Innovative Imaging Techniques Research Articles

LC-OCT for early diagnosis and characterization of dermatologic adverse events to oncologic drugs and correlation to histopathology.

Targeted and immune therapies have recently been associated with the occurrence of multiple cutaneous toxicities, often challenging to differentiate by clinical examination alone without histology. Line-field confocal optical coherence tomography (LC-OCT) is a non-invasive and innovative imaging technique that has been shown to be almost as effective as histology in diagnosing several skin conditions. Our study aimed to assess the effectiveness of LC-OCT in predicting the clinical evolution of early maculopapular eruptions related to antineoplastic targeted therapy and immunotherapy. In the period between May 2023 and December 2023, consecutive patients with clinical cutaneous maculopapular reactions caused by oncologic targeted therapy or immunotherapy were enrolled at the dermatologic outpatient clinic of the Fondazione Policlinico A. Gemelli IRCCS, Rome. Patients underwent clinical dermatological examination, video-dermoscopy, LC-OCT, and incisional skin biopsy of a target cutaneous lesion. To investigate the evolutionary pattern of maculopapular lesions (psoriasic eruption, lichenoid eruption, eczematous eruption, bullous eruption), LC-OCT and histopathological images have been compared based on specific characteristics (hyperkeratosis, acanthosis, spongiosis; papillomatosis; lichenoid inflammatory infiltrate; presence of intraepidermal/subepidermal cleavage plan with formation of a bulla). Eighteen patients were included in this study (11 males, 7 females, median age 64.5). LC-OCT demonstrated an overall concordance with histology of 77.8%, with a Cohen's Kappa of 0.69 (P < 0.0001). Sensitivity exceeded 70%, and specificity was ≥88.2%. The Area Under the Curve (AUC) ranged from 0.9 to 1 for psoriasis and lichenoid eruption and from 0.7 to 0.9 for eczematous and bullous eruption. LC-OCT appears to be a promising tool for the early differential diagnosis of adverse skin reactions related to targeted therapy and immunotherapy, offering the potential to avoid skin biopsies in fragile cancer patients.

Label-Free Non-Contact Vascular Imaging using Photon Absorption Remote Sensing.

Functional vascular imaging is a critical method for early detection and prevention of disease. Established non-contact vascular imaging techniques capture predominantly structural information. In this study, a novel non-contact label-free in vivo Photon Absorption Remote Sensing (PARS) microscope is developed for structural and functional vascular imaging. The presented in vivo PARS microscope captures the endogenous absorption of green (532nm) light to form a complete picture of vasculature and surrounding tissues. Imaging system repeatability is enhanced through robust transient absorption signal extraction, and state-of-the-art real-time alignment methods. Detailed imaging of vascular structure is demonstrated through in vivo microscopy of two established animal models: mouse ear and chicken embryo. Preliminary functional contrast is realized through video rate imaging of red blood cell dynamics in the capillary networks of chicken embryos. The presented in vivo PARS microscope successfully captures detailed structural and functional vascular contrast. This innovative non-contact label-free imaging technique holds promise as a tool for preventative medical care, as functional change often precedes structural change.

New fast imaging techniques for electrical source transient electromagnetic data: Approaches and application

The rapid imaging of electrical source transient electromagnetic (TEM) data involves two essential processes: the calculation of apparent resistivity and the conversion of time to depth. Traditionally, the definition of full-time apparent resistivity is defined by considering solely the vertical magnetic field, which is predicated on the monotonic relationship between the resistivity and the electromagnetic field response. Based on the concept of peak time, we have developed distinct methodologies for calculating the apparent resistivity for both the horizontal electric field (ex) and the vertical induced voltage (vz), which demonstrated accuracy across the entire time range examined. We also introduced a formula to address discrepancies in apparent resistivity arising from the non-dipole size effect of the source, thereby ensuring that the algorithm can adapt to any transmitting and receiving configuration. Furthermore, we provided straightforward and precise time-depth conversion equations applicable to both ex and vz, which facilitate the rapid imaging of observational data. Multiple numerical examples were employed to illustrate the effectiveness and robustness of this approach. Finally, we applied this imaging technique to the data processing of actual measured data from a survey area conducted in Ningxia Province, and the imaging results accurately reflected the distribution of the electrical structure of the subsurface strata. The innovative imaging technique presented in this study holds considerable potential for the expedited processing and analysis of ground-based and semi-aerial electrical source transient electromagnetic survey data, which are widely employed in contemporary applications.

