Integrating radiomics into holomics for personalised oncology : from algorithms to bedside

Gatta, Roberto (Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland) ; Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland) ; Ratib, Osman (Riviera-Chablais Hospital, Rennaz, Switzerland ; Department of Medical Imaging, Lausanne University Hospital, Lausanne, Switzerland) ; Michielin, Olivier (Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland) ; Leimgruber, Antoine (Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland ; Riviera-Chablais Hospital, Rennaz, Switzerland)

Radiomics, artificial intelligence, and deep learning figure amongst recent buzzwords in current medical imaging research and technological development. Analysis of medical big data in assessment and follow-up of personalised treatments has also become a major research topic in the area of precision medicine. In this review, current research trends in radiomics are analysed, from handcrafted radiomics feature extraction and statistical analysis to deep learning. Radiomics algorithms now include genomics and immunomics data to improve patient stratification and prediction of treatment response. Several applications have already shown conclusive results demonstrating the potential of including other “omics” data to existing imaging features. We also discuss further challenges of data harmonisation and management infrastructure to shed a light on the much-needed integration of radiomics and all other “omics” into clinical workflows. In particular, we point to the emerging paradigm shift in the implementation of big data infrastructures to facilitate databanks growth, data extraction and the development of expert software tools. Secured access, sharing, and integration of all health data, called “holomics”, will accelerate the revolution of personalised medicine and oncology as well as expand the role of imaging specialists.


Keywords:
Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Date:
2020-02
Pagination:
9 p.
Published in:
European radiology experimental
Numeration (vol. no.):
2020, vol. 4, article 11, pp. 1-9
DOI:
ISSN:
2509-9280
Appears in Collection:



 Record created 2020-11-18, last modified 2020-11-20

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