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Highlights • Artificial intelligence is profoundly changing professions, applications and research. • Emerging AI methods may enable more comprehensive optimisation, dosimetry and QA. • Challenges in data utilisation involve access, privacy, labeling and validation. • Technological transform has also potential impact on our multidisciplinary role. • Our professional role and education should keep up with the development of AI methods. Abstract Big data and deep learning will profoundly change various areas of professions and research in the future. This will also happen in medicine and medical imaging in particular. As medical physicists, we should pursue beyond the concept of technical quality to extend our methodology and competence towards measuring and optimising the diagnostic value in terms of how it is connected to care outcome. Functional implementation of such methodology requires data processing utilities starting from data collection and management and culminating in the data analysis methods. Data quality control and validation are prerequisites for the deep learning application in order to provide reliable further analysis, classification, interpretation, probabilistic and predictive modelling from the vast heterogeneous big data. Challenges in practical data analytics relate to both horizontal and longitudinal analysis aspects. Quantitative aspects of data validation, quality control, physically meaningful measures, parameter connections and system modelling for the future artificial intelligence (AI) methods are positioned firmly in the field of Medical Physics profession. It is our interest to ensure that our professional education, continuous training and competence will follow this significant global development. [ABSTRACT FROM AUTHOR]

• Shielding use in radiology has been re-evaluated. • Major European bodies involved in imaging radiation safety have issued consensus based recommendations. • This paper represents multidisciplinary based recommendations for shielding use. • In the majority of cases patient contact shielding use is not recommended. Patient contact shielding has been in use for many years in radiology departments in order to reduce the effects and risks of ionising radiation on certain organs. New technologies in projection imaging and CT scanning such as digital receptors and automatic exposure control (AEC) systems have reduced doses and improved image consistency. These changes and a greater understanding of both the benefits and the risks from the use of shielding have led to a review of shielding use in radiology. A number of professional bodies have already issued guidance in this regard. This paper represents the current consensus view of the main bodies involved in radiation safety and imaging in Europe: European Federation of Organisations for Medical Physics, European Federation of Radiographer Societies, European Society of Radiology, European Society of Paediatric Radiology, EuroSafe Imaging, European Radiation Dosimetry Group (EURADOS), and European Academy of DentoMaxilloFacial Radiology (EADMFR). It is based on the expert recommendations of the Gonad and Patient Shielding (GAPS) Group formed with the purpose of developing consensus in this area. The recommendations are intended to be clear and easy to use. They are intended as guidance, and they are developed using a multidisciplinary team approach. It is recognised that regulations, custom and practice vary widely on the use of patient shielding in Europe and it is hoped that these recommendations will inform a change management program that will benefit patients and staff. [ABSTRACT FROM AUTHOR]

• Value of imaging physics rests on combined physics expertise and care responsibility. • Imaging physics should assure that each single patient gets an optimum imaging exam. • Physics should assure consistent safety, quality, and quantitation across practice. • Value- and evidence-based imaging require design and management of quality measures. • Physics should include task optimization, outcome measures, and principle-informed AI. Inspired by the principles of Medical Physics 3.0, this paper frames a new model of clinical physics practice, anchored to clinical realities, clinical priorities, and advanced physics. The model is based on the conviction that the physicist is vested with the expertise and the responsibility to ensure each patient gets the optimum imaging exam towards the best clinical outcome. Key expectations and activities are encapsulated into 12 areas: scientific perspective, quality and safety assurance, regulatory compliance, technology assessment, use optimization, performance monitoring, technology acquisition, technology commissioning, vendor cooperation, translational practice, research consultancy, and technology education. The paper further highlights key challenges to effective clinical physics practice of increased scope of competency, balancing rigor and relevance, managing metrological surrogates of quality and safety, and integrating principle- and data-informed approaches. Mindful to practically mitigate these challenges, clinical imaging physics can play an essential role to enable evidence-based imaging care. [ABSTRACT FROM AUTHOR]

• A shortage of investment may compromise society's ability to manage radiation risks. • ICRP announced a call for action to strengthen expertise in radiological protection. • In this paper, the authors expressed their support to the ICRP's call for action. The International Commission on Radiological Protection (ICRP), recently expressed concern that "a shortage of investment in training, education, research, and infrastructure seen in many sectors and countries may compromise society's ability to properly manage radiation risks" and in 2022 announced the "Vancouver call for action to strengthen expertise in radiological protection worldwide". As representatives of organisations in formal relations with ICRP, we decided to promote this position paper to declare and emphasise that strengthening the expertise in radiological protection is a collective priority for all of us. [ABSTRACT FROM AUTHOR]

• Peer-reviewed papers published in the years 2015–2019 by AIFM members were surveyed. • A total of 1210 papers, mostly in the field of Radiation Oncology (48%) were found. • The most represented journal was Physica Medica , with 15% of papers. • This survey constitutes a basis to promote future AIFM scientific activities. • This survey will be useful for comparison with other countries, first within Europe. Within the Italian Association of Medical Physics and Health Physics (AIFM) working group "FutuRuS" we carried out a survey regarding the number of the peer-reviewed articles by AIFM members. We surveyed papers published in the years 2015–2019. Data extracted from Scopus included information regarding authors, title, journal, impact factor (IF), leading or standard authorship by AIFM members, keywords, type of collaboration (monocentric/multicentric/international), area of interest [radiation oncology (RO), radiology (RAD), nuclear medicine (NM), radioprotection (RP) and professional issue (PI)] and topics. We found 1210 papers published in peer-reviewed journals: 48%, 22%, 16%, 6%, 2 and 6% in RO, RAD, NM, RP, PI and other topics, respectively. Forty-seven percent of the papers involved monocentric teams, 31% multicentric and 22% international collaborations. Leading authorship of AIFM members was in 56% of papers, with a corresponding IF equal to 52% of the total IF (3342, IF mean = 2.8, IF max = 35.4). The most represented journal was Physica Medica , with 15% of papers, while a relevant fraction of IF (54%) appeared in clinically oriented journals. The number of papers increased significantly between 2015 and 2016 and remained almost constant in 2017–2019. This survey led to the first quantitative assessment of the number and theme distribution of peer-reviewed scientific articles contributed by AIFM members. It constitutes a ground basis to support future AIFM strategies and promote working groups on scientific activity of medical physicists, and to build the basis for rational comparison with other countries, first of all within Europe. [ABSTRACT FROM AUTHOR]

• Realistic dose enhancement of gold nanoparticles for X-rays with secondary particle equilibrium. • Novel approach to estimate uncertainty of correction for lack of secondary particle equilibrium. • Set of consistency checks allowed identifying and correcting normalization problems. • Good agreement of dose enhancement ratios for extended field within uncertainty of correction. • DERs deviate from unity only within the first few 100 nm and maximum values are below 20. Results of a Monte Carlo code intercomparison exercise for simulations of the dose enhancement from a gold nanoparticle (GNP) irradiated by X-rays have been recently reported. To highlight potential differences between codes, the dose enhancement ratios (DERs) were shown for the narrow-beam geometry used in the simulations, which leads to values significantly higher than unity over distances in the order of several tens of micrometers from the GNP surface. As it has come to our attention that the figures in our paper have given rise to misinterpretation as showing 'the' DERs of GNPs under diagnostic X-ray irradiation, this article presents estimates of the DERs that would have been obtained with realistic radiation field extensions and presence of secondary particle equilibrium (SPE). These DER values are much smaller than those for a narrow-beam irradiation shown in our paper, and significant dose enhancement is only found within a few hundred nanometers around the GNP. The approach used to obtain these estimates required the development of a methodology to identify and, where possible, correct results from simulations whose implementation deviated from the initial exercise definition. Based on this methodology, literature on Monte Carlo simulated DERs has been critically assessed. [ABSTRACT FROM AUTHOR]

