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Advances in Radiation Therapy for Tumor Treatment

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (10 January 2024) | Viewed by 2633

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Special Issue Editors

Dr. Matteo Pepa

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Guest Editor

Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), 27100 Pavia, Italy
Interests: radiation oncology; particle beam therapy; bioengineering

Dr. Stefania Volpe

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Guest Editor

1. Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
2. Division of Radiation Oncology, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
Interests: radiation oncology; head and neck radiotherapy; quantitative imaging
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Special Issue Information

Dear Colleagues,

We are inviting submissions to the Special Issue on Advances in Radiation Therapy for Tumor Treatment, which aims to cover all of the latest outstanding developments in radiation oncology.

Radiotherapy has a central role in the multidisciplinary field of oncology, being indicated in approximately half of cancer patients, possibly in synergistic combination with other treatment modalities. Technological advances in imaging and treatment planning and delivery have led to more accurate treatments, reduced treatment times, improved oncological outcomes, and reduced toxicity. A deeper understanding of tumour biology has fostered the personalization of treatments and a more accurate selection of patients. The advent of artificial intelligence and the availability of a large amount of data hold promise for the optimization of the whole radiotherapy workflow and refinement of the response assessment.

Even though most patients receive photon therapy, the number of particle therapy facilities is increasing worldwide. Overall, advances in radiation oncology have enabled highly personalized and precise treatments, with a positive impact on tumour outcomes and patients’ quality of life. Despite legitimate enthusiasm for the unquestionable advances in the field, there are still open challenges that need to be addressed cancer community to make treatments even more effective and safe and to remove barriers to access to care.

For this Special Issue, we invite submissions exploring cutting-edge research and recent advances in the field of radiation oncology. Both theoretical and experimental studies are welcome for submission, as are comprehensive reviews and survey papers.

Potential topics include, but are not limited to:

Applications of artificial intelligence and big data in radiation oncology
Advanced segmentation approaches
Advanced image processing and analysis
Novel imaging biomarkers for personalized treatments
Innovative models for the prediction of radiotherapy toxicity outcomes
Modern imaging for precision radiotherapy
Offline/online motion management and tumour tracking
Recent developments in image guidance
Adaptive radiotherapy
Advances in particle therapy
Advances in radiotherapy planning and delivery
The interplay of radiotherapy with surgery and systemic treatments
Novel approaches for the optimization of the patient care flow
Advanced strategies for patient empowerment

Dr. Matteo Pepa
Dr. Stefania Volpe
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. Applied Sciences 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 2400 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
particle therapy
medical imaging
imaging biomarkers
artificial intelligence
big data
image guidance
motion management
tumour tracking
treatment planning
personalized treatments

Published Papers (3 papers)

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Research

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15 pages, 6163 KiB

Open AccessArticle

Setup Optimization in Ocular Proton Therapy at the National Centre for Oncological Hadrontherapy: Comparison of Two Approaches to Refine the Position of an Eye-Tracking Device

by Giulia Sellaro, Andrea Pella, Matteo Pepa, Federica Galante, Mario Ciocca, Maria Rosaria Fiore, Agnieszka Chalaszczyk, Chiara Paganelli, Marco Rotondi, Alessandro Vai, Ester Orlandi and Guido Baroni

Appl. Sci. 2024, 14(4), 1537; https://doi.org/10.3390/app14041537 - 14 Feb 2024

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Abstract

This study describes a method for setup optimization in patient simulation for ocular proton therapy (OPT) at the National Center for Oncological Hadrontherapy (CNAO) in Pavia, Italy, with the aim of minimizing the occupancy time of clinical areas and streamlining the actual procedure. Setup repeatability is ensured by patient-specific immobilization tools and relies on the patient’s ability to maintain a stable gaze direction according to the treatment plan. This is facilitated by aligning a light source (LED) on a patient-specific base along the prescribed gaze direction. At CNAO, a dedicated Eye-Tracking System (ETS) was designed to provide the patient with a visible source of light aligned to the desired gaze direction. The ETS position is defined prior to treatment planning, relying on optical-tracking guidance and comparing the position of passive markers fixed on the ETS chassis with patient-specific models prepared offline in accordance with the desired geometry. OPT at CNAO started in 2016 and may be considered as a consolidated clinical routine. However, all the preparation phases, including patient-specific ETS models and setup, still require long sessions in clinical areas such as the computed tomography (CT) and the treatment rooms, with a non-negligible impact on other activities. This study describes a novel approach for patient-specific definition of the ETS position and orientation, aiming at minimizing the time required for preparatory activities inside clinical areas. To minimize the occurrence of biases and to reproduce as much as possible a real end-to-end approach, we included in the analysis data of patients that received OPT in our facility. The study was performed in parallel, carrying out the alignment with the standard method currently used in the clinical workflow of CNAO and with the proposed method. Results are presented as 3D residuals and gaze deviations, comparing ETS alignment based on the new approach with respect to the clinical standard method. The preliminary results of this study are evidence of the capability of the procedure to align the ETS position, allowing performing of the procedure in a non-clinical dedicated room. Full article

