Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study

INTRODUCTION

To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low- and intermediate-risk prostate cancer (PCa) treated with stereotactic ablative radiotherapy (SABR).

METHODS

Retrospective evaluation was performed for 30 patients using pre-treatment multi-parametric MR image datasets between 2017 and 2021. MR-based mean- and minimum apparent diffusion coefficients (ADCmean, ADCmin) were calculated for the intraprostatic dominant lesion. Therapeutic response was assessed using PSA levels. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis. Statistics performed with a significance level of p ≤ 0.05.

RESULTS

No biochemical relapse was detected after a median follow-up of twenty-three months (range: 3-50), with a median PSA of 0.01 ng/ml (range: 0.006-2.8) at the last examination. Significant differences were observed between the pre-treatment ADCmean, ADCmin parameters, and the group averages of patients with low and high 1-year-PSA measurements (p < 0.0001, p < 0.0001). In prediction, the random forest (RF) model outperformed the decision tree (DT) and support vector machine (SVM) models by yielding area under the curves (AUC), with 0.722, 0.685, and 0.5, respectively.

CONCLUSION

Our findings suggest that pre-treatment MR diffusion data may predict therapeutic response using the novel approach of machine learning in PCa patients treated with SABR.

IMPLICATIONS FOR PRACTICE

Clinicians shall measure and implement the evaluation of the suggested parameters (ADCmin, ADCmean) to provide the most accurate therapy for the patient.

Fractal Analyses of HRV Signals: A Comparative Study

In this paper, we have investigated the scaling behavior of the heart rate variability signals using the power spectral density (PSD), the discrete wavelet transform (DWT), and dispersive analysis (DA), and the maximum likelihood estimator (MLE) method. Results suggested the lowest variance for the MLE method, greatest variance for the PSD methods, the other methods somewhere in between.

Nonlinear Dynamics of Respiratory Patterns during Maturation

Objectives: In this paper, we quantify the fractal scaling characteristics of phrenic neurograms during eupnea in piglets, the output of the respiratory neural network that accompany maturation We also attempt to investigate whether the fractal properties are altered with maturation.

Methods: The phrenic neurogram in piglets was recorded from the C5 phrenic nerve during eupnea at four postnatal ages; the 3-6 days, the 7-14 days, 15-21 days and the 26-31 days age groups and analyzed using the maximum likelihood estimator (MLE).

Results: Our results suggest that the mean fractal measures over a recording of five consecutive breaths during eupnea for each piglet in each group were higher during the first 6 days and slightly decreased for the 7-14 days and significantly decreased for the 15-21 days and significantly increased for subsequent maturation (the 26-31 days old group).

Conclusions: We suggest that there is a significant alteration in the fractal organization in piglet respiratory patterns during maturation and a decrease in the fractal value is unique to the15-21 days old group.

Analysis of Acceleration Signals using Wavelet Transform

In this study, we attempted to discriminate the acceleration signal for horizontal level and stairway walking using wavelet-based fractal analysis method. The acceleration signal was measured close to the center of gravity of the body, while the subjects walked continuously in the corridor and up and down the stairs. We used the wavelet-based fractal analysis method to discriminate walking pattern. The parameter H which is related directly to the fractal dimension was estimated by the wavelet coefficient and was changed into low value during walking upstairs. By manually setting the threshold level for individual, it was possible to discriminate walking upstairs from the other walking type. However, the common feature among subjects was not shown between level walking and walking downstairs.

An Assessment of Thermal Stresses in Injection Moulded ABS Copolymer

Thermal residual stresses in injection mouldings result from the non-uniform cooling of the melt in the mould. Normally, compressive stresses develop at the surface and tensile ones within the core of the mouldings. The magnitude of these residual stresses was examined for an acrylonitrile-butadienestyrene copolymer (ABS) under various injection moulding conditions. Although the occurrences of thermal stresses are inevitable, the warpage results only when the residual stresses are out of balance. The imbalance of the residual stresses are caused by the non-uniform temperature distribution through the thickness of the mouldings which may be caused by variation in cross section, part geometry and temperature difference between the two surfaces. The magnitudes of thermal residual stresses in injection moulded ABS flat plaques were determined using a layer removal technique. The development of warpage in a 3D component (an L-shaped bracket) was modelled using the residual stresses obtained for the flat plaques and the predictions were compared with the experimental warpage measurements.

