/- 11 and 1,020 +/- 305 s, compared to control values of 41 +/- 10 and 1,358 +/- 320 s, respectively. EFL O(2) debt was 52 +/- 22% greater than control (2.19 +/- 0.58 vs. 1.49 +/- 0.38 l). We conclude that EFL exercise increases the O(2) debt and leads to hypoxemia in part due to hypercapnia.

Effects of rehabilitation on chest wall volume regulation during exercise in COPD patients.

In order to investigate underlying mechanisms, the present authors studied the effect of pulmonary rehabilitation on the regulation of total chest wall and compartmental (ribcage, abdominal) volumes during exercise in patients with chronic obstructive pulmonary disease. In total, 20 patients (forced expiratory volume in one second, mean +/- SEM 39 +/- 3% predicted) undertook high-intensity exercise 3 days x week(-1) for 12 weeks. Before and after rehabilitation, the changes in chest wall (cw) volumes at the end of expiration (EEV) and inspiration (EIV) were computed by optoelectronic plethysmography during incremental exercise to the limit of tolerance (W(peak)). Rehabilitation significantly improved W(peak) (57+/-7 versus 47+/-5 W). In the post-rehabilitation period and at identical work rates, significant reductions were observed in minute ventilation (35.1+/-2.7 versus 38.4+/-2.7 L x min(-1)), breathing frequency (26+/-1 versus 29+/-1 breaths x min(-1)) and EEV(cw) and EIV(cw) (by 182+/-79 and 136+/-37 mL, respectively). Inspiratory reserve volume was significantly increased (by 148+/-70 mL). Volume reductions were attributed to significant changes in abdominal EEV and EIV (by 163+/-59 and 125+/-27 mL, respectively). The improvement in W(peak) was similar in patients who progressively hyperinflated during exercise and those who did not (24 and 26%, respectively). In conclusion, pulmonary rehabilitation lowers chest wall volumes during exercise by decreasing the abdominal volumes. The improvement in exercise capacity following rehabilitation is independent of the pattern of exercise-induced dynamic hyperinflation.

Modeling the time-varying microstructure of simulated sleep EEG spindles using time-frequency analysis methods.

The time-varying microstructure of sleep spindles may have clinical significance and can be quantified and modeled with a number of techniques. In this paper, sleep spindles were regarded as AM-FM signals modeled by six parameters. The instantaneous envelope (IE) and instantaneous frequency (IF) waveforms were estimated using four different methods, namely Hilbert Transform (HT), Complex Demodulation (CD), Wavelet Transform (WT) and Matching Pursuit (MP). The six model parameters were subsequently estimated from the IE and IF waveforms. The average error, taking into account the error for each model parameter, was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT, for three different spindle model examples. The amount of distortion induced by the use of a given method is also important; distortion was the greatest (0.4 sec) in the case of HT. Therefore, in the case of real spindles, one could utilize CD and MP and, if the spindle duration is more than 1 sec, HT as well.

Characterization of carotid atherosclerotic plaques using frequency-based texture analysis and bootstrap.

Texture analysis of B-mode ultrasound images of carotid atheromatous plaque can be valuable for the accurate diagnosis of atherosclerosis. In this paper, two frequency-based texture analysis methods based on the Fourier Power Spectrum and the Wavelet Transform were used to characterize atheromatous plaques. B-mode ultrasound images of 10 symptomatic and 9 asymptomatic plaques were interrogated. A total of 109 texture features were estimated for each plaque. The bootstrap method was used to compare the mean values of the texture features extracted from the two groups. After bootstrapping, three features were found to be significantly different between the two types of plaques: the average value of the angular distribution corresponding to the wedge centered at 90 degrees, the standard deviation at scale 1 derived from the horizontal detail image, and the standard deviation at scale 2 derived from the horizontal detail image. It is concluded that frequency-based texture analysis in combination with a powerful statistical technique, such as bootstrapping, may provide valuable information about the plaque tissue type.

Patterns of dynamic hyperinflation during exercise and recovery in patients with severe chronic obstructive pulmonary disease.

BACKGROUND: Not all patients with severe chronic obstructive pulmonary disease (COPD) progressively hyperinflate during symptom limited exercise. The pattern of change in chest wall volumes (Vcw) was investigated in patients with severe COPD who progressively hyperinflate during exercise and those who do not. METHODS: Twenty patients with forced expiratory volume in 1 second (FEV(1)) 35 (2)% predicted were studied during a ramp incremental cycling test to the limit of tolerance (Wpeak). Changes in Vcw at the end of expiration (EEVcw), end of inspiration (EIVcw), and at total lung capacity (TLCVcw) were computed by optoelectronic plethysmography (OEP) during exercise and recovery. RESULTS: Two significantly different patterns of change in EEVcw were observed during exercise. Twelve patients had a progressive significant increase in EEVcw during exercise (early hyperinflators, EH) amounting to 750 (90) ml at Wpeak. In contrast, in all eight remaining patients EEVcw remained unchanged up to 66% Wpeak but increased significantly by 210 (80) ml at Wpeak (late hyperinflators, LH). Although at the limit of tolerance the increase in EEVcw was significantly greater in EH, both groups reached similar Wpeak and breathed with a tidal EIVcw that closely approached TLCVcw (EIVcw/TLCVcw 93 (1)% and 93 (3)%, respectively). EEVcw was increased by 254 (130) ml above baseline 3 minutes after exercise only in EH. CONCLUSIONS: Patients with severe COPD exhibit two patterns during exercise: early and late hyperinflation. In those who hyperinflate early, it may take several minutes before the hyperinflation is fully reversed after termination of exercise.

