An Exploratory Study for Characterizing and Predicting Prostate Abnormalities Using MRI-Based Radiomics and Artificial Intelligence (EINSTEIN)

Yassine Bouchareb*, Gayathri Delanerolle, Yarab Al-Bulushi, Ali Al Khudhuri, Srinivasa Rao Sirsangandla, Ghalib Al Badaai, Heitor Cavalini, Peter Phiri, Ashish Shetty, Jian Qing Shi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Introduction: Prostate Cancer (PCa) is the fourth most prevalent cancer globally, and the most common among men. Most PCa patients in Oman are presented during the advanced stages of the disease with widespread metastatic disease reducing their overall rates of survival. Characterisation of the Omanis PCa population could be beneficial to develop a clinical profile demonstrating specific characteristics to better classify and derive radiomics signatures. These could help in developing artificial intelligence methods to assist with earlier and quicker diagnosis of possible prostate lesions.

Methods: A retrospective, cross-sectional study has been designed to determine the pathological and radiological characteristics based on multi-sequence 3-dimensional Magnetic Resonance Imaging (MRI). The MRI records are maintained within the existing
electronic healthcare records of the Sultan Qaboos University Hospital’s Department of Radiology and Molecular Imaging. Data will be extracted based on a confirmed diagnosis reported between the 1st of January 2010 and October 2023. All patients included
within the study will be aged between 18-99 years. A study specific data extraction template has been devised to gather demographic details, clinical parameters, and radiological findings based on existing imaging reports within the HIS and PACS systems.

Ethics approval: Research Ethics approval reference for this study is (MREC #3176 REF. NO. SQU-EC/ 283\2023)

Conclusion: The data analysis will be conducted using statistical software to conduct a Joinpoint regression analysis and linear regression modelling. We will also conduct a descriptive analysis.
Original languageEnglish
Pages (from-to)619-622
JournalAmerican Journal of Biomedical Science & Research
Volume22
Issue number5
DOIs
Publication statusPublished - 24 May 2024
Externally publishedYes

Keywords

  • Prostate cancer
  • Middle eastern population
  • clinical epidemiology
  • Artificial intelligence
  • Radiomics

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