Australasian Physical & Engineering Sciences in Medicine最新文献

Substantial concentration has been associated to the monitoring of vital signs and human activity using wireless body area networks. However, one of the key technical challenges is to characterize an optimized transceiver geometry for desired isolation/bandwidth and specific absorption rate (SAR) characteristics, independent of transceiver chip on-body location. A microwave performance evaluation of monopole wearable transceiver was completed and results presented. A novel on-body antenna transceiver was designed, simulated and fabricated using an ultra-thin substrate RO 3010 (h = 250 µm) that ensures compactness and enhanced flexibility. The designed transceiver was evolved using very high value of dielectric constant using CST® Studio Suit and FEKO® numerical platforms. The on-body characterization for both fatty and bone tissues was experimentally verified for a bandwidth of 200 MHz. The fabricated configuration and real-time testing provides very promising microwave radiation parameters with a gain of 2.69 dBi, S₁₁ < - 13 dB at an operational frequency of 2.46 GHz. Multi-banding was achieved by introducing fractals in the design of the printed monopole. SAR calculations for feet, head and arm at microwave power levels ranging from 100 to 800 mW are incorporated. Furthermore, the real time data acquisition using developed transceiver and its experimental verification is illustrated.

Electrocardiogram (ECG) beat classification is a significant application in computer-aided analysis and diagnosis technologies. This paper proposed a method to detect, extract informative features, and classify ECG beats utilizing real ECG signals available in the standard MIT-BIH Arrhythmia database, with 10,502 beats had been extracted from it. The present study classifies the ECG beat into six classes, normal beat (N), Left bundle branch block beat, Right bundle branch block beat, Premature ventricular contraction, atrial premature beat, and aberrated atrial premature, using Gaussian mixture and wavelets features, and by applying principal component analysis for feature set reduction. The classification process is implemented utilizing two classifier techniques, the probabilistic neural network (PNN) algorithm and Random Forest (RF) algorithm. The achieved accuracy is 99.99%, and 99.97% for PNN and RF respectively. The precision is 99.99%, and 99.98% for PNN and RF respectively. The sensitivity is 99.99%, and 99.81% for PNN and RF respectively, while the specificity is 99.97%, 99.96% for PNN and RF respectively. It has been shown that the combination of Gaussian mixtures coefficients and the wavelets features have provided a valuable information about the heart performance and can be used significantly in arrhythmia classification.

The advantages, in terms of heart dose sparing, resulting from using a breath-hold technique when treating supine left breast radiotherapy patients are widely accepted, and increasing numbers of radiotherapy departments are implementing breath-hold techniques. However, due to differences in patient setup and treatment planning protocols between radiotherapy departments, it is important to assess the benefits of using a breath-hold technique within each department, before or during implementation. This study investigated the use of retrospective analysis of past patient treatment plans, as a means to identify the potential for breath-hold techniques to benefit patients. In-house "Treatment and Dose Assessor" code was used to complete a bulk retrospective evaluation of dose-volume metrics for 708 supine and 13 prone breast and chest wall radiotherapy treatments, that were planned using the same clinical protocols, which did not utilise a breath hold technique. For supine patients, results showed statistically significant differences between heart doses from left and right breast treatment plans, in the absence of significant differences between lung doses from left and right breast treatment plans, confirming the potential benefit of using a breath-hold technique for supine left breast radiotherapy patients. Fewer than 1% of the right breast treatment plans showed heart doses high enough to suggest a possible benefit from using a breath-hold technique. Approximately 50% of the prone left breast treatment plans included very low heart doses without intervention, and may therefore have shown no noticeable dosimetric benefit from the use of a breath hold. This study demonstrated the extent of information that can be obtained using retrospective data analysis, before or instead of obtaining multiple CT images of patients and completing a process of dual planning and prospective dose evaluation.

This prospective study of weekly CT scanning and plan adaption during H&N IMRT reports on the frequency of plan adaptations based on dosimetric differences between original and re-optimised IMRT plans. The volumetric and geometric change occurring in target volumes and salivary glands is also described. Ten H&N cancer patients underwent weekly planning CT imaging and re-optimisation of the IMRT plan if PTV or OAR coverage was unacceptable. Comparisons of PTV and parotid gland dosimetry between the original and adaptive plans were made. Parotid and submandibular gland volume changes and shift were calculated. Eight of ten patients required one or more plan adaptations, with 41% of adaptations occurring by fraction ten. Salivary glands reduced in volume, with a medial shift of the lateral border of the parotid gland and a superior shift of the submandibular gland. Change in PTV coverage did not correlate with weight loss or nutritional score. Inadequate PTV coverage, requiring plan adaptation, occurs early in the course of IMRT. A weekly Adaptive RT (ART) protocol results in significant improvement of PTV coverage. Implementation of a clinical ART protocol should include imaging and dose calculation within the first ten fractions.

