Maximum Frequency Envelope Research Articles

511 Parity and age at first childbirth in relation to the risk of different breast cancer subgroups

The ability of two Doppler waveform quality indices to discriminate between high- and low-quality waveforms was tested using 427 sets of umbilical artery Doppler waveforms from patients. The waveforms had been acquired using a 4-MHz continuous-wave Doppler unit. The quality indices (QI) were based on an assessment of the degree of noise of the maximum frequency envelope of the waveforms, and were first a correlation between successive waveform envelopes (QI1), and, second, a sum of local linearity measures (Q12). The sets of waveforms were graded subjectively according to the clarity of the outline of the waveforms, the degree of interference in the region of the spectrum above the outline, and in terms of the degree of variability caused by fetal breathing. At 90% sensitivity for detection of low-quality waveforms according to a high envelope clarity score, the specificities were 68.2% and 52.7%, respectively, for Q11 and Q12. Q11 was independent from pulsatility index and waveform length, but showed strong dependence on fetal breathing. QI2 showed strong independence from pulsatility and fetal breathing and reasonable independence from waveform length. Both Q11 and Q12 performed poorly when there was a large degree of noise in the region of the spectrum above the envelope; however, this poor performance was often related to the inability of the maximum frequency follower to estimate correctly the maximum frequency envelope in those conditions so that the high waveform quality values reflected the erroneous calculation of pulsatility index in those cases.

Usage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signals

In this paper, we have proposed a novel similarity-based weighting method (SBWM), which combines similarity measure and weighting based on trend association (WBTA) method proposed by Sun Yi et al. (ICNN&B international conference, vol 1, pp 266-269, 2005). The aim of this study is to improve the classification accuracy of atherosclerosis, which is a common disease among the public. The proposed method consists of three parts: (1) feature extraction part related with atherosclerosis disease using fast Fourier transformation (FFT) modeling and calculation of maximum frequency envelope of sonograms, (2) data pre-processing part using SBWM, including different similarity measures such as cosine amplitude method, max-min method, absolute exponential method, and exponential similarity coefficient, and (3) classification part using artificial immune recognition system (AIRS) and Fuzzy-AIRS classifier algorithms. While AIRS and Fuzzy-AIRS algorithms obtained 71.92 and 78.94% success rates, respectively, the combination of SBWM with classifier algorithms including AIRS and Fuzzy-AIRS obtained 100% success rate on all the similarity measures. These results show that SBWM has produced very promising results in the classification of atherosclerosis from carotid artery Doppler signals. In future, we will use a larger dataset to test the proposed method.

Determining Fractal Dimension of Umbilical Artery Doppler Signals Using Hurst Exponent

Doppler signals from the umbilical artery of 20 women with normal pregnancy between 18 and 20 weeks of gestation were recorded. The AR spectral analysis method has been used to obtain the Doppler sonograms of umbilical artery belonging to normal pregnant subjects and fractal dimension curves were calculated using Hurst exponent. RI; PI and S/D indexes have been calculated from the maximum frequency envelope of Doppler sonograms and from the fractal dimension curve. Area under the curve from ROC curve for RI, PI and S/D indexes derived from maximum frequency waveform were calculated as 0.931, 0.959, 0.938, respectively and area under the curve for RI, PI and S/D indexes derived from fractal dimension curve were calculated as 0.933, 0.961, and 0.941, respectively. These results show that, the Doppler indexes derived from fractal dimension curve are as sensitive as Doppler indexes derived from maximum velocity curve. Power Spectral Density graphics were derived from Doppler signals and Hurst exponent values calculated to evaluate the blood flow changing during pregnancy. ROC curve for PSD(HURST) index was calculated as 0.97. According to this result, PSD(HURST) index is more sensitive to detect the blood flow changing than traditional Doppler indexes.