Effects of Imatinib Mesylate on Renin–Angiotensin System (RAS) Activity during the Clinical Course of Chronic Myeloid Leukaemia

The renin–angiotensin system (RAS) is involved in cell growth, proliferation and differentiation in bone marrow in an autocrine–paracrine manner, and it modulates normal and neoplastic haematopoietic cell proliferation. This study aimed to assess expressions of the RAS components, renin, angiotensinogen and angiotensin-converting enzyme (ACE), during imatinib mesylate treatment of patients with chronic myeloid leukaemia (CML). Expressions of RAS components were studied in patients with CML at the time of diagnosis ( n = 83) and at 3, 6 and 12 months after diagnosis ( n = 35) by quantitative real-time polymerase chain reaction. De novo CML patients had increased ACE, angiotensinogen and renin mRNA levels and these expression levels decreased following administration of imatinib. The RAS activities were significantly different among Sokal risk groups of CML, highlighting the altered biological activity of RAS in neoplastic disorders. The results of this study confirm that haematopoietic RAS affects neoplastic cell production, which may be altered via administration of tyrosine kinase inhibitors such as imatinib mesylate.

Investigating the interaction between oncogene and tumor suppressor protein

It is known that cancer develops when cells in a part of the body begin to grow out of control. Because cancer cells continue to grow and divide with no order, they never differentiate into the specific tissue, and thus, they are functionally different from normal cells. However, there are some genes that help to prevent cells' malignant behavior, and therefore, are referred to as tumor suppressor genes. Here, we have investigated the structural and functional relationships of p53, oncogene and interleukin 2 (IL2) proteins using the resonant recognition model (RRM), a physico-mathematical approach based on digital signal processing methods. In addition, using the RRM concepts, we have designed the peptide analoges that would exhibit tumor-suppression-like activity and be used in anticancer vaccine development.

Influence of peripheral chemodenervation on the complexity of respiratory patterns during early maturation

Previous studies in humans have revealed that, during development, the fetus/neonate may be susceptible to environmental perturbations such as overheating, smoking, hypercapnia and hypoxia (LEWIS and BOSQUE, 1995; MASKERY, 1995). In particular, alterations in behavioural states during early development can result in permanent alterations in their organisational states and subsequent abnormalities in the regulation of the cardiovascular and respiratory systems. The influence of the peripheral chemoreceptor afferent input on the approximate entropy (complexity) of the phrenic neurogram in the piglet was investigated in three different age groups: 3-7 days (n = 7), 10-16 days (n = 6) and 25-31 days (n = 4). The phrenic neurogram was recorded from piglets during control (40% O2) and severe hypoxia (gasping) (5-10% O2), before and after peripheral chemodenervation, and was analysed using the approximate entropy (ApEn) method. The results show that the complexity values of the phrenic neurogram during eupnea and gasping did not change significantly before and after chemodenervation, regardless of postnatal age. The complexity values during gasping were not significantly influenced by the carotid chemodenervation for the 3-7 day-old group, but they were significantly decreased by the carotid chemodenervation for the 10-16 day-old age group (p < 0.01) and the 25-31 day-old age group (p < 0.05). However, the complexity values significantly decreased when the O2 concentration was shifted from eupnea to gasping (p < 0.001), both before and after the chemodenervation (p < 0.001), regardless of the postnatal age. These results suggest that the peripheral chemodenervation reduces the complexity of the phrenic neurograms during gasping only for the 10-16 day-old and 25-31 day-old age groups, and it has no significant influence on the 3-7 day-old age group. Therefore it is speculated that the peripheral chemoreceptors may be inactive for the first seven days of postnatal life and become more active after seven days.

Fractal dynamics of body motion in post-stroke hemiplegic patients during walking

In this paper, we quantify the complexity of body motion during walking in post-stroke hemiplegic patients. The body motion of patients and healthy elderly subjects was measured by using the accelerometry technique. The complexity of body motion was quantified using the maximum likelihood estimator (MLE-) based fractal analysis methods. Our results suggest that the fractal dimensions of the body motion in post-stroke hemiplegic patients at several Brunnstrom stages were significantly higher than those of healthy elderly subjects (p < 0.05). However, in the hemiplegic patients, the fractal dimensions were more related to Brunnstrom stages.

