Atomic force microscopy (AFM) is a scanning imaging technique able to work at the nanoscale. It uses a cantilever with a tip to move across samples' surface and a laser to measure the cantilever bending, enabling the assessment of interaction forces between tip and sample and creating a three-dimensional visual representation of its surface. AFM has been gaining notoriety in the biomedical field due to its high-resolution images, as well as due to its ability to measure the inter- and intramolecular interaction forces involved in the pathophysiology of many diseases. Here, we highlight some of the current applications of AFM in the biomedical field. First, a brief overview of the AFM technique is presented. This theoretical framework is then used to link AFM to its novel translational applications, handling broad clinical questions in different areas, such as infectious diseases, cardiovascular diseases, cancer, and neurodegenerative diseases. Morphological and nanomechanical characteristics such as cell height, volume, stiffness, and adhesion forces may serve as novel parameters used to tailor patient care through nanodiagnostics, individualized risk stratification, and therapeutic monitoring. Despite an increasing development of AFM biomedical research with patient cells, showing its unique capabilities in terms of resolution, speed, and accuracy, there is a notable need for applied AFM research in clinical settings. More translational research with AFM may provide new grounds for the valuable collaboration between biomedical researchers and healthcare professionals.

The rapid advancement of medical technologies presents significant challenges for researchers and practitioners. While traditional clinical trials remain the gold standard, they are often limited by high costs, lengthy durations, and ethical constraints. In contrast, in-silico trials and digital twins have emerged not only as efficient and ethical alternatives but also as a complementary technology that can extend beyond classical trials to predict and design new strategies. The successful application of digital twins in industries like nuclear energy, automotive engineering, and aviation underscores their potential in human health.

In April 2024, Duke University hosted the first international summit on Virtual Imaging Trials in Medicine (VITM). The summit brought together over 130 experts from academia, industry, and regulatory bodies to discuss the latest developments, challenges, and future directions in this field. The event featured plenary speakers, presentations, and panel discussions, emphasizing the integration of clinical and in-silico methods to enhance medical evaluations.

Key takeaways included the necessity of diverse and realistic digital patient representations, the integration of physics and biology in simulations, and the development of robust validation frameworks. The summit also highlighted the importance of regulatory science and the establishment of Good Simulation Practices to ensure the credibility and reliability of virtual trials.

The key discussions and insights from the VITM summit underscore the potential of in-silico trials to revolutionize medical research and patient care through personalized, efficient, and ethical evaluation methods. The collaborative efforts and recommendations from this summit aim to drive future advancements in virtual imaging trials in medicine.

Despite women's early involvement in and contributions to the field of radiology, such as Marie Curie's work in radiation physics and chemistry, women have long remained lacking in their representation among radiologists, including in academics. While many other medical specialties have gradually become more proportionate or even equalized in their gender distribution, radiology continues to exist as a predominately male specialty. In this special topics issue, we aim to explore the landscape of female representation in academic radiology over time, not only in number, but in research productivity, recognition and accolades, and grant and funding reception. We discuss the progress that has been made and factors that have influenced that progress, as well as the crucial role that women currently hold in the field of academic radiology.

NIR-II imaging has the advantages of high sensitivity, spatiotemporal resolution, and high penetration depth, thereby serving as a potential alternative to conventional imaging methods. Herein, a novel NIR-II dye IR-1010 (λex/λem = 1010/1058 nm) is reported with high quantum yield (3.08%) and good stability, by incorporating p-methoxyphenyl groups into a quinolinium cyanine dye. Then a multifunctional nanoprobe, termed IUFP NPs, is developed by the incorporation of upconversion (UC) nanoparticles (NPs), perfluoro-15-crown-5-ether (PFCE), and IR-1010, to display the novel performance of multimodal imaging. Under the single-wavelength excitation (980 nm), IUFP NPs simultaneously emit the NIR-II fluorescence of IR-1010 and visible UC luminescence of UCNPs, and thus realize the UC imaging for cells, and NIR-II fluorescence/photoacoustic/19F magnetic resonance imaging for blood vessels, lymph nodes and tumor in mice. This work affords a novel approach to NIR-II dyes and a general strategy for the design of multimodal imaging probes.

The appendix vermiformis is a part of the gastrointestinal tract, situated in the lower right quadrant of the abdomen. Acute appendicitis, acute inflammation of the appendix vermiformis, is the most common cause of acute abdomen requiring surgical intervention. Although computed tomography (CT) offers high diagnostic efficacy in assessing the appendix across various anatomical positions, it also involves radiation exposure. Reducing exposure factors and narrowing the field of view (FOV) are ways to decrease the radiation dose to the patient. To narrow the FOV, appendix locations within the population must be defined using metric markers.

To determine the location of the appendix vermiformis on CT using the vertebrae and the right iliac bone as anatomical landmarks.

This retrospective study examined 470 patients presenting with abdominal pain who underwent abdominal CT scans between January 01, 2015 and January 01, 2018. Forty-three patients were excluded due to various reasons. The most superior and inferior points and the origin of the appendix were measured separately in relation to the vertebrae and right iliac bone for localization. The population was divided into normal and acute appendicitis groups, and the relationship between appendix location and anthropometric parameters relationship was examined. P values below 0.05 were considered statistically significant.

The final analysis included 427 adult patients (206 females and 221 males) with a mean age of 42.1 ± 19.5 years. An ascending appendix course was the most common (90.4%). The appendix ranged from the L2 vertebral body level to the coccygeal vertebral level relative to the vertebrae. The appendix ranged between (-) 140.5 mm and (+) 87.4 mm relative to the right iliac bone. A negative correlation was found between patient age, height, body mass index, and the highest and lowest points of the appendix in regard to the vertebrae.