Medical diagnosis of atherosclerosis from Carotid Artery Doppler Signals using principal component analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS)

In this study, we proposed a new medical diagnosis system based on principal component analysis (PCA), k-NN based weighting pre-processing, and Artificial Immune Recognition System (AIRS) for diagnosis of atherosclerosis from Carotid Artery Doppler Signals. The suggested system consists of four stages. First, in the feature extraction stage, we have obtained the features related with atherosclerosis disease using Fast Fourier Transformation (FFT) modeling and by calculating of maximum frequency envelope of sonograms. Second, in the dimensionality reduction stage, the 61 features of atherosclerosis disease have been reduced to 4 features using PCA. Third, in the pre-processing stage, we have weighted these 4 features using different values of k in a new weighting scheme based on k-NN based weighting pre-processing. Finally, in the classification stage, AIRS classifier has been used to classify subjects as healthy or having atherosclerosis. Hundred percent of classification accuracy has been obtained by the proposed system using 10-fold cross validation. This success shows that the proposed system is a robust and effective system in diagnosis of atherosclerosis disease.

Neural network analysis of Doppler ultrasound blood flow signals: A pilot study

It has been hypothesised that each artery in the human body has its own characteristic “signature”—a unique Doppler flow profile which can identify the artery and which may also be modified by the presence of disease. To test this hypothesis an artificial neural network (ANN) was trained to recognise three groups of maximum frequency envelopes derived from Doppler ultrasound spectrograms; these were the common carotid, common femoral and popliteal arteries. Data were collected from 24 subjects known to have no significant atheromatous disease. The maximum frequency envelopes were used to create sets of training and testing vectors for a backpropagation ANN. The ANN demonstrated a high success rate for appropriate classification of the test vectors: 100% for the carotid; 92% for the femoral; and 96% for the popliteal artery. This work has demonstrated the ability of the ANN to differentiate accurately between different and similar flow profiles, outlining the potential of this technology to identify subtle changes induced by the onset of arterial disease within a specific vessel. It should be noted that the ANN not only models the maximum frequency envelope but also, unlike standard indices, makes a decision as to which artery the maximum frequency envelope belongs to, thus providing the potential to obviate human subjective classification.

An investigation of simulated umbilical artery doppler waveforms. I. The effect of three physical parameters on the maximum frequency envelope and on pulsatility index

The effect of three physical parameters on the accuracy of estimation of the maximum frequency envelope and pulsatility index (PI) of simulated umbilical artery Doppler waveforms was investigated. The physical parameters were beam-vessel angle, the offset between the beam axis and vessel axis, and the thickness of overlying attenuating material. Waveforms were acquired using a physiological flow phantom. The maximum frequency envelope was calculated using a threshold maximum frequency follower which was adaptive to the level of background noise. A gold standard maximum frequency envelope was obtained from the ensemble averaged waveform when there was alignment of beam and vessel axis, a 50° beam-vessel angle and 2 cm of attenuating material. Indices of bias, variability and accuracy of estimation of the maximum frequency envelope and PI were calculated by comparing subsequent maximum frequency envelopes with the gold standard maximum frequency envelope. Both the maximum frequency envelope and PI were estimated to a similar degree of accuracy over a wide range of physical conditions. In this study, the error in PI was less than 0.15 for beam-vessel angles less than 80°, for beam-vessel axis offset distances less than 7.5 mm, at a transducer-vessel distance of 5 cm, and for attenuator thicknesses less than 4.5 cm. The percentage root-mean square error for estimation of the maximum frequency envelope was approximately 10% or less for beam-vessel angles less than 75°, for beam-vessel axis offset distances less than 7.5 mm, and for attenuator thicknesses less than 4 cm.

An investigation of simulated umbilical artery Doppler waveforms. III. The effect of noise reduction algorithms on the maximum frequency envelope and on the pulsatility index