Analysis and quantification of arterial wall motion from B-mode ultrasound images - comparison of block-matching and optical flow.

Motion of the carotid atheromatous plaque may be responsible for plaque rupture and cerebrovascular symptoms. B-mode ultrasound allows non-invasive recording of arterial wall and plaque motion. Our aim was to analyze quantitatively patterns of arterial wall motion with different techniques. Temporal sequences of digitized B-mode ultrasound images of the carotid arteries of 10 young healthy subjects were interrogated. Arterial wall motion was analyzed using: a/ block-matching, and b/ optical flow. The motion of selected regions of the luminal surface of the arterial wall was estimated using region tracking and block-matching. The motion of areas of the arterial wall was estimated using optical flow. Waveforms showing radial and axial displacements, as well as radial and axial velocities were produced for the selected ROIs using both techniques. Both techniques produced waveforms with peaks, corresponding to cardiac cycle events, that occurred at similar time points. To study the similarity of the waveforms obtained from the two techniques, a cross-correlation coefficient was calculated. Cross-correlation coefficients were 0.72..0.22 and 0.70..0.19 for displacements and velocities, respectively, in the radial direction. In the axial direction, the coefficients were 0.32..0.39 and 0.24..0.22 for displacements and velocities, respectively. On the basis of this relative comparison of methods, we conclude that significant observations can be made for each motion analysis technique in terms of characterization of the mechanical properties of the tissue.

Comparison of B-mode, M-mode and Hough transform methods for measurement of arterial diastolic and systolic diameters.

Measurements of arterial diameter during the cardiac cycle are increasingly used to study the mechanical properties of the arterial wall and changes associated with disease. In this paper, diastolic and systolic diameters of the carotid arteries were estimated from ultrasound imaging using the following three different procedures: a/ B-mode imaging with region tracking and block-matching, b/ M-mode imaging with automated edge detection and c/ automatic segmentation of the arterial lumen at diastole and systole using the Hough transform. Transverse images of the carotid artery were used, in which the arterial lumen has an almost circular appearance. The values for systolic and diastolic diameters estimated with the Hough transform, 0.69±0.04 and 0.61±0.06, respectively, were closer to those estimated with B-mode and motion tracking, 0.75±0.07 and 0.67±0.09. A large difference was found for a subject with an atherosclerotic vessel wall. It is concluded that the Hough transform can be efficiently used to automatically segment healthy arterial wall lumen from B-mode ultrasound images of the carotid artery, assuming a circular shape. In atherosclerotic vessel walls the assumption for circular shape may no longer be valid, and thus the use of an elliptical shape may be more appropriate.

Robotic control in hand-assisted laparoscopic nephrectomy in humans - a pilot study.

Computer-assisted surgical devices, including laparoscopic surgical robotic arms, can be used in urologic surgery to minimize trauma. In this study, we explored the feasibility and applicability of using a robotic arm, AESOP (Computer Motion Inc, Goleta, CA), as a substitute for surgical assistants during hand-assisted laparoscopic nephrectomies in humans. Four patients (3 men and 1 woman, mean age 66 years) underwent robotic-assisted laparoscopic nephrectomy. The hand-assisted laparoscopic nephrectomy was completed successfully in all patients. The average operative time, estimated blood loss, and time to hospital discharge was 252.5 minutes, 0.57 ml, and 4.5 days, respectively. Postoperative satisfactory function was confirmed through laboratory tests, imaging exams and biochemical tests. No complications were reported for any of the patients. Parameters, such as the operative time, are expected to be further reduced when more experience with the use of the robot has been acquired. In conclusion, robotic-assisted laparoscopic nephrectomy is feasible and safe, and can be performed without complications. The potential long-term cost effectiveness of using robotic surgical assistants in laparoscopic surgery highlights the economic impact of this research and warrants further investigation.

Characterization of carotid atherosclerosis based on motion and texture features and clustering using fuzzy c-means.

Analysis of B-mode ultrasound images of the carotid atheromatous plaque includes the estimation of texture from static images and the estimation of motion from image sequences. The combination of these two types of information may be valuable for accurate diagnosis of vascular disease. The purpose of this paper was to study texture and motion patterns of carotid atherosclerosis and select the optimal combination of features that can characterize plaque. B-mode ultrasound images of 10 symptomatic and 9 asymptomatic plaques were interrogated. A total of 99 texture features were estimated using first-order statistics, second-order statistics, Laws texture energy and the fractal dimension. Only five texture features were significantly different between the two groups. In the same subjects, the motion of selected plaque regions was estimated using region tracking and block-matching and expressed through: a/maximal surface velocity (MSV), and b/maximal relative surface velocity (MRSV). MSV and MRSV were significantly lower in asymptomatic plaques suggesting more homogeneous motion patterns. Clustering using fuzzy c-means correctly classified 74% of plaques based on texture features only, and 79% of plaques based on motion features only. Classification performance reached 84% when a combination of motion and texture features was used.