The study's findings unveiled the locations of the appendix in the population in relation to the bony anatomical landmarks. These data can be used as the basis for future research aimed at reducing patient exposure to ionizing radiation.

Evidence-based radiographic guidelines are used to justify the need for radiographs and prevent their overuse. This study aimed to assess whether 4th-year chiropractic interns at the International Medical University plan to use x-ray imaging in their future private practice in line with the principles taught throughout their chiropractic program and the evidence-based imaging guidelines.

A survey questionnaire was distributed to 74 final year chiropractic interns, with 62 completed responses. The questionnaire consisted of 8 case scenarios representing potential chiropractic patients. The interns were asked to decide whether to x-ray the patient or not, and which x-ray views to request if they chose to x-ray the patient.

Results were compared with the gold standard using percentage agreement. The findings revealed that the chiropractic students adhered to the gold standard answers for 6 out of 8 cases. However, they did not perform well in selecting the correct x-ray views for the 3 cases where radiography was indicated by the gold standard.

Results suggest that while the interns have a good understanding of when radiography is necessary, they may need additional training in selecting the appropriate x-ray views for each case.

The radiology report is the primary means of conveying imaging findings between radiologists and clinicians. As a result, clinician satisfaction with the radiology report is an indicator of its quality and clinical relevance. It is crucial to identify factors that can enhance the radiology report in order to improve service delivery.

This study evaluates clinician and radiologist opinions, preferences and clinician utilisation of the radiology report.

Mixed quantitative and qualitative survey questionnaires were distributed in-person and online from December 2022 to February 2023 to a total of 287 clinicians and 43 independent medical practitioners specialising in radiology.

A total of 73.0% of radiologists and 56.5% of clinicians expressed satisfaction with the radiology reports. Additionally, 72.0% of radiologists expressed dissatisfaction with the history provided on the referral forms. It was found that 87.6% of clinicians read the radiology report, while 26.2% reviewed the radiological imaging without referring to it. Interestingly, 77.8% of clinicians preferred itemised listed reports, whereas 53.8% of radiologists preferred reports in paragraph format. It was discovered that 69.6% of radiologists and 65.4% of clinicians preferred a standardised reporting format.

More than half of the clinicians and most of the radiologists expressed satisfaction with the radiology report. Both clinicians and radiologists showed a preference for a structured reporting format. A crucial element in constructing a good radiology report was having a relevant clinical history. The radiologist continued to be the preferred professional for interpreting radiological imaging.

This survey was a good starting point for improving communication between clinicians and radiologists. This will ultimately result in reports that are more useful to clinicians and radiologists who have a better understanding of what should be included in reports and how they should be structured.

Advances in radiology are crucial not only to the future of the field but to medicine as a whole. Here, we present three emerging areas of medicine that are poised to change how health care is delivered-hospital at home, artificial intelligence, and precision medicine-and illustrate how advances in radiological tools and technologies are helping to fuel the growth of these markets in the United States and across the globe.

CT scan utilizes ionizing radiation poses a danger to the patient's health. Thus, telling the patient about ionizing radiation would be critical in promoting shared decision-making and improving patient-doctor communication. However, few studies have examined this topic broadly.

The study was conducted to identify the frequency of physicians informing patients about the radiation risk before ordering a CT scan, as well as to examine the association between patients' demographic characteristics and their awareness of the radiation risks associated with CT scans.

A cross-sectional study was conducted among 387 patients who had undergone CT scans at a tertiary hospital in Riyadh, Saudi Arabia. Data were collected via phone interviews using a structured questionnaire. Chi-squared tests were employed to assess associations between patients' demographic characteristics and their awareness of CT scan radiation risks.

When examining knowledge, 58% of patients knew that CT involves harmful radiation. This knowledge was significantly associated with higher education level and previous experience with CT scans. Regarding doctors' practice of providing information to patients about the scan, 344 (88.9%) patients indicated that their doctor had explained to them why they needed the scan. Only 28 (7.2%) patients stated that their doctor had mentioned the amount of radiation, and 74 (19.1%) patients indicated that doctors mentioned the risks associated with the radiation of the scan. Almost all patients (96.9%) preferred to be told about why they needed a CT scan.

The vast majority of patients who underwent CT scans did not receive enough information about the harm of the scans. However, most of them preferred to know about this harm.

Medical imaging is essential for the proper diagnosis and treatment of many diseases. The literature has found that medical imaging generally accounts for a significant percentage of total healthcare spending. We analyzed a national database between 2013 and 2021, with more than 19 million patients on average, to review which health conditions account for the highest spending on medical imaging in the Colombian health system. We segmented the analysis by type of medical imaging, life cycles, health condition and sex. Our findings indicate that cardiac and mental illnesses account for the highest per capita spending on medical imaging, especially for the elderly. As a proportion of total expenditure, hypertension and tuberculosis are added, with special emphasis on the infancy-childhood life cycle.

Radiological imaging is a crucial diagnostic tool for the pediatric population. However, it is associated with several unique challenges in this age group compared to adults. These challenges mainly come from the fact that children are not small-sized adults and differ in development, anatomy, physiology, and pathology compared to adults. This paper reviews relevant articles published between January 2015 and October 2023 to analyze challenges associated with imaging technologies currently used in pediatric radiology, emerging technologies, and their role in resolving the challenges and future prospects of pediatric radiology. In recent decades, imaging technologies have advanced rapidly, developing advanced ultrasound, computed tomography, magnetic resonance, nuclear imaging, teleradiology, artificial intelligence, machine learning, three-dimensional printing, radiomics, and radiogenomics, among many others. By prioritizing the unique needs of pediatric patients while developing such technologies, we can significantly alleviate the challenges faced in pediatric radiology.

Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) platforms have long served as a cornerstone in radiology education, offering rich visual content, interactive sessions, and peer-reviewed materials. They excel in teaching intricate concepts and techniques that necessitate visual aids, such as image interpretation and procedural demonstrations. However, Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI)-powered language model, has made its mark in radiology education. It can generate learning assessments, create lesson plans, act as a round-the-clock virtual tutor, enhance critical thinking, translate materials for broader accessibility, summarize vast amounts of information, and provide real-time feedback for any subject, including radiology. Concerns have arisen regarding ChatGPT's data accuracy, currency, and potential biases, especially in specialized fields such as radiology. However, the quality, accessibility, and currency of e-learning content can also be imperfect. To enhance the educational journey for radiology residents, the integration of ChatGPT with expert-curated e-learning resources is imperative for ensuring accuracy and reliability and addressing ethical concerns. While AI is unlikely to entirely supplant traditional radiology study methods, the synergistic combination of AI with traditional e-learning can create a holistic educational experience.

Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory processes, demyelination, neurodegeneration, and axonal damage within the central nervous system (CNS). Retinal imaging, particularly Optical coherence tomography (OCT), has emerged as a crucial tool for investigating MS-related retinal injury. The integration of artificial intelligence(AI) has shown promise in enhancing OCT analysis for MS. Researchers are actively utilizing AI algorithms to accurately detect and classify MS-related abnormalities, leading to improved efficiency in diagnosis, monitoring, and personalized treatment planning. The prognostic value of AI in predicting MS disease progression has garnered substantial attention. Machine learning (ML) and deep learning (DL) algorithms can analyze longitudinal OCT data to forecast the course of the disease, providing critical information for personalized treatment planning and improved patient outcomes. Early detection of high-risk patients allows for targeted interventions to mitigate disability progression effectively. As such, AI-driven approaches yielded remarkable abilities in classifying distinct MS subtypes based on retinal features, aiding in disease characterization and guiding tailored therapeutic strategies. Additionally, these algorithms have enhanced the accuracy and efficiency of OCT image segmentation, streamlined diagnostic processes, and reduced human error. This study reviews the current research studies on the integration of AI,including ML and DL algorithms, with OCT in the context of MS. It examines the advancements, challenges, potential prospects, and ethical concerns of AI-powered techniques in enhancing MS diagnosis, monitoring disease progression, revolutionizing patient care, the development of patient screening tools, and supported clinical decision-making based on OCT images.

To develop ultrasound-guided radiotherapy, we proposed an assistant structure with embedded markers along with a novel alternative method, the Aligned Peak Response (APR) method, to alter the conventional delay-and-sum (DAS) beamformer for reconstructing ultrasound images obtained from a flexible array. We simulated imaging targets in Field-II using point target phantoms with point targets at different locations. In the experimental phantom ultrasound images, image RF data were acquired with a flexible transducer with in-house assistant structures embedded with needle targets for testing the accuracy of the APR method. The lateral full width at half maximum (FWHM) values of the objective point target (OPT) in ground truth ultrasound images, APR-delayed ultrasound images with a flat shape, and images acquired with curved transducer radii of 500 mm and 700 mm were 3.96 mm, 4.95 mm, 4.96 mm, and 4.95 mm. The corresponding axial FWHM values were 1.52 mm, 4.08 mm, 5.84 mm, and 5.92 mm, respectively. These results demonstrate that the proposed assistant structure and the APR method have the potential to construct accurate delay curves without external shape sensing, thereby enabling a flexible ultrasound array for tracking pancreatic tumor targets in real time for radiotherapy.

Musical intervention (MI) is a valuable strategy for addressing the psychological and emotional challenges faced by patients undergoing imaging procedures. This study explores MI's impact on psychophysiological outcomes during imaging procedures, detailing the sound repertoire and technical characteristics employed in MI.

A systematic review (SR) and meta-analysis (MA) were conducted. Electronic database searches of PubMed, Web-of-Science, and Scopus were performed encompassing original randomised research and quasi-experimental articles published until June 2023.

Thirteen articles were included in this SR, scoring between 23 and 68 on the Joanna Briggs Institute (JBI) Checklist. Four articles were included to perform a MA concerning anxiety and heart rate (HR) outcomes. Most studies utilised digital playlists as the medium for MI. Headphones were commonly used, with an average volume of 50-60 dB and a musical frequency of 60-80 beats/min. While authors generally preferred selecting musical genres for the repertoire, two articles specifically chose Johann Pachelbel's "Canon in D major" as their musical theme. In terms of psychological parameters, the experimental groups exhibited lower anxiety values than the control groups, with further reductions after MI. However, MA shows that this trend is only marginally significant. Patient comfort and overall examination experience showed improvement with MI. Regarding physiological parameters, HR, especially in the final phase of the examination, was significantly lower in the experimental group compared to the control group.

Across multiple studies, MI demonstrated the ability to reduce anxiety and HR. However, no specific music repertoire emerged as the most effective.

MI arises as a painless, reliable, low-cost, and side-effect-free strategy, presenting imaging departments with a practical means to enhance patient comfort and mitigate anxiety and stress during medical procedures.