Ambulatory blood pressure monitoring (ABPM) involves measuring blood pressure by means of a tensiometer carried by the patient for a duration of 24 h, it currently occupies a central place in the diagnosis and follow-up of hypertensive patients, it provides crucial information which allows to make a specific diagnosis and adapt therapeutic attitude accordingly. The traditional analysis process suffers from different problems: it requires a lot of time and expertise, and several calculations should be performed manually by the expert, who is generally very busy. In this work, we attempt to improve the analysis of ABPM data using multi-label classification methods, where a record is associated with more than one label (class) at the same time. Seven algorithms are experimentally compared on a new multi-label ABPM-dataset. Experiments are conducted on 270 hypertensive patient records characterized by 40 attributes and associated with six labels. Results show that the multi-label modeling of ABPM data helps to investigate label dependencies and provide interesting insights, which can be integrated into the ABPM devices to dispense automatically detailed reports with possible future complications.

Multiparametric MRI (mpMRI) is an imaging modality that combines anatomical MR imaging with one or more functional MRI sequences. It has become a versatile tool for detecting and characterising prostate cancer (PCa). The traditional role of mpMRI was confined to PCa staging, but due to the advanced imaging techniques, its role has expanded to various stages in clinical practises including tumour detection, disease monitor during active surveillance and sequential imaging for patient follow-up. Meanwhile, with the growing speed of data generation and the increasing volume of imaging data, it is highly demanded to apply computerised methods to process mpMRI data and extract useful information. Hence quantitative analysis for imaging data using radiomics has become an emerging paradigm. The application of radiomics approaches in prostate cancer has not only enabled automatic localisation of the disease but also provided a non-invasive solution to assess tumour biology (e.g. aggressiveness and the presence of hypoxia). This article reviews mpMRI and its expanding role in PCa detection, staging and patient management. Following that, an overview of prostate radiomics will be provided, with a special focus on its current applications as well as its future directions.

Assessing vocal fold (VF) vibrations is important for the diagnosis of several diseases, and is made possible through the analysis of videoendoscopy recordings. However, the visual analysis of these recordings is hard due to the high acquisition rate. For this reason, it is commonly used to extract the laryngeal activity information from the recordings and represent it in a way suitable to be visually analyzed. Waveforms, images and playbacks are examples of representations reported in the literature. The main limitation of some of them is the lack of precisely locating the pathology within the VFs. Whereas others require the segmentation of the glottis in all the images of the video which is a complex and hard task given the high amount of images in the video and the necessity for the user intervention. To overcome these problems, the present study proposes a new waveform that maps the local vibrations of the VFs without the need for segmenting all the images of the video. Instead, the segmentation is restricted to only one image per vibratory cycle. Then, a new optical flow based technique is proposed to deduce the cycle-to-cycle dynamics of the VFs. The ability of the proposed approach to provide a reliable visual assessment is experimentally evaluated using different types of phonation and different vocal pathologies.

An Advanced Markus chamber on the surface of solid water phantom was used to determine surface dose reduction, with either a lead or air interface, as a function of surface-interface separation (t). The beam quality dependence of dose reduction was investigated using the 50 kV, 100 kV and 150 kV beams of an Xstrahl 150 superficial X-ray unit. For each beam the dose correction factor, DCF(t), namely the ratio of surface dose (t) to surface dose (t = 100 mm), was determined. Monte Carlo simulations of DCF(t) with a lead interface were compared with corresponding measured values. Simulated spectra were calculated at the phantom surface for full backscatter (t = 100 mm) and with either a lead or air interface at 2 mm or 8 mm depth. For each depth and beam quality lead fluorescent radiation at the surface was evident. The variation of DCF(t) for each beam and field size exhibits a minima at t ≈ 5 mm and in the range 1 mm ≤ t ≤ 40 mm surface dose reduction is larger for 100 kV than 150 kV. Monte Carlo simulated DCF(t) are consistent with corresponding measured DCF(t). From simulated spectra L-series fluorescent X-rays (≈ 15 keV) emanating from lead at t = 2 mm are evident for all beams and fluorescent K-series X-rays only occur with 100 kV and 150 kV beams.

Neuronal current magnetic resonance imaging (NC-MRI) is a new method in functional imaging of the brain that could cause the alteration in the phase of magnetic resonance signal. The phase variance is defined as the inverse of the signal to noise ratio (SNR). The intrinsic SNR of the MRI signal is characterized by the coil performance. We evaluated the relation between the geometry and the shape of coils in order to find the minimum detectable change in the signal phase and the possibility of direct detection of neuronal activity by MRI. Full wave equations were solved by the finite element method to calculate the SNR for circular, elliptical, and square shape surface coils. The simulation was repeated for Larmor frequencies of 64 MHz and 85.2 MHz and the coil sizes between 1.5 and 7.5 cm. Relative intrinsic signal to noise ratio (rISNR) of coils with a respect to a selected reference coil and a reference point in the sample was estimated. The circular coil had higher rISNR than other shapes. The increase of the strip width in the coils raised the rISNR 5-20%. For typical imaging parameters, rISNR reference was about 66 which led to a minimum detectable change in MRI signal phase of 0.87° (11.4 nT). It may also be reduced up to tenfold in a 1.5 cm circular coil. Detection of subtle phase signal change due to neuronal activity in surface coils needs a large amount of data acquisition and averaging, but it is intrinsically feasible.