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Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes. [ABSTRACT FROM AUTHOR]

This research explores the use of the pepN activity fluorescent sensor DCM-Ala in bacterial biofilms, emphasizing its significance due to the critical role of biofilms in various biological processes. Advanced imaging techniques were employed to visualize pepN activity, introducing a novel approach to examining biofilm maturity. We found that the overexpression of pepN increases the ability of E. coli to form biofilm. The findings demonstrate varying levels of pepN activity throughout biofilm development, suggesting potential applications in biofilm research and management. The results indicate that the fluorescent emission from this sensor could serve as a reliable indicator of biofilm maturity, and the imaging techniques developed could enhance our understanding and control of biofilm-related processes. This work highlights the importance of innovative methods in biofilm study and opens new avenues for utilizing chemical emissions in biofilm management. [ABSTRACT FROM AUTHOR]

Simple Summary: As breast cancer rates rise, more patients choose breast reconstruction. Autologous breast reconstruction (ABR) may be more cost-effective and offer superior patient quality of life compared to prosthetic implant-based reconstruction but it involves heightened surgical complexity and extended operative time. Imaging facilitates surgical planning, patient selection, and reduces the time spent in the operating room, thereby enhancing the likelihood of surgical success and decreasing complication rates. Advanced imaging has also spurred innovative surgical techniques aimed at improving aesthetic outcomes and minimizing donor-site morbidity, including robotic-assisted deep inferior epigastric flap perforator (DIEP) flap harvest and stacked microsurgical flaps. The evolution of imaging actively shapes clinical management in the field. Ultrasonography (US), computed tomography angiography (CTA), and magnetic resonance angiography (MRA) stand out as the most extensively researched imaging modalities for ABR. Ongoing advancements include "real-time" angiography and three-dimensional (3D) surface imaging, and future prospects incorporate augmented or virtual reality (AR/VR) and artificial intelligence (AI). These technologies may further enhance perioperative efficiency, reduce donor-site morbidity, and improve surgical outcomes in ABR. [ABSTRACT FROM AUTHOR]

In previous studies, the incidence of traumatic intracranial aneurysms (TICAs) after civilian gunshot wound to the head (cGSWH) was ∼3%. Given the use of delayed vessel imaging, we hypothesize that a significant fraction of TICAs is missed on initial non-contrasted scans. This study was designed to characterize acute TICAs using admission computed tomographic angiography (aCTA) in cGSWH. Over the period from 2017 to 2022, 341 patients were admitted to R. Adams Cowley Shock Trauma Center with cGSWH; 136 subjects had aCTA ∼3 (standard deviation [SD] 3.5) h post-injury. Demographics, clinical findings, imaging techniques, endovascular/surgical interventions, and outcomes were analyzed. Mean age was 34.7 (SD 13.1), male:female ratio was 120:16. Average admission Glasgow Coma Scale (GCS) score was 6 (SD 3.9). Entry site was frontal in 41, temporal in 55, parietal in 18, occipital in 6, suboccipital in 9, temporo-parietal in 1, and frontobasal-temporal in 6. Projectiles crossed multiple dural compartments in 76 (55%) patients. 35 TICAs were diagnosed in 28 subject: 24 were located along the middle cerebral artery (MCA), 6 in the anterior cerebral artery (ACA), 3 in the internal carotid artery (ICA), 1 in the posterior cerebral artery (PCA), and 1 in the middle meningeal artery (MMA). Eleven TICAs resolved spontaneously in nine patients. Eight aneurysms were treated by endovascular means, two via combined endovascular/open approaches. Forty-nine patients died, 10 of whom had 15 TICAs. Eighty patients developed intracerebral hematoma s (ICHs). Regression models showed that the presence of an ICH was the main predictor of TICA in cGSWH. Larger ICHs (average 22.3 cc vs. 9.4 cc in patients with and without aneurysms, respectively) in patients with cGSWH suggest hidden TICAs. Nearly 30% of patients had spontaneous resolution within 1 week. When CTA was performed acutely, TICAs were 10 times more frequent in cGSWH than in previous literature, and those patients were more likely to proceed to surgery. Almost one third of patients in this series died from the devastating effects of cGSWH. [ABSTRACT FROM AUTHOR]

Self‐assembled peptides have been among the important biomaterials due to its excellent biocompatibility and diverse functions. Over the past decades, substantial progress and breakthroughs have been made in designing self‐assembled peptides with multifaceted biomedical applications. The techniques for quantitative analysis, including imaging‐based quantitative techniques, chromatographic technique and computational approach (molecular dynamics simulation), are becoming powerful tools for exploring the structure, properties, biomedical applications, and even supramolecular assembly processes of self‐assembled peptides. However, a comprehensive review concerning these quantitative techniques remains scarce. In this review, recent progress in techniques for quantitative investigation of biostability, cellular uptake, biodistribution, self‐assembly behaviors of self‐assembled peptide etc., are summarized. Specific applications and roles of these techniques are highlighted in detail. Finally, challenges and outlook in this field are concluded. It is believed that this review will provide technical guidance for researchers in the field of peptide‐based materials and pharmaceuticals, and facilitate related research for newcomers in this field. [ABSTRACT FROM AUTHOR]

Abstract Reverse engineering, a process of extracting information or knowledge from existing objects or systems, has gained significant attention in various fields, including medicine. This article presents a comprehensive literature review and a proof of concept on the application of reverse engineering in the medical field. The review particularly focuses on the reverse engineering process, available technologies, and their specific relevance to the medical domain. Various imaging techniques, such as computed tomography and magnetic resonance imaging, are discussed in respect of their integration with reverse engineering methodologies. Furthermore, the article explores the wide range of medical applications facilitated by reverse engineering, including prosthetics, implants, tissue engineering, and surgical planning. The potential of reverse engineering to enhance personalized medicine and patient-specific treatments is highlighted. A detailed proof of concept focusing on femur reconstruction is a significant component of the article. The proof of concept showcases the practical implementation of reverse engineering techniques to assist in designing and manufacturing precise custom-made implants and bone reconstruction. It emphasizes the integration of patient-specific anatomical data obtained through imaging technologies and the subsequent utilization of reverse engineering processes for anatomical reconstruction (solid modeling). Overall, this article provides an extensive overview of reverse engineering in medical applications, incorporating a literature review and a case study. The findings highlight reverse engineering’s potential to advance medical practices, improve patient outcomes, and foster personalized treatments. The review emphasizes the reverse engineering process, available technologies, and their specific relevance to the medical field, as well as their potential and effectiveness in advancing medical practices.

Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes.

Abstract Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.

Over the past decades, the survival rates of patients with cancer have significantly increased owing to advancements in cancer treatment strategies. Radiotherapy has become an indispensable treatment modality for thoracic tumors. While it offers benefits in treating or even potentially curing cancer, thoracic radiotherapy exposes neighboring heart tissues to ionizing radiation, elevating the risk of radiation-induced heart disease (RIHD). Despite improvements in radiotherapy techniques that have reduced the incidence of RIHD, complete avoidance of heart radiation exposure remains a challenge. Cohort studies involving atomic bomb survivors and individuals with occupational radiation exposure, even at relatively low doses, have reported a significant increase in RIHD risks. The pathological mechanisms underlying RIHD have been extensively reviewed. At present, imaging techniques and traditional cardiac biomarkers are the primary methods to diagnose RIHD, with ongoing efforts to explore additional promising markers for predicting and monitoring RIHD. Moreover, traditional and novel therapeutic strategies are being actively explored to prevent or alleviate RIHD. Insights gained from therapeutic advancements in other organ systems or heart diseases caused by different factors can provide valuable ideas for RIHD management. This review discusses the recent advancements in the diagnosis and treatment of RIHD.

Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes. [ABSTRACT FROM AUTHOR]

This case concentrates on the persistent left superior vena cava (PLSVC), a rare vascular anomaly which contributes to central venous catheter (CVC) misplacement. A 72-year-old woman with renal insufficiency presented to the hospital with recurrent bleeding from her permanent CVC device placed in the right common jugular vein. An initial attempt to replace the device was unsuccessful, necessitating the placement of a secondary catheter in the left jugular vein. Shortly after the procedure, the patient developed swelling of the face and neck. Further diagnostic imaging, including a chest radiograph and computed tomography (CT), revealed CVC misplacement in the PLSVC and coronary sinus, thrombosis of the common jugular vein, and a posterior mediastinal hematoma. Conservative therapy of the mediastinal hematoma was implemented and proved effective in this case. A temporary CVC was inserted into the left femoral vein. Two months later, the catheter underwent further dysfunction and a decision was made to place a long-term permanent CVC via the right femoral vein. The patient is currently awaiting an arteriovenous fistula for dialysis use. This case emphasizes the importance of radiological techniques for CVC procedural placement, as well as the detection of congenital abnormalities. Providers regularly placing CVCs should have an in-depth knowledge of the possible complications and potential anatomical variations, especially as seen in high-risk patients. [ABSTRACT FROM AUTHOR]

Abstract Self‐assembled peptides have been among the important biomaterials due to its excellent biocompatibility and diverse functions. Over the past decades, substantial progress and breakthroughs have been made in designing self‐assembled peptides with multifaceted biomedical applications. The techniques for quantitative analysis, including imaging‐based quantitative techniques, chromatographic technique and computational approach (molecular dynamics simulation), are becoming powerful tools for exploring the structure, properties, biomedical applications, and even supramolecular assembly processes of self‐assembled peptides. However, a comprehensive review concerning these quantitative techniques remains scarce. In this review, recent progress in techniques for quantitative investigation of biostability, cellular uptake, biodistribution, self‐assembly behaviors of self‐assembled peptide etc., are summarized. Specific applications and roles of these techniques are highlighted in detail. Finally, challenges and outlook in this field are concluded. It is believed that this review will provide technical guidance for researchers in the field of peptide‐based materials and pharmaceuticals, and facilitate related research for newcomers in this field.

Early-stage rheumatoid arthritis (RA) often harbors a hidden threat: sarcopenia, a silent contributor to osteoporosis and fractures. Assessing muscle mass and quality, particularly during active RA periods when joint mobility hinders strength and function evaluations, becomes crucial. Imaging techniques emerge as invaluable tools in this diagnostic puzzle, offering accurate quantification of muscle status in RA patients. This article delves into advancements of various imaging modalities in unraveling RA-related sarcopenia.

UNLABELLED: Vitiligo is a multifaceted autoimmune depigmenting disorder affecting around 0.5 to 2.0% of individuals globally. Standardizing diagnosis and therapy tracking can be arduous, as numerous clinical evaluation methods are subject to interobserver variability and may not be validated. Therefore, there is a need for diagnostic tools that are objective, dependable, and preferably non-invasive. AIMS: This systematic review provides a comprehensive overview of the non-invasive objective skin measurement methods that are currently used to evaluate the diagnosis, severity, and progression of vitiligo, as well as the advantages and limitations of each technique. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used for the systematic review. Scopus, Embase, Cochrane Library, and Web of Science databases were comprehensively searched for non-invasive imaging and biophysical skin measuring methods to diagnose, evaluate the severity of, or monitor the effects of vitiligo treatment. The risk of bias in included articles was assessed using the QUADAS-2 quality assessment scale. RESULTS: An extensive literature search resulted in 64 studies for analysis, describing eight imaging techniques (reflectance confocal microscopy, computer-aided imaging analysis, optical coherence tomography, infrared photography, third-harmonic generation microscopy, multiphoton microscopy, ultraviolet light photography, and visible light/digital photograph), and three biophysical approaches (dermoscopy, colorimetry, spectrometry) used in diagnosing and assessing vitiligo. Pertinent information about functionality, mechanisms of action, sensitivity, and specificity was obtained for all studies, and insights into the strengths and limitations of each diagnostic technique were addressed. Methodological study quality was adequate; however, statistical analysis was not achievable because of the variety of methods evaluated and the non-standardized reporting of diagnostic accuracy results. CONCLUSIONS: The results of this systematic review can enhance clinical practice and research by providing a comprehensive overview of the spectrum of non-invasive imaging and biophysical techniques in vitiligo assessment. Studies with larger sample sizes and sound methodology are required to develop verified methods for use in future practice and research. SYSTEMATIC REVIEW REGISTRATION: (PROSPERO) database, (CRD42023395996).