• A systematic search for papers on applications of AI to medical imaging in Italy was performed. • 168 research papers were selected 65% using machine learning, 35% deep learning. • A rapid increase of interest in AI was observed in the last years. • Further collaborations, initiatives and guidelines are needed to develop the research on AI on Imaging. To perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results. A Pubmed search was conducted using terms Artificial Intelligence, Machine Learning, Deep learning, imaging, and Italy as affiliation, excluding reviews and papers outside time interval 2015–2020. In a second phase, participants of the working group AI4MP on Artificial Intelligence of the Italian Association of Physics in Medicine (AIFM) searched for papers on AI in imaging. The Pubmed search produced 794 results. 168 studies were selected, of which 122 were from Pubmed search and 46 from the working group. The most used imaging modality was MRI (44%) followed by CT(12%) ad radiography/mammography (11%). The most common clinical indication were neurological diseases (29%) and diagnosis of cancer (25%). Classification was the most common task for AI (57%) followed by segmentation (16%). 65% of studies used machine learning and 35% used deep learning. We observed a rapid increase of research in Italy on artificial intelligence in the last 5 years, peaking at 155% from 2018 to 2019. We are witnessing an unprecedented interest in AI applied to imaging in Italy, in a diversity of fields and imaging techniques. Further initiatives are needed to build common frameworks and databases, collaborations among different types of institutions, and guidelines for research on AI. [ABSTRACT FROM AUTHOR]

• Deep learning (DL) has the potential to enhance processing and interpretation of MRI. • This review gives an overview of the use of DL in MRI for neuro-oncology. • DL applications can improve MRI technological innovation, diagnosis and follow-up. Magnetic Resonance Imaging (MRI) provides an essential contribution in the screening, detection, diagnosis, staging, treatment and follow-up in patients with a neurological neoplasm. Deep learning (DL), a subdomain of artificial intelligence has the potential to enhance the characterization, processing and interpretation of MRI images. The aim of this review paper is to give an overview of the current state-of-art usage of DL in MRI for neuro-oncology. We reviewed the Pubmed database by applying a specific search strategy including the combination of MRI, DL, neuro-oncology and its corresponding search terminologies, by focussing on Medical Subject Headings (Mesh) or title/abstract appearance. The original research papers were classified based on its application, into three categories: technological innovation, diagnosis and follow-up. Forty-one publications were eligible for review, all were published after the year 2016. The majority (N = 22) was assigned to technological innovation, twelve had a focus on diagnosis and seven were related to patient follow-up. Applications ranged from improving the acquisition, synthetic CT generation, auto-segmentation, tumor classification, outcome prediction and response assessment. The majority of publications made use of standard (T1w, cT1w, T2w and FLAIR imaging), with only a few exceptions using more advanced MRI technologies. The majority of studies used a variation on convolution neural network (CNN) architectures. Deep learning in MRI for neuro-oncology is a novel field of research; it has potential in a broad range of applications. Remaining challenges include the accessibility of large imaging datasets, the applicability across institutes/vendors and the validation and implementation of these technologies in clinical practise. [ABSTRACT FROM AUTHOR]

• We present an ultrafast, microfocus, laser driven X-ray source. • The source runs in air using an ultrafast laser with moderate energy and a high repetition rate. • The X-ray source uses a target system to refresh the material and keep the focus to achieve stability. • The source size is small (10 μ m x 12 μ m) and we use it for high resolution radiography. • Using different materials the X-ray spectrum can be changed to fit the application. Hard X-ray radiation with high brightness and high fluxes is nowadays available on the fourth generation of synchrotrons and X-FELs, but the large size and complexity of these sources makes its use difficult for widespread applications. New table top X-ray sources driven by ultrashort high power lasers offer a compelling route to expand the availability of hard X-ray sources. They can be used for advanced imaging techniques, due to its small source size and spatial coherence. We present in this paper the validation of a compact laser-driven X-ray microfocus source for high-resolution radiography imaging. This novel device was built at the Laser Laboratory for Acceleration and Applications (L2A2) at the University of Santiago de Compostela. This paper describes the laser-plasma X-ray source with improved stability and characterize some of its properties. We demonstrate the high-contrast and resolution of the images obtained with this source by using masks with well known geometries, and detailed analysis by using the modulation transfer function. Finally, we discuss the properties of this source in comparison to other compact microfocus X-ray sources. [ABSTRACT FROM AUTHOR]

• Computational anthropomorphic breast models based on mathematical formulations. • Computational breast models based on patient medical images. • Physical 3D anthropomorphic breast phantoms. • 3D printing technology for fabrication of anthropomorphic breast models. Anthropomorphic breast phantoms are both, computational and physical, anatomically and radiologically realistic models of the human female breast, and are considered an excellent tool for development, comparing, characterizing and optimizing of novel and existing breast screening and diagnostic modalities. Their role in the objective assessment of diagnostic task performance of breast imaging systems without conducting high cost and time-consuming clinical trials, as well as in developing and optimizing clinical protocols and image reconstruction algorithms is tangible increasing. The aim of this paper is to present a historical journey from the advent of the breast anthropomorphic models used with x-ray modalities, their further development and realistic improvement, to current achievements. Anthropomorphic breast models are both computational and physical. Computational phantoms are mainly based on mathematical formulations and patient medical images. The mathematical breast models consist of mathematical description of the breast structures, while the patient-based are created from segmented clinical datasets acquired by dedicated breast Computed Tomography. The later approach guarantees a very high degree of realism. Molding techniques, 3D printing and low cost paper-based approaches are the main methods for creation of physical breast anthropomorphic models. Among them, 3D printing technologies provide an excellent opportunity to create realistic models of the breast by using a number of printing materials with x-ray characteristics similar to these of breast tissues. The anatomical and radiological realism of the anthropomorphic breast phantoms together with the possibility for unlimited exposure during important diagnostic tasks is transforming them into a key instrument of every Radiology Department. [ABSTRACT FROM AUTHOR]

• The ICRP system is mature, integrated, self-consistent and reduced staff dose limits by a factor of 30–50 over the years. • The International Congress of Radiology influence on the culture and governance of ICRP is profound and still lives on. • ICRP recommendations strongly support protection of workers and the public, with less emphasis on patients. • The ICRP approach to recommendations on medical exposures is often hands-off, e.g. with justification or pregnancy. • The social sciences and humanities have been notably absent from the commission membership and its programme of work. Starting from Röntgen's discovery and the first radiograph of his wife's hand, the curtain was raised on a new technique with remarkable possibilities for contributing to human health. While growth in applications proceeded rapidly, it was accompanied by significant harms to those involved and by inappropriate opportunistic application. This paper places the attempts to deal with the harms and inappropriate activities side by side with the positive developments. It attempts a narrative on the development of medical radiation protection over the 125-year period and places it in the context of a commentary on governance and ethics. The substance of the narrative is based on the recommendations of ICRP as they developed and altered over time. The governance commentary is based on assessing the independence of ICRP and its attention to medical exposures. In terms of ethics, the recommendations at each stage are reviewed in the light of values that are deemed appropriate to both medical ethics and radiation protection. The paper, while celebrating Röntgen-125, also hopefully provides a perspective for discussion as ICRP's centenary in 2028 approaches. This is an important part of ensuring continued acceptance and confident use of X-Rays, and helps underwrite the possibility of further developments in the area. [ABSTRACT FROM AUTHOR]

• HR transversal images were used for the reconstruction of missing pixels in the superior-inferior direction. • Multiple Gaussian process regression model was developed to enhance superior-inferior resolution of lung 4D-CT. • Experimental results showed the remarkable performance of the proposed method. Four-dimensional computed tomography (4D-CT) plays a useful role in many clinical situations. However, due to the hardware limitation of system, dense sampling along superior–inferior direction is often not practical. In this paper, we develop a novel multiple Gaussian process regression model to enhance the superior-inferior resolution for lung 4D-CT based on transversal structures. The proposed strategy is based on the observation that high resolution transversal images can recover missing pixels in the superior-inferior direction. Based on this observation and motived by random forest algorithm, we employ multiple Gaussian process regression model learned from transversal images to improve superior–inferior resolution. Specifically, we first randomly sample 3 × 3 patches from original transversal images. The central pixel of these patches and the eight-neighbour pixels of their corresponding degraded versions form the label and input of training data, respectively. Multiple Gaussian process regression model is then built on the basis of multiple training subsets obtained by random sampling. Finally, the central pixel of the patch is estimated based on the proposed model, with the eight-neighbour pixels of each 3 × 3 patch from interpolated superior-inferior direction images as inputs. The performance of our method is extensively evaluated using simulated and publicly available datasets. Our experiments show the remarkable performance of the proposed method. In this paper, we propose a new approach to improve the 4D-CT resolution, which does not require any external data and hardware support, and can produce clear coronal/sagittal images for easy viewing. [ABSTRACT FROM AUTHOR]

