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New Vistas in Radiotherapy

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 (30 April 2023) | Viewed by 6065

Special Issue Editors


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Guest Editor
Department of Medical Physics & Biomedical Engineering, Faculty of Engineering Science, University College London, London, UK
Interests: radiation dosimetry; radiation detectors; radiotherapy treatment planning; radiotherapy technological developments
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department Dept of Medical Physics & Biomedical Engineering, Faculty of Engineering Science, University College London, London, UK
Interests: radiation dosimetry; radiation detectors; radiotherapy treatment planning; radiotherapy technological developments; biological image guided adaptive radiotherapy treatments; clinical trials

Special Issue Information

Dear Colleagues,

More than half of cancer patients receive radiotherapy as part of their treatment and ongoing developments in the field have ensured that radiotherapy remains a key treatment option. Technological developments have seen the implementation of image guided, high precision treatments such as stereotactic radiosurgery (SRS) and stereotactic ablative radiotherapy (SABR) employing high dose, low fraction treatment regimens. The number of proton and carbon beam therapy facilities continues to rise globally and developments in molecular radiotherapy and brachytherapy have also been seen. Advances in artificial intelligence and machine learning are leading to the automation of various stages of the radiotherapy process. Synergistic approaches using biological and immunotherapy agents are also being developed. These approaches have been supported by developments in preclinical investigations in small animal imaging and irradiation (SARP). Tissue engineering is also advancing as a promising biometric approach, producing 3D models that capture structural, biophysical, biochemical and biomechanical features of the tumour microenvironment to enable treatment response studies. Together with these developments challenges remain in both introducing truly personalized radiotherapy to expanding access to radiotherapy globally. The aim of this special issue is to provide an up to date overview of developments in all stages of the radiotherapy patient’s pathway, from pre-clinical studies through to treatment planning and treatment delivery.

Prof. Dr. Andrew Nisbet
Dr. Spyros Manolopoulos
Guest Editors

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Keywords

  • proton and ion beam therapy
  • stereotactic radiotherapy
  • image-guided radiotherapy
  • automation in radiotherapy
  • brachytherapy
  • molecular radiotherapy
  • adaptive radiotherapy
  • personalised radiotherapy
  • biological and immunotherapy agents
  • preclinical radiotherapy studies

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Published Papers (2 papers)

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Research

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19 pages, 1695 KiB  
Article
Buildup Factor Computation and Percentage Depth Dose Simulation of Tissue Mimicking Materials for an External Photon Beam (0.15–15 MeV)
by Omrane Kadri and Abdulrahman Alfuraih
Appl. Sci. 2022, 12(9), 4250; https://doi.org/10.3390/app12094250 - 22 Apr 2022
Cited by 1 | Viewed by 1815
Abstract
Nowadays, the use of tissue mimicking material (TMM) is widespread in both diagnostic and therapeutic medicine, as well as for quality assurance and control. For example, patient exposure evaluation during therapeutic tests has been commonly measured using TMMs. However, only a few materials [...] Read more.
Nowadays, the use of tissue mimicking material (TMM) is widespread in both diagnostic and therapeutic medicine, as well as for quality assurance and control. For example, patient exposure evaluation during therapeutic tests has been commonly measured using TMMs. However, only a few materials have been developed for research use at the megavoltage photon energy encountered in medical radiology. In this paper, we extended our previous work to cover the photon energy range of 0.15–15 MeV for five human tissues (adipose, cortical bone, fat, lung and muscle). As a selection criterion for TMM, other than the attenuation coefficient, we introduced the computation of the buildup factor (BUF) for a given couple of energy and depth based on the geometric progression fitting method. Hence, we developed a C++ program able to compute BUF for depths up to 40 mean free path. Moreover, we simulated the percentage depth dose (PDD) of a 6 MV photon beam through each tissue and their equivalent materials using the Geant4 Monte Carlo toolkit (version 10.5). After the comparison of a set of parameters (mass attenuation and mass energy absorption coefficients, BUF, equivalent and effective atomic numbers, electron density, superficial and maximal dose and dose at 10 and 20 cm depths), we found that SB3 (a mixture of epoxy and calcium carbonate) and MS15 (a mixture of epoxy, phenol, polyethylene and aluminum oxide) accurately imitate cortical bone and muscle tissues, respectively. AP6 (a mixture of epoxy, phenol, polyethylene and teflon), glycerol trioleate and LN1 (a mixture of polyurethane and aluminum oxide) are also suitable TMMs for adipose, fat and lung tissues, respectively. Therefore, this work can be useful to physician researchers in dosimetry and radiological diagnosis. Full article
(This article belongs to the Special Issue New Vistas in Radiotherapy)
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Review

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17 pages, 2945 KiB  
Review
Is Diffusion Tensor Imaging-Guided Radiotherapy the New State-of-the-Art? A Review of the Current Literature and Technical Insights
by Jordan Colman, Laura Mancini, Spyros Manolopoulos, Meetakshi Gupta, Michael Kosmin and Sotirios Bisdas
Appl. Sci. 2022, 12(2), 816; https://doi.org/10.3390/app12020816 - 13 Jan 2022
Cited by 3 | Viewed by 2948
Abstract
Despite the increasing precision of radiotherapy delivery, it is still frequently associated with neurological complications. This is in part due to damage to eloquent white matter (WM) tracts, which is made more likely by the fact they cannot be visualised on standard structural [...] Read more.
Despite the increasing precision of radiotherapy delivery, it is still frequently associated with neurological complications. This is in part due to damage to eloquent white matter (WM) tracts, which is made more likely by the fact they cannot be visualised on standard structural imaging. WM is additionally more vulnerable than grey matter to radiation damage. Primary brain malignancies also are known to spread along the WM. Diffusion tensor imaging (DTI) is the only in vivo method of delineating WM tracts. DTI is an imaging technique that models the direction of diffusion and therefore can infer the orientation of WM fibres. This review article evaluates the current evidence for using DTI to guide intracranial radiotherapy and whether it constitutes a new state-of-the-art technique. We provide a basic overview of DTI and its known applications in radiotherapy, which include using tractography to reduce the radiation dose to eloquent WM tracts and using DTI to detect or predict tumoural spread. We evaluate the evidence for DTI-guided radiotherapy in gliomas, metastatic disease, and benign conditions, finding that the strongest evidence is for its use in arteriovenous malformations. However, the evidence is weak in other conditions due to a lack of case-controlled trials. Full article
(This article belongs to the Special Issue New Vistas in Radiotherapy)
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