TY - JOUR
T1 - AI-based applications in hybrid imaging
T2 - how to build smart and truly multi-parametric decision models for radiomics
AU - Castiglioni, Isabella
AU - Gallivanone, Francesca
AU - Soda, Paolo
AU - Avanzo, Michele
AU - Stancanello, Joseph
AU - Aiello, Marco
AU - Interlenghi, Matteo
AU - Salvatore, Marco
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Introduction: The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes. Objective: The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.
AB - Introduction: The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes. Objective: The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.
KW - Artificial intelligence
KW - Decision models
KW - Hybrid imaging
KW - PET/CT
KW - PET/MRI
KW - Radiomics
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U2 - 10.1007/s00259-019-04414-4
DO - 10.1007/s00259-019-04414-4
M3 - Review article
C2 - 31292700
AN - SCOPUS:85069658181
VL - 46
SP - 2673
EP - 2699
JO - European Journal of Pediatrics
JF - European Journal of Pediatrics
SN - 0340-6199
IS - 13
ER -