Advances in artificial intelligence and machine learning models, like Chat Generative Pre-trained Transformer (ChatGPT), have occurred at a remarkably fast rate. OpenAI released its newest model of ChatGPT, GPT-4, in March 2023. It offers a wide range of medical applications. The model has demonstrated notable proficiency on many medical board examinations. This study sought to assess GPT-4's performance on the Orthopaedic In-Training Examination (OITE) used to prepare residents for the American Board of Orthopaedic Surgery (ABOS) Part I Examination. The data gathered from GPT-4's performance were additionally compared with the data of the previous iteration of ChatGPT, GPT-3.5, which was released 4 months before GPT-4. GPT-4 correctly answered 251 of the 396 attempted questions (63.4%), whereas GPT-3.5 correctly answered 46.3% of 410 attempted questions. GPT-4 was significantly more accurate than GPT-3.5 on orthopedic board-style questions (P<.00001). GPT-4's performance is most comparable to that of an average third-year orthopedic surgery resident, while GPT-3.5 performed below an average orthopedic intern. GPT-4's overall accuracy was just below the approximate threshold that indicates a likely pass on the ABOS Part I Examination. Our results demonstrate significant improvements in OpenAI's newest model, GPT-4. Future studies should assess potential clinical applications as AI models continue to be trained on larger data sets and offer more capabilities. [Orthopedics. 2024;47(2):e85-e89.].

Since winter 2020/21, general practitioners (GPs) in the Republic of Ireland (RoI) have been granted access to diagnostic imaging studies on a new publicly funded pathway, expediting access to services previously obtained via hospital-based doctors.

Outline GP perspectives on imaging studies obtained via the new "GP Access to Community Diagnostics" initiative.

A mixed-methods design was employed. Referrals over the first six months of 2019 and 2021 were collated by a private imaging provider, and a randomly selected subset of 2021 studies (maximum 30 referrals per GP) was returned to participating GPs to provide detail on the impact on each patient's care. In-depth qualitative interviews were also conducted with participating GPs.

Eleven GPs supplied detailed information on 81 studies organized through the new initiative. GPs reported that the initiative had led to a large proportion of cases being managed solely in general practice, with an 81% reduction in referrals to acute hospital settings and a 58% reduction in referrals to secondary care clinics. GPs felt imaging studies improved patient care in 86% of cases and increased GP workload in 58% of cases. GP qualitative interviews revealed four key themes: improved patient care, increased GP workload, reduction in hospital referrals, and opinions on ongoing management of such initiatives, including guidelines.

GPs felt enhancing access to diagnostics improved patient care by expediting diagnosis, decision-making, and treatment and by reducing hospital referrals. GPs were generally positive about the initiative and made some suggestions on future management of the initiative.

To explore the nature and extent of peer-reviewed literature related to the use of diagnostic imaging by nurse practitioners (NPs) to inform future practice and research.

Nurse practitioners undertake advanced assessment, diagnosis, and management of patients, including requesting and interpretation of diagnostic imaging. It is unclear what evidence exists related to the quality use of radiological investigations by NPs in recent years.

A scoping review based on the steps suggested by the Joanna Briggs Institute.

A structured review of the databases Medline, CINAHL and Embase was undertaken using the keywords and MESH terms 'nurse practitioner', 'medical imaging', 'diagnostic imaging', 'scan' and 'radiography'. Only English language articles were included, and no date limit was applied. Database review was completed on 30 May 2021.

Eight themes were identified-country and clinical context, requesting diagnostic imaging, performing diagnostic imaging, image-guided interventions, interpreting diagnostic imaging, training education and knowledge, impact on resource usage and comparison with medical practitioners. There were more studies across a greater breadth of clinical specialties and imaging modalities in the United States than in other countries. Nurse practitioner practice is frequently benchmarked against that of medical colleagues. There is a paucity of studies focusing on educational preparation and the lack of relevant university curricula for NPs around diagnostic imaging.

There are significant gaps in the evidence outside of the United States across several of the identified themes. Further studies are needed to explore NP access to and use of diagnostic imaging and to understand the barriers and facilitators to this.

Studies from four countries were included in this review. The evidence suggests that, where studied, nurse practitioners (NPs) can safely and appropriately request and interpret plain x-rays in the emergency and minor injuries setting. Further research is needed to evaluate the educational needs of NPs in relation to diagnostic imaging and their use of advanced imaging techniques, particularly outside of the United States.

No patient or public contribution.

The optic disc and the macular are two major anatomical structures in the human eye. Optic discs are associated with the optic nerve. Macular mainly involves degeneration and impaired function of the macular region. Reliable optic disc and macular segmentation are necessary for the automated screening of retinal diseases.

A swept-source OCTA system was designed to capture OCTA images of human eyes. To address these segmentation tasks, first, we constructed a new Optic Disc and Macula in fundus Image with optical coherence tomography angiography (OCTA) dataset (ODMI). Second, we proposed a Coarse and Fine Attention-Based Network (CFANet).

The five metrics of our methods on ODMI are 98.91 % , 98.47 % , 89.77 % , 98.49 % , and 89.77 % , respectively.

Experimental results show that our CFANet has achieved good performance on segmentation for the optic disc and macula in OCTA.

By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions.

This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed.

The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated.

The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts.

The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.

The prognosis of local prostate cancer has improved drastically during the past 60 years. Similarly, the prognosis in metastatic stage is constantly improving due to a number of new pharmaceuticals introduced over the past 10 years. Previously, only palliative treatments were available for prostate cancer, but today, there are multiple options for treatment with curative intent: robotic-assisted radical prostatectomy, stereotactic radiotherapy and brachytherapy. Additionally, life-prolonging chemotherapeutic and androgen-suppressive treatments, as well as diagnostic imaging and staging, have improved considerably. This review summarizes the history of the treatment and diagnostics of prostate cancer, with a focus on the past 60 years. The aim was to provide a concise and easy-to-read introduction on the matter for all people that work with prostate cancer, as well as for patients. The literature was thoroughly examined covering the period from the earliest traceable records to the latest state-of-the-art studies.