• Machine learning has been integrated to PET in attenuation correction (AC) and low-count reconstruction in recent years. • The proposed methods, study designs and key results of the current published studies are reviewed in this paper. • Machine learning generates synthetic CT from MR or non-AC PET for PET AC, or directly maps non-AC PET to AC PET. • Deep learning-based methods have advantages over conventional machine learning methods in low-count PET reconstruction. The rapid expansion of machine learning is offering a new wave of opportunities for nuclear medicine. This paper reviews applications of machine learning for the study of attenuation correction (AC) and low-count image reconstruction in quantitative positron emission tomography (PET). Specifically, we present the developments of machine learning methodology, ranging from random forest and dictionary learning to the latest convolutional neural network-based architectures. For application in PET attenuation correction, two general strategies are reviewed: 1) generating synthetic CT from MR or non-AC PET for the purposes of PET AC, and 2) direct conversion from non-AC PET to AC PET. For low-count PET reconstruction, recent deep learning-based studies and the potential advantages over conventional machine learning-based methods are presented and discussed. In each application, the proposed methods, study designs and performance of published studies are listed and compared with a brief discussion. Finally, the overall contributions and remaining challenges are summarized. [ABSTRACT FROM AUTHOR]

• Blended Learning framework implemented into a postgraduate Medical Physics course. • Framework included the Virtual Radiotherapy Environment (VERT). • Greater emphasis on real world medical physics learning experiences. • Short high-quality online videos of clinical medical physics procedures were used. • Students understanding of effective learning strategies found to need improvement. As a specialist field of study, medical physicists require a broad range of knowledge and skills to operate competently in their workplace. In Australia, these competencies are accredited by the Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM). Education and training for medical physicists therefore consists of an exhaustive range of knowledge areas. This is made even more challenging due to the extremely diverse backgrounds of students in these specialist courses of study. These factors frequently lead to a disengagement by students with learning activities. To address some of these challenges, the Radiotherapy Physics unit in a Masters level Medical Physics course of study was re-designed to increase active learning that included scaffolded in-class and online tasks and supported by virtual reality simulations. These re-design initiatives were informed by a diverse team including academic and clinical medical physicists as well as education experts. A survey, conducted over two consecutive years was used to gain students perceptions about the re-design. The questions were designed to see if the students felt engaged with the various learning activities. Analysis of the survey data indicates that there was an overall improvement in students' engagement with the learning activities and the learning content. The paper further discusses nuanced understanding about the ways in which students engaged with the various learning activities including online, in-class, practicals and industry attachments. The paper discusses the appropriately informed learning activities that can be used to improve student engagement for highly specialised, content heavy areas of study. [ABSTRACT FROM AUTHOR]

• MC simulations were performed based on DICOM data of PAD procedures. • Digital Variance Angiography (DVA) enabled low-dose and DSA protocols were compared. • The DVA group (53 ppl.) had 82.6 man × mSv, the DSA (54 ppl.) group had 194.7 man × mSv. • DSA vs. DVA organ cancer risk reduction: LAR incidence: 25%–75%; mortality: 51%–84%. • DVA can serve as a useful tool to optimise patients' exposure in angiography. By modelling patient exposures of interventional procedures, this study compares the reduction of radiation detriment between Digital Variance Angiography (DVA) and Digital Subtraction Angiography (DSA). The paper presents a retrospective risk assessment using an in-house developed tool on 107 patient exposures from a clinical trial of DVA used to diagnose peripheral arterial disease (PAD). DICOM exposure parameters were used to initiate the PENELOPE (PENetration and Energy LOss of Positrons and Electrons) Monte Carlo simulation, radiation quality and quantity, and irradiation geometry. The effective dose and the lifetime attributable risk (LAR) for cancer incidence and mortality are calculated based on the International Commission on Radiation Protection's (ICRP) 103 recommendations and the Committee on the Biological Effects of Ionising Radiations' latest (BEIR VII) report, respectively. The study found that procedures conducted using DVA significantly reduce the radiation exposure of patients, compared to DSA. The collective effective dose for the DVA group was 58% lower than that for the DSA group. Correspondingly, the LAR of different organs showed a substantial decrease for cancer incidence (25–75%) and mortality (51–84%). DVA demonstrates a considerable reduction in physical dosimetric quantities and consequently effective dose and cancer risk, suggesting its potential as a safer alternative to DSA in interventional radiology. The use of DVA supports the optimisation of patient radiation protection and aligns with the principles of ALARA (as low as reasonably achievable). [ABSTRACT FROM AUTHOR]

• Medical physics/physics in medicine in Ireland has a rich heritage dating back to Robert Boyle. • The work of early contributors is striking and continues to be relevant. • This historical perspective helps to understand the present state of medical physics services in Ireland. • Medical physics in Ireland has matured over the last generation. Medical physics and other contributions from physics to medicine are relatively well known, if not well documented in Ireland. Less well known are contributions from medicine to the development of physics, which can and do occur. This paper addresses examples of all three. The methods employed include documentary research and interviews with those who share(d) the stage in the area. Documentary evidence for historical aspects of medical physics over the last century are relatively sparse and incomplete. Notwithstanding this, they can and do enable a picture to be built up of how the arrangements in place now have come about, particularly when they are accompanied by mature recollections of the participants. Good critically assessed and accessible sources have been identified covering the seventeenth to nineteenth century material presented. Examples are presented based on the work of significant contributors, each with strong Irish connections, including Robert Boyle, Erwin Schrödinger, Fearghus O'Foghludha, and Edith Stoney the first female medical physicist. Their contributions are striking and continue to be relevant now. The findings provide a rich context and heritage for medical physics in Ireland and in the international community. They will include the contemporary period in a second paper, Part 2 of this study. [ABSTRACT FROM AUTHOR]

• Despite advances in knowledge, tumour hypoxia remains a challenge in radiotherapy. • Several hypoxia-targeting methods exists, all with their advantages and drawbacks. • In silico models are complementary tools offering novel solutions to manage hypoxia. • The paper reviews the current landscape of hypoxia models and response to therapy. • Future models must consider connected vascular networks to simulate agent delivery. The negative impact of tumour hypoxia on cancer treatment outcome has been long-known, yet there has been little success combating it. This paper investigates the potential role of in silico modelling to help test emerging hypoxia-targeting treatments in cancer therapy. A Medline search was undertaken on the current landscape of in silico models that simulate cancer therapy and evaluate their ability to test hypoxia-targeting treatments. Techniques and treatments to combat tumour hypoxia and their current challenges are also presented. Hypoxia-targeting treatments include tumour reoxygenation, hypoxic cell radiosensitization with nitroimidazoles, hypoxia-activated prodrugs and molecular targeting. Their main challenges are toxicity and not achieving adequate delivery to hypoxic regions of the tumour. There is promising research toward combining two or more of these techniques. Different types of in silico therapy models have been developed ranging from temporal to spatial and from stochastic to deterministic models. Numerous models have compared the effectiveness of different radiotherapy fractionation schedules for controlling hypoxic tumours. Similarly, models could help identify and optimize new treatments for overcoming hypoxia that utilize novel hypoxia-targeting technology. Current therapy models should attempt to incorporate more sophisticated modelling of tumour angiogenesis/vasculature and vessel perfusion in order to become more useful for testing hypoxia-targeting treatments, which typically rely upon the tumour vasculature for delivery of additional oxygen, (pro)drugs and nanoparticles. [ABSTRACT FROM AUTHOR]

• The free-electrons-fraction is the fraction of the electrons generated that are collected without attachment. • The method proposed is based only from measure of charge collected varying the voltage applied. • The method proposed can be use in the commissioning phase of a dedicated to the Flash radiotherapy Linac. The free electron fraction is the fraction of electrons, produced inside the cavity of an ionization chamber after irradiation, which does not bind to gas molecules and thereby reaches the electrode as free electrons. It is a fundamental quantity to describe the recombination processes of an ionization chamber, as it generates a gap of positive charges compared to negative ones, which certainly will not undergo recombination. The free electron fraction depends on the specific chamber geometry, the polarizing applied voltage and the gas thermodynamic properties. Therefore, it is necessary to evaluate such fraction in an accurate and easy way for any measurement condition. In this paper, a simple and direct method for evaluating the free electron fraction of ionization chambers is proposed. We first model the capture process of the electrons produced inside an ionization chamber after the beam pulse; then we present a method to evaluate the free electron fraction based on simple measurements of collected charge, by varying the applied voltage. Finally, the results obtained using an Advanced Markus chamber irradiated with a Flash Radiotherapy dedicated research Linac (ElectronFlash) to estimate the free electron fraction are presented. The proposed method allows the use of a conventional ionization chamber for measurements in ultra-high-dose- per -pulse (UHDP) conditions, up to values of dose- per -pulse at which the perturbation of the electric field due to the generated charge can be considered negligible. [ABSTRACT FROM AUTHOR]

