Australasian Physical & Engineering Sciences in Medicine最新文献

Many studies have performed dosimetric studies using various metal implants however these are difficult to translate to other implants of a different geometry or material (Rijken and Colyer, J Appl Clin Med Phys 18:5:301-306, 2017; Ade and du Plessis, J Appl Clin Med Phys 18:5:162-173, 2017; Prabhakar et al. Rep Pract Oncol Radiother 18:209-213, 2013; Ng et al. Rep Pract Oncol Radiother 20:273-277, 2015; Reft et al. Med Phys 30:1162-1182, 2003; Sasaki et al., Nihon Hoshasen Gijutsu Gakkai Zasshi 72(9):735-745, 2016). In this study, the ability of the Monaco Monte Carlo algorithm (Elekta AB, Stockholm, Sweden) to model radiation transport through different types of metals was evaluated. Investigation of the capabilities and limitations of the algorithm is required for the potential use of Monaco for planning radiotherapy treatments when avoidance of metal implants is clinically undesirable. A MapCHECK 2 diode array (Sun Nuclear Corp, Melbourne, USA) and a PTW 30013 Farmer chamber was used to measure the dose at depth, downstream of 1 cm × 5 cm × 5 cm metal blocks of three known compositions; stainless steel, aluminium and MCP96. The setup was imaged using a CT scanner and imported into the Monaco TPS where the beam arrangement was replicated. The density of the metals was overridden using the known electron density of each (IMPAC Medical Systems Inc, Monaco dose calculation technical reference. IMPAC Medical Systems, Sunnydale, CA, 2013). The differences between the dose measured using the ion chamber and calculated using Monaco downstream of the 1 cm metal blocks were respectively: - 1.2%, - 2.2% and 9.5% when irradiated using a 6 MV beam, and - 0.9%, - 1.3% and 14%, when irradiated using a 15 MV beam. This was then repeated using 2 cm and 3 cm of each metal type giving similar results for aluminium and stainless steel and increased discrepancy for MCP96. Discrepancies between treatment planning software and measurements at depth have been shown to give uncertainties between 5 and 23% in previous studies (Rijken and Colyer, J Appl Clin Med Phys 18:5:301-306, 2017; Ade and du Plessis, J Appl Clin Med Phys 18:5:162-173, 2017; Prabhakar et al. Rep Pract Oncol Radiother 18:209-213, 2013; Ng et al. Rep Pract Oncol Radiother 20:273-277, 2015; Reft et al. Med Phys 30:1162-1182, 2003; Sasaki et al., Nihon Hoshasen Gijutsu Gakkai Zasshi 72(9):735-745, 2016). This study uses basic shapes providing results that remove the uncertainties in geometry and can therefore be applied to any shape. This will help determine whether errors in dose calculations are due to the TPS particle transport algorithms or due to other effects, such as inaccurate contouring or incorrect densities. Thus giving the planner an additional degree of freedom in their planning and decision making process.

This study aims to develop a semi-automatic system for brain tumor segmentation in 3D MR images. For a given image, noise was corrected using SUSAN algorithm first. A specific region of interest (ROI) that contains tumor was identified and then the intensity non-uniformity in ROI was corrected via the histogram normalization and intensity scaling. Each voxel in ROI was presented using 22 features and then was categorized as tumor or non-tumor by a multiple-classifier system. T1- and T2-weighted images and fluid-attenuated inversion recovery (FLAIR) were examined. The system performance in terms of Dice index (DI), sensitivity (SE) and specificity (SP) was evaluated using 150 simulated and 30 real images from the BraTS 2012 database. The results showed that the presented system with an average DI > 0.85, SE > 0.90, and SP > 0.98 for simulated data and DI > 0.80, SE > 0.84, and SP > 0.98 for real data might be used for accurate extraction of the brain tumors. Moreover, this system is 6 times faster than a similar system that processes the whole image. In comparison with two state-of-the-art tumor segmentation methods, our system improved DI (e.g., by 0.31 for low-grade tumors) and outperformed these algorithms. Considering the costs of imaging procedures, tumor identification accuracy and computation times, the proposed system that augmented general pathological information about tumors and used only 4 features of FLAIR images can be suggested as a brain tumor segmentation system for clinical applications.