Imaging in France: 2024 Update.

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Advancing automobile dry clutch fault diagnosis through innovative imaging techniques and Vision transformer integration

The study investigates the significance of clutch condition monitoring in automotive transmissions to preempt mechanical failures, enhance efficiency, and mitigate risks to human safety and maintenance costs. It explores the integration of Vision Transformer (ViT) with imaging techniques, such as scalograms, spectrograms, polar plots, radar plots, and Hilbert-Huang transforms, to diagnose faults in dry friction clutches. By transforming vibration signals into image representations and utilizing ViT for fault classification, the study aims to identify the most effective imaging technique and optimal hyperparameters for accurate fault diagnosis. Experimental studies on a test rig with varying fault conditions demonstrate the effectiveness of ViT in diagnosing clutch faults when coupled with different image conversion techniques. The results highlight the potential of integrating spectrogram image processing with ViT, achieving a 100% accuracy in fault diagnosis for clutch systems, thus advancing the analysis of faults in clutch systems.

Multislit gamma camera for external beam radiotherapy assistance: Experimental proof of concept

The orthogonal computed tomography (OrthoCT) concept, based on orthogonal ray imaging, is a low-dose imaging technique currently under investigation to potentially aid in external-beam radiation therapy treatments. This technique involves detecting radiation scattered within the patient and emitted at approximately 90&amp;deg; from the direction of the incoming beam. This scattered radiation can be collected by a 1D-detector system with a multisliced collimator positioned perpendicular to the incident beam axis. Such a system holds promise for on-board imaging with the patient positioned and prepared for treatment, as well as for real-time treatment monitoring. In this study, a multi-slice OrthoCT detector prototype was developed and tested under in-beam irradiation. The system utilizes gadolinium orthosilicate scintillator crystals coupled to photomultiplier tubes and a collimator made of lead slices. Experimental measurements were conducted using a heterogeneous phantom made of acrylic with an air cavity inside. The phantom was irradiated with a TrueBeam linac operating at 6 MV in the flattening-filter-free mode. The findings of this study indicate that this innovative imaging technique is capable of providing morphological images of the phantom. This accomplishment is achieved without the need to rotate the X-ray source around the object to be irradiated, demonstrating the feasibility of such a system.

Integration of spectral computed tomography in arterial imaging.

Artery imaging, a crucial component in the diagnosis and management of vascular disease, assumes a significant role in the field of medical research. Utilizing advanced imaging modalities such as computed tomography (CT) and magnetic resonance angiography (MRA), artery imaging provides detailed insights into blood flow, detecting conditions such as atherosclerosis, aneurysms, and other vascular abnormalities with high precision. Spectral CT is an innovative imaging technique that goes beyond traditional CT scans, capturing data at multiple energy levels to provide detailed insights into the composition of tissues and materials within the scanned region. Notably, recent studies and clinical applications have underscored the diagnostic advantages offered by spectral CT in the detection and characterization of various arterial diseases. The integration of spectral CT into the realm of arterial imaging presents a promising avenue for improving the diagnosis and management of vascular disease. This comprehensive review aims to provide an extensive overview, delving into the potential benefits, optimization, challenges, and future of spectral CT in arterial imaging.

In vivo multiscale analyses of spring viremia of carp virus (SVCV) infection: From model organism to target species.

Spring viremia of carp virus (SVCV) has a broad fish host spectrum and is responsible for a disease that generally affects juvenile fishes with a mortality rate of up to 90%. In the absence of treatments or vaccines against SVCV, the search for prophylactic or therapeutic solutions is thus relevant, particularly to identify solutions compatible with mass vaccination. In addition to being a threat to aquaculture and ecosystems, SVCV is a unique pathogen to study virus-host interactions in the zebrafish model. Establishing the first reverse genetics system for SVCV and the design of recombinant SVCV (rSVCV) expressing fluorescent or bioluminescent proteins adds a new dimension for the study of these interactions using innovative imaging techniques. The infection by bath immersion of zebrafish larvae with rSVCV expressing mCherry allows us to define the first SVCV replication sites and the host innate immune responses using different transgenic lines of zebrafish. The fins were found as the main initial sites of infection in both zebrafish and carp, its natural host. Hence, new insights into the physiopathology of SVCV infection have been described. We report that neutrophils are recruited at the sites of infection and persist up to the death of the animal leading to an uncontrolled inflammation correlated with the expression of the pro-inflammatory cytokine IL1β. Tissue damage was observed at the site of initial replication, a likely consequence of virus-induced injury or the pro-inflammatory response. Interestingly, SVCV infection by bath immersion triggers a persistent pro-inflammatory response rather than activation of the antiviral IFN signaling pathway as observed following intravenous injection, highlighting the importance of the route of infection on the progression of pathogenicity. Thus, this model of zebrafish larvae infection by rSVCV offers new perspectives to study in detail virus-host interactions and to discover new prophylactic or therapeutic solutions.