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Background: Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods: The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results: Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/ NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion: Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified. [ABSTRACT FROM AUTHOR]

Chronic kidney disease (CKD) is a global health issue with a rising prevalence, affecting 697.5 million people worldwide. It imposes a substantial burden, contributing to 35.8 million disability-adjusted life years (DALYs) and 1.2 million deaths in 2017. The mortality rate for CKD has increased by 41.5% between 1990 and 2017, positioning it as a significant cause of global mortality. CKD is associated with diverse health complications, impacting cardiovascular, neurological, nutritional, and endocrine aspects. One prominent complication is CKD–mineral and bone disorder (MBD), a complex condition involving dysregulation of bone turnover, mineralization, and strength, accompanied by soft tissue and vascular calcification. Alterations in mineral metabolism, including calcium, phosphate, parathyroid hormone (PTH), vitamin D, fibroblast growth factor-23 (FGF-23), and Klotho, play pivotal roles in CKD-MBD. These disturbances, observed early in CKD, contribute to the progression of bone disorders and renal osteodystrophy (ROD). Vascular calcification (VC) is a key component of CKD-MBD, accelerated by CKD. The pathophysiology involves complex processes in vascular smooth muscle cells and the formation of calciprotein particles (CPP). VC is closely linked to cardiovascular events and mortality, emphasizing its prognostic significance. Various serum markers and imaging techniques, including lateral plain X-ray, Kauppila Score, Adragao Score, and pulse wave velocity, aid in VC detection. Additionally, pQCT provides valuable information on arterial calcifications, offering an advantage over traditional scoring systems. CKD poses a substantial global health burden, and its complications, including CKD-MBD and VC, significantly contribute to morbidity and mortality. Understanding the intricate relationships between mineral metabolism, bone disorders, and vascular calcification is crucial for effective diagnosis and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Background In vitro experiments are critical for understanding the impact of medical devices and techniques on blood vessels and blood flow. However, their interpretation is often limited by anatomical models’ inability to capture the wide range of vessel sizes observed in real‐world practice. The current study aims to address this limitation by describing the distribution of vessel diameters in a real‐world population. Methods This systematic literature review using the PubMed database analyzed cerebral vessel diameters in patients from 2000 to 2022. The diameter measurements of various vessels within the neurovasculature were extracted. Random‐effects meta‐analyses were performed to synthesize vessel diameters across studies. Predicted distributions were generated from the meta‐analytical results. Results Seventy‐six studies were included in the analysis. The M1 segment, internal carotid artery (cervical and communicating segments), A1 segment, V2 segment, V4 segment, and basilar artery had sufficient data for generating predicted distributions of vessel diameters. Predicted mean diameters were as follows: M1 segment, 2.55 ± 0.42 mm (95th interpercentile range [IPR]: 1.71–3.38); internal carotid artery‐cervical segment, 4.74 ± 0.64 mm (95th IPR: 3.49–5.99); internal carotid artery‐communicating segment, 3.40 ± 0.64 mm (95th IPR: 2.15–4.66); A1 segment, 1.89 ± 0.34 mm (95th IPR: 1.23–2.55); V2 segment, 3.36 ± 0.67 mm (95th IPR: 2.05–4.67); V4 segment, 2.42 ± 0.74 mm (95th IPR: 0.98–3.86); and basilar artery, 2.96 ± 0.52 mm (95th IPR: 1.94–3.97). Conclusion Cerebral vessel diameter measurements can vary substantially due to patient‐specific factors and imaging techniques. This literature review highlights the diverse range of vessel sizes observed in different patient populations, emphasizing the need for anatomical models that accurately represent clinical observations.

The spatiotemporal compartmentalization of membrane-associated glycosylphosphatidylinositol-anchored proteins (GPI-APs) on the cell surface regulates their biological activities. These GPI-APs occupy distinct cellular functions such as enzymes, receptors, and adhesion molecules, and they are implicated in several vital cellular processes. Thus, unraveling the mechanisms and regulators of their membrane organization is essential. In polarized epithelial cells, GPI-APs are enriched at the apical surface, where they form small cholesterol-independent homoclusters and larger heteroclusters accommodating multiple GPI-AP species, all confined within areas of approximately 65–70 nm in diameter. Notably, GPI-AP homoclustering occurs in the Golgi apparatus through a cholesterol- and calcium-dependent mechanism that drives their apical sorting. Despite the critical role of Golgi GPI-AP clustering in their cell surface organization and the importance of cholesterol in heterocluster formation, the regulatory mechanisms governing GPI-AP surface organization, particularly in the context of epithelial polarity, remain elusive. Given that the actin cytoskeleton undergoes substantial remodeling during polarity establishment, this study explores whether the actin cytoskeleton regulates the spatiotemporal apical organization of GPI-APs in MDCK cells. Utilizing various imaging techniques (number and brightness, FRET/FLIM, and dSTORM coupled to pair correlation analysis), we demonstrate that the apical organization of GPI-APs, at different scales, does not rely on the actin cytoskeleton, unlike in fibroblastic cells. Interestingly, calcium chelation disrupts the organization of GPI-APs at the apical surface by impairing Golgi GPI-AP clustering, emphasizing the existence of an interplay among Golgi clustering, apical sorting, and surface organization in epithelial cells. In summary, our findings unveil distinct mechanisms regulating the organization of GPI-APs in cell types of different origins, plausibly allowing them to adapt to different external signals and different cellular environments in order to achieve specialized functions.

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize environmental impacts. DPA encompasses various agricultural domains, including pest control, pest management, fertilization, irrigation management, sowing, transplanting, crop health monitoring, yield forecasting, harvesting, and post-harvest stages. Among the enabling technologies for DPA, Unmanned Aerial Vehicles (UAVs) have gained significant attention and market growth. The advancements in control systems, robotics, electronics, and artificial intelligence have led to the development of sophisticated agricultural drones. UAVs offer advantages such as versatility, quick and accurate remote sensing capabilities, and high-quality imaging at affordable prices. Furthermore, the miniaturization of sensors and advancements in nanotechnology enable UAVs to perform multiple operations simultaneously without compromising flight autonomy. However, various variables, including aircraft mass, payload capacity, size, battery characteristics, flight autonomy, cost, and environmental conditions, impact the performance and applicability of UAV systems in agriculture. The economic considerations involve the purchase of drones, equipment, and the expertise of trained pilots for flight management and data processing. Payload capacity, flight range, and financial factors influence agriculture’s choice and implementation of UAVs. The research and patent trends show the growing interest in UAVs for agricultural applications. This paper provides a general review of UAV types, construction architectures, and their diverse applications in agriculture until 2022.

