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Dr Francesco Grussu
1st floor Russell Square House
10-12 Russell Square
London
WC1B 5EH
Tel: +442031087499
Appointment
  • Research Associate
  • Neuroinflammation
  • Institute of Neurology
  • Faculty of Brain Sciences
Biography

  • Laurea Triennale, Biomedical Engineering (BEng), University of Cagliari (Italy), 2006-2009. 
  • Laurea Magistrale, Bioengineering (MEng, Neuroengineering & Cognitive Neurosciences), University of Genoa (Italy), 2009-2012. 
  • Research assistant, Queen Mary University of London (EECS, School of Electronic Engineering and Computer Science), spring 2012. 
  • PhD student at UCL, supervised by Prof Claudia Gandini Wheeler-Kingshott and Prof Daniel Alexander, 2012-2016. 
  • Postdoctoral research associate, UCL Institute of Neurology, 2016-present.


My PhD was funded by a UCL Grand Challenge Studentship, and focussed on the investigation of innovative diffusion magnetic resonance imaging methods for the multiple sclerosis spinal cord. The work was carried out between the UCL Institute of Neurology (Department of Neuroinflammation, Queen Square MS Centre) and the Centre for Medical Image Computing (CMIC), Microstructure Imaging Group. I completed my PhD on the 28/03/2016, with a thesis entitled "Microstructural imaging of the human spinal cord with advanced diffusion MRI". 


Now, I work as a postdoctoral Research Associate at the Centre for Medical Image Computing and at the UCL Institute of Neurology. 


Research Summary

My research is to do with quantitative magnetic resonance imaging (MRI) in multiple sclerosis (MS). MS is a complex disease affecting brain, spinal cord and optic nerves, and is one of the major causes of disability among young adults. Although MRI is key for the diagnosis and the monitoring of MS, conventional methods underestimate the real, widespread effect that the disease has on the central nervous system. Conventional MRI provides measures that only partially explain disease progression and accrual of disability, leading to poor and often inaccurate long-term predictions of the disease course. 


In my work, I experiment the potential of novel, quantitative MRI methods for MS. The new methods aim to map in a non-invasive fashion microstructural features specific to neuronal morphology, providing metrics that may detect early, microscopic tissue damage. The new indices have the potential of becoming useful biomarkers characterising early microstructural pathology, before the appearance of macroscopic radiological signs. Ultimately, the new metrics should improve the accuracy of diagnosis and prognosis and should more effectively monitor treatment efficacy than current, conventional readouts.


I have a double appointment at the Centre for Medical Image Computing and at the Queen Square MS Centre of the UCL Institute of Neurology. I work under the mentorship of Prof Claudia Gandini Wheeler-Kingshott, Prof Daniel Alexander and Dr M Jorge Cardoso.

Teaching Summary

I help with teaching activities at the UCL Institute of Neurology, conveying some lectures on MRI for the MSc in "Advanced Neuroimaging (ADNI)". I also convey a workshop for the ADNI course on Earth's field MRI, and take active part in the supervision of MSc research projects.

Appointments
08-FEB-2016 – 30-JUN-2018 Research Associate Institute of Neurology and Department of Computer Science UCL, United Kingdom
Academic Background
2016 PhD Doctor of Philosophy – Magnetic Resonance Imaging University College London
2012 LAUM Laurea magistrale – Bioengineering Universita degli Studi di Genova
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