Abstract #0588

Validation of in vivo VERDICT fIC against matched histology from whole-mount prostatectomy

Marta Masramon Munoz¹, Manju Mathew², Saurabh Singh^2,3, Thomy Mertzanidou¹, Shipra Suman^1,2, Joey Clemente², Adam Retter², Marianthi-Vasilik Papoutsaki², Lorna Smith², Francesco Grussu^1,4,5, Veeru Kasivisvanathan⁶, Alistair Grey^7,8, Eoin Dineen⁶, Greg Shaw^6,7,8, Martyn Carter⁹, Dominic Patel¹⁰, Lucy Caselton², Caroline M. Moore⁶, David Atkinson², Aiman Haider¹¹, Alex Freeman¹¹, Daniel Alexander¹, Shonit Punwani², and Eleftheria Panagiotaki¹

¹Centre for Medical Imaging Computing, University College London, London, United Kingdom, ²Centre for Medical Imaging, University College London, London, United Kingdom, ³Department of Radiology, UCLH, London, United Kingdom, ⁴Department of Neuroinflammation, University College London, London, United Kingdom, ⁵Radiomics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain, ⁶Division of Surgery and Interventional Sciences, University College London, London, United Kingdom, ⁷Department of Urology, UCLH, London, United Kingdom, ⁸Department of Urology, Barts Health NHS Foundation Trust, London, United Kingdom, ⁹Faculty of the Built Environment, University College London, London, United Kingdom, ¹⁰Department of Pathology, University College London Cancer Institute, London, United Kingdom, ¹¹Department of Pathology, UCLH, London, United Kingdom

Synopsis

Keywords: Simulation/Validation, Validation, Prostate cancer diffusion VERDICT

Motivation: Intracellular volume fraction (fIC) maps from VERDICT-MRI have shown potential to improve prostate cancer (PCa) stratification, but the microstructural origin of the signal has not yet been investigated in in vivo settings.

Goal(s): Investigate the accuracy of fIC from in vivo VERDICT-MRI as a measurement of cell density using matched prostatectomy specimens.

Approach: Using personalised moulds from multiparametric (mp)MRI and deep learning image registration, we align whole prostatectomy histology images with corresponding VERDICT MR images. We compare fIC maps against cell density maps derived from histology.

Results: fIC maps show very strong agreement with histology-derived cell density maps of epithelial cells (r=0.8303).

Impact: Our study shows that VERDICT fIC maps are accurate descriptors of epithelial cell density in the prostate. The biological interpretability of these maps will facilitate translation into clinical practice, improving PCa stratification from MRI.

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