Investigating body motion patterns in patients with Parkinson's disease using matching pursuit algorithm

Several recent studies have quantified abnormalities in Parkinsonian gait. However, few studies have attempted to quantify the regularity of body motion during walking in patients with Parkinson's disease. The aim of the paper was to characterise body motion patterns in healthy, elderly subjects and patients with Parkinson's disease during walking. Body motion was recorded during walking for 16 patients with Parkinson's disease and ten healthy, elderly subjects using a tri-axial accelerometer device. To characterise the body motion patterns, time-frequency patterns of the body acceleration signal were estimated using a matching pursuit algorithm. Data from the study showed that the healthy, elderly subjects and patients with Parkinson's disease had different time-frequency patterns. The time-frequency patterns were classified into four distinct patterns based on their time durations: vertical (< 0.15 s), circular (0.15-0.5 s), short horizontal (0.5-2.0 s) and long horizontal (> 2.0 s). The data showed that the energy of the long horizontal patterns, representing long-term smooth and regular (rhythmic) activities, significantly decreased, but the energy of the circular patterns, representing irregular activities, increased in the patients with mild Parkinson's disease, compared with those of the healthy, elderly subjects (p < 0.01). Futhermore, these features were seen more clearly in the body motions of severe case patients than is that of mild case patients. It was concluded that these differences are probably due to a lack of ability to control normal and smooth movement is Parkinson's disease.

Nonlinear dynamics of respiratory patterns during maturation

OBJECTIVES

In this paper, we quantify the fractal scaling characteristics of phrenic neurograms during eupnea in piglets, the output of the respiratory neural network that accompany maturation We also attempt to investigate whether the fractal properties are altered with maturation.

METHODS

The phrenic neurogram in piglets was recorded from the C5 phrenic nerve during eupnea at four postnatal ages; the 3-6 days, the 7-14 days, 15-21 days and the 26-31 days age groups and analyzed using the maximum likelihood estimator (MLE).

RESULTS

Our results suggest that the mean fractal measures over a recording of five consecutive breaths during eupnea for each piglet in each group were higher during the first 6 days and slightly decreased for the 7-14 days and significantly decreased for the 15-21 days and significantly increased for subsequent maturation (the 26-31 days old group).

CONCLUSIONS

We suggest that there is a significant alteration in the fractal organization in piglet respiratory patterns during maturation and a decrease in the fractal value is unique to the 15-21 days old group.

Multi-and monofractal indices of short-term heart rate variability

Indices of heart rate variability (HRV) based on fractal signal models have recently been shown to possess value as predictors of mortality in specific patient populations. To develop more powerful clinical indices of HRV based on a fractal signal model, the study investigated two HRV indices based on a monofractal signal model called fractional Brownian motion and an index based on a multifractal signal model called multifractional Brownian motion. The performance of the indices was compared with an HRV index in common clinical use. To compare the indices, 18 normal subjects were subjected to postural changes, and the indices were compared on their ability to respond to the resulting autonomic events in HRV recordings. The magnitude of the response to postural change (normalised by the measurement variability) was assessed by analysis of variance and multiple comparison testing. Four HRV indices were investigated for this study: the standard deviation of all normal R-R intervals; an HRV index commonly used in the clinic; detrended fluctuation analysis, an HRV index found to be the most powerful predictor of mortality in a study of patients with depressed left ventricular function; an HRV index developed using the maximum likelihood estimation (MLE) technique for a monofractal signal model; and an HRV index developed for the analysis of multifractional Brownian motion signals. The HRV index based on the MLE technique was found to respond most strongly to the induced postural changes (95% CI). The magnitude of its response (normalised by the measurement variability) was at least 25% greater than any of the other indices tested.

Effect of supraglottic mechanoreceptors on spatial mapping of respiratory related evoked responses using wavelet and Laplacian methods

Respiratory related evoked potentials (RREPs) were recorded from eight normal subjects in response to brief pressure pulses of -10 cm H2O with a duration of 200 ms to identify the contribution of supralaryngeal mechanoreceptors to the evoked responses by constraining application of the stimulus to the larynx and sublaryngeal regions through insertion of a laryngeal mask airway (LMA). Wavelet decomposition of RREP responses from 30 electrodes on the right side of the scalp was performed for eight frequency scales in time. The RREPs at each wavelet scale were enhanced by eliminating the wavelet coefficients due to artifacts and noise. After denoising, the third (125-150 Hz), fourth (62.5-125 Hz), fifth (31.25-62.5 Hz) and sixth (13.62-31.25 Hz) wavelet scales were used for estimation of the Laplacian. In addition, the global field power was calculated to quantify the wavelet-filtered RREP activity and to extract features for statistical analysis. Our results show that estimates of the global field power at the fourth and fifth wavelet scales are more significantly decreased after the insertion of the LMA than was true for scales 3 and 6. Further, after the LMA was inserted, the Laplacian showed reduced activity in the posterior-lateral region in four subjects and reductions in other places in the rest.

