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With advancements in systemic therapy, the incidence of brain metastases (BMs) continues to rise, leading to severe neurological complications. Effective and precise treatment modalities are, therefore, critically important for managing BMs. Radiation therapy (RT), including photon therapy, has been essential in managing BMs. Recent technological advances have significantly enhanced the precision, efficacy, and safety of these treatments. This comprehensive review provides an in-depth examination of the latest advancements in radiation and photon therapy technologies for treating BMs, focusing on innovations such as stereotactic radiosurgery (SRS), whole-brain radiation therapy (WBRT), laser interstitial thermal therapy (LITT), and other radiation-related treatment modalities. Additionally, we discuss clinical outcomes, challenges, and future directions in this rapidly evolving field. While a detailed comparison of techniques is beyond the scope of this paper, this paper provides up-to-date technical information for physicians, medical physicists, patients, and researchers in related fields, potentially enhancing clinical outcomes. Among the treatment modalities, SRS has become a cornerstone of RT for BMs, with its implementation spanning multiple modalities over the past few decades. Given its inherent minimally invasive nature and growing clinical acceptance, SRS is positioned to further evolve as a key therapeutic tool in both neurosurgery and radiotherapy.

Patient-specific quality assurance (QA) for Volumetric Modulated Arc Therapy (VMAT) plans is routinely performed in the clinical. However, it is labor-intensive and time-consuming for medical physicists. QA prediction models can address these shortcomings and improve efficiency. Current approaches mainly focus on single cancer and single modality data. They are not applicable to clinical practice. To assess the accuracy of QA results for VMAT plans, this paper presents a new model that learns complementary features from the multi-modal data to predict the gamma passing rate (GPR). According to the characteristics of VMAT plans, a feature-data fusion approach is designed to fuse the features of imaging and non-imaging information in the model. In this study, 690 VMAT plans are collected encompassing more than ten diseases. The model can accurately predict the most VMAT plans at all three gamma criteria: 2%/2 mm, 3%/2 mm and 3%/3 mm. The mean absolute error between the predicted and measured GPR is 2.17%, 1.16% and 0.71%, respectively. The maximum deviation between the predicted and measured GPR is 3.46%, 4.6%, 8.56%, respectively. The proposed model is effective, and the features of the two modalities significantly influence QA results.

We have previously shown that pachymic acid (PA) inhibited tumorigenesis of gastric cancer (GC) cells. However, the exact mechanism underlying the radiation response of GC was still elusive. To evaluate the effects of PA treatment on radiation response of GC cell lines both in vitro and in vivo, a colony formation assay and xenograft mouse model were employed. Changes in Bax and HIF1$\alpha$ expressions were assessed in GC cells following PA treatment. Luciferase reporter and chromatin immune-precipitation assays were carried out to investigate the regulation of Bax through HIF1$\alpha$. Stable HIF1$\alpha$ knockdown was introduced into GC cells to further study the mechanism underlying PA-enhanced response to radiation both in vitro and in vivo. PA greatly enhanced the sensitivity of GC cells to radiation in vitro and in vivo, upregulated Bax expression and inhibited hypoxia. Bax expression was under hypoxia inhibition, and PA increased Bax expression through repressing HIF1$\alpha$. Stable HIF1$\alpha$ overexpression in GC cells abolished the sensitizing effect of PA on GC cells to radiation both in vitro and in vivo. PA functions as a radiation sensitizing compound in GC. PA treatment induces the expression of pro-apoptotic factor Bax by inhibiting hypoxia/HIF1$\alpha$, supporting the therapeutic potential of PA in radiation therapy against GC.

Hadrontherapy is today an established modality in cancer radiation therapy. Based on the superior ballistic and radiobiological properties of accelerated ions, this discipline experienced a remarkable growth in the last 20 years. This paper reviews the history of hadrontherapy, from the early days to the most recent developments. In particular, the evolution of proton and carbon ion therapy is presented together with a glance at future solutions such as single-room facilities.