Myocardial infarction is a serious medical condition that requires prompt and accurate diagnosis for effective treatment. In this paper, we present a novel approach for detecting and classifying MI in echocardiogram frames using an enhanced CNN algorithm and an ECV-3D network. The proposed method aims to improve the accuracy and efficiency of MI diagnosis by leveraging advanced deep learning techniques. Through extensive experimentation, we demonstrated the effectiveness of our approach in achieving high accuracy and robustness in MI detection and classification. These results indicate the potential of our method to aid in the early and precise diagnosis of MI, thereby contributing to improved patient outcomes and clinical decision-making. After conducting thorough experimentation, our proposed approach achieved an impressive accuracy of 97.05% in the detection and classification of myocardial infarction in echocardiogram frames. This shows the robustness and reliability of our method, indicating its potential to significantly impact the accurate diagnosis of MI and subsequently improve patient outcomes. Furthermore, the area under the curve attained by our model is 0.82, reaffirming the efficacy of the enhanced CNN algorithm and ECV-3D network in accurately detecting and classifying MI. It is noteworthy that all the parameters utilized in our approach have demonstrated a high level of accuracy, emphasizing the effectiveness of our deep learning techniques in enhancing the diagnostic process for MI. Moreover, the proposed method efficiently process large volumes of echocardiogram frames, making it suitable for real-time clinical applications.

This research explores the use of the pepN activity fluorescent sensor DCM-Ala in bacterial biofilms, emphasizing its significance due to the critical role of biofilms in various biological processes. Advanced imaging techniques were employed to visualize pepN activity, introducing a novel approach to examining biofilm maturity. We found that the overexpression of pepN increases the ability of E. coli to form biofilm. The findings demonstrate varying levels of pepN activity throughout biofilm development, suggesting potential applications in biofilm research and management. The results indicate that the fluorescent emission from this sensor could serve as a reliable indicator of biofilm maturity, and the imaging techniques developed could enhance our understanding and control of biofilm-related processes. This work highlights the importance of innovative methods in biofilm study and opens new avenues for utilizing chemical emissions in biofilm management.

Background: Pulmonary atelectasis is a commonly occurs during anesthesia. In these cases, mechanical ventilation (MV) associated with alveolar recruitment maneuvers (ARMs) and positive end-expiratory pressure (PEEP) is indicated to reverse the condition, ensure adequate gas exchange and improve oxygenation. ARMs can trigger volutrauma, barotrauma, and atelectrauma. Therefore, computed tomography (CT) is the gold-standard method for monitoring lung aeration after ARM. Objective: To evaluate lung volume distribution after stepwise ARMs using computed tomography (CT). Methods: Twelve dogs weighing 24.0 ± 6.0 kg, aged 3 ± 1 years, of both sexes and different breeds, underwent orchiectomy or ovariohysterectomy. The animals were anesthetized and ventilated in volume-controlled mode. ARMs were then initiated by positive end-expiratory pressure (PEEP) titration (5, 10, 15, and 20 cmH2O). CT scans, cardiovascular parameters, and ventilatory mechanics were evaluated at all time points. Data were assessed for normality using the Shapiro-Wilk test and a two-way analysis of variance, followed by a post-hoc Bonferroni test to identify differences between time points. Statistical significance was attributed to a value of p of <0.05. Results: CT demonstrated that the ARMs increased ventilation throughout the lung, including the dependent regions, with volumes that increased and decreased proportionally with PEEP titration. When they reached PEEP 10 and 5 cmH2O descending (d), they remained significantly higher than those in PEEP 0 cmH2O (baseline). Static compliance improved about 40% at PEEP 10d and PEEP 5d compared to baseline. There was an increase in heart rate (HR) from PEEP 15 increasing (i) (74.5%) to PEEP 10d (54.8%) compared to baseline. Mean arterial blood pressure (MABP) decreased approximately 9% from PEEP 15i to PEEP 15d compared to baseline. Conclusion: Lung attenuation and regional and global volumes assessed by CT showed that maximum pulmonary aeration distribution followed by PEEP titration occurred at PEEP 20 cmH2O, maintaining the lungs normoaerated and without hyperaeration. [ABSTRACT FROM AUTHOR]

The pathways through which mature blood cells in the bone marrow (BM) enter the blood stream and exit the BM, hematopoietic stem cells in the peripheral blood return to the BM, and other substances exit the BM are referred to as the marrow–blood barrier (MBB). This barrier plays an important role in the restrictive sequestration of blood cells, the release of mature blood cells, and the entry and exit of particulate matter. In some blood diseases and tumors, the presence of immature cells in the blood suggests that the MBB is damaged, mainly manifesting as increased permeability, especially in angiogenesis. Some imaging methods have been used to monitor the integrity and permeability of the MBB, such as DCE-MRI, IVIM, ASL, BOLD-MRI, and microfluidic devices, which contribute to understanding the process of related diseases and developing appropriate treatment options. In this review, we briefly introduce the theory of MBB imaging modalities along with their clinical applications. [ABSTRACT FROM AUTHOR]

Echocardiographic evaluation of the right side of the heart is limited by inherent difficulties in accessing views, and thus a variety of other diagnostic modalities, including computed tomography, have been proposed for right heart evaluation. The aim of this cross-sectional study was to review previously reported data and add computed tomography as a new tool for assessment of the right side of the heart, using echocardiography as a reference. Physical examination, electrocardiogram, echocardiogram, and thoracic computed tomography images were acquired in 6 healthy dogs. Structural assessments of the right atrium, the right ventricle, and the pulmonary artery were performed. Data from computed tomography were compared with conventional echocardiography. The agreement between the techniques was satisfactory for most of the evaluated parameters. There was no correlation between tomographic variables and weight and heart rate. Males had a higher mean basal right ventricle diameter (20.92 ± 1.45) compared to females (16.84 ± 0.03). There was a statistically significant difference between the medium right ventricle, right atrium, right ventricle free wall, aorta, pulmonary artery, and left ventricle diameters and the right ventricle/ left ventricle ratio between computed tomography and ultrasound. Good repeatability was found for the tomographic analyses, and the coefficients of variation were similar for most variables between the intraobserver and interobserver analyses. Computed tomography-derived measurements are simple to perform and have good repeatability and satisfactory agreement for most of the parameters evaluated on the echocardiogram. [ABSTRACT FROM AUTHOR]

