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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
  • UCL Queen Square 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 at UCL, 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. Conventional MRI provides measures that only partially explain visualise the extent of diseases, as it only reveals macroscopic damage and does not detect early microstructural pathology. This leads to poor and often inaccurate long-term predictions of the disease courses, as well as inaccurate diagnoses. 


In my work, I experiment the potential of novel, quantitative MRI methods to improve current clinical protocols. The new methods aim to map in a non-invasive fashion microstructural features specific to cell morphology, providing metrics that may detect early 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.


In my work I study the potential of quantitative MRI in two conditions: multiple sclerosis and prostate cancer. I have a double appointment at the Queen Square MS Centre (UCL Institute of Neurology) and at the Centre for Medical Image Computing (UCL Department of Computer Science), and I work closely with the Centre for Medical Imaging (UCL Division of Medicine).


I work under the mentorship of Prof Claudia Gandini Wheeler-Kingshott and Prof Daniel Alexander.

Teaching Summary

I help with teaching activities at the UCL Institute of Neurology, conveying some lectures and workshops on MRI for the MSc in "Advanced Neuroimaging (ADNI)" and supervising MSc research projects.

Appointments
08-FEB-2016 – 30-JUN-2021 Research Associate QS 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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