Prototype Cherenkov detector characterization for muon tomography applications

Muography is an innovative imaging technique using naturally produced elementary particles – atmospheric muons – used to determine the distribution of density inside massive objects. The modification of the particles flux – by scattering or absorption – reflects the contrasts in density within the medium and therefore offers the possibility for an image of the crossed volumes. In most muography setups the imaging process is based on the tracking of the particles which accounts for the absorption or the scattering of the muons trajectories. Neither the energy nor the identity of the particles (the so-called PID) is exploited since this information traditionally relies on the use of calorimeters and/or high intensity magnetic fields. Both these techniques hinder detector portability which in the case of muography is important and this renders them impractical for its purpose. In this paper we characterize the performance of a simple and small water Cherenkov detector capable of providing some insights on the energy of muons and the PID for the crossing particles that could potentially improve the background rejection for a muography survey when operating in conjunction with a muon telescope. We tested a prototype of such water Cherenkov detector in combination with two small muon hodoscopes. Both systems are using the same opto-electronics chain – optical fibers and pixellized photosensors – and the same data acquisition (DAQ) readout system which ensures an easy integration and implementation within presently running systems. This article presents the test setup, the detector response to cosmic muons and its performance evaluation against a basic simulation of its geometry and detection principle.

DIABETES AND PERIODONTAL DISEASE: INTERCONNECTED PATHOPHYSIOLOGY AND CLINICAL IMPLICATIONS: A COMPREHENSIVE REVIEW

The bidirectional relationship between diabetes mellitus (DM) and periodontal disease is well-documented, with poor glycemic control exacerbating periodontal inflammation and vice versa. Novel therapies, including anti-inflammatory agents, antioxidants, and biologics, show promise in reducing systemic inflammation and improving glycemic control. Advances in identifying salivary biomarkers such as miRNAs 146a/b and 155, IL-1β, MMP8, and IL-6 have improved early detection of periodontitis in diabetic patients. Additionally, innovative imaging techniques like Raman spectroscopy and multiplex hand-held biosensors have enhanced diagnostic accuracy. Longitudinal studies and clinical trials remain essential to validate the long-term benefits and safety of new biomarkers and therapies. Recent studies highlight the importance of integrated care and interdisciplinary collaboration between dental and medical professionals to effectively manage these interrelated conditions. Future research should focus on understanding the biological pathways linking DM and periodontal disease, with a particular emphasis on the roles of inflammatory cytokines, oxidative stress, and the microbiome. Public health initiatives should aim to increase awareness of the bidirectional relationship between DM and periodontal disease through educational campaigns and community-based screening programs. Policy recommendations should encourage integrated health services and interdisciplinary training programs. The integration of artificial intelligence and machine learning in diagnostic tools offers potential for early detection and personalized treatment plans, further improving patient outcomes. Addressing these research gaps through continued investigation and technological innovation is crucial for enhancing the prevention, diagnosis, and management of diabetes and periodontal disease. These efforts will ultimately lead to better health outcomes and quality of life for affected individuals.

Assessment of Tricuspid Regurgitation by Cardiac Magnetic Resonance Imaging: Current Role and Future Applications.