As a sign of chronic kidney disease (CKD) progression, renal fibrosis is an irreversible and alarming pathological change. The accurate diagnosis of renal fibrosis depends on the widely used renal biopsy, but this diagnostic modality is invasive and can easily lead to sampling error. With the development of imaging techniques, an increasing number of noninvasive imaging techniques, such as multipara meter magnetic resonance imaging (MRI) and ultrasound elastography, have gained attention in assessing kidney fibrosis. Depending on their ability to detect changes in tissue stiffness and diffusion of water molecules, ultrasound elastography and some MRI techniques can indirectly assess the degree of fibrosis. The worsening of renal tissue oxygenation and perfusion measured by blood oxygenation level-dependent MRI and arterial spin labeling MRI separately is also an indirect reflection of renal fibrosis. Objective and quantitative indices of fibrosis may be available in the future by using novel techniques, such as photoacoustic imaging and fluorescence microscopy. However, these imaging techniques are susceptible to interference or may not be convenient. Due to the lack of sufficient specificity and sensitivity, these imaging techniques are neither widely accepted nor proposed by clinicians. These obstructions must be overcome by conducting technology research and more prospective studies. In this review, we emphasize the recent advancement of these noninvasive imaging techniques and provide clinicians a continuously updated perspective on the assessment of kidney fibrosis. [ABSTRACT FROM AUTHOR]

Lung neuroendocrine neoplasms (LNENs) are lesions originating from diffuse endocrine cells within the bronchial walls and lung parenchyma. In recent years, there have been significant advances in the diagnosis and therapy of these neoplasms. This paper reviews recent developments in these areas, focusing on the latest research and treatment strategies. In the context of diagnosis, new imaging technologies including high-resolution computed tomography (CT), high-resolution and positron emission tomography-computed tomography (PET-CT) imaging, are providing more precise information on tumor spread and evaluation of metabolic activity. Advances in the field of molecular biomarkers allow a more personalized approach to the diagnosis of LNENs. In the therapeutic area, new targeted drugs and immunotherapy are showing promise in the treatment of LNENs. The development of molecular therapies such as tyrosine kinase inhibitors and somatostatin analogs, is opening up new treatment perspectives, increasing the efficacy of therapy, and improving patient quality of life. The paper also focuses on important research directions and clinical advances in the diagnosis and therapy of LNENs, presenting the current state of knowledge about these rare tumors. The conclusions aim to provide a synthetic view of the latest developments in the field, encouraging further research and improving treatment strategies for LNENs. [ABSTRACT FROM AUTHOR]

Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal subepithelial tumors originating from abnormal proliferation of interstitial cells of Cajal, with worldwide incidence of about 1–2 per 100,000. Herein, we report an unusual case of a 55-year-old man who presented a severe digestive hemorrhage as a rare post-surgical complication after intestinal GIST surgical removal. The patient was admitted to the Emergency Department of our center affected by abdominal epigastric pain. Different imaging techniques were performed leading to the final diagnosis of a GIST and surgical intervention planning. Immediately after intervention the patient developed a severe intestinal hemorrhage. Multidetector computed tomography (MDCT) confirmed the ongoing bleeding and the patient underwent a new intervention to control the hemorrhage. The aim of the paper is to show the different imaging techniques used to assess GIST. MDCT represents the gold standard for diagnosis and in the emergency setting is used to identify post-surgical complications.

Host-pathogen interactions play a critical role in infectious diseases, and understanding the underlying mechanisms is vital for developing effective therapeutic strategies. The visualization and characterization of bacterial proteins within host cells is key to unraveling the dynamics of these interactions. Various protein labeling strategies have emerged as powerful tools for studying host-pathogen interactions, enabling the tracking, localization, and functional analysis of bacterial proteins in real-time. However, the labeling and localization of Salmonella secreted type III secretion system (T3SS) effectors in host cells poses technical challenges. Conventional methods disrupt effector stoichiometry and often result in non-specific staining. Bulky fluorescent protein fusions interfere with effector secretion, while other tagging systems such as 4Cys-FLaSH/Split-GFP suffer from low labeling specificity and a poor signal-to-noise ratio. Recent advances in state-of-the-art techniques have augmented the existing toolkit for monitoring the translocation and dynamics of bacterial effectors. This comprehensive review delves into the bacterial protein labeling strategies and their application in imaging host-pathogen interactions. Lastly, we explore the obstacles faced and potential pathways forward in the realm of protein labeling strategies for visualizing interactions between hosts and pathogens.

The COVID-19 pandemic, caused by a novel coronavirus, has become a global epidemic. Although the reverse transcription-polymerase chain reaction (RT-PCR) test is the current gold standard for detecting the virus, its low reliability has led to the use of CT and X-ray imaging in diagnostics. As limited vaccine availability necessitates rapid and accurate detection, this study applies k-means and fuzzy c-means segmentation to CT and X-ray images to classify COVID-19 cases as either diseased or healthy for CT scans and diseased, healthy, or non-COVID pneumonia for X-rays. Our research employs four open-access, widely-used datasets and is conducted in four stages: preprocessing, segmentation, feature extraction, and classification. During feature extraction, we employ the Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Histogram of Oriented Gradients (HOG). In the classification process, our approach involves utilizing k-Nearest Neighbor (kNN), Support Vector Machines (SVM), and Extreme Learning Machines (ELM) techniques. Our research achieved a sensitivity rate exceeding 99%, which is higher than the 60-70% sensitivity rate of PCR tests. As a result, our study can serve as a decision support system that can help medical professionals make rapid and precise diagnoses with a high level of sensitivity.

