Melphalan concentration and distribution in the tissues of tumour-bearing limbs treated by isolated limb perfusion.

Levels of melphalan (L-phenylalanine mustard) were measured in the tissues of tumour-bearing limbs treated by isolated limb perfusion (ILP). 41 samples of melanoma tissue, normal fat and skin were excised from 15 patients during ILP. A high performance liquid chromatography assay was used to measure melphalan concentrations. Levels of melphalan were higher in tumour than in fat (P < 0.01, Wilcoxon signed-ranks test), and not significantly different from levels in adjacent skin. In 2 cases there was significant regional toxicity in the treated limb, but this was not related to the levels of melphalan measured in the tissues of the limb. It is encouraging that the concentrations of melphalan which were achieved in large necrotic nodules by ILP were similar to those in well-perfused normal skin.

High temporal resolution ECG-gated scintigraphic angiocardiography.

The cardiac blood pool is visualized with high temporal resolution during a complete, average, cardiac cycle. The technique yields both qualitative and quantitative measures of cardiac performance.

Limb ischaemia after intra-arterial injection of Temazepam gel: histology of nine cases.

AIMS: To record the histopathological findings associated with intra-arterial injection of Temazepam gel by nine drug misusers. METHODS: Standard histological examination and immunocytochemistry for endothelial markers (factor VIII related antigen, Ulex europaeus lectin) were carried out. RESULTS: Intra-arterial injection of Temazepam gel may cause severe vascular injury and lead to amputation of fingers or limbs. Histological changes include myocyte necrosis, interstitial oedema, extensive arterial, venous, and capillary thrombosis, and sometimes vasculitis, endothelial swelling, and denudation. CONCLUSIONS: Inadvertent injection of Temazepam gel into arteries may cause catastrophic ischaemic damage, possibly as a result of toxic effects on endothelial cells.

Practical considerations for the use of a pulmonary artery thermistor catheter.

The use of a pulmonary artery thermistor catheter for pressure measurement and thermodilution cardiac output determination was evaluated in 11 dogs. Pulmonary artery wedge pressure was a reliable index of left atrial pressure at end-expiratory pressures less than 10 cm. H2O. Fluctuations in pulmonary artery temperature occurred at a frequency equal to the respiratory rate and an amplitude of 0.010 to 0.086 degrees C. Changes in amplitude were associated with changes in ventilatory waveform, respiratory rate, and level of anesthesia. Intermittent and continuous positive-pressure ventilation generally dampened and reversed the pulmonary artery temperature pattern exhibited during spontaneous breathing. This suggested that when end expiration is used to time indicator injection, cardiac output will be underestimated during spontaneous breathing and overestimated during continuous or intermittent positive-pressure ventilation. When indicator was injected at the same point in the ventilatory cycle, successive values of cardiac output deviated from one another by 0.0 to 6.7 percent. Deviations as large as 14 percent resulted if sequential injections were out of phase by half a respiratory cycle. These deviations can be minimized by injecting indicator at the same point in the respiratory cycle, if it is not feasible to measure cardiac output during apnea. The clinical utility of a pulmonary artery thermistor catheter can be optimized through appreciation of its specific strengths and limitations.

Safety considerations in clinical engineering.

Clinical engineering is a professional specialty which emerged in the 1960s primarily in response to concern about the hazard of electrocution in hospitals. It has already developed to encompass a much broader range of topics affecting the safe and effective use of technology in health care. However, safety remains as one major focus of clinical engineering. In this paper, issues arising in relation to electrical safety and treated in considerable detail. The next major safety area of concern involves medical gases. This area is newer and, consequently, the issues are less well resolved and therefore it is treated in less detail. Other safety issues, which are numerous, await review at some time in the future.

Myoelectric control of prostheses.

The development of myoelectric control systems for powered limb prostheses has advanced rapidly in recent years. The main thrusts in this development have been in realizing self-contained prostheses and in realizing better prostheses control through improvements in the myoelectric signal processing techniques. This review considers the latter of these two areas. It first presents an historical look at myoelectric signal processing and identifies the problems. It then presents a general look at the myoelectric signal and those characteristics which give rise to these problems. A review of the literature related to various control strategies and signal processing techniques to overcome these problems is given. Finally, future trends to be expected in this area are discussed.

Psychological morbidity in the first year after breast surgery.

