Radiotherapy is an essential component of cancer treatment, but healthy tissues can be exposed to out-of-field doses, potentially causing adverse effects and secondary cancers. This study investigates peripheral doses outside the electron beam applicator in an Elekta Versa HD linear accelerator. Peripheral doses outside an electron applicator were measured using 6, 9, and 12 MeV...
This study evaluates the dosimetric accuracy of PLA and ABS 3D-printed phantoms compared to real tissues using Monte Carlo simulations in radionuclide therapy. Materials and methods: A phantom representing average liver and lung volumes, with a 10 mm tumor mimic in the liver, was simulated for radioembolization using 1 mCi Tc-99 m and 1 mCi Y-90. The dose distribution (DD) was...
Cardiomechanical monitoring techniques record cardiac vibrations on the chest via lightweight electrodeless sensors that allow long-term patient monitoring. Heartbeat detection in cardiomechanical signals is generally achieved by leveraging a simultaneous electrocardiography (ECG) signal to provide a reliable heartbeats localization, which however strongly limits long-term...
Training deep learning models generally requires large, costly datasets which can limit their application towards in-house segmentation tasks. This study investigates the trade-off in dataset size within the context of pelvic multi-organ MR segmentation where we evaluate the performance of nnU-Net, a well-known segmentation model, under conditions of limited domain and data...
Non-Destructive Testing (NDT) is a commonly used technique for barrier verification within radiation protection, ensuring compliance with national standards and state regulations. There are currently limited published methods in NDT for lead shielding above 25 kg/m2, and thus this research aimed to develop a reproducible method to aid in ‘in the field’ NDT for lead barriers...
Subclinical amplitudes complicate the differentiation between essential tremor (ET) and Parkinson’s disease (PD) tremor, which is uncertain even when the tremors are apparent. Despite their prevalence—up to 30% of PD cases exhibit subclinical tremors—these tremors remain inadequately studied. Therefore, this study explores the potential of artificial intelligence (AI) to address...
Artificial Intelligence (AI) based auto-segmentation has demonstrated numerous benefits to clinical radiotherapy workflows. However, the rapidly changing regulatory, research, and market environment presents challenges around selecting and evaluating the most suitable solution. To support the clinical adoption of AI auto-segmentation systems, Selection Criteria recommendations...
Prostate cancer is a significant global health issue due to its high incidence and poor outcomes in metastatic disease. This study aims to develop models predicting overall survival for patients with metastatic biochemically recurrent prostate cancer, potentially helping to identify high-risk patients and enabling more tailored treatment options. A multi-centre cohort of 180 such...
Neointimal coverage and stent apposition, as assessed from intravascular optical coherence tomography (IVOCT) images, are crucial for optimizing percutaneous coronary intervention (PCI). Existing state-of-the-art computer algorithms designed to automate this analysis often treat lumen and stent segmentations as separate target entities, applicable only to a single stent type and...
To confirm the performance improvement of virtual monoenergetic images (VMIs) for iodine contrast tasks in a clinical photon-counting detector CT (PCD CT) using Fourier-based assessment, compared with those in the latest-generation dual-source dual-energy CT (DECT). A water-filled bath with a diameter of 300 mm, which contains rod-shaped phantoms equivalent to diluted iodine (2...
Variability in plan quality of radiotherapy is commonly attributed to the planner’s skill rather than technological parameters. While experienced planners can set reasonable parameters before optimization, less experienced planners face challenges. This study aimed to assess the quality of volumetric-modulated arc therapy (VMAT) in patients with left-sided breast cancer following...
Increasingly, interventional thoracic workflows utilize cone-beam CT (CBCT) to improve navigational and diagnostic yield. Here, we investigate the feasibility of implementing free-breathing 4D respiratory CBCT for motion mitigated imaging in patients unable to perform a breath-hold or without suspending mechanical ventilation during thoracic interventions. Circular 4D respiratory...
The treatment, planning, simulation, and setup of radiotherapy patients contain many processes subject to errors involving both staff and equipment. Cone-beam-CT (CBCT) provides a final check of patient positioning and corrections based on this can be made prior to treatment delivery. Statistical Process Control (SPC) techniques are used in various industries for quality...
Radiochromic film, evaluated with flatbed scanners, is used for practical radiotherapy QA dosimetry. Film and scanner component effects contribute to the Lateral Response Artefact (LRA), which is further enhanced by light polarisation from both. This study investigates the scanner bed’s contribution to LRA and also polarisation from the mirrors for widely used EPSON scanners, as...
Theory and modelling suggest that detection of neuronal activity may be feasible using phase sensitive MRI methods. Successful detection of neuronal activity both in vitro and in vivo has been described while others have reported negative results. Magnetic resonance electrical properties tomography may be a route by which signal changes can be identified. Here, we report...
In recent years, eye lens exposure among radiation workers has become a serious concern in medical X-ray fluoroscopy and interventional radiology (IVR), highlighting the need for radiation protection education and training. This study presents a method that can maintain high accuracy when calculating spatial dose distributions obtained via Monte Carlo simulation and establishes...
The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for personalized treatment strategies and improving patient outcomes. One hundred and twenty-six patients with NSCLC were enrolled in...
Manual contouring of organs at risk (OAR) is time-consuming and subject to inter-observer variability. AI-based auto-contouring is proposed as a solution to these problems if it can produce clinically acceptable results. This study investigated the performance of multiple AI-based auto-contouring systems in different OAR segmentations. The auto-contouring was performed using...
This guideline has been prepared by the ACPSEM to provide a standardised quality assurance program to be used within General X-ray imaging environments. The guideline includes the responsibilities of various multidisciplinary team members within medical imaging facilities. It must be noted that the listed tests and testing frequencies are not intended to replace or become...
This study aimed to identify potential anatomical variation triggers using magnetic resonance imaging for plan adaption of cervical cancer patients to ensure dose requirements were met over an external beam radiotherapy course. Magnetic resonance images (MRIs) acquired before and during treatment were rigidly registered to a pre-treatment computerised tomography (CT) image for 11...
Photoplethysmography, a widely embraced tool for non-invasive blood pressure (BP) monitoring, has demonstrated potential in BP prediction, especially when machine learning techniques are involved. However, predictions with a singular model often fall short in terms of accuracy. In order to counter this issue, we propose an innovative ensemble model that utilizes Light Gradient...