The effect of two noise reduction algorithms on the accuracy of estimation of the maximum frequency envelope and pulsatility index (PI) of simulated umbilical artery Doppler waveforms was investigated. The algorithms were: first, smoothing of the envelope from unfiltered Doppler spectra using a double window modified trimmed mean (DWMTM) filter and second, speckle and noise reduction of the Doppler spectrum using an image processing method. The test population consisted of waveforms where the degree of beam-vessel misalignment had been varied. The accuracy of estimation of the maximum frequency envelope and the PI was calculated by comparing each set of waveforms with the gold-standard maximum frequency envelope from the ensemble averaged waveform obtained with no misalignment. Speckle reduction gave rise to PI values that were low by 0.1 (3%–4%). When there was no background noise present the improvements in envelope estimation were factors of 1.27 and 1.24, respectively, for the DWMTM method and the spectral filter, whereas the factors were 1.56 and 2.07 when background noise was present. For estimation of PI the DWMTM filter was superior. For no background noise the DWMTM filter gave a factor of 3.36 improvement whereas there was no improvement with the spectral filter. When background noise was present the factors for improvement in PI estimation were 2.39 and 4.16.

Clinical trial of umbilical artery doppler waveform quality indices

The ability of two Doppler waveform quality indices to discriminate between high- and low-quality waveforms was tested using 427 sets of umbilical artery Doppler waveforms from patients. The waveforms had been acquired using a 4-MHz continuous-wave Doppler unit. The quality indices (QI) were based on an assessment of the degree of noise of the maximum frequency envelope of the waveforms, and were first a correlation between successive waveform envelopes (QI1), and, second, a sum of local linearity measures (QI2). The sets of waveforms were graded subjectively according to the clarity of the outline of the waveforms, the degree of interference in the region of the spectrum above the outline, and in terms of the degree of variability caused by fetal breathing. At 90% sensitivity for detection of low-quality waveforms according to a high envelope clarity score, the specificities were 68.2% and 52.7%, respectively, for QI1 and QI2. QI1 was independent from pulsatility index and waveform length, but showed strong dependence on fetal breathing. QI2 showed strong independence from pulsatility and fetal breathing and reasonable independence from waveform length. Both QI1 and QI2 performed poorly when there was a large degree of noise in the region of the spectrum above the envelope; however, this poor performance was often related to the inability of the maximum frequency follower to estimate correctly the maximum frequency envelope in those conditions so that the high waveform quality values reflected the erroneous calculation of pulsatility index in those cases.

An investigation of simulated umbilical artery Doppler waveforms. II. A comparison of three Doppler waveform quality indices

Three Doppler waveform quality indices based upon assessment of the noise of the maximum frequency envelope of simulated umbilical artery waveforms were investigated. These indices were: an estimate of the correlation between successive waveforms (QI1), a local linearity measure (QI2) and a ratio of two regions of the Fourier transform amplitude spectrum of the maximum frequency envelope (QI3). Simulated umbilical artery waveforms were acquired from a physiological flow phantom. A test population was used consisting of a large number of waveforms where one of three physical variables had been adjusted to produce waveforms of varying quality. These three physical variables were: beam-vessel angle, beam-vessel axial misalignment and attenuator thickness. For this group of waveforms the accuracy of estimation of the maximum frequency envelope and pulsatility index (PI) were known. All three quality indices gave good separation of high- and low-quality waveforms based upon threshold values of the accuracy of PI and maximum frequency envelope. The dependence of each quality index on fetal breathing, waveform length and waveform pulsatility was investigated. QI2, the local linearity measure, showed most promise in its independence from these variables.

A comparison of three different filters for speckle reduction of doppler spectra

This paper is concerned with speckle suppression in Discrete Fourier Transform based Doppler signals by means of digital image processing. The Doppler spectrum is treated as a greyscale image, and three different noise smoothing algorithms are applied to it. These are the Double Window Modified Trimmed Mean filter, which is nonlinear, and Lee's and the directional filter, which are adaptive in the sense that the smoothing performed by them at each point of the image is controlled by a local image measure. In order to evaluate the performance of the filters, they were applied to a variety of regular waveforms obtained from a physiological flow phantom. Ensemble averaging of a large number of unfiltered spectra was used as the “gold standard” in the evaluation, i.e., as the output of an ideal filter which reveals the exact nature of the underlying Doppler spectrum after speckle has been eliminated. Comparison of the “gold standard” with the ensemble averaged filtered data allowed the noise reduction, bias and distortion of the maximum frequency envelope introduced by filtering to be examined. Overall, the best performance was offered by the directional filter whose action was controlled by the combination of the local edge content and the slope of the least-squares-fit line passing through the data points along each particular direction.