Respiratory related evoked responses to graduated pressure pulses using wavelet transform methods

In this study, the respiratory related evoked responses (RREPs) from ten normal subjects in response to brief varying pressure pulses at -6, - 10 and - 17 cm H2O with a duration of 200 ms were recorded to investigate how midlatency cortical evoked potentials measured on the scalp are affected in response to pressure pulses of varying magnitude at the mouth. Wavelet decomposition was performed for eight frequency scales in time for the RREPs. The RREPs at each wavelet scale were enhanced by eliminating the wavelet coefficients due to the artifacts and noise. After denoising, the third (125-250 Hz), fourth (62.5-125 Hz), fifth (31.25-62.5 Hz) and sixth (15.62-31.25 Hz) wavelet scales were quantified using the global field power estimates which serve to reduce the contamination by facial electromyogram responses evoked by the pressure stimulus. Our results show that the estimates of the global field power (GFP) at the third, fourth and fifth wavelet scales between 25 and 100 ms poststimulus were significantly increased when the pressure pulse was increased from -6 to -17cm H2O. On average, the total GFP from all scales, summed over the period 30-90 ms poststimulus, doubled from baseline with the -6 cm H2O stimulus, and increased linearly by 40% between -6 and -17 H2O. This supports the use of the GFP as an index of respiratory mechanoreceptor input to the central nervous system.

Thermal analysis studies of poly(etheretherketone)/hydroxyapatite biocomposite mixtures

Biocomposite formulations which have the potential to combine the proven mechanical performance of poly(etheretherketone) (PEEK) with the inherent bioactivity of hydroxyapatite (HA), may have a utility as load-bearing materials in a medical implant context. The effect of thermal processing on the relevant properties of the PEEK and/or HA components in any fabricated composite structure is, however, an important consideration for their effective exploitation. This paper reports the results of a detailed thermal characterization study of a series of PEEK/HA mixtures using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and modulated differential scanning calorimetry (MDSC). The TGA analyses show minimal weight loss for all of the mixtures and for a pure PEEK sample up to approximately 530 degrees C. Above this point there is a sharp on-set of decomposition for the PEEK component in each case. The temperature at which this feature occurs varies for each mixture in the approximate range 539-556 degrees C. This observation is supported by the presence of exotherms in the corresponding DSC scans, in the same temperature region, which are also assigned to PEEK decomposition. The temperature at which the degradation on-set occurs is found to decrease with increasing HA contribution. The use of the modulated DSC technique allows a number of important thermal events, not easily identifiable from the data obtained by the conventional method, to be clearly observed. In particular, the glass transition temperature (Tg) of the polymer can now be accurately determined. Using these thermal analysis data, calculations of the % crystallinity of PEEK in the mixtures have been made and compared with that of a 100% polymer sample. From these studies it is evident that the presence of HA does not adversely affect the degree of crystallinity of the PEEK component in the mixtures of interest over the thermal range studied.

Analysis of acceleration signals using wavelet transform

In this study, we attempted to discriminate the acceleration signal for horizontal level and stairway walking using wavelet-based fractal analysis method. The acceleration signal was measured close to the center of gravity of the body, while the subjects walked continuously in the corridor and up and down the stairs. We used the wavelet-based fractal analysis method to discriminate walking pattern. The parameter H which is related directly to the fractal dimension was estimated by the wavelet coefficient and was changed into low value during walking upstairs. By manually setting the threshold level for individual, it was possible to discriminate walking upstairs from the other walking type. However, the common feature among subjects was not shown between level walking and walking downstairs.

Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study

In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

Contribution of supraglottal mechanoreceptor afferents to respiratory-related evoked potentials in humans

We used the global field power (GFP) to estimate the magnitude and timing of activation of the somatosensory cortex by respiratory mechanoreceptor afferents in normal humans in response to brief, negative oral pressure pulses applied at the onset of inspiration. We compared responses before (test) and after insertion of a laryngeal mask airway (LMA) that prevented supraglottal airway receptors from sensing the applied stimulus. Evoked potential responses without supraglottic stimulation were smaller, with delayed or missing features, than those with all receptors stimulated. Supraglottic receptors contribute about one-half of the GFP summed over the 100 ms poststimulus, and subglottal receptors, including those in the larynx, provide a GFP response approximately 38% above baseline. The most obvious difference between test and LMA responses occurred at 55 ms on average, when the LMA GFP lacked activation features seen in the test condition. We conclude that mechanoreceptors above the larynx are responsible for a major portion of the midlatency afferent information arriving at the somatosensory cortex in response to applied pressure pulses.

Global field power helps separate respiratory-related evoked potentials from EMG contamination

Respiratory-related evoked potentials (RREPs) were stimulated by brief (200-ms) oral pressure pulses (-10 cmH(2)O) applied at the onset of inspiration in 12 subjects. Scalp potentials were measured at 30 sites on a rectangular grid that encompassed the right side of the scalp overlying the somatosensory cortex (SSC). Concurrent and significant masseter EMG (mEMG) activity was evoked by the pressure pulse, and we found correlational evidence for contamination of the RREP by the mEMG. The global field power (GFP) was used to provide a robust, reference-independent measure of SSC activation that provided partial insulation from mEMG contamination. The mean GFP from all subjects, reflective of afferent information from respiratory mechanoreceptors, showed a latency to onset of significant afferent SSC activity of approximately 25 ms. Scalp GFP activity during control experiments (absence of applied pressure) was significant and may reflect ongoing afferent activity from inspiration.

Enhancement of spectral analysis of myoelectric signals during static contractions using wavelet methods

In this paper, we introduce wavelet packets as an alternative method for spectral analysis of surface myoelectric (ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. Our simulation results show that wavelet packet estimate has slightly less mean square error (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give us some advantages over the traditional methods such as multiresolution of frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. We also introduce wavelet shrinkage method for improving spectral estimates by significantly reducing the MSE's for both Fourier and wavelet packet methods.

Investigating the contamination of electroencephalograms by facial muscle electromyographic activity using matching pursuit

It has been widely recognized and previously reported that electrical fields from facial muscle electromyographic (EMG) activity can contaminate the electroencephalogram (EEG), even when closely spaced, bipolar electrode configurations are used (personal observations). We suspected that EEG signals evoked in response to pressure changes in the upper airway may include EMG contamination subsequent to muscle reflexes triggered by the stimuli. We evaluated the potential contamination of the background EEG by voluntary activation of a facial muscle by obtaining simultaneous recordings in human subjects of the EEG (from Cz-C4) and masseter muscle EMG (from a bipolar surface electrode pair) before (quiet) and after voluntary tensing (VTen). Matching pursuit analysis permitted identification of different time-frequency patterns for each signal during the quiet period because the EMG signal has mostly atoms above 30 Hz compared to the EEG signal. However, the EEG showed periods of low-frequency activity unmatched in the EMG TF pattern below 30 Hz. During the tensing, most of the atoms of both the EEG and EMG shifted to the higher frequency regions above 100 Hz, making the separation difficult. These results further suggest that the matching pursuit method may not separate the background EEG from phasic EMG signals, both of which are nonstationary in nature.

A system for medical consultation and education using multimodal human/machine communication

Recent developments in networking and computing have enabled collaborative biomedical engineering research by geographically separated participants. One of the most promising goals is to use these technologies to extend human intellectual capabilities in medical decision making. These emerging technologies are poised to drastically reduce healthcare cost by providing service at remote locations. This also increases diagnosis capacity since information is made available to experts at any location. In this paper, we propose a novel application of a recently developed interactive and distributed system in medical consultation and education. Our approach builds on the notion that interactive and distributive capabilities of the system are crucial for medical consultation and education. The presented application uses a multiuser, collaborative environment with multimodal human/machine communication in the dimensions of sight, sound, and touch. The experimental setup, consisting of two user stations, and the multimodal interfaces, including sight (eye-tracking), sound (automatic speech), and touch (microbeam pen), were tested and evaluated. The system uses a collaborative workspace as a common visualization space. Users communicate with the application through a fusion agent by eye-tracking, speech, and microbeam pen. The audio/video teleconferencing is also included to help the radiologists to communicate with each other simultaneously while they are working on the mammograms. The system used in this study has three software agents: a fusion agent, a conversational agent, and an analytic agent. The fusion agent interprets multimodal commands by integrating the multimodal inputs. The conversational agent answers the user's questions and detects human-related or semantic errors and notifies the user about the results of the image analysis. The analytic agent enhances the digitized images using the wavelet denoising algorithm if requested by the user. To show how well the system performs in practice, we used the system for medical consultation on mammograms. Results also show that the relevant information about the region of interest (ROI) of the mammograms chosen by the users is extracted automatically and used to enhance the mammograms.

