Please see our latest publications. Full list is available on google scholar).

Prostate MR image quality of apparent diffusion coefficient maps versus fractional intracellular volume maps from VERDICT MRI using the PI-QUAL score and a dedicated Likert scale for artefacts

This study aimed to assess the image quality of apparent diffusion coefficient (ADC) maps derived from conventional diffusion-weighted MRI and fractional intracellular volume maps (FIC) from VERDICT MRI (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) in patients from the INNOVATE trial. The inter-reader agreement was also assessed.

Saurabh Singh, Francesco Giganti, Louise Dickinson, Harriet Rogers, Baris Kanber, Joey Clemente, Hayley Pye, Susan Heavey, Urszula Stopka-Farooqui, Edward W. Johnston, Caroline M Moore, Alex Freeman, Hayley C Whitaker, Daniel C Alexander, Eleftheria Panagiotaki, Shonit Punwani

European Journal of Radiology (2023)

ssVERDICT: Self-Supervised VERDICT-MRI for Enhanced Prostate Tumour Characterisation

Demonstrating and assessing self-supervised machine learning fitting of the VERDICT (Vascular, Extracellular and Restricted DIffusion for Cytometry in Tumours) model for prostate.

Snigdha Sen, Saurabh Singh, Hayley Pye, Caroline M. Moore, Hayley Whitaker, Shonit Punwani, David Atkinson, Eleftheria Panagiotaki1, and Paddy J.Slator

arXiv:2309.06268 (2023)

Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology

VERDICT (Vascular, Extracellular, and Restricted DIffusion for Cytometry in Tumours) is a diffusion MRI framework for the characterisation of different components of tumours, which has shown diagnostic utility for body cancer. The aim of this study was to extend the VERDICT framework to comprehensively characterise brain tumours, which is challenging due to the complexity of brain tissues. The resulting biomarkers showed agreement with histology and followed the expected trends when comparing different tumour types and sub-regions. These preliminary results hold promise for the non-invasive characterisation of brain tumours by VERDICT-MRI, which would be an important tool for diagnosis and monitoring of treatment effects.

Matteo Figini,Antonella Castellano,Michele Bailo,Marcella Callea, Marcello Cadioli, Marcello Cadioli, Samira Bouyagoub, Marco Palombo, Valentina Pieri, Pietro Mortini, Andrea Falini, Daniel C. Alexander, Mara Cercignani and Eleftheria Panagiotaki

Cancers (2023)

Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3+3, 3+4 and larger or equal to 4+3.

Marco Palombo, Vanya Valindria, Saurabh Singh, Eleni Chiou, Francesco Giganti, Hayley Pye, Hayley C. Whitaker, David Atkinson, Shonit Punwani, Daniel C. Alexander & Eleftheria Panagiotaki

Nature (2023)

Avoiding Unnecessary Biopsy after Multiparametric Prostate MRI with VERDICT Analysis: The INNOVATE Study

In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert score of 3 or higher) have no clinically significant (Gleason score ≤3+3, benign) biopsy findings. Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor (VERDICT) MRI analysis could improve the stratification of positive mpMRI findings. We evaluate VERDICT MRI, mpMRI-derived apparent diffusion coefficient (ADC), and prostate-specific antigen density (PSAD) as determinants of clinically significant PCa (csPCa).

Saurabh Singh , Harriet Rogers, Baris Kanber, Joey Clemente, Hayley Pye, Edward W. Johnston, Tom Parry, Alistair Grey, Eoin Dinneen, Greg Shaw, Susan Heavey, Urszula Stopka-Farooqui, Aiman Haider, Alex Freeman, Francesco Giganti, David Atkinson, Caroline M. Moore, Hayley C. Whitaker, Daniel C. Alexander, Eleftheria Panagiotaki, Shonit Punwani

Radiology (2022)

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models

False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively.

Snigdha Sen, Vanya Valindria, Paddy J. Slator, Hayley Pye, Alistair Grey , Alex Freeman, Caroline Moore, ayley Whitaker, Shonit Punwani, Saurabh Singh and Eleftheria Panagiotaki

Diagnostics (2022)