Role of artificial intelligence in brain tumour imaging.

Journal: European journal of radiology
Published Date:

Abstract

Artificial intelligence (AI) is a rapidly evolving field with many neuro-oncology applications. In this review, we discuss how AI can assist in brain tumour imaging, focusing on machine learning (ML) and deep learning (DL) techniques. We describe how AI can help in lesion detection, differential diagnosis, anatomic segmentation, molecular marker identification, prognostication, and pseudo-progression evaluation. We also cover AI applications in non-glioma brain tumours, such as brain metastasis, posterior fossa, and pituitary tumours. We highlight the challenges and limitations of AI implementation in radiology, such as data quality, standardization, and integration. Based on the findings in the aforementioned areas, we conclude that AI can potentially improve the diagnosis and treatment of brain tumours and provide a path towards personalized medicine and better patient outcomes.

Authors

  • Ezekiel Chukwujindu
    Independent Scholar, Canada. Electronic address: ezekiel.chukwujindu@mail.mcgill.ca.
  • Hafsa Faiz
    Independent Scholar, Canada. Electronic address: hafsa.faiz@medportal.ca.
  • Sara Ai-Douri
    University of Guelph, N1G 2W1, Canada. Electronic address: asarar9@gmail.com.
  • Khunsa Faiz
    McMaster University, Department of Radiology, L8S 4L8, Canada. Electronic address: khunsa.faiz@medportal.ca.
  • Alexandra De Sequeira
    Royal College of Surgeons in Ireland, 123 St. Stephen's, Green D02 YN77, Ireland. Electronic address: alexandradesequ22@rcsi.com.