This study proposes the use of the ScanNet real-time target moving monitoring method that allows the therapist to set up three primary color detection threshold values, the detection range, the automatic compensation of the distance of the device and the angle of the device. Moreover, the real-time images detected are used for reminding the patient to maintain the therapeutic posture. If the displacement exceeds the permitted range, an alert message will be sent out. Moreover, because the operation is simple, and the system requirements are not too demanding, ScanNet, in addition to its use in monitoring displacement during radiation therapy, can be applied to MRI and other treatments that require the patient to maintain a position for a long time or on patients receiving residential respiratory therapy.

For precise treatment purposes in hadron therapy, the beam has to be monitored in real time without being degraded. For the first time, silicon strip detectors have been fabricated over an area as large as 20.25 cm² with an ultra low thickness of 20 or 10 μm in order to reduce the material budget and hence the beam degradation provoked by the sensor. In this work, we describe the novel design and its fabrication process. Afterwards, we present the first electrical characterizations compared to the application requirements. The novel devices and their fabrication process are validated through measurements and simulations. A low strip-to-strip behavior variation is demonstrated as well as a very good interstrip insulation and a very low leakage current. These novel fabricated devices constitute a very promising technology for future hadron therapy beam monitoring.

The static leaf sequencing (SLS) problem arises in radiation therapy for cancer treatments, aiming to accomplish the delivery of a radiation prescription to a target tumor in the minimum amount of delivery time. Geometrically, the SLS problem can be formulated as a 3-D partition problem for which the 2-D problem of partitioning a polygonal domain (possibly with holes) into a minimum set of monotone polygons is a special case. In this paper, we present new geometric algorithms for a basic case of the 3-D SLS problem (which is also of clinical value) and for the general 3-D SLS problem. Our basic 3-D SLS algorithm, based on new geometric observations, produces guaranteed optimal quality solutions using O(1) Steiner points in polynomial time; the previously best known basic 3-D SLS algorithm gives optimal outputs only for the case without considering any Steiner points, and its time bound involves a multiplicative factor of a factorial function of the input. Our general 3-D SLS algorithm is based on our basic 3-D SLS algorithm and a polynomial time algorithm for partitioning a polygonal domain (possibly with holes) into a minimum set of x-monotone polygons, and has a fast running time. Experiments of our SLS algorithms and software in clinical settings have shown substantial improvements over the current most popular commercial treatment planning system and the most well-known SLS algorithm in medical literature. The radiotherapy plans produced by our software not only take significantly shorter delivery times, but also have a much better treatment quality. This proves the feasibility of our software and has led to its clinical applications at the Department of Radiation Oncology at the University of Maryland Medical Center. Some of our techniques and geometric procedures (e.g., for partitioning a polygonal domain into a minimum set of x-monotone polygons) are interesting in their own right.

The 3-D static leaf sequencing (SLS) problem arises in radiation therapy for cancer treatments, aiming to deliver a prescribed radiation dose to a target tumor accurately and efficiently. The treatment time and machine delivery error are two crucial factors to the solution (i.e., a treatment plan) for the SLS problem. In this paper, we prove that the 3-D SLS problem is NP-hard, and present the first ever algorithm for the 3-D SLS problem that can determine a tradeoff between the treatment time and machine delivery error (also called the "tongue-and-groove" error in medical literature). Our new 3-D SLS algorithm with error control gives the users (e.g., physicians) the option of specifying a machine delivery error bound, and subject to the given error bound, the algorithm computes a treatment plan with the minimum treatment time. We formulate the SLS problem with error control as computing a k-weight shortest path in a directed graph and build the graph by computing g-matchings and minimum cost flows. Further, we extend our 3-D SLS algorithm to all the popular radiotherapy machine models with different constraints. In our extensions, we model the SLS problems for some of the radiotherapy systems as computing a minimum g-path cover of a directed acyclic graph. We implemented our new 3-D SLS algorithm suite and conducted an extensive comparison study with commercial planning systems and well-known algorithms in medical literature. Some of our experimental results based on real medical data are presented.

Benitec MOU with Biomics Biotechnologies China.

Arkema & Aussie Chemeq Sign Manufacturing Cooperation Agreement.

