NMBL

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Anthony Gatti

IMG_0639
Postdoctoral Scholar
Wu Tsai Human Performance Alliance
aagatti@stanford.edu
Lucas Center, Room PS055
Personal Website
Twitter
Google Scholar

Research Interests

My research takes a multi-disciplinary approach to understanding knee health and disease. I have and continue to develop methods for automatically quantifying knee anatomy and integrating subject-specific, or theoretically simulated, anatomies with biomechanical models. I accomplish these objectives using medical imaging, machine learning, and musculoskeletal modeling. Ultimately, I use these methods to better understand knee physiology including the acute response to exercise as well as the natural aging and disease processes.

Degrees

Ph.D. in Rehabilitation Science, McMaster University, 2021
M.Sc. in Rehabilitation Science, McMaster University, 2015
B.Sc. in Kinesiology, McMaster University, 2013

Honors and Awards

• Canadian Institutes of Health Research Postdoctoral Fellowship (top 1%, 2022)
• Excellence in Rehabilitation Science Research Award, McMaster University (2021)
• Faculty of Health Sciences Graduate Programs Excellence Award, McMaster University (3x: 2015, 2018, 2019)
• Mitacs Accelerate Entrepreneur (2019)
• Distinction, Comprehensive Examination, McMaster University (2018)
• Graduate Student Innovation and Entrepreneurship Award, McMaster University (2017)
• Forge Student Start-Up Competition Winner, McMaster University (2017)
• Ontario Graduate Scholarship (3x: 2016, 2017, 2018)
• The Arthritis Society PhD Salary Award (2016)
• Canadian Society for Biomechanics Master’s Competition Finalist (2016)
• Faculty of Health Sciences Graduate Programs Outstanding Achievement Award (2015)
• Finalist, Three Minute Thesis Competition, McMaster University (2015)
• Third Place, Three Minute Thesis Competition, McMaster University (2014)

Representative Publications

Gatti AA, Keir PJ, Noseworthy MD, Maly MR, “Investigating Acute Changes in Osteoarthritic Cartilage by Integrating Biomechanics and Statistical Shape Models of Bone: Data from the Osteoarthritis Initiative”, Magnetic Resonance Materials in Physics, Biology and Medicine, 2022, https://doi.org/10.1007/s10334-022-01004-8;

Gatti AA, Maly MR., “Automatic Knee Cartilage and Bone Segmentation using Multi-Stage Convolutional Neural Networks: Data from the Osteoarthritis Initiative”, Magnetic Resonance Materials in Physics, Biology and Medicine, 2021, https://doi.org/10.1007/s10334-021-00934-z;

Brisson NM*, Gatti AA*, Damm P, Duda GN, Maly MR, “Association of machine learning based predictions of medial knee contact force with cartilage loss over 2.5 years in knee osteoarthritis”, Arthritis & Rheumatology, 2021, * denotes co-first-authorship;
https://doi.org/10.1002/art.41735;

Gatti AA, Keir PJ, Noseworthy MD, Beauchamp MK, Maly MR., “Equations to Prescribe Bicycle Saddle Height Based on Desired Joint Kinematics and Bicycle Geometry”, European Journal of Sports Science, 2021, https://doi.org/10.1080/17461391.2021.1902570;

Gatti AA, Keir PJ, Noseworthy MD, Beauchamp MK, Maly MR., “Hip and Ankle Kinematics Are The Most Import Predictors Of Knee Joint Loading During Bicycling”, Journal of Science and Medicine in Sport, 2020, https://doi.org/10.1016/j.jsams.2020.07.001;

Gatti AA., Noseworthy M., Stratford P., Brenneman E., Totterman S., Tamez-Peña J., and Maly M.R. “Acute changes in knee cartilage transverse relaxation time after running and bicycling”, Journal of Biomechanics, 2017, https://doi.org/10.1016/j.jbiomech.2017.01.017;

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