Australasian Physical and Engineering Sciences in Medicine This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Sensitivity investigation of open-ended coaxial probe in skin cancer detection
In this study, we aim to provide a comprehensive examination of this method, including the minimum detectable tumor size by using a three-layer skin model via simulation and demonstrated that open-ended coaxial probe method can be used for detection of early-stage skin cancer. The smallest detecting size are subject to different subtypes: for BCC, inside the skin is 0.5  mm radius × 0.1 mm height; for SCC, inside the skin is 1.4 mm × 1.3 mm in radius and height; the smallest distinguishing size of BCC is 0.6 mm × 0.7 mm in radius and height; for SCC is 1.0 mm × 1.0 mm in radius and height; for M...
Source: Australasian Physical and Engineering Sciences in Medicine - March 13, 2023 Category: Biomedical Engineering Source Type: research

EPSM 2022, Engineering and Physical Sciences in Medicine
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - March 10, 2023 Category: Biomedical Engineering Source Type: research

Fluoroscopically guided vascular and cardiac transcatheter procedures: a comparison of occupational and patient dose by anatomical region
AbstractX-ray guided procedures are being performed by an increasing variety of medical specialties. Due to improvements in vascular transcatheter therapies, there is an increasing overlap of imaged anatomy between medical specialties. There is concern that non-radiology fluoroscopic operators may not have sufficient training to be well informed of the potential implications of radiation exposure and mitigation strategies to reduce dose. This was a prospective, observational, single center study  to compare occupational and patient dose levels when imaging different anatomical regions during fluoroscopically guided cardia...
Source: Australasian Physical and Engineering Sciences in Medicine - March 6, 2023 Category: Biomedical Engineering Source Type: research

Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes
AbstractThe analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks, sports performance, stress levels, etc. This activity can be recorded using different techniques, with electrocardiogram and photoplethysmogram being the most common. Both techniques make significantly different waveforms, however the first derivative of the photoplethysmographic data produces a signal structurally similar to the electrocardiogram, so any technique focusing on detecting QRS complexes, and thus heartbeats in electrocardiogram, is potentially applicable t...
Source: Australasian Physical and Engineering Sciences in Medicine - March 6, 2023 Category: Biomedical Engineering Source Type: research

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status
AbstractThe early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate patient management and outcome improvement. However, the disease progression is influenced by multiple factors, such as patient characteristics and treatment strategies, and hence satisfactory performance of OS prediction remains challenging. Accordingly, we proposed a deep learning approach based on comprehensive predictors, including clinical, imaging, and genetic information, to accomplish reliable and personalized OS prediction in patients with BMs after receivin...
Source: Australasian Physical and Engineering Sciences in Medicine - March 1, 2023 Category: Biomedical Engineering Source Type: research

Accuracy of a time-of-flight (ToF) imaging system for monitoring deep-inspiration breath-hold radiotherapy (DIBH-RT) for left breast cancer patients
This study aimed to benchmark the accuracy of a Time-of-Flight (ToF) imaging system for monitoring breath-hold during DIBH-RT. The accuracy of an Argos P330 3D ToF camera (Bluetechnix, Austria) was evaluated for patient setup verification and intra-fraction monitoring among 13 DIBH-RT left breast cancer patients. The ToF imaging was performed simultaneously with in-room cone beam computed tomography (CBCT) and electronic portal imaging device (EPID) imaging systems during patient setup and treatment delivery, respectively. Patient surface depths (PSD) during setup were extracted from the ToF and the CBCT images during free...
Source: Australasian Physical and Engineering Sciences in Medicine - February 27, 2023 Category: Biomedical Engineering Source Type: research

ACPSEM position paper: the safety of magnetic resonance imaging linear accelerators
AbstractMagnetic Resonance Imaging linear-accelerator (MRI-linac) equipment has recently been introduced to multiple centres in Australia and New Zealand. MRI equipment creates hazards for staff, patients and others in the MR environment; these hazards must be well understood, and risks managed by a system of environmental controls, written procedures and a trained workforce. While MRI-linac hazards are similar to the diagnostic paradigm, the equipment, workforce and environment are sufficiently different that additional safety guidance is warranted. In 2019 the Australasian College of Physical Scientists and Engineers in ...
Source: Australasian Physical and Engineering Sciences in Medicine - February 27, 2023 Category: Biomedical Engineering Source Type: research

An anthropomorphic 3D printed inhomogeneity thorax phantom slab for SBRT commissioning and quality assurance
In this study, a 5  cm thick anthropomorphic thoracic slab phantom was designed and 3D printed using models exported from a CT dataset to demonstrate the feasibility of manufacturing anthropomorphic 3D printed phantoms onsite in a clinical radiotherapy department. The 3D printed phantom was manufactured with polylact ic acid with an in-fill density of 80% to simulate tissue density and 26% to simulate lung density. A common radio-opacifier, barium sulfate (BaSO4), was added 6% w/w to an epoxy resin mixture to simulate similar HU numbers for bone equivalency. A half-cylindrical shape was cropped away from the spine region ...
Source: Australasian Physical and Engineering Sciences in Medicine - February 20, 2023 Category: Biomedical Engineering Source Type: research