In this prospective study, the psychological morbidity associated with the treatment of breast cancer was assessed. The study population comprised all patients referred to one centre with a recently diagnosed breast lump, who were to undergo surgery. Psychological morbidity was assessed preoperatively and at 6 and 12 months postoperatively by modified Rotterdam Symptom Checklist. Three hundred and twenty patients completed all three questionnaires: 93 women undergoing mastectomy, 73 women having conservation therapy for breast cancer and 156 women having biopsy for benign breast disease. Patients with a breast malignancy smaller than 4 cm in diameter were treated by lumpectomy and radiotherapy, anti-oestrogen therapy or chemotherapy alone or in combination. Psychological morbidity among patients with malignant disease was significantly greater than that seen in the group with benign disease. Among cancer patients, a significant decrease in anxiety and depression occurred during the year following surgery. The study failed to demonstrate any psychological advantage associated with breast conservation.

A new strategy for multifunction myoelectric control.

This paper describes a novel approach to the control of a multifunction prosthesis based on the classification of myoelectric patterns. It is shown that the myoelectric signal exhibits a deterministic structure during the initial phase of a muscle contraction. Features are extracted from several time segments of the myoelectric signal to preserve pattern structure. These features are then classified using an artificial neural network. The control signals are derived from natural contraction patterns which can be produced reliably with little subject training. The new control scheme increases the number of functions which can be controlled by a single channel of myoelectric signal but does so in a way which does not increase the effort required by the amputee. Results are presented to support this approach.

Operator error in a level coded myoelectric control channel.

Two forms of error exist in the level coded myoelectric control channel: system error and operator error. Currently in level coded (3-state) myoelectric prosthesis, target and switching level settings are optimized for the presence of system error only. In this study, system error was minimized in order to examine operator error. The magnitude of the operator error was found to exceed the magnitude of the experimental system error as well as the system error associated with a typical prosthesis control unit. These findings suggest that operator error should be considered when optimizing target levels and decision boundaries for level coded myoelectric prosthesis controllers. Since the operator response was estimated to be normally distributed, it is described by its mean and standard deviation. This information can be used to determine the desired optimal settings.

Two-channel enhancement of a multifunction control system.

The enhancement of an existing myoelectric control system has been investigated. The original one-channel system used an artificial neural network to classify myoelectric patterns. This research shows that a two-channel control system can improve the classification accuracy of the pattern classifier significantly, thus improving the reliability of the prosthesis.

Adaptive stimulus artifact reduction in noncortical somatosensory evoked potential studies.

Somatosensory evoked potentials (SEP's) are an important class of bioelectric signals which contain clinically valuable information. The surface measurements of these potentials are often contaminated by a stimulus evoked artifact. The stimulus artifact (SA), depending upon the stimulator and measurement system characteristics, may obscure some of the information carried by the SEP's. Conventional methods for SA reduction employ hardware-based circuits which attempt to eliminate the SA by blanking the input during SA period. However, there is a danger of losing some of the important SEP information, especially if the stimulating and recording electrodes are close together. In this paper, we apply both linear and nonlinear adaptive filtering techniques to the problem of SA reduction. Nonlinear adaptive filters (NAF's) based on truncated second-order Volterra series expansion are discussed and their applicability to SA cancellation is explored through processing both simulated and in vivo SEP data. The performances of the NAF and the finite impulse response (FIR) linear adaptive filter (LAF) are compared by processing experimental SEP data collected from different recording sites. Due to the inherent nonlinearities in the generation of the SA, the NAF is shown to achieve significantly better SA cancellation compared to the LAF.

The application of neural networks to myoelectric signal analysis: a preliminary study.

Two neural network implementations are applied to myoelectric signal (MES) analysis tasks. The motivation behind this research is to explore more reliable methods of deriving control for multidegree of freedom arm prostheses. A discrete Hopfield network is used to calculate the time series parameters for a moving average MES model. It is demonstrated that the Hopfield network is capable of generating the same time series parameters as those produced by the conventional sequential least squares (SLS) algorithm. Furthermore, it can be extended to applications utilizing larger amounts of data, and possibly to higher order time series models, without significant degradation in computational efficiency. The second neural network implementation involves using a two-layer perceptron for classifying a single site MES based on two features, specifically the first time series parameter, and the signal power. Using these features, the perceptron is trained to distinguish between four separate arm functions. The two-dimensional decision boundaries used by the perceptron classifier are delineated. It is also demonstrated that the perceptron is able to rapidly compensate for variations when new data are incorporated into the training set. This adaptive quality suggests that perceptrons may provide a useful tool for future MES analysis.