• Gamma ray emission with all the series at equilibrium is much higher than that due to 225Ac only. • Shielding cannot be evaluated according to a simple mono-exponential model. • Accurate fitting parameters are provided, allowing to easily interpolate transmission factors. 225Ac is the most promising alpha emitter for radiopharmaceutical therapy. Labeling PSMA, it showed to be effective in the treatment of prostate cancer and research is undergoing in order to improve its production capacity. Currently, there are still few data published concerning operational radiation protection in its use, both in clinics and in radiopharmacy, and even some basic data are not readily available. This papers aims to estimate the emission gamma-ray constant of 225Ac when at equilibrium with its descendants, and the transmission factors for a broad beam of the gamma-rays emitted by 225Ac and its descendants. Monte Carlo simulations were performed using FLUKA 4.2, considering firstly the source in air, in absence of any shielding, and secondly by adding an increasing thicknesses of Lead, Concrete or Tungsten. In order to obtain statistically meaningful results, high-statistics simulations were performed by sampling up to 1010 primary decay events. As the shielding thickness increased, an appropriate variance reduction technique (importance biasing) was applied. The specific gamma ray emission constant for 225Ac at equilibrium with descendants resulted (3.26 ± 0.03) × 10-5 mSv/h per 1 MBq at a distance of 100 cm. The transmission factors are presented in detail and data have been appropriately interpolated and fitting parameters are reported. The attenuation curves show a clear bi-exponential trend: performing shielding calculations by adopting a simple approach based on a single value of Half Value Layer (HVL) or Tenth Value Layer (TVL) cannot provide adequate results. In conclusion, our results may be useful in the design of shielded hot cells or accessories necessary for operational radiation protection. [ABSTRACT FROM AUTHOR]

• The algorithm developed was applied prospectively in patients to check its validity. • The present study was divided into ex vivo and in vivo experiments. • Non-invasive characterization of calcium renal stones is quite useful in selecting suitable treatment modality. • This study introduces the concept of DECT based characterization of materials using effective atomic number (Z eff) and electron density(ρ e) Non-invasive DECT based characterization of renal stones using their effective atomic number (Z eff) and the electron density (ρe) in patients. This paper aims to develop a method for in-vivo characterization of renal stone. Differentiation of renal stones in-vivo especially sub types of calcium stones have very important advantage for better judgement of treatment modality. 50 extracted renal stones were scanned ex-vivo using dual energy CT scanner. A method was developed to characterize these renal stones using effective atomic number and electron density obtained from dual energy CT data. The method and formulation developed in ex-vivo experiments was applied in in-vivo study of 50 randomly selected patients of renal stones who underwent dual energy CT scan. The developed method was able to characterize Calcium Oxalate Monohydrate (COM) and the combination of COM and Calcium Oxalate Dihydrate (COD) stones non-invasively in patients with a sensitivity of 81% and 83%respectively. The method was also capable of differentiating Uric, Cystine and mixed stones with the sensitivity of 100, 100 and 85.71% respectively. The developed dual energy CT based method was capable of differentiating sub types of calcium stones which is not differentiable on single energy or dual energy CT images. [ABSTRACT FROM AUTHOR]

• Impact of the initial energy on the proximity function. • Impact of the cut-off energy on the proximity function. • Impact of the Monte Carlo codes on the proximity function. • Differences between TS and TS codes, TS and CH codes with the same cut-off energy. The proximity function is an important index in microdosimetry for describing the spatial distribution of energy, which is closely related to the biological effects of organs or tissues in the target area. In this work, the impact of parameters, such as physic models, cut-off energy, and initial energy, on the proximity function are quantitated and compared. According to the track structure (TS) and condensed history (CH) low-energy electromagnetic models, this paper chooses a variety of Monte Carlo (Monte Carlo, MC) codes (Geant4-DNA, PHITS, and Penelope) to simulate the track structure of low-energy electrons in liquid water and evaluates the influence of the electron initial energy, cut-off energy, energy spectrum, and physical model factors on the differential proximity function. The results show that the initial energy of electrons in the low-energy part (especially less than 1 keV) has a greater impact on the differential proximity function, and the choice of cut-off energy has a greater impact on the differential proximity function corresponding to small radius sites (generally less than 10 nm). The difference in the electronic energy spectrum has little effect on the result, and the proximity functions of different physics models show better consistency under large radius sites. This work comprehensively compares the differential proximity functions under different codes by setting a variety of simulation conditions and has basic guiding significance for helping users simulate and analyze the deposition characteristics of microscale electrons according to the selection of an appropriate methodology and cut-off energy. [ABSTRACT FROM AUTHOR]

• The work by Raptis et al. shows an advantage of proton therapy for breast cancer with respect to second cancer induction. • The reported values are lower than those reported in other publications for both photon and proton treatments. • The authors found that motion and radiobiological uncertainties did not change the advantage of protons over photons. • Treatment for breast cancer patients should consider second cancer risk together with other complication probabilities. The paper by Raptis et al. concludes that proton therapy has an advantage over photon therapy with respect to the induction of a second cancer. Furthermore, the authors conclude that physiological movements and radiobiological parameters do not affect the general trend of lower risk associated with proton therapy. The work is based on a modeling framework which is different from most previously used models on the same subject. This invited commentary puts the findings of the paper in context with other published modeling studies on second cancer risk after proton and photon radiation therapy for breast cancer. [ABSTRACT FROM AUTHOR]

Highlights • Modeling intraoperative electron therapy (IOERT) machine by using Monte Carlo. • A surgical simulation and navigation of IOERT operation was simulated. • Feasibility to move from manual dosimetry of IOERT to 3D dosimetry was presented. Abstract Purpose This paper studies the feasibility of using Monte Carlo (MC) for treatment planning of intraoperative electron radiation therapy (IOERT) procedure to get 3D dose by using patient's CT images. Methods The IOERT treatment planning was performed using the following successive steps: I) The Mobetron 1000® machine was modelled with the EGSnrc MC codes. II) The MC model was validated with measurements of percentage depth doses and profiles for three energies (12, 9, 6) MeV. III) CT images were imported as DICOM files. IV) Contouring of the planning target volume (PTV) and the organs at risk was done by the radiation oncologist. V) The medical physicist with the radiation oncologist, had chosen the same parameters of IOERT procedures like energy, applicator (type, size) and using or not bolus. VI) Finally, dose calculation and analysis of 3D maps was carried out. Results The tuning process of the MC model provides good results, as the maximum value of the root mean square deviation (RMSD) was less than 3% between the MC simulated PDDs and the measured PDDs. The contouring and dose analysis review were easy to conduct for the classical treatment planning system. The radiation oncologist had many tools for dose analysis such as DVH and color wash for all the slides. Summation of the 3D dose of IOERT with other radiotherapy plans is possible and helpful for total dose estimation. Archiving and documentation is as good as treatment planning system (TPS). Conclusions The method displayed in this paper provides a step forward for IOERT Dosimetry and allows to obtain accurate dosimetry of treated volumes. [ABSTRACT FROM AUTHOR]

Highlights • The paper focuses on the dosimetry in nuclear medicine. • The personal dose equivalent H p (0.07) in workers handling 99mTc isotopes was analysed. • Correction coefficients for fingertips when using a wrist dosimeter was developed. • A wrist dosimeter can be used to measure the values of H p (0.07) for fingertips. Abstract Purpose Individual dosimetry is undoubtedly one of the best methods of assessing the exposure of personnel to ionizing radiation, however in case of nuclear medicine, the method applied to measure the dose does not always present a picture of the worker's actual exposure. The highly non-homogeneous dose distribution on the hand means that the ring dosimeter, routinely used to measure the H p (0.07), provides only approximate dose values received by fingertips, the body part most exposed to ionizing radiation. This paper is an attempt to answer the question whether the wrist dosimeter used as a replacement for the ring dosimeter is able to provide information on doses for the most exposed fragments of the hand of an employee during handling procedures with the use of radiopharmaceuticals. Materials Throughout measurements performed in five nuclear medicine facilities, high-sensitivity thermoluminescent detectors were used. Results Correction coefficients have been determined, which constitute an amendment to be made to move from the dose recorded by the wrist dosimeter to the doses received by the most exposed hand fragments. The fingertips received on average 25 times higher doses, compared to the values recorded by the wrist dosimeter. Conclusions A wrist dosimeter can be used to measure the H p (0.07) in nuclear medicine, including as a gauge of the most exposed parts of the hand – the fingertips. However, the applicability of correction coefficients makes it necessary to ensure a stable position of the wrist dosimeter during routine procedures. [ABSTRACT FROM AUTHOR]