Tricuspid regurgitation (TR) is a prevalent valvular disease with a significant mortality rate. The evaluation of TR severity and associated right heart remodeling and dysfunction is crucial to determine the optimal therapeutic strategy and to improve prognosis. While echocardiography remains the first-line imaging technique to evaluate TR, it has many limitations, both operator- and patient-related. Cardiovascular magnetic resonance imaging (CMR) has emerged as an innovative and comprehensive non-invasive cardiac imaging technique with additional value beyond routine echocardiographic assessment. Besides its established role as the gold standard for the evaluation of cardiac volumes, CMR can add important insights with regard to valvular anatomy and function. Accurate quantification of TR severity, including calculation of regurgitant volume and fraction, can be performed using either the well-known indirect volumetric method or novel 4D flow imaging. In addition, CMR can be used to assess the impact on the right heart, including right heart remodeling, function and tissue characterization. Several CMR-derived parameters have been associated with outcome, highlighting the importance of multi-modality imaging in patients with TR. The aim of this review is to provide an overview of the current role of CMR in the assessment and management of patients with TR and its future applications.

Beyond Blood Sugar: How Left Atrium Strain Predicts Cardiac Outcomes in Type 2 Diabetes.

Speckle tracking echocardiography is an innovative imaging technique that evaluates myocardial motion, including the function of the left atrium (LA). The assessment of the left atrium's function across its dimensions can have diagnostic and prognostic roles in various cardiovascular conditions. Left atrial strain has been recognized as a valuable predictor of mortality and cardiovascular incidents in the general population across various conditions. For individuals with type 2 diabetes mellitus (T2DM), left atrial dysfunction, as gauged by speckle tracking echocardiography, appears particularly prognostic. Parameters such as peak atrial longitudinal strain (PALS) and left atrial stiffness have been linked with heightened risks of severe cardiovascular events, including atrial fibrillation (AF), heart failure (HF) hospitalizations, or mortality. Consequently, recognizing left atrial dysfunction early is crucial for accurate diagnosis, guiding treatment choices, comprehensive patient management, and prognosis evaluation. Using two-dimensional (2D) speckle tracking echocardiography, results from recent studies report that treatment with empagliflozin significantly enhanced LA function in patients with type 2 diabetes mellitus, improving left atrial strain (LAS) contraction and reservoir values. Furthermore, treatments with glucagon-like peptide-1 (GLP)-1 receptor agonists and sodium-glucose cotransporter-2 (SGLT-2) inhibitors were shown to improve LA reservoir strain more effectively than insulin alone, suggesting their potential in reducing cardiovascular complications in T2DM patients. This narrative review further addresses ongoing challenges and potential enhancements needed to boost the clinical value of left atrium strain, emphasizing its significance in managing and improving outcomes for diabetic patients.

Diagnosis and Treatment of Spontaneous Intracranial Hypotension: Role of Epidural Blood Patching.

This review focuses on the challenges of diagnosing and treating spontaneous intracranial hypotension (SIH), a condition caused by spinal CSF leakage. It emphasizes the need for increased awareness and advocates for early and thoughtful use of empirical epidural blood patches (EBPs) in suspected cases. SIH diagnosis is hindered by variable symptoms and inconsistent imaging results, including normal brain MRI and unreliable spinal opening pressures. It is crucial to consider SIH in differential diagnoses, especially in patients with connective tissue disorders. Early EBP intervention is shown to improve outcomes. SIH remains underdiagnosed and undertreated, requiring heightened awareness and understanding. This review promotes proactive EBP use in managing suspected SIH and calls for continued research to advance diagnostic and treatment methods, emphasizing the need for innovative imaging techniques for accurate diagnosis and timely intervention.

Advances in preclinical approaches for intravesical therapy of bladder cancer.

The purpose of this review is to explore new strategies to treat bladder cancer. This article addresses challenges and opportunities in intravesical therapy of bladder cancer. The review examines the latest advances in the development of preclinical approaches for intravesical therapy of bladder cancer. It discusses strategies to improve drug delivery efficiency by using synthesized diverse carriers. Immunotherapy with protein aggregate magnesium-ammonium phospholinoleate-palmitoleate anhydride has been shown to be more effective than intravesical Bacillus Calmette-Guerin. Novel drug delivery systems such the urinary drug-disposing strategy and intravesical nanoparticle formulations improve the drug delivery efficiency while minimizing adverse reactions. Innovative imaging techniques using near-infrared fluorescence probes and multifunctional nano-transformers enable real-time detection and targeted therapy in bladder cancer treatment. Treatment of bladder cancer is clinically challenging. However, recent progress in drug delivery technologies shows promise. Optimizing these technologies helps improve patient outcomes, and facilitates clinical translation of different treatment modalities.