The glymphatic system is a newly discovered waste-clearing system that is analogous to the lymphatic system in our central nervous system. Furthermore, disruption in the glymphatic system has also been associated with many neurodegenerative disorders (e.g., Alzheimer’s disease), traumatic brain injury, and subarachnoid hemorrhage. Thus, understanding the function and structure of this system can play a key role in researching the progression and prognoses of these diseases. In this review article, we discuss the current ways to map the glymphatic system and address the advances being made in preclinical mapping. As mentioned, the concept of the glymphatic system is relatively new, and thus, more research needs to be conducted in order to therapeutically intervene via this system.

Considerable progress has been made in our knowledge of the morphological and functional varieties of anchoring junctions. Cell-cell adhesion contacts consist of discrete junctional structures responsible for the mechanical coupling of cytoskeletons and allow the transmission of mechanical signals across the cell collective. The three main adhesion complexes are adherens junctions, tight junctions, and desmosomes. Microscopy has played a fundamental role in understanding these adhesion complexes on different levels in both physiological and pathological conditions. In this review, we discuss the main light and electron microscopy techniques used to unravel the structure and composition of the three cell-cell contacts in epithelial and endothelial cells. It functions as a guide to pick the appropriate imaging technique(s) for the adhesion complexes of interest. We also point out the latest techniques that have emerged. At the end, we discuss the problems investigators encounter during their cell-cell adhesion research using microscopic techniques.

This case concentrates on the persistent left superior vena cava (PLSVC), a rare vascular anomaly which contributes to central venous catheter (CVC) misplacement. A 72-year-old woman with renal insufficiency presented to the hospital with recurrent bleeding from her permanent CVC device placed in the right common jugular vein. An initial attempt to replace the device was unsuccessful, necessitating the placement of a secondary catheter in the left jugular vein. Shortly after the procedure, the patient developed swelling of the face and neck. Further diagnostic imaging, including a chest radiograph and computed tomography (CT), revealed CVC misplacement in the PLSVC and coronary sinus, thrombosis of the common jugular vein, and a posterior mediastinal hematoma. Conservative therapy of the mediastinal hematoma was implemented and proved effective in this case. A temporary CVC was inserted into the left femoral vein. Two months later, the catheter underwent further dysfunction and a decision was made to place a long-term permanent CVC via the right femoral vein. The patient is currently awaiting an arteriovenous fistula for dialysis use. This case emphasizes the importance of radiological techniques for CVC procedural placement, as well as the detection of congenital abnormalities. Providers regularly placing CVCs should have an in-depth knowledge of the possible complications and potential anatomical variations, especially as seen in high-risk patients.

Resumen: La extracción de dispositivos de estimulación cardiaca es una técnica segura en manos expertas, con una tasa de complicaciones entre el 0,5-15%. Estas complicaciones deben ser conocidas y siempre tenidas en cuenta por el operador, por lo que es siempre útil poder prevenirlas o al menos minimizar sus consecuencias.El objetivo de este trabajo es poner en valor la utilidad de las técnicas de imagen como herramientas diagnósticas que nos permiten realizar un abordaje seguro en la extracción de dispositivos, analizando sus características esenciales.La radiografía de tórax convencional aporta información del estado del generador y los electrodos (número, tipo, fijación, estado y recorrido). La tomografía axial computarizada (TAC) nos revela el recorrido intravascular de los electrodos, las eventuales perforaciones en las cámaras cardiacas, una obstrucción en la vena cava superior y, también, la enfermedad asociada. La tomografía por emisión de positrones/TAC (PET/TAC) nos ayuda a diagnosticar en algunos casos una infección incierta. La ecocardiografía intraoperatoria permite un registro dinámico de las cavidades cardiacas, detectando de forma precoz las eversiones bajo tracción del ventrículo derecho y las roturas valvulares o cardiacas que pueden ocurrir durante el procedimiento. La toracoscopia permite además, bajo visión directa el diagnóstico precoz de complicaciones vasculares (subclavias, tronco innominado y cava superior) o cardiacas. Finalmente, con la realidad aumentada obtenemos imágenes en 3D que superponemos con las obtenidas por radioscopia, identificando bucles y adherencias con mucha facilidad.En conclusión, las técnicas de imagen son una ayuda esencial para la prevención de complicaciones durante la extracción percutánea y, en caso de producirse, actuar rápidamente en consecuencia. Abstract: The removal of cardiac pacing devices is a safe technique in experienced hands, with a complication rate between 0.5-15%. These complications should be known and always taken into account by the operator, so it is always useful to prevent them or, at least, minimize their consequences.The aim of this work is to highlight the usefulness of imaging techniques as diagnostic Con tecnología de Editorial Manager® y ProduXion Manager® de Aries Systems Corporation tools that allow us to perform a safe approach in the extraction of devices, analyzing their essential characteristics.Conventional chest X-ray provides information on the state of the generator and electrodes (number, type of electrode, fixation, state and route). Axial computed tomography reveals the intravascular path of the electrodes, possible perforations in cardiac chambers, obstruction in the superior vena cava and associated pathology.Positron emission tomography (PET-CT) helps us to diagnose in some cases an uncertain infection. Intraoperative echocardiography allows a dynamic recording of the cardiac cavities, detecting early eversions under traction of the RV and valvular or cardiac ruptures that may occur during the procedure. Thoracoscopy also allows early diagnosis of vascular (subclavian, innominate trunk and superior cava) or cardiac complications under direct vision. Finally, with Augmented Reality we obtain 3D images that we superimpose with those obtained by fluoroscopy, identifying loops and adhesions very easily.In conclusion, imaging techniques are an essential aid in preventing complications during percutaneous extraction and, should they occur, to act quickly accordingly.

