Australasian Physical & Engineering Sciences in Medicine最新文献

Radiochromic film is a good dosimeter choice for patient QA for complex treatment techniques (IMRT, VMAT, SABR, SBRT) because of its near tissue equivalency, very high spatial resolution and established method of use. Commercial scanners are usually used for film dosimetry, among which EPSON scanners are the most common. NCCI have used an EPSON V700 scanner, but recently acquired a new model EPSON V800 scanner. The purpose of this work was to evaluate any differences between these two scanners to consider whether they can be used interchangeably or not. Different aspects of film dosimetry, e.g. lateral response artefact (LRA) effect, orientation effect, scanner response etc., were compared. EBT3 films were irradiated with 40 × 40 cm² field size 6 MV beams and scanned in both the scanners. The scanned images were read in ImageJ V1.49 software. The data obtained was then copied in MS Excel to compare the scanners. The V800 scanner causes more polarisation, which results in more LRA effect than for the V700 scanner. The responses of the scanners in all three colour channels are not the same for the same film and irradiation. The V800 scanner shows an increase of response of up to 1.6% compared to 3.7% increase in the V700 scanner after scanning a piece of irradiated film 20 times. The scanners cannot be used interchangeably. The correction factors for LRA effect and the calibration curves are different. Further characterisation, evaluation and commissioning is required before clinical use.

With the extension of ion species in ion-beam radiotherapy, the sole dependence of relative biological effectiveness (RBE) on linear energy transfer (LET) is insufficient when comparing RBE for ion beams with the same LET value. The aim of the present study was to provide a systematic study of the nanodosimetry for ion beams with the same LET value. Based on the calculated LET profiles of ion beams with range about 130 mm, lineal energy spectra and dose-averaged lineal energy [Formula: see text] on 4 nm site for various clinical ion beams were obtained. Then, the lineal energy spectra and [Formula: see text] values were compared for ion beams with the same LET values. The results showed that the relationships between [Formula: see text] and LET for various ion beams present an dependence on ion species. For ion beams with the same LET value, the ion beams with smaller nucleon number yielded greater [Formula: see text] values. The probability of the small-nucleon-number ion beams to generate large energy deposition events on nanoscale was higher than that of the large-nucleon-number ion beams. The dependence of the relationship between RBE and LET on ion species might be attributed to the fluctuation of energy depositions on nanometer scale.

The development of brain-computer interface (BCI) systems is an important approach in brain studies. Control of communication devices and prostheses in real-world scenarios requires complex movement parameters. Decoding a variety of neural signals captured by micro-wire arrays is a potential applicant for extracting movement-related information. The present work was conducted to compare the functionality of partial least square (PLS) regression and Kalman filter to predict the force parameter from local field potential (LFP) signals of the primary motor cortex (M1). The signals were recorded using a 16-channel micro-wire array from the forelimb-related area of the M1 of three rats performing a behavioral task in which the force signal of the rat's forelimb paw was generated. Our results show that PLS regression and Kalman filters with the mean performance of 0.75 and 0.72 in terms of the correlation coefficient (CC) and 0.37 and 0.48 in terms of normalized mean square error (NMSE), respectively, are effective methods for decoding the force parameter from LFPs. Kalman filter underperforms PLS both in performance and speed. Although adding nonlinearity to the Kalman filter results in equally accurate CC performance as PLS, it has even more computational cost. Therefore, it is inferred that nonlinear methods do not necessarily have better functionality than linear ones and PLS, as a simple fast linear method could be an effectively applicable regression technique for BCIs.

Electroencephalogram (EEG) has become a practical tool for monitoring and diagnosing pathological/psychological brain states. To date, an increasing number of investigations considered differences between brain dynamic of patients with schizophrenia and healthy controls. However, insufficient studies have been performed to provide an intelligent and accurate system that detects the schizophrenia using EEG signals. This paper concerns this issue by providing new feature-level fusion algorithms. Firstly, we analyze EEG dynamics using three well-known nonlinear measures, including complexity (Cx), Higuchi fractal dimension (HFD), and Lyapunov exponents (Lya). Next, we propose some innovative feature-level fusion strategies to combine the information of these indices. We evaluate the effect of the classifier parameter (σ) adjustment and the cross-validation partitioning criteria on classification accuracy. The performance of EEG classification using combined features was compared with the non-combined attributes. Experimental results showed higher classification accuracy when feature-level features were utilized, compared to when each feature was used individually or all fed to the classifier simultaneously. Using the proposed algorithm, the classification accuracy increased up to 100%. These results establish the suggested framework as a superior scheme compared to the state-of-the-art EEG schizophrenia diagnosis tool.

There have been increasing cases of people seeking treatment for neck and back pain. The most common cause of neck and back pain is due to long-term poor sitting posture. The most common poor sitting posture cases are humpback, and head and neck being too far forward. It is easy to cause neck and back pain and other symptoms. Therefore, the development of wearable posture monitoring system for dynamic assessment of sitting posture becomes both helpful and necessary. In addition to recording the wearer's posture when sitting with quantitative assessment, it is needed to execute real-time action feedback for correctness of posture, in order to reduce neck and back pain due to long-term poor sitting posture. This study completed an instant recording and dynamic assessment of position measurement and feedback system. The system consists of a number of dynamic measurement units that can describe the posture trajectory, which integrates three-axis gyro meter, three-axis accelerometer, and magnetometer in order to measure the dynamic tracking. In the reliability analysis experiment, angle measurement error is less than 2%. The correlation coefficient between correlation analysis and Motion Analysis (MA) is 0.97. It is shown that the motion trajectory of this system is highly correlated with MA. In the feasibility test of sitting position detection, it is possible to detect the sitting position from the basic action of the walking, standing, sitting and lying down, and the sensitivity reaches 95.84%. In the assessment of the sitting position, the information published by the Canadian Centre for Occupational Health and Safety was used, as well as the recommendations of professional physicians as a basis for evaluating the threshold of the sitting measurement parameters and immediately feedback to the subjects. The system developed in this study can be helpful to reduce neck and back pain due to long-term poor sitting posture.