Treffer: The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer.

Title:
The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer.
Authors:
Santaolalla A; King's College London, School of Cancer and Pharmaceutical Sciences, Translational Oncology and Urology Research (TOUR), London, United Kingdom., Hulsen T; Philips Research, Department of Hospital Services and Informatics, Eindhoven, Netherlands., Davis J; Philips, Data Science Services, Best, Netherlands., Ahmed HU; Imperial College London, Faculty of Medicine, Imperial Prostate, Department of Surgery and Cancer, London, United Kingdom., Moore CM; Division of Surgical and Interventional Science, University College London, London, United Kingdom., Punwani S; Centre for Medical Imaging, University College London, London, United Kingdom., Attard G; Cancer Institute, University College London, London, United Kingdom., McCartan N; Division of Surgical and Interventional Science, University College London, London, United Kingdom., Emberton M; Division of Surgical and Interventional Science, University College London, London, United Kingdom., Coolen A; King's College London, School of Cancer and Pharmaceutical Sciences, Translational Oncology and Urology Research (TOUR), London, United Kingdom.; Department of Biophysics, Donders Institute, Radboud University Nijmegen, Nijmegen, Netherlands., Van Hemelrijck M; King's College London, School of Cancer and Pharmaceutical Sciences, Translational Oncology and Urology Research (TOUR), London, United Kingdom.
Source:
Frontiers in artificial intelligence [Front Artif Intell] 2021 Nov 16; Vol. 4, pp. 769582. Date of Electronic Publication: 2021 Nov 16 (Print Publication: 2021).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101770551 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-8212 (Electronic) Linking ISSN: 26248212 NLM ISO Abbreviation: Front Artif Intell Subsets: PubMed not MEDLINE
Imprint Name(s):
Original Publication: Lausanne, Switzerland : Frontiers Media SA, [2018]-
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Grant Information:
MR/R014043/1 United Kingdom MRC_ Medical Research Council
Contributed Indexing:
Keywords: artificial intelligence; data integration; data management; data science; data warehouse; database; prostate cancer; risk stratification
Entry Date(s):
Date Created: 20211206 Latest Revision: 20250530
Update Code:
20250530
PubMed Central ID:
PMC8637844
DOI:
10.3389/frai.2021.769582
PMID:
34870187
Database:
MEDLINE

Weitere Informationen

Introduction. Prostate cancer (PCa) is the most frequent cancer diagnosis in men worldwide. Our ability to identify those men whose cancer will decrease their lifespan and/or quality of life remains poor. The ReIMAGINE Consortium has been established to improve PCa diagnosis. Materials and methods. MRI will likely become the future cornerstone of the risk-stratification process for men at risk of early prostate cancer. We will, for the first time, be able to combine the underlying molecular changes in PCa with the state-of-the-art imaging. ReIMAGINE Screening invites men for MRI and PSA evaluation. ReIMAGINE Risk includes men at risk of prostate cancer based on MRI, and includes biomarker testing. Results. Baseline clinical information, genomics, blood, urine, fresh prostate tissue samples, digital pathology and radiomics data will be analysed. Data will be de-identified, stored with correlated mpMRI disease endotypes and linked with long term follow-up outcomes in an instance of the Philips Clinical Data Lake, consisting of cloud-based software. The ReIMAGINE platform includes application programming interfaces and a user interface that allows users to browse data, select cohorts, manage users and access rights, query data, and more. Connection to analytics tools such as Python allows statistical and stratification method pipelines to run profiling regression analyses. Discussion. The ReIMAGINE Multimodal Warehouse comprises a unique data source for PCa research, to improve risk stratification for PCa and inform clinical practice. The de-identified dataset characterized by clinical, imaging, genomics and digital pathology PCa patient phenotypes will be a valuable resource for the scientific and medical community.
(Copyright © 2021 Santaolalla, Hulsen, Davis, Ahmed, Moore, Punwani, Attard, McCartan, Emberton, Coolen and Van Hemelrijck.)

TH is employed by Philips Research. JD is employed by Philips. HA research is supported by core funding from the United Kingdom’s National Institute of Health Research (NIHR) Imperial Biomedical Research Centre. He currently receives funding from the Wellcome Trust, Medical Research Council (UK), Cancer Research UK, Prostate Cancer UK, National Institute for Health Research (UK), The Urology Foundation, BMA Foundation, Imperial Health Charity, NIHR Imperial BRC, Sonacare Inc, Trod Medical and Sophiris Biocorp for trials in prostate cancer. He was a paid medical consultant for Sophiris Biocorp in the previous 3 years. He is a proctor for HIFU and cryotherapy and paid for training other surgeons in this procedure. CM is supported by the National Institute for Health Research, and has funding from Movember, Prostate Cancer UK, Cancer Research UK and The Urology Foundation. She has received speaker fees from Astellas and Janssen, and is paid for training surgeons in focal therapy procedures. ME serves as a consultant/educator/trainer for Sonacare, Exact Imaging, Angiodynamics, and Profound Medical; and receives research support from the NIHR UCLH/UCL Biomedical Research Centre. AC receives funding from Cancer Research UK and is director of Saddle Point Science. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.