A simple quantitative screening test for the detection of extracranial carotid artery disease.

A simple screening test, using continuous wave Doppler ultrasound, for the detection of all grades of extracranial carotid artery disease has been described. The test is composed of two parts: (1) the determination of the direction of flow at the orbit and (2) on-line principal component factor analysis of the maximum frequency envelope of the Doppler shifted signal obtained from the common carotid artery. A total of 154 vessel segments have been investigated; 69 normal, 41 with a stenosis of 10-49%, 32 with a stenosis of 50-99% and 12 occlusions. Of these, 70 vessel segments were assessed prospectively and they formed the data base from which the principal components and the classification factor were calculated. The remaining 84 vessel segments were analysed prospectively on-line. The combined results gave an overall sensitivity to the detection of disease of 90% and a specificity of 77%. It has been shown that although classification of Doppler waveforms by principal component analysis is a fairly sophisticated technique it is possible, by careful design of the algorithms, to design a near real-time on-line analysis system for derived waveforms such as the maximum frequency envelope.

An automatic system for capturing and processing ultrasonic Doppler signals and blood pressure signals.

A totally automatic system for capturing and processing ultrasonic Doppler signals and blood pressure signals at pre-programmed intervals is described. The Doppler signals are Fourier transformed and a composite maximum frequency envelope extracted from the spectral data. The frequency envelope is split into individual cardiac cycles and a number of Doppler parameters calculated. All Doppler and blood pressure results are stored on disc, and the most important may be displayed in the form of trend graphs on a computer screen. The system has been used to study variations in middle cerebral artery blood flow velocity and systemic blood pressure in neonates over periods of several hours.

The relationship between time averaged intensity weighted mean velocity, and time averaged maximum velocity in neonatal cerebral arteries

It is usual practice to calculate the mean velocity of blood flow in neonatal cerebral vessels from the intensity weighted mean (IWM) Doppler shift signal. Theoretically however the maximum frequency envelope could be used for similar purposes, and indeed may have certain advantages. The purpose of this study was to confirm the suitability of the maximum frequency method. Good quality Doppler recordings from the anterior cerebral and middle cerebral arteries of both term and very low birth weight babies were analyzed by both methods and compared. A small number of recordings were then deliberately degraded, either by the addition of noise or by the use of inappropriate filters, and reanalyzed. The results of these comparisons suggest that the maximum frequency follower should be the follower of choice for neonatal cerebral blood flow studies.

Assessment of aortoiliac stenosis by femoral artery pressure measurement and Doppler waveform analysis

Two-hundred and four aortoiliac segments of 102 patients with arterial disease of the legs were examined for evidence of aortoiliac stenosis by Doppler analysis of the common femoral artery, angiography and direct femoral artery pressure (FAP) measurements at rest and after induction of hyperaemia with papaverine. From the continuous wave and multigate Pulsed Doppler waveforms registered at rest and during postocclusion hyperaemia, the following instantaneous maximum frequency envelope parameters were calculated: maximum forward frequency, maximum reverse frequency, systolic upslope time (UST) and Pulsatility Index. The overall correlation of these parameters with the apriori classifications of the aortoiliac segments, based on FAP measurements and angiography, were poor. By multiple regression analysis the UST appeared to be the Doppler waveform parameter with the best predictive value for significant aortoiliac stenosis.

The accuracy of duplex scanning in the evaluation of early carotid disease.

The accuracy of duplex scanning in 69 comparisons with biplanar angiography in the detection of early carotid disease has been assessed. The various criteria reported for the categorisation of less than 50% disease have been critically analysed. As part of the study, 50 internal carotid arteries of 25 young, presumed normal medical students of mean age 20 years have been examined. The results suggest that duplex scanning has the ability to grade less than 50% carotid disease into normal, 1-24% and 25-49% stenosis categories. The most sensitive indicator of early disease is obtained from the real-time B-scan. The waveform changes of the maximum frequency envelope were more sensitive than spectral broadening except where full spectral broadening was present. For confident assessment, the real-time B-scan and pulsed Doppler must always be used in conjunction.