The wide applicability of acoustics in the life of mankind spread over health, energy, environment, and others. These acoustic technologies rely on the properties of the materials with which they are made of. However, traditional devices have failed to develop into low-cost, portable devices and need to overcome issues like sensitivity, tunability, and applicability in biological in vivo studies. Nanomaterials, especially 2D materials, have already been proven to produce high optical contrast in photoacoustic applications. One such wonder kid in the materials family is MXenes, which are transition metal carbides, that are nowadays flourishing in the materials world. Recently, it has been demonstrated that MXene nanosheets and quantum dots can be synthesized by acoustic excitations. In addition, MXene can be used as a mechanical sensing material for building piezoresistive sensors to realize sound detection as it produces a sensitive response to pressure and vibration. It has also been demonstrated that MXene nanosheets show high photothermal conversion capability, which can be utilized in cancer treatment and photoacoustic imaging (PAI). In this review, we have rendered the role of acoustics in the palette of MXene, including acoustic synthetic strategies of MXenes, applications such as acoustic sensors, PAI, thermoacoustic devices, sonodynamic therapy, artificial ear drum, and others. The review also discusses the challenges and future prospects of using MXene in acoustic platforms in detail. To the best of our knowledge, this is the first review combining acoustic science in MXene research.

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.4% of world population. Pulmonary imaging has been widely investigated toward improving our understanding of disease etiologies and early diagnosis and assessment of disease progression and clinical outcomes. DL has been broadly applied to solve various pulmonary image processing challenges including classification, recognition, registration, and segmentation. This paper presents a survey of pulmonary diseases, roles of imaging in translational and clinical pulmonary research, and applications of different DL architectures and methods in pulmonary imaging with emphasis on DL-based segmentation of major pulmonary anatomies such as lung volumes, lung lobes, pulmonary vessels, and airways as well as thoracic musculoskeletal anatomies related to pulmonary diseases.

The success of cephalometric analysis depends on the accurate detection of cephalometric landmarks on scanned lateral cephalograms. However, manual cephalometric analysis is time-consuming and can cause inter- and intra-observer variability. The purpose of this study was to automatically detect cephalometric landmarks on scanned lateral cephalograms with low contrast and resolution using an attention-based stacked regression network (Ceph-Net).

The main body of Ceph-Net compromised stacked fully convolutional networks (FCN) which progressively refined the detection of cephalometric landmarks on each FCN. By embedding dual attention and multi-path convolution modules in Ceph-Net, the network learned local and global context and semantic relationships between cephalometric landmarks. Additionally, the intermediate deep supervision in each FCN further boosted the training stability and the detection performance of cephalometric landmarks.

Ceph-Net showed a superior detection performance in mean radial error and successful detection rate, including accuracy improvements in cephalometric landmark detection located in low-contrast soft tissues compared with other detection networks. Moreover, Ceph-Net presented superior detection performance on the test dataset split by age from 8 to 16 years old.

Ceph-Net demonstrated an automatic and superior detection of cephalometric landmarks by successfully learning local and global context and semantic relationships between cephalometric landmarks in scanned lateral cephalograms with low contrast and resolutions.

The classical transillumination technique has been revitalized through recent advancements in optical technology, enhancing its applicability in the realm of biomedical research. With a new perspective on near-axis scattered light, we have harnessed near-infrared (NIR) light to visualize intricate internal light-absorbing structures within animal bodies. By leveraging the principle of differentiation, we have extended the applicability of the Beer-Lambert law even in cases of scattering-dominant media, such as animal body tissues. This approach facilitates the visualization of dynamic physiological changes occurring within animal bodies, thereby enabling noninvasive, real-time imaging of macroscopic functionality in vivo. An important challenge inherent to transillumination imaging lies in the image blur caused by pronounced light scattering within body tissues. By extracting near-axis scattered components from the predominant diffusely scattered light, we have achieved cross-sectional imaging of animal bodies. Furthermore, we have introduced software-based techniques encompassing deconvolution using the point spread function and the application of deep learning principles to counteract the scattering effect. Finally, transillumination imaging has been elevated from two-dimensional to three-dimensional imaging. The effectiveness and applicability of these proposed techniques have been validated through comprehensive simulations and experiments involving human and animal subjects. As demonstrated through these studies, transillumination imaging coupled with emerging technologies offers a promising avenue for future biomedical applications.

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging.

In chest computed tomography (CT), the breasts located within the scan range receive a substantial radiation dose. Due to the risk of breast-related carcinogenesis, analyzing the breast dose for justification of CT examinations seems necessary. The main goal of this study is to overcome the limitations of conventional dosimetry methods, such as thermoluminescent dosimeters (TLDs) by introducing the adaptive neuro-fuzzy inference system (ANFIS) approach. In this study, the breast dose of 50 adult female patients who underwent chest CT examinations was measured directly by TLDs. Then, the ANFIS model was developed with four inputs including dose length product (DLP), volumetric CT dose index (CTDIvol), total mAs, and size-specific dose estimate (SSDE), and one output (TLD dose). Additionally, multiple linear regression (MLR) as a traditional prediction model was used for linear modeling and its results were compared with the ANFIS. The TLD reader results showed that the breast dose value was 12.37 ± 2.46 mGy. Performance indices of the ANFIS model, including root mean square error (RMSE) and correlation coefficient (R), were calculated at 0.172 and 0.93 for the testing dataset, respectively. Also, the ANFIS model had superior performance in predicting the breast dose than the MLR model (R = 0.805). This study demonstrates that the proposed ANFIS model is efficient for patient dose prediction in CT scans. Therefore, intelligence models such as ANFIS are suggested to estimate and optimize patient dose in CT examinations.