AstraZeneca and Mental Health Research Institute in Australia Announce Collaboration to Improve Early Detection of Alzheimer's Disease.

Avexa Gets CSIRO Investment.

Living Cell Technologies' Encapsulated Choroid Plexus Cells May Be Used To Treat Hearing Loss.

Sundia MediTech Acquires Protein Folding Technology.

Beijing Cancer Hospital Introduces Fast and Precise RapidArc Radiotherapy Cancer Treatments.

Zydus Cadila and Karo Bio's Research Collaboration has Generated Promising Lead Compounds.

ICON Acquires Veeda Laboratories Limited.

Novavax-Cadila to Conduct Swine Flu Clinical Trials.

Axygen & Astellas form JV to Develop Protein Drugs.

Rexahn, KRICT to Develop Anti-Cancer Drugs.

Japan's Largest Pharmaceutical Firm Opens Regional HQ in Singapore.

Experts at World Congress of Internal Medicines Reinforce Importance of BETADINE^® in Disease Prevention, Infection Control and Oral Mucositis Treatment.

First Dengue Vaccination Program in the Americas Starts in Paraná State of Brazil.

Agilent Technologies Array CGH Platform Assures Quality of Cancer Cell Lines Used in Biomedical Research.

ARTES and Burnet Institute Join Forces to Develop Novel Hepatitis C Vaccine.

Cardiac Imaging Reveals the Association Between Increased Prevalence of Coronary Issues Among Men with HIV and Higher Indications of Cardiac Inflammation.

NCCS Awards Contract for Proton Beam Therapy System to Hitachi Asia Ltd.

Hitachi is Selected by National Cancer Centre Singapore for Southeast Asia’s First Proton Beam Therapy System.

FEI Introduces New Talos S/TEM for Life and Materials Sciences.

Systematic Review of 58 Publications of Real-World Use of GARDASIL^® Presented at AOGIN Congress.

It is important to deliver radiation to treatment targets with accuracy. Typically, patients are positioned using marks on the surface of the skin. However, without imaging procedures, there is no information about the location of mobile internal organs and targets. The use of implanted radiopaque markers can help localize internal target organs using imaging modalities. Quality assurance procedures have been performed on commercially available spiral gold markers to determine their location and image quality. The results obtained from different, least essential imaging modalities employed in radiation therapy showed that these markers are not as clearly visible on radiographs as compared to the modalities with electronic output formats. The image quality was also poorer on megavoltage as compared to kilovoltage X-ray imaging modalities.

Automatically delineating Organs-at-Risks (OARs) on computed tomography (CT) has the benefit of both reducing the time and improving the quality of radiotherapy (RT) planning. A 3D convolutional deep learning framework for multi-organs segmentation is proposed in this work; moreover, for the small volume OARs, a robust 3D squeeze-and-excitation (SE) feature extraction mechanism and a new Dice loss function are incorporated in the traditional 3D U-Net. We collected 60 thorax CT images set with annotations and expanded to 260 patients by the augmented method of randomly rotating $\pm$6 degrees with a 1/3 probability and adding Gaussian noise. The objective is to segment five important organs: esophagus, spinal cord, heart, and bilateral lungs. Compared with 3D U-Net, 3D-2D U-Net proposed in our work increases the Dice similarity coefficient by 5% on average for the heart and bilateral lungs, and 3D Small Volume U-Net can further increase the Dice similarity coefficient to above 80% for the spinal cord. The experiment results demonstrate that the proposed model can improve the delineation accuracy of OARs from CT images.

