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.

A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes
This study fused deep learning with a regularized nomogram to construct a novel deep learning nomogram from CGM profiles to identify patients at high risk of DR. Specifically, a deep learning network was employed to mine the nonlinear relationship between CGM profiles and DR. Moreover, a novel nomogram combining CGM deep factors with basic information was established to score the patients ’ DR risk. This dataset consists of 788 patients belonging to two cohorts: 494 in the training cohort and 294 in the testing cohort. The area under the curve (AUC) values of our deep learning nomogram were 0.82 and 0.80 in the training ...
Source: Australasian Physical and Engineering Sciences in Medicine - April 11, 2023 Category: Biomedical Engineering Source Type: research

Correction factors for commissioning and patient specific quality assurance of stereotactic fields in a Monte Carlo based treatment planning system
This study derived correction factors for VOI averaged TPS doses calculated for small fields, allowing correction to an isocentre dose following account for statistical noise. These factors were used to determine an optimal VOI to represent small volume ionisation chambers during patient specific quality assurance (PSQA). A retrospective comparison of 82 SRS and 28 SBRT PSQA measurements to TPS calculated doses from varying VOI was completed to evaluate the determined volumes. Small field commissioning correction factors of under 5% were obtained for field sizes of 8  mm and larger. Optimal spherical VOI with radius betwe...
Source: Australasian Physical and Engineering Sciences in Medicine - April 6, 2023 Category: Biomedical Engineering Source Type: research

Density-adaptive registration of pointclouds based on Dirichlet Process Gaussian Mixture Models
AbstractWe propose an algorithm for rigid registration of pre- and intra-operative patient anatomy, represented as pointclouds, during minimally invasive surgery. This capability is essential for development of augmented reality systems for guiding such interventions. Key challenges in this context are differences in the point density in the pre- and intra-operative pointclouds, and potentially low spatial overlap between the two. Solutions, correspondingly, must be robust to both of these phenomena. We formulated a pointclouds registration approach which considers the pointclouds after rigid transformation to be observati...
Source: Australasian Physical and Engineering Sciences in Medicine - April 4, 2023 Category: Biomedical Engineering Source Type: research

Establishment of a local diagnostic reference level for dental intraoral bitewing X-rays
AbstractA state-based local diagnostic reference level (LDRL) for dental intraoral X-rays has been established. LDRL values of 2.0 mGy incident air kerma (IAK) and 57 mGy •cm2 air kerma-area product (KAP) for an adult posterior bitewing X-ray were determined based on 811 X-ray units surveyed. This IAK LDRL value is greater than those established in several other nations and regions around the world in similar studies. Analyses of radiographic technique and equipment usage are included to provide broad guidance as to ways that imaging could be optimised, such as in the selection of exposure factors, collimators, image rec...
Source: Australasian Physical and Engineering Sciences in Medicine - April 4, 2023 Category: Biomedical Engineering Source Type: research

Repeatability of brain phase-based magnetic resonance electric properties tomography methods and effect of compressed SENSE and RF shimming
AbstractMagnetic resonance electrical properties tomography (MREPT) is an emerging imaging modality to noninvasively measure tissue conductivity and permittivity. Implementation of MREPT in the clinic requires repeatable measurements at a short scan time and an appropriate protocol. The aim of this study was to investigate the repeatability of conductivity measurements using phase-based MREPT and the effects of compressed SENSE (CS), and RF shimming on the precision of conductivity measurements. Conductivity measurements using turbo spin echo (TSE) and three-dimensional balanced fast field echo (bFFE) with CS factors were ...
Source: Australasian Physical and Engineering Sciences in Medicine - March 30, 2023 Category: Biomedical Engineering Source Type: research

High-resolution entry and exit surface dosimetry in a 1.5  T MR-linac
This study investigated the response of a MOSFET detector, known as the MOSkin™, for high-resolution surface and near-surface percentage depth dose measurements on an Elekta Unity. Simulations with Geant4 and the Monaco treatment planning system (TPS), and EBT-3 film measurements, were also performed for comparison. Measured MOSkin™ entry surface doses, relative to Dmax, were (9.9  ± 0.2)%, (10.1 ± 0.3)%, (11.3 ± 0.6)%, (12.9 ± 1.0)%, and (13.4 ± 1.0)% for 1 × 1 cm2, 3  × 3 cm2, 5  × 5 cm2, 10  × 10 cm2, and 22  × 22 cm2 fields, respectively. For the investigated fields...
Source: Australasian Physical and Engineering Sciences in Medicine - March 29, 2023 Category: Biomedical Engineering Source Type: research

Image masking using convolutional networks improves performance classification of radiation pneumonitis for non-small cell lung cancer
This study proposes a prediction model for RP grade  ≥ 2 using a convolutional neural network (CNN) model with image cropping. The 3D computed tomography (CT) images cropped in the whole-body, normal lung (nLung), and nLung regions overlapping the region over 20 Gy (nLung∩20 Gy) used in treatment planning were used as the input data. The o utput classifies patients as RP grade <  2 or RP grade ≥ 2. The sensitivity, specificity, accuracy, and area under the curve (AUC) were evaluated using the receiver operating characteristic curve (ROC). The accuracy, specificity, sensitivity, and AUC were 53.9%, ...
Source: Australasian Physical and Engineering Sciences in Medicine - March 28, 2023 Category: Biomedical Engineering Source Type: research

