Alistair Grey

Dr. Alistair Grey


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 July 2022 in Diagnostics
Verified
Journal Article
Open access
PDF file
SSSnigdha Sen
Snigdha Sen
VVVanya Valindria
Vanya Valindria
PSPaddy J. Slator
Paddy J. Slator
HPHayley Pye
Hayley Pye
AGAlistair Grey
Alistair Grey
EPEleftheria Panagiotaki
Eleftheria Panagiotaki
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. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular–extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.

1 March 2018 in Contemporary Clinical Trials
Verified
Journal Article
Open access
AGAlistair Grey
Alistair Grey
RSRebecca Scott
Rebecca Scott
SCSusan Charman
Susan Charman
JMJan van der Meulen
Jan van der Meulen
PFPeter Frinking
Peter Frinking
HAHashim U. Ahmed
Hashim U. Ahmed
To compare the proportion of clinically significant prostate cancers (PCa) found in lesions detected by multiparametric MRI (mpMRI) with that found in lesions detected by multiparametric ultrasound (mpUSS), in men at risk. CADMUS (Cancer Detection by Multiparametric Ultrasound of the prostate) is a prospective, multi-centre paired cohort diagnostic utility study with built-in randomisation of order of biopsies. The trial is registered ISRCTN38541912. All patients will undergo the index test under evaluation (mpUSS±biopsies), as well as the standard test (mpMRI±biopsies). Eligible men will be those at risk of harbouring prostate cancer usually recommended for prostate biopsy, either for the first time or as a repeat, who have not had any prior treatment for prostate cancer. Men in need of repeat biopsy will include those with prior negative results but ongoing suspicion, and those with an existing prostate cancer diagnosis but a need for accurate risk stratification. Both scans will be reported blind to the results of the other and the order in which the targeted biopsies derived from the two different imaging modalities are taken will be randomised. Comparison will be drawn between biopsy results of lesions detected by mpUSS with those lesions detected by mpMRI. Agreement over position between the two imaging modalities will be studied. CADMUS will provide level one evidence on the performance of mpUSS derived targeted biopsies in the identification of clinically significant prostate cancer in comparison to mpMRI targeted biopsies. Recruitment is underway and expected to complete in 2018.

26 May 2022 in Preprints.org
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Preprint
Open access
PDF file
SSSnigdha Sen
Snigdha Sen
VVVanya Valindria
Vanya Valindria
PSPaddy J. Slator
Paddy J. Slator
HPHayley Pye
Hayley Pye
AGAlistair Grey
Alistair Grey
EPEleftheria Panagiotaki
Eleftheria Panagiotaki
False positives on multiparametric (mp)-MRI result in a large number of unnecessary biopsies in men with clinically insignificant diseases. This study investigates whether quantitative diffusion MRI can improve differentiation between false positives, true positives and normal tis-sue. Twenty-three patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffu-sion for Cytometry in Tumours (VERDICT)-MRI, followed by transperineal biopsy. The patients were categorised into two groups following biopsy: (1) significant cancer - true positive (2) atro-phy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN) - false positive. The clinical apparent diffusion coefficient (ADC) values of the lesions were obtained, and the intravoxel inco-herent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted using a deep learning approach. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular-extravascular vol-ume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were only found for the VERDICT fIC. These results demonstrate that model-based diffusion MRI could reduce the number of unnecessary biopsies due to false positive prostate lesions and shows promising sensitivity to benign diseases that mimic cancer.

Verified
Journal Article
Open access
PDF file
CMCaroline M. Moore
Caroline M. Moore
AGAlistair Grey
Alistair Grey
KWKara L Watts
Kara L Watts
RSRafael Sanchez-Salas
Rafael Sanchez-Salas
HAHashim Uddin Ahmed
Hashim Uddin Ahmed
JRJan Philipp Radtke
Jan Philipp Radtke
The 7th Bench-to-Bedside Uro-Oncology: GU Cancers Triad Meeting, organized in conjunction with the 45th Annual Congress of the Société Internationale d’Urologie, was held on 31 October 2025, in Edinburgh, Scotland, and transmitted live on the SIU@U Congress app