Effects of maternal alcohol intake on fractal properties in human fetal breathing dynamics

Fractal methods have been found to be useful in characterizing biomedical signals. The use of fractal estimation requires the estimation of parameter H, which is directly related to the fractal dimension D. Here, we propose a new approach which is a combination of the wavelet transform and fractal estimators to characterize the human fetal breathing signals before and after the intake of two glasses of wine by a mother. This study was performed on 26 fetuses. The variances of the wavelet coefficients were estimated at each scale. The slope of the representation on a logarithmic plot from the scales 5 to 1 was found to be increased after alcohol intake. Our results suggested that fetal breathing rates have a rough structure before the alcohol intake and a smooth structure after alcohol intake.

Fractal analyses of HRV signals: a comparative study

In this paper, we have investigated the scaling behavior of the heart rate variability signals using the power spectral density (PSD), the discrete wavelet transform (DWT), and dispersive analysis (DA), and the maximum likelihood estimator (MLE) method. Results suggested the lowest variance for the MLE method, greatest variance for the PSD methods, the other methods somewhere in between.

Sequential polyurethane-poly(methylmethacrylate) interpenetrating polymer networks as ureteral biomaterials: mechanical properties and comparative resistance to urinary encrustation

The mechanical properties and resistance to urinary encrustation of sequential-interpenetrating polymer networks (IPNs) composed of polyurethane (PU) and polymethylmethacrylate (PMMA), have been described. Mechanical properties were determined using tensile testing and dynamic mechanical analysis, whereas resistance to encrustation was examined using an in vitro model for encrustation simulating in vivo encrustation. Maximum and minimum tensile strength at break, Young's modulus, storage and loss moduli were associated with PMMA and PU, respectively. IPNs demonstrated intermediate mechanical properties which were dependent on the concentrations of the component polymers. Conversely, maximum elongation at break was observed for PU and this parameter decreased as the concentration of PMMA increased in the IPN. The dynamic mechanical damping parameter, tan delta, was similar for all IPNs at 37 degrees C. Increased advancing and decreased receding contact angles were observed for IPNs in comparison with the native PU. The rate and extent of encrustation, measured as the percentage surface coverage, was similar for PU, IPNs and PMMA. In contrast, encrustation on polyhydroxyethylmethacrylate, a model hydrogel, was greater than observed for the IPNs or component polymers. No apparent correlation was observed between the rate and/or extent of encrustation and polymer contact angle. It is concluded that these IPNs may be of clinical benefit in patients providing stent resistance to extrinsic compression of the ureter in comparison with native PU. The comparable resistance to encrustation between the IPNs and PU indicates that the use of IPNs should not be restricted in this regard.

Mechanical performance of polyurethane ureteral stents in vitro and ex vivo

A serious problem associated with the use of ureteral stents is fracture in situ. Following clinical observations of fracture of polyurethane stents in vivo, this study examined the mechanical properties of 17 polyurethane stents (double-J containing drainage holes) retrieved from patients over a 24-week period of insertion. In addition, stents were immersed in human and artificial urine in an in vitro model at 37 degrees C to determine their general propensity to fracture. Mechanical properties of ureteral stents were examined using the standard ASTM D-412 tensile test and by the novel application of dynamic mechanical analysis (DMA). The ultimate tensile strength and elongation at break (but not the Young's modulus) of unused polyurethane stent sections containing side-drainage holes were greater than stent sections devoid of side-drainage holes. No correlations were observed between increased or decreased Young's modulus, ultimate tensile strength or elongation at break of polyurethane stents and their time of immersion in either human urine or artificial urine in simulated upper urinary tract conditions of 37 degrees C and 5% CO2. Similarly, no correlations were observed between Young's modulus, ultimate tensile strength or elongation of polyurethane stents and stent dwell time in situ. DMA of retrieved stents revealed that their tan delta value and storage modulus did not differ significantly from unused stents following dwell times in situ of up to 24 weeks. No changes in the glass transition temperatures were observed in retrieved stents. Although patient variation was observed, the results indicate that the polyurethane stents examined in vitro and following removal from patients did not exhibit any greater propensity to fracture than their unused counterparts. Fracture of retrieved polyurethane stents, arising in vivo and also during subsequent tensile testing, was observed to occur along the drainage holes, suggesting that elimination of these holes will reduce the incidence of polyurethane ureteral stent fracture in use.