Evaluation of intrafractional prostate displacement during prostate radiotherapy using real-time ultrasound system
The objectives of this study are to evaluate intrafraction prostate displacements and derive planning target volume (PTV) margins for prostate radiotherapy at our institution. The ultrasound (US) data of nine prostate cancer patients referred for VMAT radiotherapy was retrieved. Prior to beam on, patient position was set up with the US probe positioned transperineally with the aid of reference images (fused US and computed tomography images). In each fraction, prostate displacements in three directions [superior/inferior (SI), left/right (LR) and anterior/posterior (AP)] were recorded. PTV margins were determined using Van...
Source: Australasian Physical and Engineering Sciences in Medicine - February 20, 2023 Category: Biomedical Engineering Source Type: research

ACPSEM position paper: dosimetry for magnetic resonance imaging linear accelerators
This report provides recommendations on reference dosimetry measurements for MRI-linacs on behalf of the Australiasian College of Physical Scientists and Engineers in Medicine (ACPSEM) MRI-linac working group. There are two configurations considered for MRI-linacs, perpendicular and parallel, referring to the relative direction of the magnetic field and radiation beam, with different impacts on dose deposition in a medium. These recommendations focus on ion chambers which are most commonly used in the clinic for reference dosimetry. Water phantoms must be MR safe or conditional and practical limitations on phantom set-up m...
Source: Australasian Physical and Engineering Sciences in Medicine - February 20, 2023 Category: Biomedical Engineering Source Type: research

Comparison of the radiomics-based predictive models using machine learning and nomogram for epidermal growth factor receptor mutation status and subtypes in lung adenocarcinoma
AbstractThe purpose of this study is to develop the predictive models for epidermal growth factor receptor (EGFR) mutation status and subtypes [exon 21-point mutation (L858R) and exon 19 deletion mutation (19Del)] and evaluate their clinical usefulness. Total 172 patients with lung adenocarcinoma were retrospectively analyzed. The analysis of variance and the least absolute shrinkage were used for feature selection from plain computed tomography images. Then, radiomic score (rad-score) was calculated for the training and test cohorts. Two machine learning (ML) models with 5-fold were applied to construct the predictive mod...
Source: Australasian Physical and Engineering Sciences in Medicine - February 14, 2023 Category: Biomedical Engineering Source Type: research

Fully automatic carotid arterial stiffness assessment from ultrasound videos based on machine learning
This study aims to evaluate the stiffness of the CCA using machine learning (ML) through the features of diameter change ( ΔD) and stiffness parameters. This study was conducted in seven stages: data collection, preprocessing, CCA segmentation, CCA lumen diameter (DCCA) computing during cardiac cycles, denoising signals of DCCA, computational of AS parameters, and stiffness assessment using ML. The 51 videos (with 25  s) of CCA B-mode ultrasound (US) were used and analyzed. Each US video yielded approximately 750 sequential frames spanning about 24 cardiac cycles. Firstly, US preset settings with time gain compensation w...
Source: Australasian Physical and Engineering Sciences in Medicine - February 14, 2023 Category: Biomedical Engineering Source Type: research

Open-source, fully-automated hybrid cardiac substructure segmentation: development and optimisation
In this study, a novel model was designed to deliver reliable, accurate, and anatomically consistent segmentation of 18 cardiac substructures on computed tomography (CT) scans. Thirty manually contoured CT scans were included. The proposed multi-stage method leverages deep learning (DL), multi-atlas mapping, and geometric modelling to automatically segment the whole heart, cardiac chambers, great vessels, heart valves, coronary arteries, and conduction nodes. Segmentation performance was evaluated using the Dice similarity coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD), and volume ratio. Perfo...
Source: Australasian Physical and Engineering Sciences in Medicine - February 13, 2023 Category: Biomedical Engineering Source Type: research

Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning
ConclusionsA deep learning model was developed, to transform 3D optical scan data of a patient into an estimated MRI volume, potentially increasing the usefulness of optical scanning in radiation therapy planning. This work has demonstrated that much of the human cranial anatomy can be predicted from the external shape of the head and may provide an additional source of valuable imaging data. Further research is required to investigate the feasibility of this approach for use in a clinical setting and further improve the model ’s accuracy. (Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - February 8, 2023 Category: Biomedical Engineering Source Type: research

MRI image synthesis for fluid-attenuated inversion recovery and diffusion-weighted images with deep learning
This study aims to synthesize fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted images (DWI) with a deep conditional adversarial network from T1- and T2-weighted magnetic resonance imaging (MRI) images. A total of 1980 images of 102 patients were split into two datasets: 1470 (68 patients) in a training set and 510 (34 patients) in a test set. The prediction framework was based on a convolutional neural network with a generator and discriminator. T1-weighted, T2-weighted, and composite images were used as inputs. The digital imaging and communications in medicine (DICOM) images were converted to 8-bit red ...
Source: Australasian Physical and Engineering Sciences in Medicine - January 30, 2023 Category: Biomedical Engineering Source Type: research