BackgroundPulmonary atelectasis is a commonly occurs during anesthesia. In these cases, mechanical ventilation (MV) associated with alveolar recruitment maneuvers (ARMs) and positive end-expiratory pressure (PEEP) is indicated to reverse the condition, ensure adequate gas exchange and improve oxygenation. ARMs can trigger volutrauma, barotrauma, and atelectrauma. Therefore, computed tomography (CT) is the gold-standard method for monitoring lung aeration after ARM.ObjectiveTo evaluate lung volume distribution after stepwise ARMs using computed tomography (CT).MethodsTwelve dogs weighing 24.0 ± 6.0 kg, aged 3 ± 1 years, of both sexes and different breeds, underwent orchiectomy or ovariohysterectomy. The animals were anesthetized and ventilated in volume-controlled mode. ARMs were then initiated by positive end-expiratory pressure (PEEP) titration (5, 10, 15, and 20 cmH2O). CT scans, cardiovascular parameters, and ventilatory mechanics were evaluated at all time points. Data were assessed for normality using the Shapiro–Wilk test and a two-way analysis of variance, followed by a post-hoc Bonferroni test to identify differences between time points. Statistical significance was attributed to a value of p of

AbstractAs a sign of chronic kidney disease (CKD) progression, renal fibrosis is an irreversible and alarming pathological change. The accurate diagnosis of renal fibrosis depends on the widely used renal biopsy, but this diagnostic modality is invasive and can easily lead to sampling error. With the development of imaging techniques, an increasing number of noninvasive imaging techniques, such as multipara meter magnetic resonance imaging (MRI) and ultrasound elastography, have gained attention in assessing kidney fibrosis. Depending on their ability to detect changes in tissue stiffness and diffusion of water molecules, ultrasound elastography and some MRI techniques can indirectly assess the degree of fibrosis. The worsening of renal tissue oxygenation and perfusion measured by blood oxygenation level-dependent MRI and arterial spin labeling MRI separately is also an indirect reflection of renal fibrosis. Objective and quantitative indices of fibrosis may be available in the future by using novel techniques, such as photoacoustic imaging and fluorescence microscopy. However, these imaging techniques are susceptible to interference or may not be convenient. Due to the lack of sufficient specificity and sensitivity, these imaging techniques are neither widely accepted nor proposed by clinicians. These obstructions must be overcome by conducting technology research and more prospective studies. In this review, we emphasize the recent advancement of these noninvasive imaging techniques and provide clinicians a continuously updated perspective on the assessment of kidney fibrosis.

Some reports in the literature show the advantages of fluoride-containing apatite ceramics over hydroxyapatite (HAP), at least in some aspects. While HAP has been used extensively in the treatment of bone defects, fluoridated apatite has hardly been tested in vivo. In order to verify the biological properties of fluoride-doped apatite and to assess its therapeutic potential, we synthesized fluorapatite (FAP) and applied it as a filling in bone defects of experimental animals (rabbits). The treatment effects were evaluated on extracted bones after 3 and 6 months from implantation using peripheral quantitative computed tomography (pQCT), dual-energy X-ray absorptiometry (DXA), radiography (X-ray) and histological staining. The study proved the integration between FAP and the bone tissue, thus indicating its stimulating effect on new bone formation and mineralization. The results achieved after 3 months of treatment were difficult to interpret unequivocally and suggested the transient delay in FAP integration of bone in comparison with HAP. The reasons for this phenomenon are unclear. Most likely, these differences between FAP and HAP resulted mainly from the different porosities, densities and ionic reactivity of the ceramics, which in our opinion affected their solubility, integration and degree of bone tissue resorption. However, it was shown that 6 months after implantation, similar level of bone defect regeneration was achieved for both FAP and HAP. In this article, we present our hypothesis concerning the basis of this phenomenon. [ABSTRACT FROM AUTHOR]

In the last two decades, forensic pathology and crime scene investigations have seen a rapid increase in examination tools due to the implementation of several imaging techniques, e.g., CT and MR scanning, surface scanning and photogrammetry. These tools encompass relatively simple visualization tools to powerful instruments for performing virtual 3D crime scene reconstructions. A multi-modality and multiscale approach to a crime scene, where 3D models of victims and the crime scene are combined, offers several advantages. A permanent documentation of all evidence in a single 3D environment can be used during the investigation phases (e.g., for testing hypotheses) or during the court procedures (e.g., to visualize the scene and the victim in a more intuitive manner). Advanced computational approaches to understand what might have happened during a crime can also be applied by, e.g., performing a virtual animation of the victim in the actual context, which can provide important information about possible dynamics during the event. Here, we present an overview of the different techniques and modalities used in forensic pathology in conjunction with crime scene investigations. Based on our experiences, the advantages and challenges of an image-based multi-modality approach will be discussed, including how their use may introduce new visualization modalities in court, e.g., virtual reality (VR) and 3D printing. Finally, considerations about future directions in research will be mentioned. [ABSTRACT FROM AUTHOR]

The glymphatic system is a newly discovered waste-clearing system that is analogous to the lymphatic system in our central nervous system. Furthermore, disruption in the glymphatic system has also been associated with many neurodegenerative disorders (e.g., Alzheimer's disease), traumatic brain injury, and subarachnoid hemorrhage. Thus, understanding the function and structure of this system can play a key role in researching the progression and prognoses of these diseases. In this review article, we discuss the current ways to map the glymphatic system and address the advances being made in preclinical mapping. As mentioned, the concept of the glymphatic system is relatively new, and thus, more research needs to be conducted in order to therapeutically intervene via this system. [ABSTRACT FROM AUTHOR]

Featured Application: Telescopes, remote sensing, and surveying instruments, incorporating highly specialized requirements, from a compact design to one with a wide field of view for remote sensing applications. Each may be designed starting from the paraxial optics (first principles), featuring a three-element on-axis system, and using only the paraxial optics as displayed in the Y-Ȳ diagram. The off-axis three-mirror optical system is derived from the classical Cooke triplet or a derivative of the inverse-telephoto lens. By properly arranging an internal reimaging mechanism or altering the location of the optical stop, one can create different versions of three-mirror optical systems. They include very compact configurations and wide field-of-view imagers. Insights into the optical design process, manufacturing, stray light management, and remote sensing applications are presented. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by a novel coronavirus, has become a global epidemic. Although the reverse transcription-polymerase chain reaction (RT-PCR) test is the current gold standard for detecting the virus, its low reliability has led to the use of CT and X-ray imaging in diagnostics. As limited vaccine availability necessitates rapid and accurate detection, this study applies k-means and fuzzy c-means segmentation to CT and X-ray images to classify COVID-19 cases as either diseased or healthy for CT scans and diseased, healthy, or non-COVID pneumonia for X-rays. Our research employs four open-access, widely used datasets and is conducted in four stages: preprocessing, segmentation, feature extraction, and classification. During feature extraction, we employ the Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Histogram of Oriented Gradients (HOG). In the classification process, our approach involves utilizing k-Nearest Neighbor (kNN), Support Vector Machines (SVM), and Extreme Learning Machines (ELM) techniques. Our research achieved a sensitivity rate exceeding 99%, which is higher than the 60-70% sensitivity rate of PCR tests. As a result, our study can serve as a decision support system that can help medical professionals make rapid and precise diagnoses with a high level of sensitivity. [ABSTRACT FROM AUTHOR]