Medical imaging features along the entire healthcare continuum and is known for its fast-paced technological evolution which enables it to keep up with the demands of the healthcare system to provide safe, quality services. The overall efficacy and efficiency of the system depends on practitioners' clinical competence, achieved through professional education and continuous professional development. Recent studies have revealed concerns regarding newly graduated healthcare professionals' preparedness and readiness to handle actual practice.

We conducted qualitative face-to-face and telephonic interviews with a convenient and purposive sample of 23 participants consisting of recently graduated radiographers (n=14), radiography students (n=5) and supervising radiographers (n=4) in Australia. Verbatim transcriptions were analyzed inductively to identify themes pertaining to perspectives and experiences of the work readiness of novice radiographers.

The findings of our study suggest that the workplace immersion and transitioning of recently graduated radiographers into their professional roles requires a process of experiential learning and honing of knowledge and skills if they are to function efficiently and independently in a team-oriented workplace. Radiographic services are spread across various levels of care and are an integral part of the organizational structure of a healthcare system. Maladaptive transitions to the workplace may be the result of low self-confidence, a lack of support, uncertainty in inter-collegial interactions, or unrealistic performance expectations. The overarching themes of communication and interaction emerged clearly as recently graduated radiographers navigated the four roles of coordinator, collaborator, mediator, and advocate.

The application of radiographic skills is embedded in a workplace culture of communication and safety. Transitioning to independent practice takes place in a complex, multifaceted environment and is accompanied by internal and external expectations. Because each workplace has a unique context, system and culture, no novice radiographic professional can ever be fully prepared through pre-service training and workplace induction.

X-ray imaging uses ionizing radiation to generate diagnostic images. However, unnecessary radiation exposure can pose potential risks, including an increased risk of malignancy. One factor contributing to unnecessary radiation exposure is the rejection and retaking of X-ray images, which can lead to higher patient and occupational radiation doses. This study aimed to assess digital radiography rejection rates, causes of recurrence, and the most commonly repeated types of examinations. A cross-sectional online-based survey was conducted in 2022, involving 62 randomly selected radiographers in the UAE. The survey was distributed to radiographers through the head of radiology departments in various hospitals. Hospitals agreed to participate in the survey without disclosing their name. The data collected was analyzed using Excel. The study showed that 71% of radiographers working in the UAE hold a bachelor's degree. The examinations most frequently repeated were related to anatomical areas, with the spine accounting for 37.7% and facial bone for 19.7% of cases. The factors influencing repetition were primarily related to positioning (48.4%) and artifacts (21%), with the motion being the main cause of artifacts, including voluntary and involuntary movements. This study concluded that the most prevalent cause of repeating and retaking images is positioning, followed by artifacts. Furthermore, night shifts and workload impact radiographer performance, increasing the likelihood of picture retakes. The average number of rejects and repeated images has been reduced as new generations and modern equipment have been introduced, which also helped decrease the numbers.

Direct access to diagnostic imaging in General Practice provides an avenue to reduce referrals to hospital-based specialities and emergency departments, and to ensure timely diagnosis. Enhanced GP access to radiology imaging could potentially reduce hospital referrals, hospital admissions, enhance patient care, and improve disease outcomes. This scoping review aims to demonstrate the value of direct access to diagnostic imaging in General Practice and how it has impacted on healthcare delivery and patient care.

A search was conducted of 'PubMed', 'Cochrane Library', 'Embase' and 'Google Scholar' for papers published between 2012-2022 using Arksey and O'Malley's scoping review framework. The search process was guided by the PRISMA extension for Scoping Reviews checklist (PRISMA-ScR).

Twenty-three papers were included. The studies spanned numerous geographical locations (most commonly UK, Denmark, and Netherlands), encompassing several study designs (most commonly cohort studies, randomised controlled trials and observational studies), and a range of populations and sample sizes. Key outcomes reported included the level of access to imaging serves, the feasibility and cost effectiveness of direct access interventions, GP and patient satisfaction with direct access initiatives, and intervention related scan waiting times and referral process.

Direct access to imaging for GPs can have many benefits for healthcare service delivery, patient care, and the wider healthcare ecosystem. GP focused direct access initiatives should therefore be considered as a desirable and viable health policy directive. Further research is needed to more closely examine the impacts that access to imaging studies have on health system operations, especially those in General Practice. Research examining the impacts of access to multiple imaging modalities is also warranted.

Computed tomography (CT) is an extensively used imaging modality capable of generating detailed images of a patient's internal anatomy for diagnostic and interventional procedures. High-resolution volumes are created by measuring and combining information along many radiographic projection angles. In current medical practice, single and dual-view two-dimensional (2D) topograms are utilized for planning the proceeding diagnostic scans and for selecting favorable acquisition parameters, either manually or automatically, as well as for dose modulation calculations. In this study, we develop modified 2D to three-dimensional (3D) encoder-decoder neural network architectures to generate CT-like volumes from single and dual-view topograms. We validate the developed neural networks on synthesized topograms from publicly available thoracic CT datasets. Finally, we assess the viability of the proposed transformational encoder-decoder architecture on both common image similarity metrics and quantitative clinical use case metrics, a first for 2D-to-3D CT reconstruction research. According to our findings, both single-input and dual-input neural networks are able to provide accurate volumetric anatomical estimates. The proposed technology will allow for improved (i) planning of diagnostic CT acquisitions, (ii) input for various dose modulation techniques, and (iii) recommendations for acquisition parameters and/or automatic parameter selection. It may also provide for an accurate attenuation correction map for positron emission tomography (PET) with only a small fraction of the radiation dose utilized.

