INNOVATE: A prospective cohort study combining serum and urinary biomarkers with novel diffusion-weighted magnetic resonance imaging for the prediction and characterization of prostate cancer

Whilst multi-parametric magnetic resonance imaging (mp-MRI) has been a significant advance in the diagnosis of prostate cancer, scanning all patients with elevated prostate specific antigen (PSA) levels is considered too costly for widespread National Health Service (NHS) use, as the predictive value of PSA levels for significant disease is poor. Despite the fact that novel blood and urine tests are available which may predict aggressive disease better than PSA, they are not routinely employed due to a lack of clinical validity studies. Furthermore approximately 40 % of mp-MRI studies are reported as indeterminate, which can lead to repeat examinations or unnecessary biopsy with associated patient anxiety, discomfort, risk and additional costs.

We aim to clinically validate a panel of minimally invasive promising blood and urine biomarkers, to better select patients that will benefit from a multiparametric prostate MRI. We will then test whether the performance of the mp-MRI can be improved by the addition of an advanced diffusion-weighted MRI technique, which uses a biophysical model to characterise tissue microstructure called VERDICT; Vascular and Extracellular Restricted Diffusion for Cytometry in Tumours. INNOVATE is a prospective single centre cohort study in 365 patients. mp-MRI will act as the reference standard for the biomarker panel. A clinical outcome based reference standard based on biopsy, mp-MRI and follow-up will be used for VERDICT MRI.

We expect the combined effect of biomarkers and VERDICT MRI will improve care by better detecting aggressive prostate cancer early and make mp-MRI before biopsy economically viable for universal NHS adoption.

INNOVATE is registered on, with reference NCT02689271 .

BMC cancer. 2016 Oct 21*** epublish ***

Edward Johnston, Hayley Pye, Elisenda Bonet-Carne, Eleftheria Panagiotaki, Dominic Patel, Myria Galazi, Susan Heavey, Lina Carmona, Alexander Freeman, Giorgia Trevisan, Clare Allen, Alexander Kirkham, Keith Burling, Nicola Stevens, David Hawkes, Mark Emberton, Caroline Moore, Hashim U Ahmed, David Atkinson, Manuel Rodriguez-Justo, Tony Ng, Daniel Alexander, Hayley Whitaker, Shonit Punwani

UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE, UK. ., Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT, UK., Department of Computer Science, UCL, Gower Street, London, WC1E 6BT, UK., Department of Research Pathology, UCL Cancer Institute, Rockefeller Building, 21 University Street, London, WC1E 6JJ, UK., Molecular Oncology group, UCL Cancer Institute, Paul O'Gorman Building, 72 Huntley Street, London, WC1E 6DD, UK., UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE, UK., Division of Surgery, 4th floor, 21 University Street, London, WC1E, UK.

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