Accuracy of the catalyst surface guidance system for patient monitoring during cranial SRS treatments
AbstractThe use of surface guided imaging in cranial stereotactic radiotherapy provides a non-ionising form of patient position verification that gives information on when patient position errors may require corrections to be applied. This work assessed the accuracy of Catalyst+ HD system for treatment geometries commonly used in cranial SRS. Average Catalyst reported error as a function of couch rotation agreed with measured kV and MV walkout within 0.5  mm for the lateral and longitudinal directions. Change in Catalyst reported error with isocentre depth relative to the monitoring region of interest (ROI) from the surfa...
Source: Australasian Physical and Engineering Sciences in Medicine - March 27, 2023 Category: Biomedical Engineering Source Type: research

Intrafraction motion during CyberKnife ® prostate SBRT: impact of imaging frequency and patient factors
Conclusions: There are several combinations of imaging intervals and movement thresholds that may be suitable for consideration during treatment p lanning with respect to imaging and calculation of the margin between the clinical target volume and planning target volume (CTV-to-PTV), resulting in adequate geometric coverage for approximately 95% of treatment time. Rectal toxicities and treatment duration need to be considered when implementin g combinations clinically. (Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - March 27, 2023 Category: Biomedical Engineering Source Type: research

Dosimetric evaluation of an intraoperative radiotherapy system: a measurement-based and Monte-Carlo modelling investigation
AbstractIntraoperative radiotherapy (IORT) is a specialised subset of radiotherapy, where a high radiation dose is delivered to a surgically exposed tumour bed in order to eradicate any remaining cancer cells. The aim of this study was to examine the dose characteristics of the Zeiss Intrabeam IORT device which provides near-isotropic emission of up to 50  kV X-rays. The EGSnrc Monte Carlo (MC) code system was used to simulate the device and percentage depth dose (PDD) data measured with a soft X-ray parallel-plate ionisation chamber were used for model verification. The model provided energy spectra, isodose curves and m...
Source: Australasian Physical and Engineering Sciences in Medicine - March 23, 2023 Category: Biomedical Engineering Source Type: research

Exploring deep residual network based features for automatic schizophrenia detection from EEG
AbstractSchizophrenia is a severe mental illness which can cause lifelong disability. Most recent studies on the Electroencephalogram (EEG)-based diagnosis of schizophrenia rely on bespoke/hand-crafted feature extraction techniques. Traditional manual feature extraction methods are time-consuming, imprecise, and have a limited ability to balance accuracy and efficiency. Addressing this issue, this study introduces a deep residual network (deep ResNet) based feature extraction design that can automatically extract representative features from EEG signal data for identifying schizophrenia. This proposed method consists of th...
Source: Australasian Physical and Engineering Sciences in Medicine - March 22, 2023 Category: Biomedical Engineering Source Type: research

Real-time deep neural network-based automatic bowel gas segmentation on X-ray images for particle beam treatment
AbstractSince particle beam distribution is vulnerable to change in bowel gas because of its low density, we developed a deep neural network (DNN) for bowel gas segmentation on X-ray images.  We used 6688 image datasets from 209 cases as training data, 736 image datasets from 23 cases as validation data and 102 image datasets from 51 cases as test data(total 283 cases). For the training data, we prepared three types of digitally reconstructed radiographic (DRR) images (all-density, bone and gas) by projecting the treatment planning CT image data. However, the real X-ray images acquired in the treatment room showed low con...
Source: Australasian Physical and Engineering Sciences in Medicine - March 21, 2023 Category: Biomedical Engineering Source Type: research

Fan beam CT image synthesis from cone beam CT image using nested residual UNet based conditional generative adversarial network
AbstractA radiotherapy technique called Image-Guided Radiation Therapy adopts frequent imaging throughout a treatment session. Fan Beam Computed Tomography (FBCT) based planning followed by Cone Beam Computed Tomography (CBCT) based radiation delivery drastically improved the treatment accuracy. Furtherance in terms of radiation exposure and cost can be achieved if FBCT could be replaced with CBCT. This paper proposes a Conditional Generative Adversarial Network (CGAN) for CBCT-to-FBCT synthesis. Specifically, a new architecture called Nested Residual UNet (NR-UNet) is introduced as the generator of the CGAN. A composite l...
Source: Australasian Physical and Engineering Sciences in Medicine - March 21, 2023 Category: Biomedical Engineering Source Type: research

A Monte Carlo study on dose distribution of an orthovoltage radiation therapy system
AbstractIt is important to plan radiotherapy treatment and establish optimal dose distribution to reduce the chances of side effects and injury. Because there are no commercially available tools for calculating dose distribution in orthovoltage radiotherapy in companion animals, we developed an algorithm to accomplish this and verified its characteristics using tumor disease cases. First, we used the Monte Carlo method to develop an algorithm to calculate the dose distribution of orthovoltage radiotherapy (280 kVp; MBR-320, Hitachi Medical Corporation, Tokyo, Japan) using BEAMnrc at our clinic. Using development of Monte C...
Source: Australasian Physical and Engineering Sciences in Medicine - March 20, 2023 Category: Biomedical Engineering Source Type: research

Multicomponent mathematical model for tumor volume calculation with setup error using single-isocenter stereotactic radiotherapy for multiple brain metastases
AbstractWe evaluated the tumor residual volumes considering six degrees-of-freedom (6DoF) patient setup errors in stereotactic radiotherapy (SRT) with multicomponent mathematical model using single-isocenter irradiation for brain metastases. Simulated spherical gross tumor volumes (GTVs) with 1.0 (GTV 1), 2.0 (GTV 2), and 3.0 (GTV 3)-cm diameters were used. The distance between the GTV center and isocenter (d) was set at 0 –10 cm. The GTV was simultaneously translated within 0–1.0 mm (T) and rotated within 0 °–1.0° (R) in the three axis directions using affine transformation. We optimized the tumor growth model p...
Source: Australasian Physical and Engineering Sciences in Medicine - March 20, 2023 Category: Biomedical Engineering Source Type: research