An Innovative Apical-4-Chamber-long-axis Imaging Approach Precisely Tracks Progressive Deterioration of Mouse Ventricles, Atria, and Atrioventricular Valves

Transthoracic echocardiography stands as the primary non-invasive method for cardiac function evaluation in clinical settings. It’s widely used to assess chamber sizes, heart wall integrity, as well as the hemodynamic performance of the left ventricle (LV), right ventricle (RV), atria, and valves. However, applying comprehensive echocardiography assessments to mice has been challenging, primarily due to diffculties in obtaining on-axis apical 4-chamber views; most mouse studies have thus been restricted to evaluating the LV using short-axis M-mode assays. To overcome this limitation, we’ve recently developed a novel methodology to consistently obtain high-quality apical 4-chamber-long-axis (A4CLAX) view images of mouse heart. This advancement permits a range of clinically relevant functional assessments, including Long Axis Biplane (LAX-BP) assay, which has been shown to surpasses M-mode in estimating LV function. In this study, we delve into the breadth of comprehensive echocardiography assessments made possible for mice through the A4CLAX imaging approach. We performed a severe transverse aortic constriction (TAC) surgery on mice and monitored the pathological development in their hearts post-surgery. Alongside the expected hypertrophy, the LAX-BP assay revealed LV volumetric dilation as early as 1-week after TAC surgery Indicative of decompensated heart failure; however, m-mode was not able to pick up on this early dilation due to its lack of longitudinal assessment and inconsistent measurements of EDV and ESV. The apical 4 chamber view significantly improved the consistency and reliability of trans mitral and pulmonary vein doppler recordings and enabled us to reliably estimate the pressure relationships of the LV and Left Atrial (LA) pressure, which is consistent with the LAX-BP detected LV decompensation. Additionally, the high clarity of the 4 chamber images achieved improved visualization of both mitral and tricuspid valve leaflets. This allowed more precise characterization of valvular issues, including mitral regurgitation caused by LV dilatation, as well as identification of less common pathological occurrences like desynchronization of the tricuspid and mitral valve opening. A speckle tracking assay of the Right ventricle (RV) showed that a delayed contraction of the lateral apical RV wall caused the tricuspid valve to not open during the early filling phase, but rather at the atrial kick, leading to this valve desynchrony. This delayed contraction indicates a possible elevation of pulmonary pressure, as evidenced by pulmonary vein doppler indices and the analysis of pulmonary congestion. In conclusion, the innovative A4CLAX imaging technique revolutionizes murine heart analysis, bringing it in line with clinical echocardiography standards allowing for a whole heart analysis approach. It sensitively identifies subtle anomalies, providing a precise characterization of cardiac remodeling and disease progression in mouse hearts. This study has been supported by grants NIH-R01HL139006 and R21OD031965. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Fully dense generative adversarial network for removing artifacts caused by microwave dielectric effect in thermoacoustic imaging

Microwave-induced thermoacoustic (TA) imaging (MTAI) combines pulsed microwave excitation and ultrasound detection to provide high contrast and spatial resolution images through dielectric contrast, which holds great promise for clinical applications. However, artifacts caused by microwave dielectric effect will seriously affect the accuracy of MTAI images that will hinder the clinical translation of MTAI. In this work, we propose a deep learning-based method fully dense generative adversarial network (FD-GAN) for removing artifacts caused by microwave dielectric effect in MTAI. FD-GAN adds the fully dense block to the generative adversarial network (GAN) based on the mutual confrontation between generator and discriminator, which enables it to learn both local and global features related to the removal of artifacts and generate high-quality images. The practical feasibility was tested in simulated, experimental data. The results demonstrate that FD-GAN can effectively remove the artifacts caused by the microwave dielectric effect, and shows superiority in denoising, background suppression, and improvement of image distortion. Our approach is expected to significantly improve the accuracy and quality of MTAI images, thereby enhancing the diagnostic accuracy of this innovative imaging technique.

Light on Alzheimer's disease: from basic insights to preclinical studies.

Alzheimer's disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.