The red dot system uses expertise in the identification of anomalies to assist radiologists in distinguishing radiological abnormalities and managing them before the radiologist report is sent. This is a small step on the road to greater role development for radiographers. This practice has existed for more than 20 years in the UK. Today, it is only the UK seeking to legislate radiographer reports. The aim of this paper is to put focus on this issue, determine whether radiographer reports are necessary, and explore whether there are any benefits that can be highlighted to encourage health authorities worldwide to allow radiographers to write clinical reports. Additionally, this study was conducted to evaluate the role of radiographers (non-radiologists) in medical image interpretation, using 95 samples that were collected randomly and a representative sample of radiographers and radiologists of both genders. The SPSS program was used for the statistical analysis of the samples and to scientifically explain the results. We found that radiologists have no objections to the participation of radiographers in diagnosis assistance, interpretation, and clinical reporting through the red dot system. Therefore, there was support for the future implementation of such a system in health care.

Terahertz (THz) technology is developing a non-invasive imaging system for biosensing and clinical diagnosis. THz medical imaging mainly benefits from great sensitivity in detecting changes in water content and structural variations in diseased cells versus normal tissues. Compared to healthy tissues, cancerous tumors contain a higher level of water molecules and show structural changes, resulting in different THz absorption. Here we described the principle of THz imaging and advancement in the field of translational biomedicine and early detection of pathologic tissue, with a particular focus on oncology. In addition, although the main forte of THz imaging relies on detecting differences in water content to distinguish the exact margin of tumor, THz displays limited contrast in living tissue for in-vivo clinical imaging. In the last few years, nanotechnology has attracted attention to aid THz medical imaging and various nanoparticles have been investigated as contrast enhancements to improve the accuracy, sensitivity, and specificity of THz images. Most of these multimodal contrast agents take advantage of the temperature-dependent of THz spectrum to the conformational variation of the water molecule. We discuss advances in developing THz contrast agents to accelerate the advancement of non-invasive THz imaging with improved sensitivity and specificity for translational clinical oncology.

With the modernization and digitisation of the healthcare system, the need for exchanging medical data has become increasingly compelling. Biomedical imaging has been no exception, where the gathering of medical imaging acquisitions from multi-site collaborations have enabled to reach data sizes never imaginable until few years ago. Usually, medical imaging data have very large volume and diverse complexity, requiring bespoken transfer systems that protect personal information as well as data integrity. Despite many digital innovations, there are still technical and regulatory bottlenecks that make biomedical imaging data exchange challenging. Here we present Bitbox, a web-based application which provides a reliable yet straightforward service to securely exchange medical imaging data. With Bitbox, both imaging and non-imaging data of any type can be transferred from any external and independent site into a centralized server. A showcase of the system will be illustrated for the COVID-19 Clinical Neuroscience Study (COVID-CNS) project, a UK-wide experimental medicine study to investigate the neurological and neuropsychiatric effects of COVID-19 infections in hundreds of patients.

This present systematic review examines spine surgery literature supporting augmented reality (AR) technology and summarizes its current status in spinal surgery technology. Database search strategies were retrieved from PubMed, Web of Science, Cochrane Library, Embase, from the earliest records to April 1, 2021. Our review briefly examines the history of AR, and enumerates different device application workflows in a variety of spinal surgeries. We also sort out the pros and cons of current mainstream AR devices and the latest updates. A total of 45 articles are included in our review. The most prevalent surgical applications included are the augmented reality surgical navigation system and head-mounted display. The most popular application of AR is pedicle screw instrumentation in spine surgery, and the primary responsible surgical levels are thoracic and lumbar. AR guidance systems show high potential value in practical clinical applications for the spine. The overall number of cases in AR-related studies is still rare compared to traditional surgical-assisted techniques. These lack long-term clinical efficacy and robust surgical-related statistical data. Changing healthcare laws as well as the increasing prevalence of spinal surgery are generating critical data that determines the value of AR technology.

With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most widely utilized in biomedical image segmentation to address the automation in identification and detection of the target regions or sub-regions. In recent studies, U-Net based approaches have illustrated state-of-the-art performance in different applications for the development of computer-aided diagnosis systems for early diagnosis and treatment of diseases such as brain tumor, lung cancer, alzheimer, breast cancer, etc., using various modalities. This article contributes in presenting the success of these approaches by describing the U-Net framework, followed by the comprehensive analysis of the U-Net variants by performing (1) inter-modality, and (2) intra-modality categorization to establish better insights into the associated challenges and solutions. Besides, this article also highlights the contribution of U-Net based frameworks in the ongoing pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) also known as COVID-19. Finally, the strengths and similarities of these U-Net variants are analysed along with the challenges involved in biomedical image segmentation to uncover promising future research directions in this area.

Three-Dimensional (3D) medical animations incorporated into applications are highly beneficial for clinical outreach and medical communication purposes that work towards educating the clinician and patient. Aortic aneurysms are a clinically important area to communicate with multiple audiences about various treatment options; both abdominal and thoracic aortic aneurysms were selected to create 3D animations and applications to educate medical professionals and patients regarding treatment options. Fenestrated endovascular aortic repair (FEVAR) and thoracic endovascular aortic repair (TEVAR) are both tried and tested minimally invasive surgical methods for treating thoracic aortic aneurysms respectively. The Terumo Aortic Custom Relay Proximal Scalloped stent graft and Fenestrated Anaconda stent graft were both designed specifically for these procedures; however, it can be difficult to visually communicate to clinicians and patients in a straightforward way how these devices work. Therefore, we have developed two interactive applications that use 3D visualisation techniques to demonstrate how these aortic devices function and are implemented. The objective of these applications is to engage both clinicians and patients, therefore demonstrating that the addition of anatomically accurate 3D visualisations within an interactive interface would have a positive impact on public engagement while also ensuring that clinicians will have the best possible understanding of the potential uses of both devices, enabling them to exploit their key features to effectively broaden the treatable patient population.Detailed anatomical modelling and animation was used to generate realistic and accurate rendered videos showcasing both products. These videos were integrated into an interactive application within a modern, professional graphic interface that allowed the user to explore all aspects of the stent device. The resulting applications were broken down into three modules: deployment, clinical performance and features. Following application development, these applications were evaluated by professionals in the field. Overall, positive feedback was received regarding the user-friendly nature of the applications and highly effective animations to showcase the products. The clinical applications and feature modules were particularly successful, while the deployment modules had a neutral response. Biomedical applications such as these show great potential for communicating the key features of medical devices and promoting discussion between clinicians and patients; further testing would need to be conducted on a larger group of participants in order to validate the learning effectiveness of the applications.

