Artificial Intelligence Applications in Interventional Radiology

This review is a brief overview of the current status and the potential role of artificial intelligence (AI) in interventional radiology (IR). The literature published in the last decades was reviewed and the technical developments in terms of radiomics, virtual reality, robotics, fusion imaging, cone-beam computed tomography (CBCT) and Imaging Guidance Software were analyzed. The evidence shows that AI significatively improves pre-procedural planning, intra-procedural navigation, and post-procedural assessment. Radiomics extracts features from optical images of personalized treatment strategies. Virtual reality offers innovative tools especially for training and procedural simulation. Robotic systems, combined with AI, could enhance precision and reproducibility of IR procedures while reducing operator exposure to X-ray. Fusion imaging and CBCT, augmented by AI software, improve real-time guidance and procedural outcomes.

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Publication Details

Journal
Journal of Personalized Medicine
Published
2025-11-28
DOI
https://doi.org/10.3390/jpm15120569
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Artificial Intelligence Applications in Interventional Radiology

Sonia Triggiani, Antonio De Leo, Carolina Lanza, Velio Ascenti et al.
Journal of Personalized Medicine
Radiomics and Machine Learning in Medical Imaging
article

Artificial Intelligence Applications in Interventional Radiology

Sonia Triggiani, Antonio De Leo, Carolina Lanza, Velio Ascenti, Pierluca Torcia, Pierpaolo Biondetti, Salvatore Alessio Angileri, Flavio Arnone, Anna Maria Ierardi, Serena Carriero, Gianpaolo Carrafiello, Simone Mortellaro, Marco Ginolfi
article en

Abstract

This review is a brief overview of the current status and the potential role of artificial intelligence (AI) in interventional radiology (IR). The literature published in the last decades was reviewed and the technical developments in terms of radiomics, virtual reality, robotics, fusion imaging, cone-beam computed tomography (CBCT) and Imaging Guidance Software were analyzed. The evidence shows that AI significatively improves pre-procedural planning, intra-procedural navigation, and post-procedural assessment. Radiomics extracts features from optical images of personalized treatment strategies. Virtual reality offers innovative tools especially for training and procedural simulation. Robotic systems, combined with AI, could enhance precision and reproducibility of IR procedures while reducing operator exposure to X-ray. Fusion imaging and CBCT, augmented by AI software, improve real-time guidance and procedural outcomes.

Journal of Personalized MedicineVol. 15(12)
University of Milan (IT), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT), Ospedale Maggiore (IT)
Openalex Percentile: Top 48%
Radiomics and Machine Learning in Medical Imaging
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