Introduction The International Atomic Energy Agency (IAEA) organized the 3rd international conference on radiation protection (RP) of patients in December 2017. This paper presents the conclusions on the interventional procedures (IP) session. Material and methods The IAEA conference was conducted as a series of plenary sessions followed by various thematic sessions. “Radiation protection of patients and staff in interventional procedures” session keynote speakers presented information on: 1) Risk management of skin injuries, 2) Occupational radiation risks and 3) RP for paediatric patients. Then, a summary of the session-related papers was presented by a rapporteur, followed by an open question-and-answer discussion. Results Sixty-seven percent (67%) of papers came from Europe. Forty-four percent (44%) were patient studies, 44% were occupational and 12% were combined studies. Occupational studies were mostly on eye lens dosimetry. The rest were on scattered radiation measurements and dose tracking. The majority of patient studies related to patient exposure with only one study on paediatric patients. Automatic patient dose reporting is considered as a first step for dose optimization. Despite efforts, paediatric IP radiation dose data are still scarce. The keynote speakers outlined recent achievements but also challenges in the field. Forecasting technology, task-specific targeted education from educators familiar with the clinical situation, more accurate estimation of lens doses and improved identification of high-risk professional groups are some of the areas they focused on. Conclusions Manufacturers play an important role in making patients safer. Low dose technologies are still expensive and manufacturers should make these affordable in less resourced countries. Automatic patient dose reporting and real-time skin dose map are important for dose optimization. Clinical audit and better QA processes together with more studies on the impact of lens opacities in clinical practice and on paediatric patients are needed. [ABSTRACT FROM AUTHOR]

• Challenges: Data governance, algorithm robustness, stakeholder consensus and legal liability. • General Data Privacy Regulation has been published to ensure high quality of data governance. • Model transparency, robustness and fairness are important for AI development to increase trust. • WHO and FDA published ethical AI technology regulatory framework to ensure safety of the AI system. The idea of using artificial intelligence (AI) in medical practice has gained vast interest due to its potential to revolutionise healthcare systems. However, only some AI algorithms are utilised due to systems' uncertainties, besides the never-ending list of ethical and legal concerns. This paper intends to provide an overview of current AI challenges in medical imaging with an ultimate aim to foster better and effective communication among various stakeholders to encourage AI technology development. We identify four main challenges in implementing AI in medical imaging, supported with consequences and past events when these problems fail to mitigate. Among them is the creation of a robust AI algorithm that is fair, trustable and transparent. Another issue is on data governance, in which best practices in data sharing must be established to promote trust and protect the patients' privacy. Next, stakeholders, such as the government, technology companies and hospital management, should come to a consensus in creating trustworthy AI policies and regulatory frameworks, which is the fourth challenge, to support, encourage and spur innovation in digital AI healthcare technology. Lastly, we discussed the efforts of various organizations such as the World Health Organisation (WHO), American College of Radiology (ACR), European Society of Radiology (ESR) and Radiological Society of North America (RSNA), who are already actively pursuing ethical developments in AI. The efforts by various stakeholders will eventually overcome hurdles and the deployment of AI-driven healthcare applications in clinical practice will become a reality and hence lead to better healthcare services and outcomes. [ABSTRACT FROM AUTHOR]

• Steel Tenth Value Layer for photoneutrons produced in head components of high energy medical linear accelerators were obtained. • Neutron spectrum outside the barrier for different thicknesses of Steel were evaluated. • The shielding design for an existing bunker was evaluated. • Monte Carlo particle tracking method implementing special measures for precise tracking of thermal neutrons was used. To confirm the effectiveness of steel as a material for shielding photoneutrons produced in medical linear accelerators and report values for neutron first and second tenth value layer to be used as radiation protection quantities. Monte Carlo code Geant4 was used to simulate transport of photoneutrons through primary barriers containing layers of concrete and steel. The photoneutron spectrum generated in high energy modern accelerator head components was simulated and projected to barriers of different thicknesses of steel including a control case of no barrier. To derive the neutron tenth value layer (TVL n), absorbed dose was evaluated at 1 cm depth in a water phantom outside the barrier. The fluence and energy spectrum of neutrons leaking outside the barrier were also calculated. The neutron source model was used to quantitatively assess the neutron shielding for a newly designed bunker. For an 18 MV photon beam produced by a linear accelerator, the first and second TVL n , for steel as a neutron shielding material were determined to be 15.7–16.1 cm and 28.5–32.4 cm, respectively, depending on the vendor. The lateral distribution of neutrons outside steel barriers is investigated. Also, we show the relative efficiency of steel for fast and epithermal neutrons and determine the neutron energy spectrum outside a steel barrier. This paper agrees with previous studies for Pu-Be sources, and we would advocate using these values for the purposes of high energy linear accelerator bunker design. [ABSTRACT FROM AUTHOR]

• The arts inspire, challenge, delight, & help put a scientific life in perspective. • Eighteen works from 12 artists (Europe, North America, Japan) are discussed. • Includes historical perspectives, communicating science, and borders to science. • The arts are an unexpected ally in validating a life in science/medical physics. • Visual art refreshes & is accessible when approached with sensibility and openness. The visual arts are rooted in the life of the wider community and may lack explicit medical physics reference. Nevertheless, they can be influential and can illustrate, communicate, and inform. They may also inspire, challenge, heal, give pleasure, help put one's life in perspective and enrich the experience of being a practicing scientist working in medical physics. Eighteen works from 12 artists are presented. They are a convenience sample from the author's experience. Two (Irish), though less well known, speak powerfully to scientists. Two are of the eighteenth century. The remaining works are modern from Europe, North America and Japan. All inform and challenge our behaviour as medical physicists. Headings guiding the paper address: historical perspectives; similarities of method between science and the arts; the hand as special expressions of being human; communicating science; science and a sense of wonder; borders to science; and the importance of a quiet, still, reflective approach. The author's experience complements observations published by others. The artworks described delight and are an able ally in validating a life spent in science. They refresh it and are accessible to those willing to take a risk on the approach, with sensibility and an openness. The impact of art on science and medicine is also visible in under explored institutional art collections such as those housed at the IAEA in Vienna or WHO in Geneva. [ABSTRACT FROM AUTHOR]

• A novel algorithm for generating computer-simulated soft tissue breast lesions. • Computer-simulated breast lesions generated by using fractal Perlin noise. • Includes simulated lesions inserted in computational breast phantoms. • Simulated lesions evaluated and classified by observers according to BI-RADS. • A simulation method that provides almost real-time lesion generation. Steadily increasing use of computational/virtual phantoms in medical physics has motivated expanding development of new simulation methods and data representations for modelling human anatomy. This has emphasized the need for increased realism, user control, and availability. In breast cancer research, virtual phantoms have gained an important role in evaluating and optimizing imaging systems. For this paper, we have developed an algorithm to model breast abnormalities based on fractal Perlin noise. We demonstrate and characterize the extension of this approach to simulate breast lesions of various sizes, shapes, and complexity. Recently, we developed an algorithm for simulating the 3D arrangement of breast anatomy based on Perlin noise. In this paper, we have expanded the method to also model soft tissue breast lesions. We simulated lesions within the size range of clinically representative breast lesions (masses, 5–20 mm in size). Simulated lesions were blended into simulated breast tissue backgrounds and visualized as virtual digital mammography images. The lesions were evaluated by observers following the BI-RADS assessment criteria. Observers categorized the lesions as round, oval or irregular, with circumscribed, microlobulated, indistinct or obscured margins. The majority of the simulated lesions were considered by the observers to have a realism score of moderate to well. The simulation method provides almost real-time lesion generation (average time and standard deviation: 1.4 ± 1.0 s). We presented a novel algorithm for computer simulation of breast lesions using Perlin noise. The algorithm enables efficient simulation of lesions, with different sizes and appearances. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-modality medical imaging Head & Neck phantom for quality assurance, experimental testing and training. • Realistic vasculature and micro-vasculature hardware and software model for flow imaging and perfusion scanning. • Physiologically realistic pressure-flow dynamics. • Tissue equivalent structures. • Demonstration for MRI, X-ray CT, Doppler Ultrasound and Nuclear Medicine. The head and neck phantom discussed in an accompanying paper (part 1), is imaged with MRI, X-ray CT, PET and ultrasound. MRI scans show a distinct image contrast between the brain compartment and other anatomical regions of the head. The silicone matrix that was used to create a porous brain compartment has a relatively high proton density and a spin–spin relaxation time (T 2) that is long enough to provide an MRI signal. While the longitudinal magnetization was found to recover according to a mono-exponential, a bi-exponential decay was observed for the transverse relaxation with a slow T 2 relaxation component corresponding to the perfusate and a fast T 2 relaxation component corresponding to the silicone. The fraction of the slow T 2 relaxation component increases upon perfusion. A dynamic contrast enhanced (DCE) MRI experiment is conducted in which the injection rate of the contrast agent is varied. Parametric DCE maps are created and reveal regional differences in contrast agent kinetics as a result of differences in porosity. The skull, vertebra and the brain compartment are clearly visible on X-ray CT. Dynamic PET scanning has been performed while the carotic arterial input function is monitored by use of a Geiger-Müller counter. Similar regions of perfusion are found in the PET study as in the DCE MRI study. By doping the perfusate with a lipid micelle emulsion, the phantom is applicable for carotic Doppler ultrasound demonstration and validation. [ABSTRACT FROM AUTHOR]

