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Recent Developments of Radiotherapy in Oncology
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Recent Developments of Radiotherapy in Oncology

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: closed (30 August 2025) | Viewed by 624

Special Issue Editors

Prof. Dr. Rosario Mazzola

E-Mail
Guest Editor
Advanced Radiation Oncology Department, Cancer Care Center, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy
Interests: radiation oncology; stereotactic radiosurgery; head and neck neoplasms; gynecologic oncology; lung cancer; breast cancer
Dr. Priscilla Guglielmo

E-Mail Website
Guest Editor
Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy
Interests: PET; nuclear medicine; neuroendocrine tumors; molecular imaging; PET/CT; PET/MRI
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radiotherapy continues to be a cornerstone in the treatment of various cancers, with ongoing innovations enhancing its precision and efficacy. This Special Issue, entitled "Recent Developments of Radiotherapy in Oncology”, aims to explore the latest advancements that are transforming the landscape of cancer treatment.

We invite submissions of original research and reviews that highlight novel techniques in radiotherapy. Key topics include advancements in image-guided radiotherapy, adaptive radiotherapy, and the integration of artificial intelligence to optimize treatment planning and delivery.

This Special Issue seeks to collate a comprehensive collection of research that not only elucidates recent technical and clinical advancements but also envisions future directions in the field. By doing so, we aim to enhance clinical practice and improve outcomes for oncology patients.

Prof. Dr. Rosario Mazzola
Dr. Priscilla Guglielmo
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 100 words) can be sent to the Editorial Office for announcement on this website.

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 Clinical Medicine is an international peer-reviewed open access semimonthly 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

  • radiotherapy
  • image-guided radiotherapy
  • adaptive radiotherapy
  • treatment planning
  • radiation oncology
  • immunotherapy synergy

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

Published Papers (1 paper)

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34 pages, 2393 KB  
Perspective
Voxel-Based Dose–Toxicity Modeling for Predicting Post-Radiotherapy Toxicity: A Critical Perspective
by Tanuj Puri
J. Clin. Med. 2025, 14(20), 7248; https://doi.org/10.3390/jcm14207248 - 14 Oct 2025
Viewed by 372
Abstract
This perspective paper critically examines the emerging role of voxel-based analysis (VBA), also referred to as image-based data mining (IBDM), in dose–toxicity modeling for post-radiotherapy toxicity assessment. These techniques offer promising insights into localized organ subregions associated with toxicity, yet their current application [...] Read more.
This perspective paper critically examines the emerging role of voxel-based analysis (VBA), also referred to as image-based data mining (IBDM), in dose–toxicity modeling for post-radiotherapy toxicity assessment. These techniques offer promising insights into localized organ subregions associated with toxicity, yet their current application faces substantial methodological and validation challenges. Based on prior studies and practical experience, we highlight seven key limitations: (i) lack of clinical validation for dose–toxicity models, (ii) strong dependence of results on statistical method selection (parametric vs. nonparametric), (iii) insensitivity of commonly used tests to uniform dose scaling, (iv) influence of tail selection (one- vs. two-tailed tests) on statistical power, (v) frequent misapplication of permutation testing, (vi) reliance on dose as the sole predictor while neglecting patient-, treatment-, and genomic-level covariates, and (vii) misinterpretation of voxel-wise associations as causal in the absence of appropriate causal inference frameworks. Collectively, these limitations can obscure clinically relevant dose differences, inflate false-positive or false-negative findings, obscure effect direction, introduce confounded associations, and ultimately yield inconsistent identification of high-risk subregions in organs at risk and poor reproducibility across studies. Notably, current univariable VBA/IBDM approaches should be regarded as hypothesis-generating rather than clinical decision-making tools, as unvalidated findings risk premature translation into clinical practice. Advancing personalized radiotherapy requires rigorous outcome validation, integration of multivariable and causal modeling strategies, and incorporation of clinical and genomic data. By moving beyond dose-only predictor models, VBA/IBDM can achieve greater biological relevance, reliability, and clinical utility, supporting more precise and individualized radiotherapy strategies. Full article
(This article belongs to the Special Issue Recent Developments of Radiotherapy in Oncology)
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