Novel MRI Techniques

The Centre for Medical Imaging has a major focus on the clinical translation of novel imaging technologies, allowing new approaches to assess microstructure, function and metabolism of cancer in-vivo.

Prostate scan could save thousands of unnecessary biopsies
A person on an MRI machine and the monitors showing the imaging

Prostate scan could save thousands of unnecessary biopsies

A new study found a new type of MRI scan could help doctors rule out prostate cancer more regularly, potentially saving thousands of men from undergoing unnecessary biopsies.

Hyperpolarised MRI

It is hoped that by using hyperpolarised MRI and multi-parametric MRI together, clinicians can further improve diagnostic accuracy by giving a clearer picture of the exact tumour location. Furthermore, by understanding the metabolic activity, clinicians hope to differentiate between aggressive or non-aggressive tumours, helping to guide treatment decisions.

A clinical trial at UCL uses a method which sees the patient injected with a traceable sugar before undergoing an MRI scan. Before injection, the sugar is put through a process called hyperpolarisation using specialised equipment set up at UCLH. This boosts the signal produced by the sugar by more than 10,000 times. The metabolic conversion of the sugar in the location of tumour can be picked up by MRI to determine where the tumour is and may be helpful in determining how aggressive the tumour is.

  • Lead Investigators: Professor Shonit Punwani
An axial T2 weighted MRI (A: top image) and Apparent Diffusion Coefficient map (B: middle image) acquired as part of a routine multi-parametric MRI study of the prostate
An axial T2 weighted MRI (A: top image) and Apparent Diffusion Coefficient map (B: middle image) acquired as part of a routine multi-parametric MRI study of the prostate. 13C spectroscopic lactate image (C: bottom image) demonstrates high levels of lactate at the position of the biopsy positive Gleason 3 4 tumour site (red arrow).

Quantitative MRI

Quantitative multi-parametric MRI research at CMI involves developing computational and analytic methodology for extracting quantitative data from multi-parametric (anatomical and functional) MRI and determine its biological significance.

  • Lead Investigators: Professor David Atkinson, Professor Shonit Punwani, Dr Tim Bray

Motion quantification and correction

Solving the problem of patient motion during MR imaging is part of research conducted at CMI includes MRI Motion Correction and Characterisation particularly in the imaging of the gut.

  • Lead Investigator: Professor David Atkinson, Professor Stuart Taylor

Artifical Intelligence (AI)

CMI collaborates with several partners to combine advanced imaging technologies with artificial intelligence.

  • Lead Investigators: Professor Shonit Punwani, Professor David Atkinson, Professor Sue Mallett, Dr Tim Bray
  • Partner: Quibim

Experts

Professor David Atkinson
Professor David Atkinson

Professor of Imaging in Medicine

Dr Tim Bray
Dr Tim Bray

Honorary Associate Professor

Sue Mallett
Professor Sue Mallett

Professor in Diagnostic and Prognostic Medical Statistics

Shonit Punwani portrait
Professor Shonit Punwani

Professor of Magnetic Resonance and Cancer Imaging

Professor Stuart Taylor
Professor Stuart Taylor

Professor of Medical Imaging

Publications

  1. Chowdhury R, Mueller CA ... Atkinson D ... Punwani S (2023). Quantification of Prostate Cancer Metabolism Using 3D Multiecho bSSFP and Hyperpolarized [1-13 C] Pyruvate: Metabolism Differs Between Tumors of the Same Gleason Grade. J Magn Reson Imaging. 2023 Jun;57(6): 1865-1875.
  2. Chowdhury R, Moorthy M ... Atkinson D, Gadian DG, Srirangalingam U, Punwani S (2023). First-in-human in-vivo depiction of paraganglioma metabolism by hyperpolarised 13C-magnetic resonance. BJR Case Rep. 2023 Sep 28;9(6): 20220089.
  3. Atkinson, D, Gong Y, Brembilla G, Punwani S (2021). Rapid fitting of Luminal Water Fraction in Prostate MRI. Presented at: 2021 ISMRM & SMRT Annual Meeting & Exhibition.
  4. Bray TJP, Bainbridge A, et al (2023). MAGORINO: Magnitude-only fat fraction and R*2 estimation with Rician noise modeling. Magn Reson Med. 2023 Mar;89(3): 1173-1192.
  5. Miller C, Taylor S, Emmanuel A, Zarate-Lopez N ... Atkinson D, et al (2023). P214 Cine MRI assessment of colonic motility in patients with ulcerative colitis associated constipation. Journal of Crohn's and Colitis, Volume 17, Issue Supplement 1, Feb 2023, pp i365–i366.
  6. Atkinson D (2022). Chapter 17: Retrospective correction of motion in MR images. In Motion Correction in MR: Correction of Position, Motion, and Dynamic Field Changes, 1st Edition, Vol. 6  Eds: Andre van der Kouwe, Jalal B. Andre. ISBN: 9780128244609
  7. Hepburn C, Jones A, Bainbridge A ... Bray TJP (2023). Volume of hyperintense inflammation (VHI): A quantitative imaging biomarker of inflammation load in spondyloarthritis, enabled by human-machine cooperation. PLoS One. 2023 Apr 19;18(4): e0284508.