Graft type for femoro-popliteal bypass surgery.

BACKGROUND: Vascular surgeons construct femoro-popliteal bypass grafts, from the groin to the knee, to save limbs that might otherwise require amputation in patients with severe arterial disease, and to improve walking distance in patients with less severe arterial disease. During the operation, the blocked native artery is bypassed using either a section of the patient's own vein (autologous vein), human umbilical vein (HUV), or an artificial graft e.g. Dacron or polytetrafluoroethylene (PTFE). OBJECTIVES: The objective of this review was to determine the most effective type of graft for femoro-popliteal bypass surgery. SEARCH STRATEGY: The reviewers searched the Cochrane Peripheral Vascular Diseases Group trials register, reference lists of relevant articles, and hand searched proceedings from the British and European Vascular Surgical Societies and the North American Society of Vascular Surgery. They also contacted all major manufacturers of artificial grafts and authors of published trials to enquire about unpublished trials. SELECTION CRITERIA: Randomised trials comparing one type of femoro-popliteal graft with another. DATA COLLECTION AND ANALYSIS: Both reviewers selected trials and assessed trial quality independently. MAIN RESULTS: Nine trials were included with a total of 1334 participants. These investigated a variety of graft types. In one trial of above-knee grafting, primary and secondary patency were significantly better for saphenous vein (73% and 90%, respectively) compared to PTFE (47%, p<0.05 and 47%, p<0.05) and Dacron (54%, p<0.01 and 60%, p<0.01) at four years. Two trials comparing in-situ and reversed saphenous vein grafts to the above- and below-knee popliteal artery revealed no differences in primary patency (64% v 62% respectively), secondary patency (65% v 70%), or survival with intact limb (74% both groups) with five to ten year follow-up. Three trials comparing PTFE with HUV showed significantly better secondary patency rates for HUV, (41% v 73%, p<0.005; 49% v 66%, p<0.05; 22% v 42%,p=0.005) one also showed significantly better primary patency for HUV at five years (32% v 65%, p<0.001). Comparison of PTFE grafts with, and without, a vein cuff found no difference in above-knee grafts. However, primary patency below-knee was higher with a PTFE plus vein cuff bypass (52% v 29%, p=0.03) at two years. REVIEWER'S CONCLUSIONS: There is no clear evidence which type of graft is best for femoro-popliteal grafting. In terms of autologous graft patency, in-situ and reversed vein grafts are equally successful, while HUV performs better than PTFE. A distal vein cuff may improve primary patency for below-knee PTFE femoro-popliteal grafts.

The short-time Fourier transform and muscle fatigue assessment in dynamic contractions.

The mean frequency of the power spectrum of an electromyographic signal is an accepted index for monitoring fatigue in static contractions. There is however, indication that it may be a useful index even in dynamic contractions in which muscle length and/or force may vary. The objective of this investigation was to explore this possibility. An examination of the effects of amplitude modulation on modeled electromyographic signals revealed that changes in variance created in this way do not sufficiently affect characteristic frequency data to obscure a trend with fatigue. This validated the contention that not all non-stationarities in signals necessarily manifest in power spectral parameters. While an investigation of the nature and effects of non-stationarities in real electromyographic signals produced from dynamic contractions indicated that a more complex model is warranted, the results also indicated that averaging associated with estimating spectral parameters with the short-time Fourier transform can control the effects of the more complex non-stationarities. Finally, a fatigue test involving dynamic contractions at a force level under 30% of peak voluntary dynamic range, validated that it was possible to track fatigue in dynamic contractions using a traditional short-time Fourier transform methodology.

Neural network classification of myoelectric signal for prosthesis control.

An alternate approach to deriving control for multidegree of freedom prosthetic arms is considered. By analyzing a single-channel myoelectric signal (MES), we can extract information that can be used to identify different contraction patterns in the upper arm. These contraction patterns are generated by subjects without previous training and are naturally associated with specific functions. Using a set of normalized MES spectral features, we can identify contraction patterns for four arm functions, specifically extension and flexion of the elbow and pronation and supination of the forearm. Performing identification independent of signal power is advantageous because this can then be used as a means for deriving proportional rate control for a prosthesis. An artificial neural network implementation is applied in the classification task. By using three single-layer perceptron networks, the MES is classified, with the spectral representations as input features. Trials performed on five subjects with normal limbs resulted in an average classification performance level of 85% for the four functions.