Noninvasive cardiac output estimation: a preliminary study

The availability of a simple-to-use, automatic measurement system for noninvasive flow estimation is imperative, given the clinical demand for an acceptable noninvasive procedure rather than the standard invasive procedure of thermodilution. A method for calculating cardiac output from noninvasively derived pressure pulses has been developed, and the results of a preliminary evaluation study on post-cardiac surgery patients for whom invasive flow measures were readily available for comparison are provided in this report. The proposed method relies on fast Fourier transform (FFT) analysis of pulses measured externally at the carotid and femoral pressure points. A transfer function of the aorta is computed from digitally filtered pulse measurements, and a tapered model of the aorta is parametrically adapted using a simplex optimization algorithm so that its transfer function matches that derived experimentally. An aortic input impedance term is obtained from the optimized model and utilized along with the carotid pulse (analogous to input voltage) to compute aortic flow. In addition to its automation, attractive features of this method include the requirement for relatively few pulses for analysis as well as considerable resistance to noise artifact. For 59 data records collected from 54 post-cardiac surgery patients, the average flow measurements computed over several pulses compare well with the standard, invasive method of thermodilution. Preliminary results also indicate a strong potential for tracking changes in cardiac output over time, and invite further use of the method in monitoring hemodynamically unstable patients.

Investigating the effect of maternal alcohol intake on human fetal breathing rate using adaptive time-frequency analysis methods

In this study, the matching pursuit (MP) method which is a modified version of the wavelet transform (WT) method was proposed to examine the effects of alcohol on human fetal breathing rates in both time and frequency domains. The matching pursuit method was chosen since the classical Fourier transform may not represent signals which have stationary characteristics and wavelet transform may not represent signals whose Fourier transforms have a narrow frequency support. Our results show that the horizontal structured atoms representing the sinusoidal activity at all frequency ranges disappeared and the vertical structured atoms representing the discontinuous spike type activity increased. In addition, the circular structured atoms at the high frequency range shifted to the low frequencies after the alcohol intake. The results also suggested that the matching pursuit is most suitable for analyzing the fetal breathing rate signals with and without alcohol intake.

Autoregressive spectral analysis of phrenic neurogram during eupnea and gasping

During hypoxic gasping, the phrenic neurogram (PN) has a steeper rate of rise, an augmented amplitude, and a shorter duration than is seen during eupnea. Because hypoxia reduces neuronal activity, we hypothesized that gasping would be characterized in the frequency domain by enhanced low-frequency power compared with eupnea. Autoregressive (AR) spectral analysis of the PN in chloralose-anesthetized, vagotomized, peripherally chemodenervated cats was performed during eupnea and hypoxic gasping. During eupnea, significant spectral peaks were seen at 41 +/- 2 and 93 +/- 2 (SE) Hz. In all cats, the 41-Hz spectral peak disappeared during hypoxic gasping and was replaced by a high-power, low-frequency peak at 26 +/- 1 Hz. No consistent change in the frequency or power of the high-frequency spectral peak was seen during gasping. To determine whether changes in the AR spectrum of the PN during gasping result from augmented respiratory output, we compared the AR spectra of the PN during gasping, hypercapnia (end-tidal CO2 fraction = 0.09), and carotid sinus nerve stimulation. Unlike during gasping, there was no shift in power toward lower frequencies during hypercapnia and carotid sinus nerve stimulation. We conclude that the spectral characteristics of gasping, loss of the medium-frequency peak and the appearance of low-frequency (< 30-Hz) power, are unique to this respiratory pattern.