Decoding Material Structures with Scanning Electron Diffraction Techniques

Recent advancements in electron detectors and computing power have revolutionized the rapid recording of millions of 2D diffraction patterns across a grid of probe positions, known as four-dimensional scanning transmission electron microscopy (4D-STEM). These datasets serve as the foundation for innovative STEM imaging techniques like integrated center of mass (iCOM) and symmetry STEM (S-STEM). This paper delves into the application of 4D-STEM datasets for diffraction analysis. We therefore use the term scanning electron diffraction (SED) instead of 4D-STEM in this review. We comprehensively explore groundbreaking diffraction methods based on SED, structured into two main segments: (i) utilizing an atomic-scale electron probe and (ii) employing a nanoscale electron probe. Achieving an atomic-scale electron probe necessitates a significant convergence angle (α &gt; 30 mrad), leading to interference between direct and diffracted beams, distinguishing it from its nanoscale counterpart. Additionally, integrating machine learning approaches with SED experiments holds promise in various directions, as discussed in this review. Our aim is to equip materials scientists with valuable insights for characterizing atomic structures using cutting-edge SED techniques.

Diagnosis of skin lesion using shift-invariant network and an improved grey wolf optimizer

The global incidence of skin cancer has been rising, resulting in increased mortality and morbidity if left untreated. Accurate diagnosis of skin malignancies is crucial for early intervention through excision. While various innovative medical imaging techniques, such as dermoscopy, have improved the way we examine skin cancers, the progress in medical imaging for identifying skin lesions has not kept pace. Skin lesions exhibit diverse visual features, including variations in size, shape, boundaries, and artifacts, necessitating an efficient image-processing approach to assist dermatologists in decision-making. In this research, we propose an automated skin lesion classifier called GreyNet, which utilizes optimized convolutional neural networks (CNNs) or shift-invariant networks (SIN). GreyNet comprises three components: (i) a trained fully deep CNN for semantic segmentation, relating input images to manually labeled standard scans; (ii) an enhanced dense CNN with global information exchange and adaptive feature salvaging module to accurately classify each pixel in histopathological scans as benign or malignant; and (iii) a binary grey wolf optimizer (BGWO) to improve the classification process by optimizing the network’s hyperparameters. We evaluate the performance of GreyNet in terms of lesion segmentation and classification on the HAM10000 database. Extensive empirical results demonstrate that GreyNet outperforms existing lesion segmentation methods, achieving improved dice similarity score, volume error, and average processing time of 1.008±0.009, 0.903±0.009%, and 0.079±0.010 s, respectively. Moreover, GreyNet surpasses other skin melanoma classification models, exhibiting improved accuracy, precision, specificity, sensitivity, false negative rate, false positive rate, and Jaccard similarity score (JSS) of 96.5%, 97%, 96.2%, 92.1%, 3.8%, 3%, and 89.5%, respectively. Based on our experimental analysis, we conclude that GreyNet is an efficient tool to aid dermatologists in identifying skin melanoma.

New perspectives on advances in diagnosis through imaging in chronic respiratory diseases: a systematic literature review

Background: Chronic respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, and cystic fibrosis, present substantial global health challenges. This systematic review explores recent advances in imaging-based diagnostic methods for these conditions, emphasizing high-resolution computed tomography (HRCT), magnetic resonance imaging (MRI), positron emission tomography (PET), and artificial intelligence (AI). Methodology: A systematic search of databases identified studies published in the last five years, focusing on innovative imaging techniques for chronic respiratory diseases. Inclusion criteria emphasized diagnostic accuracy and advancements in imaging modalities. Results: Seven studies were included, covering interventions in intensive care, mesenchymal stem cell therapy for COVID-19-induced acute respiratory distress syndrome (ARDS), endovascular treatment for aortic arch aneurysms, and lung cancer screening. MSC therapy demonstrated positive outcomes in ARDS patients, while endovascular repair showed technical success. LungSEARCH highlighted the effectiveness of lung cancer screening in high-risk populations. Discussion: Recent imaging technologies, including HRCT, MRI, PET, and AI, have revolutionized chronic respiratory disease diagnosis. The review emphasizes their clinical applications, impact on patient outcomes, and potential for personalized medicine. AI enhances image analysis accuracy, yet challenges like cost and interpretation discrepancies persist. Conclusion: Imaging technologies, particularly HRCT, MRI, PET, and AI, show promise in improving diagnostic accuracy and personalized treatment for chronic respiratory diseases. Collaboration among healthcare professionals, researchers, and industry stakeholders is crucial for addressing challenges and ensuring widespread access to advanced diagnostic tools. Future directions involve refining imaging methods for routine clinical integration, advancing patient care, and reducing the burden of respiratory diseases.