• Geant4 low energy photon models were updated using EPICS2017 database. • Cross-sections, scattering functions and form factors were considered. • Important improvement has been made on the parameterizations. • The simulation results using updated models were found in good agreement with XCOM. This paper describes in detail the implementation of Geant4 Livermore electromagnetic physics models based on the EPICS2017 database for the low energy transport of photons. These models describe four photon processes: gamma conversion, Compton scattering, photoelectric effect and Rayleigh scattering. New parameterizations based on EPICS2017 were performed for scattering functions of Compton effect, subshell cross-sections of the photoelectric effect and form factors of Rayleigh scattering, in order to improve the precision of fitted values compared to tabulated values. Comparisons between new and old parameterizations were also carried out to evaluate the precision of the new parameterizations. The models were tested through a comparative study, in which the mass attenuation coefficient was calculated for both total photon interaction and each process using Geant4 simulations based on EPICS2017 and EPDL97 respectively. The results obtained from the simulations were found in good agreement with the XCOM reference data. [ABSTRACT FROM AUTHOR]

• Fundamental physics shows X-ray attenuation of gold nanoparticles to be size independent. • In designing X-ray contrast agents, the size of gold nanoparticles merit no consideration. • Only those data with HU differences of 100 and above deserve consideration. Purpose : Several investigations are being carried since the past decade to use gold nanoparticles' (AuNP) suspensions as contrast agents (CA) for imaging in Computed Tomography. For this, the optimal size of AuNP has received considerable attention, which is addressed here. Material and methods: In this theoretical study, effective attenuation coefficient for a single spherical shaped AuNP is first calculated from the first principles, as a function of the nanoparticle radius ' r ', with μ (E) being the attenuation coefficient of the material for a given energy E. This result is extended to derive a formula for the attenuation coefficient and mass attenuation coefficient of a suspension of AuNP. Results: It is seen that the effective mass attenuation coefficient of the nanoparticles is a decreasing function of α (E) = 2 μ (E) r and falls inversely with α (E), for large values of α(E) ≫ 1 , there being very little change for α ≤ 1. Conclusion: The paper shows that for nanoparticles, less than 100 nm in diameter the linear attenuation coefficient of the colloidal suspension has no dependence on the nanoparticles' size and depends only on the concentration of nanoparticle material present in the suspension. [ABSTRACT FROM AUTHOR]

Purpose In this paper, we propose a novel method for human body composition measurement, especially for the bone mineral density (BMD) measurement. The proposed method, using the absorption and differential phase information retrieved from X-ray grating-based interferometer (XGBI) to measure the BMD, has potential to replace dual-energy X-ray absorptiometry (DEXA), which is currently widely used for body composition measurement. Methods The DEXA method employs two absorption images acquired at two different X-ray spectra (high energy and low energy) to calculate the human body composition. In this paper, a new method to calculate BMD using a single X-ray measurement is proposed. XGBI is a relatively new X-ray technique that provides absorption, phase and scattering information simultaneously using a single X-ray spectrum. With the absorption and differential phase information retrieved from XGBI, BMD can be measured using only one single X-ray spectrum. Numerical simulations are performed with a body phantom of bone (Cortical, ICRU-44) surrounded by soft tissue (Soft, ICRU-44). BMD is calculated with both the DEXA method and the proposed method. Results Results show that BMD can be measured accurately with the proposed method; moreover, better signal-to-noise ratio (SNR) is obtained compared to DEXA. Conclusion With the proposed method, BMD can be measured with XGBI setup. Further, the proposed method can be realized using current X-ray phase-contrast imaging (XPCI) apparatus without any hardware modification, suggesting that this technique can be a promising supplementary function to current XPCI equipment. [ABSTRACT FROM AUTHOR]

This paper describes issues of concern for protecting foetuses and breast-fed children of occupationally exposed women in nuclear medicine from unnecessary exposure of ionising radiation. The protection principle is to ensure the same level of protection for the foetus and child as for the general public. Therefore international radiation protection standards recommend a dose constraint of 1 mSv to a foetus during the remaining time of pregnancy after it is known/declared and a yearly dose constraint of 1 mSv to a breast-fed child. It is not self-evident how to guarantee this level of radiation protection. The exposure situation in nuclear medicine is complex. Exploring existing reported occupational exposure levels suggests great variability between work tasks and facilities. The standards and guidelines found give no detailed advice. Therefore each facility needs to systematically review external and internal exposure levels in order to plan appropriate protection measures and issue their own guidelines and rules. One strategy might be that each facility defines tasks that do not require any restrictions and lists such duties that are not suitable to do when pregnant or breastfeeding, taking also potential exposure levels into consideration. This paper gives examples of such types of work. Information to the staff about the necessity of declaring pregnancy or breastfeeding is of fundamental importance. The internal policies issued by the hospital management should make clear the basis for taking care of pregnant and breastfeeding employees. [ABSTRACT FROM AUTHOR]

• Medical Physics educators contribute to the education of healthcare professions. • Updated mission and vision statements for the role. • Suggested best practices for teaching non-physics healthcare professionals. • Stepwise process for curriculum development. • Research based summary recommendations. Although Medical Physics educators have historically contributed to the education of the non-physics healthcare professions, their role was not studied in a systematic manner. In 2009, EFOMP set up a group to research the issue. In their first paper, the group carried out an extensive literature review regarding physics teaching for the non-physics healthcare professions. Their second paper reported the results of a pan-European survey of physics curricula delivered to the healthcare professions and a Strengths-Weaknesses-Opportunities-Threats (SWOT) audit of the role. The group's third paper presented a strategic development model for the role, based on the SWOT data. A comprehensive curriculum development model was subsequently published, whilst plans were laid to develop the present policy statement. This policy statement presents mission and vision statements for Medical Physicists teaching non-physics users of medical devices and physical agents, best practices for teaching non-physics healthcare professionals, a stepwise process for curriculum development (content, method of delivery and assessment), and summary recommendations based on the aforementioned research studies. [ABSTRACT FROM AUTHOR]

• Systematic literature review on patient's dose savings when using patient shielding. • Patient shielding can be safely abandoned. • Unsystematic use of patient shielding in Switzerland. Patient shielding during medical X-ray imaging has been increasingly criticized in the last years due to growing evidence that it often provides minimal benefit and may even compromise image quality. In Europe, and as also shown in a short assessment in Switzerland, the use of patient shielding is inhomogeneous. The aim of this study was to systematically review recent literature in order to assess benefits and appraise disadvantages related to the routine use of patient shielding. To evaluate benefits and disadvantages related to the application of patient shielding in radiological procedures, a systematic literature review was performed for CT, radiography, mammography and fluoroscopy-guided medical X-ray imaging. In addition, reports from medical physics societies and authorities of different countries were considered in the evaluation. The literature review revealed 479 papers and reports on the topic, from which 87 qualified for closer analysis. The review considered in- and out-of-plane patient shielding as well as shielding for pregnant and pediatric patients. Dose savings and other dose and non-dose related effects of patient shielding were considered in the evaluation. Although patient shielding has been used in radiological practice for many years, its use is no longer undisputed. The evaluation of the systematic literature review of recent studies and reports shows that dose savings are rather minimal while significant dose- and non-dose-related detrimental effects are present. Consequently, the routine usage of patient protection shielding in medical X-ray imaging can be safely discontinued for all modalities and patient groups. [ABSTRACT FROM AUTHOR]

