Detection of malignant mesothelioma from 4D magnetic resonance images of the thorax: an evaluation and improvement study

• Grant number: 22/14507-9
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: February 01, 2023
• End date: July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Alexandre Xavier Falcão
• Grantee: Taylla Milena Theodoro
• Supervisor: Kevin Blyth
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: University of Glasgow, Scotland
• Associated to the scholarship: 22/03754-5 - Towards detection of malignant mesothelioma from 4D magnetic resonance images of the thorax, BP.MS

Abstract

Mesothelioma is an abnormal mass (a tumor) in the layers of tissues surrounding organs of the chest. Malignant Pleural Mesothelioma (MPM) is the most common primary malignancy of the parietal and visceral layers covering the lungs (the pleura). Current diagnostic pathways depends on invasive methods, such as biopsy. A biomarker from images would be a significant advance to detect the MPM at its early stages in a non-invasive way. Recent findings from MR image sequences (a four-dimensional image) suggest the mean intensity profile of voxels over time, in some areas of the pleura, as a potential biomarker to distinguish between benign and malignant mesothelioma. If the profiles present a curve patter termed Early Contrast Enhancement (ECE), the patient has a malignant tumor. The M.Sc. project (#2022/03754-5) aims at developing a semi-automatic image analysis technique to identify those areas of the pleura from four-dimensional MR images and verify the effectiveness of the suggested biomarker in distinguishing malignant mesothelioma from other pleural diseases. The study will be developed in cooperation with the PREDIC-Meso project at the University of Glasgow. This BEPE research proposal is to evaluate and improve the proposed technique during the internship of 6 months at the University of Glasgow, supervised by Dr. Kevin Blyth (coordinator of the project). The internship will be crucial to have access to their image dataset and train the physicians to use our software tool with the proposed technique for validation. (AU)