(This article belongs to the Special Issue Advances in Radiation Therapy for Tumor Treatment)

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10 pages, 2278 KiB

Open AccessArticle

Tumor Volume Distributions Based on Weibull Distributions of Maximum Tumor Diameters

by Uwe Schneider, Stephan Radonic and Jürgen Besserer

Appl. Sci. 2023, 13(19), 10925; https://doi.org/10.3390/app131910925 - 2 Oct 2023

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Abstract

(1) Background: The distribution of tumor volumes is important for various aspects of cancer research. Unfortunately, tumor volume is rarely documented in tumor registries; usually only maximum tumor diameter is. This paper presents a method to derive tumor volume distributions from tumor diameter distributions. (2) Methods: The hypothesis is made that tumor maximum diameters d are Weibull distributed, and tumor volume is proportional to d^k, where k is a parameter from the Weibull distribution of d. The assumption is tested by using a test dataset of 176 segmented tumor volumes and comparing the k obtained by fitting the Weibull distribution of d and from a direct fit of the volumes. Finally, tumor volume distributions are calculated from the maximum diameters of the SEER database for breast, NSCLC and liver. (3) Results: For the test dataset, the k values obtained from the two separate methods were found to be k = 2.14 ± 0.36 (from Weibull distribution of d) and 2.21 ± 0.25 (from tumor volume). The tumor diameter data from the SEER database were fitted to a Weibull distribution, and the resulting parameters were used to calculate the corresponding exponential tumor volume distributions with an average volume obtained from the diameter fit. (4) Conclusions: The agreement of the fitted k using independent data supports the presented methodology to obtain tumor volume distributions. The method can be used to obtain tumor volume distributions when only maximum tumor diameters are available. Full article

(This article belongs to the Special Issue Advances in Radiation Therapy for Tumor Treatment)

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Review

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15 pages, 1138 KiB

Open AccessReview

Radiomic Analysis for Human Papillomavirus Assessment in Oropharyngeal Carcinoma: Lessons and Pitfalls for the Next Future

by Ilaria Morelli, Carlotta Becherini, Marco Banini, Marianna Valzano, Niccolò Bertini, Mauro Loi, Giulio Francolini, Icro Meattini, Viola Salvestrini, Pierluigi Bonomo, Lorenzo Livi and Isacco Desideri

Appl. Sci. 2023, 13(23), 12942; https://doi.org/10.3390/app132312942 - 4 Dec 2023

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Abstract

Background: Oropharyngeal Squamous Cell Carcinoma (OPSCC) is rapidly increasing due to the spread of Human Papillomavirus (HPV) infection. HPV-positive disease has unique characteristics, with better response to treatment and consequent better prognosis. HPV status is routinely assessed via p16 immunohistochemistry or HPV DNA Polymerase Chain Reaction. Radiomics is a quantitative approach to medical imaging which can overcome limitations due to its subjective interpretation and correlation with clinical data. The aim of this narrative review is to evaluate the impact of radiomic features on assessing HPV status in OPSCC patients. Methods: A narrative review was performed by synthesizing literature results from PUBMED. In the search strategy, Medical Subject Headings (MeSH) terms were used. Retrospective mono- or multicentric works assessing the correlation between radiomic features and HPV status prediction in OPSCC were included. Selected papers were in English and included studies on humans. The range of publication date was July 2015–April 2023. Results: Our research returned 23 published papers; the accuracy of radiomic models was evaluated by ROC curves and AUC values. MRI- and CT-based radiomic models proved of comparable efficacy. Also, metabolic imaging showed crucial importance in the determination of HPV status, albeit with lower AUC values. Conclusions: Radiomic features from conventional imaging can play a complementary role in the assessment of HPV status in OPSCC. Both primary tumor- and nodal-related features and multisequencing-based models demonstrated higher accuracy. Full article

(This article belongs to the Special Issue Advances in Radiation Therapy for Tumor Treatment)

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