Dr. Masoom Haider
Clinician Scientist II
Dr. Masoom Haider is a radiologist and clinician scientist at the University of Toronto in the Joint Department of Medical Imaging. His research focuses on image biomarker validation using multiparametric MRI and CT technologies.
His team uses machine learning and artificial intelligence methods combined with imaging biomarkers to develop predictive and prognostic radiomics signatures for pelvic cancers, including prostate, pancreas, kidney and liver cancers.
Dr. Haider is the imaging lead on national MRI trials in prostate cancer and has worked on guideline development for the use of multiparametric prostate MRI (mpMRI) for prostate cancer, namely the Pi-Rads standard. He holds a Chair in Artificial Intelligence, Imaging Biomarkers and Radiomics at the Lunenfeld-Tanenbaum Research Institute, Sinai Health System. In the Joint Deptartment of Medical Imaging and Lunenfeld-Tanenbaum Research Institute he leads the AI, Radiomics and Oncologic Imaging Research Lab and collaborates with oncologists, computer scientists, engineers, radiologists and biomedical physicists.
Dr. Haider has held peer-reviewed grants from Prostate Cancer Canada, the Canadian Cancer Society Research Institute, Cancer Care Ontario and the Ontario Institute for Cancer Research for MRI-related prostate and pancreatic cancer research.
- Clinician Scientist II, OICR
- Professor of Radiology, Faculty of Medicine, Department of Medical Imaging, University of Toronto
- Director, Research MRI, Sinai Health System
- Head, AI, Radiomics and Oncologic Imaging Research Lab, Lunenfeld-Tanenbaum Research Institute, Sinai Health System
- Senior Scientist (cross-appointed), Sunnybrook Research Institute & the Institute of Biomaterials and Biomedical Engineering (IBBME) University of Toronto
- Associate Appointment, Institute of Medical Sciences (IMS), University of Toronto
- Magnetic resonance imaging (MRI)
- Computed tomography (CT)
- Artificial Intelligence
- Machine learning
- Quantitative imaging biomarkers
- Prostate cancer
- Pancreatic cancer
- Renal cell carcinoma
- Liver metastases
- Hepatocellular carcinoma
- Imaging for therapy response assessment
- Computer aided diagnosis (CAD)
- Klotz L, Pond G, Loblaw A, …, Haider M. Randomized Study of Systematic Biopsy Versus Magnetic Resonance Imaging and Targeted and Systematic Biopsy in Men on Active Surveillance (ASIST): 2-year Postbiopsy Follow-up. Eur Urol. 2019.
- Khalvati F, Zhang Y, Baig S, …, Haider MA. Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma. Sci Rep. 2019; 9(1):5449.
- Turkbey B, Rosenkrantz AB, Haider MA, …, Weinreb JC. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. Eur Urol. 2019; 76(3):e78.
- Khalvati F, Zhang J, Chung AG, …, Haider MA. MPCaD: A multi-scale radiomics-driven framework for automated prostate cancer localization and detection. BMC Med Imaging. 2018; 18(1):16.
- Haider MA, Vosough A, Khalvati F, …, Bjarnason GA. CT texture analysis: a potential tool for prediction of survival in patients with metastatic clear cell carcinoma treated with sunitinib. Cancer Imaging. 2017; 17(1):4.
Previous experience and education
- Chief, Department of Medical Imaging, Sunnybrook Health Sciences Centre
- Head of MRI, Department of Medical Imaging, Sunnybrook Health Sciences Centre
- Head of Abdominal and Pelvic MRI, Princess Margaret Hospital, University Health Network
- MD, University of Ottawa (with additional training at the University of Toronto, the University of Waterloo and the Cleveland Clinic)
Opportunities to collaborate
- Quantitative imaging of cancer (outside of the brain)
- Imaging of prostate cancer (renal cell carcinoma, pancreatic cancer, hepatocellular caricinoma, liver metastases)
- Machine learning as applied to diagnostic imaging in cancer
- Technology development in abdominal and pelvic MRI as applied to cancer
- Improved user interfaces for image interpretation in diagnostic imaging (radiology)
Visit OICR’s Collaborative Research Resources directory for more opportunities to collaborate with OICR researchers.
Dr. Masoom Haider