We assessed variations in chest CT usage, radiation dose and image quality in COVID-19 pneumonia. Our study included all chest CT exams performed in 533 patients from 6 healthcare sites from Brazil. We recorded patients' age, gender and body weight and the information number of CT exams per patient, scan parameters and radiation doses (volume CT dose index-CTDIvol and dose length product-DLP). Six radiologists assessed all chest CT exams for the type of pulmonary findings and classified CT appearance of COVID-19 pneumonia as typical, indeterminate, atypical or negative. In addition, each CT was assessed for diagnostic quality (optimal or suboptimal) and presence of artefacts. Artefacts were frequent (367/841), often related to respiratory motion (344/367 chest CT exams with artefacts) and resulted in suboptimal evaluation in mid-to-lower lungs (176/344) or the entire lung (31/344). There were substantial differences in CT usage, patient weight, CTDIvol and DLP across the participating sites.

MRI-based mathematical and computational modeling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modeling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modeling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modeling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.

The structure and constitution of opaque materials can be studied with X-ray imaging methods such as 3D tomography. To observe the dynamic evolution of their structure and the distribution of constituents, for example, during processing, heating, mechanical loading, etc., 3D imaging has to be fast enough. In this paper, the recent developments of time-resolved X-ray tomography that have led to what one now calls "tomoscopy" are briefly reviewed A novel setup is presented and applied that pushes temporal resolution down to just 1 ms, that is, 1000 tomograms per second (tps) are acquired, while maintaining spatial resolutions of micrometers and running experiments for minutes without interruption. Applications recorded at different acquisition rates ranging from 50 to 1000 tps are presented. The authors observe and quantify the immiscible hypermonotectic reaction of AlBi10 (in wt%) alloy and dendrite evolution in AlGe10 (in wt%) casting alloy during fast solidification. The combustion process and the evolution of the constituents are analyzed in a burning sparkler. Finally, the authors follow the structure and density of two metal foams over a long period of time and derive details of bubble formation and bubble ageing including quantitative analyses of bubble parameters with millisecond temporal resolution.

Ultrasound (US) and X-ray imaging are diagnostic methods that are commonly used to image internal body structures. Several organic and inorganic imaging contrast agents are commercially available. However, their synthesis and purification remain challenging, in addition to posing safety issues. Here, we report on the promise of widespread, safe, and easy-to-produce particulate calcium fluoride (part-CaF2) as a bimodal US and X-ray contrast agent. Pure and highly crystalline part-CaF2 is obtained using a cheap commercial product. Scanning electron microscopy (SEM) depicts the morphology of these particles, while energy-dispersive X-ray spectroscopy (EDS) confirms their chemical composition. Diffuse reflectance ultraviolet-visible spectroscopy highlights their insulating behavior. The X-ray diffraction (XRD) pattern reveals that part-CaF2 crystallizes in the face-centered cubic cell lattice. Further analyses regarding peak broadening are performed using the Scherrer and Williamson-Hall (W-H) methods, which pinpoint the small crystallite size and the presence of lattice strain. X-ray photoelectron spectroscopy (XPS) solely exhibits specific peaks related to CaF2, confirming the absence of any contamination. Additionally, in vitro cytotoxicity and in vivo maximum tolerated dose (MTD) tests prove the biocompatibility of part-CaF2. Finally, the results of the US and X-ray imaging tests strongly signal that part-CaF2 could be exploited in bimodal bioimaging applications. These findings may shed a new light on calcium fluoride and the opportunities it offers in biomedical engineering.

The aim of this study was to investigate the effects of clinical information on the accuracy, timeliness, reporting confidence and clinical relevance of the radiology report.

A systematic review of studies that investigated a link between primary communication of clinical information to the radiologist and the resultant report was conducted. Relevant studies were identified by a comprehensive search of electronic databases (PubMed, Scopus and EMBASE). Studies were screened using pre-defined criteria. Methodological quality was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quasi-Experimental Studies. Synthesis of findings was narrative. Results were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

There were 21 studies which met the inclusion criteria, of which 20 were included in our review following quality assessment. Sixteen studies investigated the effect of clinical information on reporting accuracy, three studies investigated the effect of clinical information on reporting confidence, three studies explored the impact of clinical information on clinical relevance, and two studies investigated the impact of clinical information on reporting timeliness. Some studies explored multiple outcomes. Studies concluded that clinical information improved interpretation accuracy, clinical relevance and reporting confidence; however, reporting time was not substantially affected by the addition of clinical information.

The findings of this review suggest clinical information has a positive impact on the radiology report. It is in the best interests of radiologists to communicate the importance of clinical information to reporting via the creation of criteria standards to guide the requesting practices of medical imaging referrers. Further work is recommended to establish these criteria standards.