The construction of a powerful statistical shape model (SSM) requires a rich training dataset that includes the large variety of complex anatomical topologies. The lack of real data causes most SSMs unable to generalize possible unseen instances. Artificial enrichment of training data is one of the methods proposed to address this issue. In this paper, we introduce a novel technique called constrained cage-based deformation (CCBD), which has the ability to produce unlimited artificial data that promises to enrich variability within the training dataset. The proposed method is a two-step algorithm: in the first step, it moves a few handles together, and in the second step transfers the displacements of these handles to the base mesh vertices to generate a real new instance. The evaluation of statistical characteristics of the CCBD confirms that our proposed technique outperforms notable data-generating methods quantitatively, in terms of the generalization ability, and with respect to specificity.

Following cardiac surgical procedures, multiple drainage systems remain in place inside the patient's chest to prevent the development of pericardial effusion or pneumothorax. Therefore, postoperative bleeding must be diligently observed. Currently, observation of the exudate rate is performed through periodical visual inspection of the reservoir. To improve postoperative monitoring, a measurement system based on load cells was developed to automatically detect bleeding rates. A reservoir retaining bracket was instrumented with a load cell. The signal was digitized by a microcontroller and then processed and displayed on customized software written in LabView. In cases where bleeding rates reach critical levels, the device will automatically sound an alarm. Additionally, the bleeding rate is displayed on the screen with the status of the alarm, as well as the fluid level of the reservoir. These data are all logged to a file. The measurement system has been validated for gain stability and drift, as well as for sensor accuracy, with different in vitro examinations. Additionally, performance of the measurement device was tested in a clinical pilot study on patients recovering from cardiac surgical procedures. The in vitro investigation showed that the monitoring device had excellent gain and drift stability, as well as sensor accuracy, with a resolution of 2.6 mL/h for the bleeding rate. During the clinical examination, bleeding rates of all patients were correctly measured. Continuously recording drainage volume using the developed system was comparable to manual measurements performed every 30 min by a nurse. Implementation of continuous digital measurements could improve patient safety and reduce the workload of medical professionals working in intensive care units.

To measure the effective temporal resolution (eTR) and image quality for three reconstruction modes for non-helical volume scanning in area detector CT. Temporal sensitivity profiles (TSPs) were obtained and the full width of the TSP at half maximum was used as an index of the eTR. Image quality was assessed by image noise and the corrected artifact index. The half reconstruction mode had a higher eTR than the full and automatic patient motion collection (APMC) reconstructions. Compared to full reconstruction, the image noise with APMC and half reconstruction were increased by 16% and 35%. The corrected artifact index was lowest with APMC. The square root of full width at tenth maximum of the TSP showed a high coefficient of determination (R² = 0.934) for image noise. This study revealed the TSPs and eTRs for non-helical volume scanning in area detector CT. A high eTR resulted in higher image noise.

A family of prototype 2D monolithic silicon-diode array detectors (MP512, Duo, Octa) has been proposed by the Centre for Medical Radiation Physics, University of Wollongong (Australia) for relative dosimetry in small megavoltage photon beams. These detectors, which differ in the topology of their 512 sensitive volumes, were originally fabricated on bulk p-type substrates. More recently, they have also been fabricated on epitaxial p-type substrates. In the literature, their performance has been individually characterized for quality assurance (QA) applications. The present study directly assessed and compared that of a MP512-bulk and that of a MP512-epitaxial in terms of radiation hardness, long-term stability, response linearity with dose, dose per pulse and angular dependence. Their measurements of output factors, off-axis ratios and percentage depth doses in square radiation fields collimated by the jaws and produced by 6 MV and 10 MV flattened photon beams were then benchmarked against those by commercially available detectors. The present investigation was aimed at establishing, from a medical physicist's perspective, how the bulk and epitaxial fabrication technologies would affect the implementation of the MP512s into a QA protocol. Based on results, the MP512-epitaxial would offer superior radiation hardness, long-term stability and achievable uniformity and reproducibility of the response across the 2D active area.