• Benchmark comparison of Geant4 and MCNP6 in characterisation of fast neutron beam. • SOI Bridge microdosimeter measured experimentally and compared with the two codes. • Neutron capture products from p+ B-implanted regions of the Bridge was investigated. In this study, Monte Carlo codes, Geant4 and MCNP6, were used to characterize the fast neutron therapeutic beam produced at iThemba LABS in South Africa. Experimental and simulation results were compared using the latest generation of Silicon on Insulator (SOI) microdosimeters from the Centre for Medical Radiation Physics (CMRP). Geant4 and MCNP6 were able to successfully model the neutron gantry and simulate the expected neutron energy spectrum produced from the reaction by protons bombarding a 9Be target. The neutron beam was simulated in a water phantom and its characteristics recorded by the silicon microdosimeters; bare and covered by a 10B enriched boron carbide converter, at different positions. The microdosimetric quantities calculated using Geant4 and MCNP6 are in agreement with experimental measurements. The thermal neutron sensitivity and production of 10B capture products in the p+ boron-implanted dopant regions of the Bridge microdosimeter is investigated. The obtained results are useful for the future development of dedicated SOI microdosimeters for Boron Neutron Capture Therapy (BNCT). This paper provides a benchmark comparison of Geant4 and MCNP6 capabilities in the context of further applications of these codes for neutron microdosimetry. [ABSTRACT FROM AUTHOR]

[Display omitted] • The novelty of using polyethylene glycol-based hydrogel rectal spacer for laser therapy. • The novelty of coupling tumor's vascular network with thermal parameters. • The novelty of noticing thermal phase lags during laser radiation and cooling process. • The shape and area of necrotized region estimated by generalized dual phase lag model is close to the experiments. • By injection of 4 mm PEG spacer at 4 W laser power, maximum rectum temperature is reduced by 44% in 20 s of irradiation. Focal Laser ablation therapy is a technique that exposes the prostate tumor to hyperthermia ablation and eradicates cancerous cells. However, due to the excessive heating generated by laser irradiation, there is a possibility of damage to the adjacent healthy tissues. This paper through in silico study presents a novel approach to reduce collateral effects due to heating by the placement of polyethylene glycol (PEG) spacer between the rectum and tumor during laser irradiation. The PEG spacer thickness is optimized to reduce the undesired damage at common laser power used in the clinical trials. Our study also encompasses novelty by conducting the thermal analysis based on the porous structure of prostate tumor. The thermal parameters and two thermal phase lags between the temperature gradient and the heat flux, are determined by considering the vascular network of prostate tumor. The Nelder-Mead algorithm is applied to find the minimum thickness of the PEG spacer. In the absence of the spacer, the predicted results for the laser power of 4 W, 8 W, and 12 W show that the temperature of the rectum rises up to 58.6 °C, 80.4 °C, and 101.1 °C, while through the insertion of 2.59 mm, 4 mm, and 4.9 mm of the PEG spacer, it dramatically reduces below 42 °C. The results can be used as a guideline to ablate the prostate tumors while avoiding undesired damage to the rectal wall during laser irradiation, especially for the peripheral zone tumors. [ABSTRACT FROM AUTHOR]

• Propose an image processing pipeline to quantify spinal cord atrophy. • Performance of two CNNs was compared for segmentation of the SC cross-sectional area. • Our results showed a significant difference between SC atrophy of MS and NMOSD. • The pipeline can be used as an efficient computer-aided tool to help neurologists. Quantitative measurement of various anatomical regions of the brain and spinal cord (SC) in MRI images are used as unique biomarkers to consider progress and effects of demyelinating diseases of the central nervous system. This paper presents a fully-automated image processing pipeline which quantifies the SC volume of MRI images. In the proposed pipeline, after conducting some pre-processing tasks, a deep convolutional network is utilized to segment the spinal cord cross-sectional area (SCCSA) of each slice. After full segmentation, certain extra slices interpolate between each two adjacent slices using the shape-based interpolation method. Then, a 3D model of the SC is reconstructed, and, by counting the voxels of it, the SC volume is calculated. The performance of the proposed method for the SCCSA segmentation is evaluated on 140 MRI images. Subsequently, to demonstrate the application of the proposed pipeline, we study the differentiations of SC atrophy between 38 Multiple Sclerosis (MS) and 25 Neuromyelitis Optica Spectrum Disorder (NMOSD) patients. The experimental results of the SCCSA segmentation indicate that the proposed method, adapted by Mask R-CNN, presented the most satisfactory result with the average Dice coefficient of 0.96. For this method, statistical metrics including sensitivity, specificity, accuracy, and precision are 97.51%, 99.98%, 99.92%, and 98.04% respectively. Moreover, the t-test result (p-value = 0.00089) verified a significant difference between the SC atrophy of MS and NMOSD patients. The pipeline efficiently quantifies the SC volume of MRI images and can be utilized as an affordable computer-aided tool for diagnostic purposes. [ABSTRACT FROM AUTHOR]

• Review of deep learning approaches to generate synthetic-CTs for MRI-based dose calculation. • Overview and discussion of image and dose metrics for synthetic-CT evaluation. • Review of synthetic-CT image and dose accuracy per anatomical localization. In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the electron density of tissue necessary for dose calculation. Several methods of synthetic-CT (sCT) generation from MRI data have been developed for radiotherapy dose calculation. This work reviewed deep learning (DL) sCT generation methods and their associated image and dose evaluation, in the context of MRI-based dose calculation. We searched the PubMed and ScienceDirect electronic databases from January 2010 to March 2021. For each paper, several items were screened and compiled in figures and tables. This review included 57 studies. The DL methods were either generator-only based (45% of the reviewed studies), or generative adversarial network (GAN) architecture and its variants (55% of the reviewed studies). The brain and pelvis were the most commonly investigated anatomical localizations (39% and 28% of the reviewed studies, respectively), and more rarely, the head-and-neck (H&N) (15%), abdomen (10%), liver (5%) or breast (3%). All the studies performed an image evaluation of sCTs with a diversity of metrics, with only 36 studies performing dosimetric evaluations of sCT. The median mean absolute errors were around 76 HU for the brain and H&N sCTs and 40 HU for the pelvis sCTs. For the brain, the mean dose difference between the sCT and the reference CT was <2%. For the H&N and pelvis, the mean dose difference was below 1% in most of the studies. Recent GAN architectures have advantages compared to generator-only, but no superiority was found in term of image or dose sCT uncertainties. Key challenges of DL-based sCT generation methods from MRI in radiotherapy is the management of movement for abdominal and thoracic localizations, the standardization of sCT evaluation, and the investigation of multicenter impacts. [ABSTRACT FROM AUTHOR]

[Display omitted] • The compressed-sensing-inspired (CSI) algorithms for few-view CT are reviewed. • A list of the CSI algorithms is compiled from the literature search. • The CSI algorithms allow images to be accurately reconstructed from 20 to 30 views. • The dose to the patient can be reduced by a factor of 10 and more. • Acceleration of the CSI algorithms helps introduce them in commercial low-dose CT. Optimization of the dose the patient receives during scanning is an important problem in modern medical X-ray computed tomography (CT). One of the basic ways to its solution is to reduce the number of views. Compressed sensing theory helped promote the development of a new class of effective reconstruction algorithms for limited data CT. These compressed-sensing-inspired (CSI) algorithms optimize the Lp (0 ≤ p ≤ 1) norm of images and can accurately reconstruct CT tomograms from a very few views. The paper presents a review of the CSI algorithms and discusses prospects for their further use in commercial low-dose CT. Many literature references with the CSI algorithms have been were searched. To structure the material collected the author gives a classification framework within which he describes Lp regularization methods, the basic CSI algorithms that are used most often in few-view CT, and some of their derivatives. Lots of examples are provided to illustrate the use of the CSI algorithms in few-view and low-dose CT. A list of the CSI algorithms is compiled from the literature search. For better demonstrativeness they are summarized in a table. The inference is done that already today some of the algorithms are capable of reconstruction from 20 to 30 views with acceptable quality and dose reduction by a factor of 10. In conclusion the author discusses how soon the CSI reconstruction algorithms can be introduced in the practice of medical diagnosis and used in commercial CT scanners. [ABSTRACT FROM AUTHOR]

