A. Jooya MD

Dr. Alborz Jooya

MD.CM, MSc, FRCPC, DABR

Positions

Radiation Oncologist

Arthur J.E. Child Comprehensive Cancer Centre

Assistant Professor

Cumming School of Medicine, Department of Oncology

Member

Arnie Charbonneau Cancer Institute

Contact information

Preferred method of communication

Admin Assistant: Kerry-Ann Talbot

Background

Credentials

MDCM, McGill University,

MSc, McGill University,

FRCPC - Radiation Oncology, The Ottawa Hospital, University of Ottawa,

MRL Fellowship, Princess Margaret Hospital, Toronto, ON,

Biography

Dr. Jooya is engaged in cutting-edge research on MR-LINAC technology, with a particular emphasis on stereotactic radiotherapy for breast, gastrointestinal (GI), genitourinary (GU), and oligometastatic cancers. His research integrates clinical oncology in breast, GI and GU malignancies, with a focus on incorporating MRL-based treatments. Dr. Jooya is committed to advancing oncology research and contributions to innovative cancer treatment strategies.

Research

Areas of Research

Area of Focus
  • MR-LINAC based stereotactic radiotherapy for breast, gastrointestinal (GI), genitourinary (GU), and oligometastatic cancers. 
Summary of Research

Dr. Jooya's research is interested in the use of ablative radiotherapy as a treatment modality for various primary and metastatic malignancies stereotactic body radiotherapy (SBRT) using an MR-Linac System. This includes feasibility studies of ablative treatments for GI cancers such as liver tumors, or GU tumors of prostate or kidney. Another component of MRL research includes practice-based training strategy to transition from radiation oncologist to therapist-driven adaptive stereotactic body radiotherapy (SBRT) for MR-Linac System. Additionally, despite increasing use of MRL in the management of patients with oligometastatic or upper gastrointestinal malignancies, health-related Quality Of Life (HRQOL) outcomes in patients who received SBRT on MRL systems are lacking. Dr. Jooya is interested in addressing this knowledge gap through collection and analysis of prospectively collected QOL data.