A comparison of analytical methods for the study of fractional Brownian motion

Fractional Brownian motion (FBM) provides a useful model for many physical phenomena demonstrating long-term dependencies and l/f-type spectral behavior. In this model, only one parameter is necessary to describe the complexity of the data, H, the Hurst exponent. FBM is a nonstationary random function not well suited to traditional power spectral analysis however. In this paper we discuss alternative methods for the analysis of FBM, in the context of real-time biomedical signal processing. Regression-based methods utilizing the power spectral density (PSD), the discrete wavelet transform (DWT), and dispersive analysis (DA) are compared for estimation accuracy and precision on synthesized FBM datasets. The performance of a maximum likelihood estimator for H, theoretically the best possible estimator, are presented for reference. Of the regression-based methods, it is found that the estimates provided by the DWT method have better accuracy and precision for H > 0.5, but become biased for low values of H. The DA method is most accurate for H < 0.5 for a 256-point data window size. The PSD method was biased for both H < 0.5 and H > 0.5.

Evaluation of the tracking potential of a noninvasive estimator of cardiac output

A robust, automatic measurement system for calculating cardiac output noninvasively has recently been developed. The proposed method relies on fast Fourier transform (FFT) analysis of pulses measured externally at the carotid and femoral pressure points. A transfer function of the aorta is computed from these (calibrated) pressure measurements, and a tapered model of the aorta is parametrically adapted so that its transfer function matches that derived experimentally. Incorporated in the system are a custom routine for digitally filtering pressure data and a simplex optimization algorithm for identification of aortic parameters essential to the calculation of impedance and aortic flow. Once flow has been reconstructed in the time domain it is averaged to a stroke volume and multiplied by the heart rate to yield cardiac output. Flow measurements are computed over several pulses and compared against the standard, invasive procedure of thermodilution. Preliminary results for a dynamic investigation of the method indicate a strong potential for tracking changes in cardiac output over time, thus advocating its use in monitoring hemodynamically unstable patients.

Numerical and experimental stress analysis of a polymeric composite hip joint prosthesis

A comparative stress analysis of a polymeric composite hip joint replacement was performed. A prototype short carbon-fiber reinforced PEEK (CF/PEEK) prosthesis was manufactured by injection molding. Finite element (FE) analysis was conducted on intact femurs and femurs fitted with the CF/ PEEK and the titanium prostheses under various loading conditions. FE models were validated by experimental strain gauge measurements by using synthetic femurs. There was a good agreement between the two methods except in the hoop strain of the femur in the calcar region because of the assumption of the isotropic material properties. The stem stresses were lower for the CF/PEEK prosthesis than for the titanium prosthesis. The maximum stress was in the spigot of the CF/PEEK prosthesis, but in the middle third of the stem of the titanium prosthesis. Stress generated in the cement was almost equal for both prostheses although more load was transferred, via cement, to the femur with the CF/ PEEK prosthesis because the load transfer took place over a larger area. An out-of-plane component of the joint load causes higher prosthesis and cement stresses.

The effects of morphine on the relationship between fetal EEG, breathing and blood pressure signals using fast wavelet transform

In this study, we introduce the fast wavelet transform (WT) as a method for investigating the effects of morphine on the electroencephalogram (EEG), respiratory activity and blood pressure in fetal lambs. Morphine was infused intravenously at 25 mg/h. The EEG, respiratory activity and blood pressure signals were analyzed using WT. We performed wavelet decomposition for five sets of parameters D2j where -1 < j < -5. The five series WTs represent the detail signal bandwidths: 1, 16-32 Hz; 2, 8-16 Hz; 3, 4-8 Hz; 4, 2-4 Hz; 5, 1-2 Hz. Before injection of the high-dose morphine, power in the EEG was high in all six frequency bandwidths. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the low-voltage fast activity (LVFA) EEG signal. Respiratory activity was observed during only some of the LVFA periods, and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth bands. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. There was a strong relationship between fetal EEG, blood pressure and breathing movements. However, the injection of high-dose morphine resulted in a disruption of the normal cyclic pattern between the two EEG states and a significant increase in power in the first wavelet band. In addition, the high-dose drug resulted in a significant increase in the power of respiratory signal in the fourth and fifth wavelet bands, while power was reduced in the third wavelet band. Breathing activity was also continuous after the drug. The high-dose morphine also caused a temporary power shift from the third wavelet band to the fourth wavelet band for the 30-min period after injection of drug. Finally, high-dose morphine completely destroyed the correlation between EEG, breathing and blood pressure signals.