High-resolution optoacoustic imaging at depths beyond the optical diffusion limit is conventionally performed using a microscopy setup where a strongly focused ultrasound transducer samples the image object point-by-point. Although recent advancements in miniaturized ultrasound detectors enables one to achieve microscopic resolution with an unfocused detector in a tomographic configuration, such an approach requires illuminating the entire object, leading to an inefficient use of the optical power, and imposing a trans-illumination configuration that is limited to thin objects. We developed an optoacoustic micro-tomography system in an epi-illumination configuration, in which the illumination is scanned with the detector. The system is demonstrated in phantoms for imaging depths of up to 5 mm and in vivo for imaging the vasculature of a mouse ear. Although image-formation in optoacoustic tomography generally requires static illumination, our numerical simulations and experimental measurements show that this requirement is relaxed in practice due to light diffusion, which homogenizes the fluence in deep tissue layers. [ABSTRACT FROM AUTHOR]

Today there is a rapid development taking place in phenotyping of plants using non-destructive image based machine vision techniques. Machine vision based plant phenotyping ranges from single plant trait estimation to broad assessment of crop canopy for thousands of plants in the field. Plant phenotyping systems either use single imaging method or integrative approach signifying simultaneous use of some of the imaging techniques like visible red, green and blue (RGB) imaging, thermal imaging, chlorophyll fluorescence imaging (CFIM), hyperspectral imaging, 3-dimensional (3-D) imaging or high resolution volumetric imaging. This paper provides an overview of imaging techniques and their applications in the field of plant phenotyping. This paper presents a comprehensive survey on recent machine vision methods for plant trait estimation and classification. In this paper, information about publicly available datasets is provided for uniform comparison among the state-of-the-art phenotyping methods. This paper also presents future research directions related to the use of deep learning based machine vision algorithms for structural (2-D and 3-D), physiological and temporal trait estimation, and classification studies in plants.

Background: Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods: The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results: Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion: Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

Chronic kidney disease (CKD) is a global health issue with a rising prevalence, affecting 697.5 million people worldwide. It imposes a substantial burden, contributing to 35.8 million disability-adjusted life years (DALYs) and 1.2 million deaths in 2017. The mortality rate for CKD has increased by 41.5% between 1990 and 2017, positioning it as a significant cause of global mortality. CKD is associated with diverse health complications, impacting cardiovascular, neurological, nutritional, and endocrine aspects. One prominent complication is CKD–mineral and bone disorder (MBD), a complex condition involving dysregulation of bone turnover, mineralization, and strength, accompanied by soft tissue and vascular calcification. Alterations in mineral metabolism, including calcium, phosphate, parathyroid hormone (PTH), vitamin D, fibroblast growth factor-23 (FGF-23), and Klotho, play pivotal roles in CKD-MBD. These disturbances, observed early in CKD, contribute to the progression of bone disorders and renal osteodystrophy (ROD). Vascular calcification (VC) is a key component of CKD-MBD, accelerated by CKD. The pathophysiology involves complex processes in vascular smooth muscle cells and the formation of calciprotein particles (CPP). VC is closely linked to cardiovascular events and mortality, emphasizing its prognostic significance. Various serum markers and imaging techniques, including lateral plain X-ray, Kauppila Score, Adragao Score, and pulse wave velocity, aid in VC detection. Additionally, pQCT provides valuable information on arterial calcifications, offering an advantage over traditional scoring systems. CKD poses a substantial global health burden, and its complications, including CKD-MBD and VC, significantly contribute to morbidity and mortality. Understanding the intricate relationships between mineral metabolism, bone disorders, and vascular calcification is crucial for effective diagnosis and therapeutic interventions.

Lab-on-a-chip (LOC) is a three-dimensional cell culture platform with a microfluidic flow that biomimics the physiological system of various organs. LOC emerged as a future replacement technology for in vitro cell-based models and in vivo animal models, gaining popularity in the field of physiology, pharmacology, and biology. Nowadays, sensors are incorporated into the LOC system to monitor real-time parameters of the cell and its microenvironment in response to biophysical and/or biochemical stimuli and maturation. A considerable amount of studies has been conducted to detect the mechanical, physical, electrical, and metabolic parameters of engineered organs. This paper aims to provide a comprehensive insight into how the biosensor-implemented LOC platform can be utilized for the analysis of tissue recapitulating systems with a focus on bone remodeling. We describe chip design, basic principles of sensors, and ongoing recent efforts to perform in-line analysis of engineered organoids. This review also presents various imaging techniques used as analytical tools for visualizing LOC.

The performance of asphalt concrete (AC) mixtures depends highly on their internal structure and the interaction of the mixture components under different loading conditions. Imaging techniques provide effective tools that can assess the microstructure and failure mechanisms of materials. Imaging techniques have been used in recent research studies to examine and analyze the evolution of the internal structure of AC mixtures resulting from traffic and environmental loading. Increasing knowledge of the microstructural properties and mechanical behaviour of AC mixtures could improve the design process and enable researchers to develop more accurate prediction models for the long-term performance of pavements. This paper reviews three imaging techniques which were used to characterize the microstructure of AC mixtures. These three imaging techniques are digital camera imaging, scanning electron microscope (SEM) imaging, and X-ray computed tomography (CT) scan. Extensive insight has been presented into these imaging techniques, including their principles, methods, sample preparation, and associated instruments. This review provides guidelines for future research on using these imaging techniques to analyze the microstructure of AC mixtures and assess their long-term performance. [ABSTRACT FROM AUTHOR]