Background and Purpose: In spite of major advances in cancer treatment, the prognosis of patients with oesophageal carcinoma remains poor. Squamous cell carcinoma and adenocarcinoma account for 95% of all oesophageal tumors, although other histological subtypes are occasionally seen. We aimed to evaluate whether Photofrin II can enhance the effect of ionizing radiation on oesophageal cancer in an in vitro tumor model. Material and Methods: A human oesophageal squamous cancer cell line (OE-21) and a human oesophageal adenocarcinoma cell line (OE-33) were evaluated with and without incubation with Photofrin II. Cells were irradiated using doses ranging from 0 to 8 Gy. The response rate of the cells to irradiation was evaluated by a tetrazolium-based colorimetric assay, similar to the MTT test, with the aim to determine the efficiency of Photofrin II as a radiation sensitizer in comparison to irradiation alone. Results: The OE-21 cell line demonstrated a significantly reduced cellular survival rate, when irradiated in the presence of Photofrin, as compared to a control group irradiated in the absence of Photofrin II. For the OE-33 cell line, no significant differences were found between the group treated with Photofrin II and the control group. Conclusion: Our results demonstrate in an in vitro model that Photofrin II may act as a radio-sensitizer in squamous cell oesophageal cancer, but not in oesophageal adenocarcinoma.

Computational radiation biophysics is a rapidly growing area that is contributing, alongside new hardware technologies, to ongoing developments in cancer imaging and therapy. Recent advances in theoretical and computational modeling have enabled the simulation of discrete, event-by-event interactions of very low energy (≪ 100 eV) electrons with water in its liquid thermodynamic phase. This represents a significant advance in our ability to investigate the initial stages of radiation induced biological damage at the molecular level. Such studies are important for the development of novel cancer treatment strategies, an example of which is given by microbeam radiation therapy (MRT). Here, new results are shown demonstrating that when excitations and ionizations are resolved down to nano-scales, their distribution extends well outside the primary microbeam path, into regions that are not directly irradiated. This suggests that radiation dose alone is insufficient to fully quantify biological damage. These results also suggest that the radiation cross-fire may be an important clue to understanding the different observed responses of healthy cells and tumor cells to MRT.

Radiation therapy (RT) is a treatment option for head and neck cancer (HNC), but 2% of RT patients may experience damage to the jawbone, resulting in osteoradionecrosis (ORN). The ORN can manifest years after RT exposure. Changes in the local microchemical bone quality prior to the clinical manifestation of ORN could play a key role in ORN pathogenesis. Chemical bone quality can be analyzed using Fourier transform infrared spectroscopy (FTIR), that is applied to examine the effects of cancer, chemotherapy, and RT on the quality of human mandibular bone. Cortical mandibular bone samples were harvested from dental implant beds of 23 individuals, i.e., patients with surgically and radiotherapeutically treated HNC (RT-HNC, $n=7$), surgically and radiochemotherapeutically treated HNC (CH-RT-HNC, $n=3$), only surgically treated HNC (SRG-HNC, $n=4$), and healthy controls ($n=9$). Infrared spectra were acquired from two representative regions of interest in cortical mandibular bone. Spectral parameters, i.e., mineral-to-matrix ratio (MM), carbonate-to-matrix ratio (CM), carbonate-to-phosphate ratio (CP), collagen maturity (cross-linking), crystallinity, acid phosphate substitution (APS), and advanced glycation end products (AGEs), were analyzed for each sample. Amide I region of the CH-RT-HNC group differed from the control group in cluster analysis ($p=0.02$). Apart from a minor variation trend in collagen maturity ($p=0.07$), there were no other significant differences between the groups. Thus, the effect of radiochemotherapy on mandibular bone composition should be further investigated. In future trials, this study design is potential when the effects of the cancer burden and different HNC treatment modalities on jawbone composition are studied, in order to reveal ORN pathogenesis.

There is a clear basis in physics for the clinical use of proton and carbon beams in radiation therapy, namely, the finite range of the particle beam. The range is dependent on the beam initial energy, density and atomic composition of tissues along the beam path. Beams can be designed that penetrate to the required depth and deliver a uniform biologically effective dose across the depth of interest. The yield is a superior dose distribution relative to photon beams. There is a potential clinical advantage from the high linear energy transfer (LET) characteristics of carbon beams. This is based on a lower oxygen enhancement ratio (OER) and a flatter age response function. However, due to uncertainties relating OER with relative biological effectiveness (RBE), there is no clinical evidence to date that carbon ion beams have an advantage over proton beams. We strongly support performance Phase III clinical trials of protons vs carbon ion beams designed to feature a single variable, LET. Dose fractionation would be identical in both arms and dose distribution would be similar for the sites to be tested. For sites for which the carbon beam has a demonstrated important advantage in comparative treatment planning due to the narrower penumbra would not be selected for the clinical trials.

