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Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step...
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Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step Towards Personalized Medicine

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".

Deadline for manuscript submissions: 15 August 2026 | Viewed by 2821

Special Issue Editors

Dr. Maurizio Cè

E-Mail Website
Guest Editor
Postgraduate School of Radiodiagnostics, University of Milan, 20122 Milan, Italy
Interests: interventional radiology; artificial intelligence; radiology; oncological imaging
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Pellegrino

E-Mail Website
Guest Editor
Postgraduate School of Radiodiagnostics, University of Milan, 20122 Milan, Italy
Interests: interventional radiology; artificial intelligence; radiology; radiodiagnostics
Dr. Salvatore Alessio Angileri

E-Mail Website
Guest Editor
Department of Diagnostic and Interventional Radiology, Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milan, Italy
Interests: interventional radiology; artificial intelligence; radiology; radiodiagnostics

Special Issue Information

Dear Colleague,

We are pleased to invite you to contribute to a Special Issue of the Journal of Personalized Medicine entitled "Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step Towards Personalized Medicine".

Interventional radiology (IR) is undergoing a significant transformation driven by technological advancements that enhance precision, improve safety, and broaden the scope of applications.

This Special Issue aims to explore the latest technological developments in this rapidly evolving field, with a particular focus on, but not limited to, artificial intelligence, both in the core aspects of IR and in bridging challenges between diagnostic and interventional radiology.

Topics of interest include the following:

  • Innovative techniques to address procedural challenges in IR.
  • The automation of image segmentation and analysis for procedural planning.
  • Real-time decision support systems during procedures.
  • Augmented and mixed reality for procedural navigation and planning.
  • Predictive models for treatment outcomes and clinical decision making.
  • Strategies to reduce complication rates and improve procedural success.
  • The integration of emerging technologies into clinical practice, with a focus on early-stage diagnostics and personalized treatment planning.
  • Regulatory and ethical considerations surrounding the adoption of technological innovations in IR.

We are particularly interested in papers that explore the use of artificial intelligence, as well as other emerging technologies and methodologies that are reshaping both interventional radiology and the diagnostic practices that precede IR procedures. This Special Issue will offer a comprehensive perspective on how these innovations are driving more personalized and effective patient care.

Please find the submission guidelines and deadline details below:

  • Submission Deadline: October 2025.

We look forward to receiving your contribution.

Dr. Maurizio Cè
Dr. Giuseppe Pellegrino
Dr. Salvatore Alessio Angileri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • interventional radiology
  • artificial intelligence
  • augmented reality

