Bradley MacIntosh

MSc, PhD
Senior Scientist
bmac@sri.utoronto.ca

The MacIntosh laboratory develops advanced imaging tools and methods to enhance the understanding of human brain disease, with a focus on image analysis for both clinical and research applications. Magnetic Resonance Imaging (MRI) serves as the lab’s primary modality, enabling precise measurements of neurovascular function, cerebral blood flow, and cerebrovascular reactivity. Key contributions include pioneering work in arterial spin labeling (ASL) MRI, which produces detailed, non-invasive cerebral blood flow maps, and functional MRI (fMRI) research, particularly BOLD-based cerebrovascular reactivity and cardiac pulsatility imaging.

Recently, the lab expanded its focus to Computed Tomography (CT) and Positron Emission Tomography (PET), leveraging automated image analysis to extract clinically relevant vascular features. Clinical investigations encompass a diverse range of diseases, including stroke, small vessel disease, Alzheimer’s disease, bipolar disorder, and diabetes. The lab’s work integrates deep learning techniques and collaborative pipelines to advance computational neuroradiology and improve diagnostic and therapeutic pathways in neurology and psychiatry.

Education

  • B.Sc., 1999, Theoretical Physiology, University of Toronto, Canada
  • M.Sc., 2001, Medical Biophysics, Western University, Canada
  • PhD, 2007, Medical Biophysics, University of Toronto, Canada

Appointments & Affiliations

  • Senior Scientist, Physical Sciences Platform, Sandra Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute
  • Senior Scientist, Computational Radiology Artificial Intelligence unit, Oslo University Hospital, Norway
  • Neuroimaging Lead, Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health
  • Professor, Department of Medical Biophysics, University of Toronto

Research Foci

  • Brain activation and cerebrovascular reactivity with functional MRI
  • Cerebral blood flow imaging with arterial spin labeling MRI
  • Clinical investigations in neurology and psychiatry
  • Deep learning image analysis for computational neuroradiology in stroke and dementia

Affiliated Labs & Programs

Selected Publications

  1. Jahani I, Jahani A, Delrobaei M, Khadem A, MacIntosh BJ. Classifying cognitive impairment based on FDG-PET and combined T1-MRI and rs-fMRI: An ADNI study. J Alzheimers Dis. 2024 Dec 3:13872877241302493. doi: 10.1177/13872877241302493. Epub ahead of print. PMID: 39623970.

  2. MacIntosh BJ, Liu Q, Schellhorn T, Beyer MK, Groote IR, Morberg PC, Poulin JM, Selseth MN, Bakke RC, Naqvi A, Hillal A, Ullberg T, Wassélius J, Rønning OM, Selnes P, Kristoffersen ES, Emblem KE, Skogen K, Sandset EC, Bjørnerud A. Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury. Front Neurol. 2023 Sep 28;14:1244672. doi: 10.3389/fneur.2023.1244672. PMID: 37840934; PMCID: PMC10568013.

  3. Valsamis JJ, Luciw NJ, Haq N, Atwi S, Duchesne S, Cameron W, MacIntosh BJ. An imaging-based method of mapping multi-echo BOLD intracranial pulsatility. Magn Reson Med. 2023 Jul;90(1):343-352. doi: 10.1002/mrm.29639. Epub 2023 Mar 17. PMID: 36929810.

  4. Kim WSH, Luciw NJ, Atwi S, Shirzadi Z, Dolui S, Detre JA, Nasrallah IM, Swardfager W, Bryan RN, Launer LJ, MacIntosh BJ. Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy. Hum Brain Mapp. 2022 Aug 15;43(12):3680-3693. doi: 10.1002/hbm.25876. Epub 2022 Apr 15. PMID: 35429100; PMCID: PMC9294299.

  5. Mutsaerts HJMM, Petr J, Thomas DL, De Vita E, Cash DM, van Osch MJP, Golay X, Groot PFC, Ourselin S, van Swieten J, Laforce R Jr, Tagliavini F, Borroni B, Galimberti D, Rowe JB, Graff C, Pizzini FB, Finger E, Sorbi S, Castelo Branco M, Rohrer JD, Masellis M, MacIntosh BJ; GENFI investigators. Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI). J Magn Reson Imaging. 2018 Jan;47(1):131-140. doi: 10.1002/jmri.25751. Epub 2017 May 8. PMID: 28480617; PMCID: PMC6485386.

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