Method for the measurement of the maximum doppler frequency

This paper describes a method for detection of the maximum Doppler frequency from a histogram of Doppler signals (HDS). The performance of the system is described, and its behavior in analysis of noise signals that have known lower and upper cut off frequencies is discussed. Experimental investigations show that the device correctly measures the maximum frequency envelope and can be useful in evaluating the maximum flow velocities in the blood circulation system.

'Objective' algorithm for maximum frequency estimation in Doppler spectral analysers.

Real-time spectral analysis is often used to detect the maximum frequency envelope of Doppler signals, and thus the so-called spectral broadening, which is claimed to be a sensitive indicator of arterial stenosis. However, a rational criterion for the estimation of maximum frequencies is lacking. In the paper an ‘objective’ algorithm which takes account of the specificity and the sensitivity of the procedure of maximum frequency detection is proposed. This algorithm is based on the statistical characteristics of FFT spectral estimators, and allows thresholds to be set to be used in two-step decision procedures. The proposed algorithm can be easily implemented on microcomputers and/or commercial spectral analysers. The results obtained are fairly independent of the operator’s subjective judgement and spectral analyser gain.

The use of a fast Fourier transform signal processing integrated circuit for Doppler blood flow studies.

A number of digital integrated circuits are becoming available that are specifically designed for signal processing applications (Godbole and Ali, 1981). The American Microsystems Inc. S2814A is a version of a signal processing circuit that has been specifically programmed to perform the fast Fourier transform (AMI, 1982). (The S2814A is shortly to be replaced by the compatible but redesigned S28214.) A system is described in which this circuit is used to provide frequency analysis of Doppler ultrasound signals from transcutaneous aortovelography measurements. The AMI S2814A has been incorporated into a Z80 microprocessor, S100 bus based system so that the Fourier transform values can be used immediately for further computer processing such as the calculation of the area under the maximum frequency envelope (i.e. relative stroke volume (Cross and Light, 1974)).

Detection of arterial dilatation in the distal aorta--lower limb arteries using continuous wave Doppler ultrasound.

Continuous wave Doppler ultrasound techniques were used to obtain signals from the common femoral, popliteal, posterior tibial and dorsalis pedis arterial sites and the ankle systolic pressure indices in 54 patients with arteriographic, ultrasound "B"-Scan or surgical confirmation of arterial dilatation. The Doppler-shifted signals were spectrum-analysed and processed using a maximum frequency detector. The maximum frequency envelopes were examined retrospectively to determine whether there were any characteristics of the signals which could be used as diagnostic indicators of arterial dilatation. Ankle systolic pressure indices (ASPI), pulsatility index (PI), and delta, derived from the Laplacian transform method, were used in an attempt to quantify any changes produced by dilatation. The results indicate that characteristic and distinctive maximum frequency envelope signatures can be identified with arterial dilatation but that parameters such as ASPI and PI cannot distinguish these changes from the normal state and the Laplacian transform parameter "delta" places the dilatation cases in the minor stenosis category. However, generalised dilatation can be detected with a sensitivity of 85% if pattern recognition techniques are used.

Objective feature extraction applied to the diagnosis of carotid artery disease using a Doppler ultrasound technique

Using the maximum frequency envelope obtained from the sonogram of the Doppler shifted frequencies a mathematical feature extraction technique has been used to provide an objective identification of the significant waveform features. The technique described is that of principal component factor analysis. The data used were taken from an eighteen month programme in which techniques based on the use of directional Doppler ultrasound were evaluated in comparison with direct percutaneous carotid angiography and arch aortography. A tracing of the vessel outlined based on the anterior-posterior view of the angiogram was used to classify each vessel segment studied. Two groups only are considered in this initial study, a normal group (25 vessel segments) and a stenosis group (18 vessel segments). The principal component analysis technique was shown to provide a superior classification of the vessel segments when compared with the more familiar A/B ratio. Nevertheless the principal diagnostic feature is shown to be the A/B ratio.