The effects of four time-varying factors on the mean frequency of a myoelectric signal.

Daily activities involve dynamic muscle contractions that yield nonstationary myoelectric signals (MESs). The purpose of this work was to determine the individual effects of four time-varying factors (the number and firing rate of active motor units, muscle force and joint angle) on the mean frequency of a MES. Previous theoretical and experimental work revealed that although changes in the number and firing rate of active motor units contribute to the nonstationarities of the signal, they do not significantly affect the mean frequency. In the experimental work, 12 subjects performed 25 static contractions, one for each force (20, 30, 40, 50 and 60% of maximum voluntary contraction) and elbow joint angle (50, 70, 90, 110 and 130 degrees extension) combination. A MES was recorded from the surface of the biceps brachii during each contraction. The results indicated that muscle force only weakly affects the mean frequency. Also shown was that alteration in muscle geometry resulting from changes in elbow joint angle does significantly affect the mean frequency. Knowing this is important for the assessment of muscle fatigue during dynamic contractions.

Myoelectric signal measurement during prolonged computer terminal work.

Myoelectric signal (MES) behaviour was studied during prolonged, sustained, low level contractions using a portable system with limited data storage capacity. A pre-processing technique is described which overcomes memory and data storage limitations in a portable multichannel MES data logger. This technique for data reduction was used to study MES behaviour in four muscle groups during prolonged computer terminal work. Myoelectric signal parameters were recorded from eighteen individuals while they performed computer work both without breaks, and with "microbreaks" (short rest breaks of 30 seconds duration) at twenty minute intervals. Myoelectric signal (MES) data were collected from the cervical paraspinal extensors, the lumbar erector spinae, the upper trapezius, and the forearm extensors while participants performed their usual computer work activities. No significant slope for either amplitude or mean frequency was determined in either the break or no break trials over an eighty minute recording period. Instead, most data sets revealed a cyclic trend in terms of frequency and amplitude parameters of the MES. Characteristic values were compared between trials when subjects did and did not take microbreaks. It was found that the overall median value of mean frequency was higher for the "break" than the "no break" protocol only in the cervical extensors, although the clinical significance of this finding is not well understood. By far, the most interesting finding of this work was the discovery of a cyclic trend in the mean frequency of the myoelectric signals studied. This trend was present even when participants did not take breaks. The trend is a potential indicator of the cyclic recruitment of motor units during sustained postural contractions, and is the primary area to be investigated in future studies by the authors.

Non-stationary myoelectric signals and muscle fatigue.

A mathematical derivation for the mean frequency of a myoelectric signal (MES) is provided based on an amplitude modulation model for non-stationary MES. With this derivation, it is shown that mean frequency estimates of stationary and non-stationary myoelectric signals theoretically are not significantly different in a physiologically practical context. While this prediction is confirmed via a computer simulation, it is refuted with empirical evidence. Regardless, it is shown in a final study that mean frequency is capable of tracking a downward shift in the power spectrum with fatigue even in non-stationary myoelectric signals.

Myoelectric signal analysis using neural networks.

It is shown that the capacity of a discrete Hopfield network for functional minimization allows it to extract the time-series parameters from a myoelectric signal (MES) at a faster rate than the previously used SLS algorithm. With a two-dimensional signal space consisting of one of the parameters and the signal power, a two-layer perceptron trained using back-propagation has been used to classify MES signals from different types of muscular contractions. The results suggest that neural networks may be suitable for MES analysis tasks and that further research in this direction is warranted.

Stimulus artefact in somatosensory evoked potential measurement.

When an electrical stimulus is used to evoke action potentials in peripheral nerves or the spinal cord, the stimulus causes an artefact which may interfere with measurement of the evoked potentials. This artefact, unlike all other sources of noise in the measurement, cannot be reduced by ensemble averaging. Confusion about the origin and transmission of stimulus artefact has led to considerable frustration in spinal somatosensory evoked potential (SSEP) measurements. The three mechanisms by which stimulus artefact is coupled into the measuring system are identified, and means for their reduction are discussed.