Particle therapy is the expanding radiotherapy treatment option of choice for cancer. Its cost, however, is currently hindering its worldwide expansion. Also, the ideal application of particle therapy is restricted by a series of unsolved technical challenges. Both the cost and technical limitations are directly traceable to dependence on legacy accelerators and their associated treatment possibilities. This chapter is written to address these needs. Firstly, a technical overview is presented of photon and particle therapy for cancer tumours. Secondly, the underlying limitations of the existing legacy systems are identified, especially those related to accelerators, and suggestions are made for current and future developments to address these shortcomings. The legacy systems referred to here are of the slow scanning variety using large, circular accelerators.

This paper also attempts to make a scientific comparison of the various types of accelerators currently used or being developed for particle therapy.

The following procedure is pursued to perform a comparison between various types of accelerators:

• ⁽¹⁾The parameters which are pertinent to particle therapy accelerators (‘specified parameters’) are identified from clinical efficiency and overall cost considerations.
• ⁽²⁾The range and values of ‘specified parameters’ associated with each type of particle therapy accelerator are identified.
• ⁽³⁾A comparison is made on the best match between the various types of accelerators for each of the ‘specified parameters,’ i.e., the best in class accelerator, when compared to each criterion.
• ⁽⁴⁾Based on this match, an overall conclusion is made on the type of accelerator which best fits the needs for particle therapy.

Generally, radiation oncology applies evaluation and prediction in medical imaging and diagnosis, specifically for contouring organs, which results in the production of the clinical target volume (CTV) that corresponds to disease risk and organ exclusion. Medical physicists contour organs and combine computed tomography (CT) scans to digital imaging and communications in medicine (DICOM) radiation therapy (RT) to assist physicians for diagnosing tumors and calculating the dosages in treatments including radiation and chemotherapy. Thus, to generate RT images with high accuracy, this paper proposes a new Generator Adversarial Network (GAN) for RT images called radiation therapy GAN (RTGAN). We combine multiple loss functions with synthetic similarity DICOM-RT images and compare the results with Pinnacle, a radiation oncology treatment planning system. Further, we evaluate the method to get a score of 0.984 in structured similarity (SSIM) and 31.26 in peak signal-to-noise ratio (PSNR) and find that it costs 0.058 s to finish contouring one CT image. The proposed method is applied and tested in the department of radiation oncology at the Chung Shan Medical University Hospital, and the results are similar to the ground truth images. Thus, it not only effectively reduces the false-positive rate but also makes a breakthrough in medicine.

Radiation therapy (RT) is associated with acute and late effects of normal tissues. Acute effects are often expressed during or immediately after RT and are transient, while late effects may be expressed months to years after completion of treatment and are often irreversible and may be progressive. In addition, radiation effects may clinically appear as other conditions, not related to the cancer or its treatment.

This chapter describes the RT effects associated with commonly treated malignancies, the differential diagnosis and methods to treat or limit the adverse sequelae of radiation treatment.

Although progress of radiation therapy in recent years is rapid, medical accidents like the irradiation of over and under dose occur frequently in Japan. To eradicate these accidents and to increase accuracy of radiation therapy, we are developing an implantable real time micro dosimeter system. CdTe semiconductor is used as an ideal detector. And the doses of radiation are monitored by measuring the magnetic field converted from the current. We investigated the relationship between dose rate and current value from CdTe semiconductor(4mm×4mm×0.5mm). The data showed that 70 to 90 nA of electric current is proportionally generated from the CdTe semiconductor when it is irradiated by a LINAC under an air condition by the dose rate of 1 ~ 6Gy/min. In addition, the proportion of irradiated dose and the current was confirmed under a subaqueous condition(15cm in depth). To investigate the influence of a magnetic field on a human body, we calculated the tolerance frequency for human body using FEM simulation method. The data showed that the sending and receiving of data as a frequency of magnetic field should be set 100MHz or less. We are now miniaturizing the dosimeter circuit up to the size of inserted level by a fine needle.