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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13 pages, 1510 KB  
Article
Radiomics of Hepatocellular Carcinoma: Identifying Predictors of Microvascular Invasion Using Multi-Phase CT Analysis
by Flavio Spoto, Nicolo’ Cardobi, Riccardo De Robertis, Luca Geraci, Luisa Tomaiuolo, Eda Bardhi, Beatrice Mascarin, Claudio Luchini, Andrea Ruzzenente and Mirko D’Onofrio
J. Pers. Med. 2025, 15(11), 527; https://doi.org/10.3390/jpm15110527 - 2 Nov 2025
Viewed by 693
Abstract
Objective: To explore radiomic texture features from multi-phase contrast-enhanced CT as potential predictors of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: This exploratory single-center study retrospectively analyzed 49 patients (54 HCC lesions) who underwent liver resection between 2018–2022. Radiomic analysis [...] Read more.
Objective: To explore radiomic texture features from multi-phase contrast-enhanced CT as potential predictors of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: This exploratory single-center study retrospectively analyzed 49 patients (54 HCC lesions) who underwent liver resection between 2018–2022. Radiomic analysis extracted 642 features across arterial, venous, and delayed phases using original and 5 mm-expanded tumor margins. Results: The 20–50 mm lesion subgroup (n = 37) provided the most reliable results, with arterial phase texture homogeneity features achieving AUC 0.772. Features from lesions <20 mm (n = 14, 4 MVI+) showed clear evidence of overfitting and were excluded from primary analyses. Delayed phase features showed preliminary associations (AUC 0.8) in a small LR-3/4 subset (n = 20). Limitations: This hypothesis-generating study has significant limitations including small sample size, single-center design, and lack of correction for multiple comparisons. Conclusions: Multi-phase CT radiomic analysis shows potential for MVI prediction in intermediate-sized HCC lesions, though external validation in larger cohorts is essential before clinical application. Full article
(This article belongs to the Special Issue Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step Towards Personalized Medicine)
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14 pages, 1748 KB  
Article
Medium- and Long-Term Evaluation of Splenic Arterial Embolization: A Retrospective CT Volumetric and Hematologic Function Analysis
by Filippo Piacentino, Federico Fontana, Cecilia Beltramini, Andrea Coppola, Anna Maria Ierardi, Gianpaolo Carrafiello, Giulio Carcano and Massimo Venturini
J. Pers. Med. 2025, 15(9), 424; https://doi.org/10.3390/jpm15090424 - 4 Sep 2025
Viewed by 847
Abstract
Background: Splenic arterial embolization (SAE) is a well-established technique in the non-operative management of splenic trauma and aneurysms. While its short-term safety and efficacy have been widely documented, medium- and long-term impacts on splenic volume and function remain under-investigated. This study aimed to [...] Read more.
Background: Splenic arterial embolization (SAE) is a well-established technique in the non-operative management of splenic trauma and aneurysms. While its short-term safety and efficacy have been widely documented, medium- and long-term impacts on splenic volume and function remain under-investigated. This study aimed to evaluate volumetric changes and hematological parameters following SAE, with emphasis on its role in preserving splenic integrity and potential integration with AI-enhanced imaging technologies. Methods: We retrospectively analyzed 17 patients treated with SAE between January 2014 and December 2023. Volumetric measurements were performed using computed tomography (CT) with 3D reconstructions before and after SAE. Patients were divided into two groups based on indication: polytrauma (n = 8) and splenic artery aneurysm (n = 9). Hematological parameters including white blood cells (WBCs), red blood cells (RBCs), and hemoglobin (Hb) were evaluated in correlation with clinical outcomes. Statistical significance was assessed using Student’s t-test, and power analysis was conducted. Results: Among the trauma group, mean splenic volume decreased from 190.5 ± 51.2 cm3 to 147.8 ± 77.8 cm3 (p = 0.2158), while in the aneurysm group, volume decreased from 195.4 ± 78.9 cm3 to 143.7 ± 81.4 cm3 (p = 0.184). Though not statistically significant, these changes suggest post-procedural splenic remodeling. The technical success of SAE was 100%, with no cases of late follow-up infarction, abscess, immunological impairment, or secondary splenectomy required. Hematologic parameters remained within normal limits in follow-up assessments. Conclusions: SAE represents a safe and effective intervention for spleen preservation in both traumatic and aneurysmal conditions. Although a reduction in splenic volume has been observed, white blood cell counts, a reliable indicator of splenic function, have remained stable over time. This finding supports the preservation of splenic function following SAE. Full article
(This article belongs to the Special Issue Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step Towards Personalized Medicine)
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Review

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30 pages, 7547 KB  
Review
Artificial Intelligence Applications in Interventional Radiology
by Carolina Lanza, Salvatore Alessio Angileri, Serena Carriero, Sonia Triggiani, Velio Ascenti, Simone Raul Mortellaro, Marco Ginolfi, Alessia Leo, Francesca Arnone, Pierluca Torcia, Pierpaolo Biondetti, Anna Maria Ierardi and Gianpaolo Carrafiello
J. Pers. Med. 2025, 15(12), 569; https://doi.org/10.3390/jpm15120569 - 28 Nov 2025
Viewed by 798
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Recent Innovations and Artificial Intelligence in Interventional Radiology: A Step Towards Personalized Medicine)
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