: A quantitative approach to assess the correlation of mammographic breast density with selected affecting factors.

Introduction: Breast density plays a significant role in increasing an individual's risk of breast cancer and its mortality rate.

Objectives: We aimed to assess the correlations of mammographic breast density with age, body mass index, weight, height and parity for the first time in Sri Lankan women.

Methods: 52 participants who underwent diagnostic mammographic examinations at a tertiary care hospital in Sri Lanka were selected for the study.

Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques.

Apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) is an indispensable imaging technique in clinical neuroimaging that quantitatively assesses the diffusivity of water molecules within tissues using diffusion-weighted imaging (DWI). This study focuses on developing a robust machine learning (ML) model to predict the aggressiveness of gliomas according to World Health Organization (WHO) grading by analyzing patients' demographics, higher-order moments, and grey level co-occurrence matrix (GLCM) texture features of ADC. A population of 722 labeled MRI-ADC brain image slices from 88 human subjects was selected, where gliomas are labeled as glioblastoma multiforme (WHO-IV), high-grade glioma (WHO-III), and low-grade glioma (WHO I-II).

Morphometry-based radiomics for predicting therapeutic response in patients with gliomas following radiotherapy.

Introduction: Gliomas are still considered as challenging in oncologic management despite the developments in treatment approaches. The complete elimination of a glioma might not be possible even after a treatment and assessment of therapeutic response is important to determine the future course of actions for patients with such cancers. In the recent years radiomics has emerged as a promising solution with potential applications including prediction of therapeutic response.

Knowledge and practice of infection control during radiology procedures among radiography undergraduates in Sri Lanka.

Introduction: Sufficient knowledge and adherence to infection control measures are essential for healthcare workers to effectively combat healthcare-associated infections (HCAIs). Radiography undergraduates should stay updated and proficient in their infection control practice. This study aimed to assess knowledge and practice of infection control measures during radiological procedures among radiography undergraduates in Sri Lanka.

Anxiety, depression, and stress among radiography undergraduates during the COVID-19 pandemic.

Introduction: The COVID-19 pandemic has severely impacted education and other aspects of life, causing psychological distress. The current study aims to identify anxiety, depression, and stress among radiography undergraduates during the COVID-19 pandemic.

Method: A descriptive, cross-sectional study was conducted between November and December 2021 on a sample of 140 radiography undergraduates at the Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya.

Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques.

Background: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors.

Methods: This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients.

Relative diffusion of paramagnetic metal complexes of MRI contrast agents in an isotropic hydrogel medium.

The observation of molecular diffusion by means of magnetic resonance imaging (MRI) is significant in the evaluation of the metabolic activity of living tissues. Series of MRI examinations were conducted on a diffusion model to study the behaviour of the diffusion process of different-molecular-weight (MW) paramagnetic MRI contrast agents in an isotropic agar hydrogel medium. The model consisted of a solidified 1 % agar gel with an initial concentration of 0.