• A computer-aided detection system is proposed for mass detection in 3D ABUS images. • The presented system includes two cascaded improved 3D UNets. • The 3D UNets are improved with two modified Inception modules in the encoder path. • Moreover, attention units are placed on the skip connections in the second network. • Results of the proposed system are better than the competing networks. Early detection of breast cancer has a significant effect on reducing its mortality rate. For this purpose, automated three-dimensional breast ultrasound (3-D ABUS) has been recently used alongside mammography. The 3-D volume produced in this imaging system includes many slices. The radiologist must review all the slices to find the mass, a time-consuming task with a high probability of mistakes. Therefore, many computer-aided detection (CADe) systems have been developed to assist radiologists in this task. In this paper, we propose a novel CADe system for mass detection in 3-D ABUS images. The proposed system includes two cascaded convolutional neural networks. The goal of the first network is to achieve the highest possible sensitivity, and the second network's goal is to reduce false positives while maintaining high sensitivity. In both networks, an improved version of 3-D U-Net architecture is utilized in which two types of modified Inception modules are used in the encoder section. In the second network, new attention units are also added to the skip connections that receive the results of the first network as saliency maps. The system was evaluated on a dataset containing 60 3-D ABUS volumes from 43 patients and 55 masses. A sensitivity of 91.48% and a mean false positive of 8.85 per patient were achieved. The suggested mass detection system is fully automatic without any user interaction. The results indicate that the sensitivity and the mean FP per patient of the CADe system outperform competing techniques. [ABSTRACT FROM AUTHOR]

• First review of CAD for skull fracture detection in 20 years. • Review of CAD methodologies and challenges in TBI. • Trace evolution from feature-based algorithms to deep learning. • Insights into data acquisition, algorithm tactics and evaluation in CAD. • Evaluation of CAD systems' future in TBI diagnosis. Traumatic brain injury (TBI) remains a leading cause of disability and mortality, with skull fractures being a frequent and serious consequence. Accurate and rapid diagnosis of these fractures is crucial, yet current manual methods via cranial CT scans are time-consuming and prone to error. This review paper focuses on the evolution of computer-aided diagnosis (CAD) systems for detecting skull fractures in TBI patients. It critically assesses advancements from feature-based algorithms to modern machine learning and deep learning techniques. We examine current approaches to data acquisition, the use of public datasets, algorithmic strategies, and performance metrics The review highlights the potential of CAD systems to provide quick and reliable diagnostics, particularly outside regular clinical hours and in under-resourced settings. Our discussion encapsulates the challenges inherent in automated skull fracture assessment and suggests directions for future research to enhance diagnostic accuracy and patient care. With CAD systems, we stand on the cusp of significantly improving TBI management, underscoring the need for continued innovation in this field. [ABSTRACT FROM AUTHOR]

• Reirradiation of head & neck cancer is challenging irrespective of radiation quality. • A dosimetric pilot study was conducted on proton vs photon reirradiation. • Higher maximum dose to CTV was achieved with photon vs proton plans. • Mean parotid dose was lower with proton plans. • Protons should be considered for reirradiation on an individual basis. Reirradiation of head and neck cancer (HNC) became more accessible in the last decade, owing to modern irradiation techniques which offer a reduction in treatment related toxicities. The aim of this paper was to comparatively evaluate the dosimetric aspects derived from intensity modulated photon vs. proton treatment planning in reirradiated HNC patients. Six recurrent HNC patients were enrolled in this retrospective study. For each patient two treatment plans were created: one IMRT/VMAT and one IMPT plan. The prescribed dose for the second irradiation was between 50 and 70 Gy RBE. The study comparatively analyzed the CTV coverage, doses to organs at risk (OARs) and low doses received by the healthy tissue (other than OAR). Similar CTV coverage was achieved for photon vs proton plans, with the latter presenting better homogeneity in four cases. Maximum dose to CTV was generally higher for photon plans, with differences ranging from 0.3 to 1.9%. For parotid glands and body, the mean dose was lower for proton plans. A notable reduction of low dose to healthy tissue (other than OARs) could be achieved with protons, with an average of 60% and 64% for D10% and Dmean, respectively. The dosimetric comparison between photon and proton reirradiation of HNC showed a great need for treatment individualization, concluding that protons should be considered for reirradiation on an individual basis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Optimized survey sample design improves radiological exams frequency assessments. • Data collection from a limited number of facilities may be considered in surveys. • Extrapolation of data to countrywide requires appropriate methodology & QC. • Survey sample representativity and homogeneity are important elements. The radiological examination frequency, i.e. the number of examinations performed annually, is necessary for estimating the collective effective dose of the population from medical exposures with ionizing radiation. Examination frequency surveys usually collect data from a limited number of radiological facilities participating in the survey. The collected data are then extrapolated to the existing radiological facilities in a country/region. Thus, the number of facilities and the specific facilities to participate, as well as, the extrapolation method used, are significant elements when designing the survey sample and methodology for examinations frequency assessments. This work attempted to simulate the situation when examination frequency data are collected from a limited number of facilities by investigating several "virtual sample" designs and two extrapolation methods. Comparisons between the calculated − by extrapolation – and the actual examination frequency in the country were made, for several scenarios and examination type data sets. The uncertainties were estimated and discussed thoroughly. The findings of this work highlighted the need for appropriate registry of the existing facilities in a country/region, the categorization of facilities considering the medical sector pattern in the country/region, the representativity and homogeneity of the samples used for a survey, as well as, the necessity for quality control of the collected examination frequency data. The results showed that when the aforementioned conditions were fulfilled, the examination frequency could be calculated with reasonable accuracy, based on data collected from a limited number of facilities. The paper also provides suggestions and tips for the collection and analysis of examination frequency data. [ABSTRACT FROM AUTHOR]

Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorectal cancer patients. Histopathological examination is the gold standard for screening colorectal cancer. However, the current lack of histopathological image datasets of colorectal cancer, especially enteroscope biopsies, hinders the accurate evaluation of computer-aided diagnosis techniques. Therefore, a multi-category colorectal cancer dataset is needed to test various medical image classification methods to find high classification accuracy and strong robustness. A new publicly available Enteroscope Biopsy Histopathological H&E Image Dataset (EBHI) is published in this paper. To demonstrate the effectiveness of the EBHI dataset, we have utilized several machine learning, convolutional neural networks and novel transformer-based classifiers for experimentation and evaluation, using an image with a magnification of 200 ×. Experimental results show that the deep learning method performs well on the EBHI dataset. Classical machine learning methods achieve maximum accuracy of 76.02% and deep learning method achieves a maximum accuracy of 95.37%. To the best of our knowledge, EBHI is the first publicly available colorectal histopathology enteroscope biopsy dataset with four magnifications and five types of images of tumor differentiation stages, totaling 5532 images. We believe that EBHI could attract researchers to explore new classification algorithms for the automated diagnosis of colorectal cancer, which could help physicians and patients in clinical settings. • EBHI can be applied to verify performance of existing classification methods. • This paper verifies the accuracy from linear regression to Transformer on EBHI. • Classification results by different methods are analysed on EBHI. • EBHI is very distinguishable in the results of different classification methods. [ABSTRACT FROM AUTHOR]

This paper describes an X-ray phase contrast imaging technique using analyzer-based optics called X-ray Dark-Field Imaging that has been under development for the past 10 years. We describe the theory behind XDFI, the X-ray optics required for implementing it in practice, and algorithms used for 2D, 2.5D, and 3D image reconstruction. The XDFI optical chain consists of an asymmetrically cut, Bragg-type monochromator-collimator that provides a planar monochromatic X-ray beam, a positioning stage for the specimens, a Laue-case angle analyzer, and one or two cameras to capture the dark and bright field images. We demonstrate the soft-tissue discrimination capabilities of XDFI by reconstructing images with absorption and phase contrast. By using a variety of specimens such as breast tissue with cancer, joints with articular cartilage, ex-vivo human eye specimen, and others, we show that refraction-based contrast derived from XDFI is more effective in characterizing anatomical features, articular pathology, and neoplastic disease than conventional absorption-based images. For example, XDFI of breast tissue can discriminate between the normal and diseased terminal duct lobular unit, and between invasive and in-situ cancer. The final section of this paper is devoted to potential future developments to enable clinical and histo-pathological applications of this technique. [ABSTRACT FROM AUTHOR]