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(1) Background: In digital-technology-assisted nasal defect reconstruction methods, a crucial step involves utilizing computer-aided design to virtually reconstruct the nasal defect's complete morphology. However, current digital methods for virtual nasal defect reconstruction have yet to achieve efficient, precise, and personalized outcomes. In this research paper, we propose a novel approach for reconstructing external nasal defects based on the Facial Mesh Generation Network (FMGen-Net), aiming to enhance the levels of automation and personalization in virtual reconstruction. (2) Methods: We collected data from 400 3D scans of faces with normal morphology and combined the structured 3D face template and the Meshmonk non-rigid registration algorithm to construct a structured 3D facial dataset for training FMGen-Net. Guided by defective facial data, the trained FMGen-Net automatically generated an intact 3D face that was similar to the defective face, and maintained a consistent spatial position. This intact 3D face served as the 3D target reference face (3D-TRF) for nasal defect reconstruction. The reconstructed nasal data were extracted from the 3D-TRF based on the defective area using reverse engineering software. The '3D surface deviation' between the reconstructed nose and the original nose was calculated to evaluate the effect of 3D morphological restoration of the nasal defects. (3) Results: In the simulation experiment of 20 cases involving full nasal defect reconstruction, the '3D surface deviation' between the reconstructed nasal data and the original nasal data was 1.45 ± 0.24 mm. The reconstructed nasal data, constructed from the personalized 3D-TRF, accurately reconstructed the anatomical morphology of nasal defects. (4) Conclusions: This paper proposes a novel method for the virtual reconstruction of external nasal defects based on the FMGen-Net model, achieving the automated and personalized construction of the 3D-TRF and preliminarily demonstrating promising clinical application potential. [ABSTRACT FROM AUTHOR]

Our aim was to provide a comprehensive overview of the existing literature concerning the clinical applications of positron emission computed tomography (PET) with radiopharmaceuticals targeting the translocator protein (TSPO) in gliomas. A literature search for studies about TSPO PET in the last 10 years (from 2013 to February 2023) was carried out on PubMed, Scopus, and Web of Science using the following keywords: "PET" AND "Gliomas" AND "TSPO". The Critical Appraisal Skills Program checklist for diagnostic test studies was used for testing the quality of selected papers. Ten articles were selected, encompassing 314 glioma patients submitted to PET/CT (9/10) or PET/MRI (1/10) with TSPO ligands. Among the various available TSPO tracers, the most frequently used was the third-generation ligand, [18F]-GE-180. TSPO PET results were useful to identify anaplastic transformation in gliomas and for the prognostic stratification of patients bearing homogeneous genetic alterations. When compared to amino-acid PET, TSPO PET with [18F]-GE-180 presented superior image quality and provided larger and only partially overlapping PET-based volumes. Although biased by some issues (i.e., small sample size, most of the studies coming from the same country), preliminary applications of TSPO PET were encouraging. Further studies are needed to define implications in clinical practice and shape the role of TSPO PET for patients' selection for potential TSPO-targeted molecular therapies. [ABSTRACT FROM AUTHOR]

This research aims to review and evaluate the most relevant scientific studies about deep learning (DL) models in the omics field. It also aims to realize the potential of DL techniques in omics data analysis fully by demonstrating this potential and identifying the key challenges that must be addressed. Numerous elements are essential for comprehending numerous studies by surveying the existing literature. For example, the clinical applications and datasets from the literature are essential elements. The published literature highlights the difficulties encountered by other researchers. In addition to looking for other studies, such as guidelines, comparative studies, and review papers, a systematic approach is used to search all relevant publications on omics and DL using different keyword variants. From 2018 to 2022, the search procedure was conducted on four Internet search engines: IEEE Xplore, Web of Science, ScienceDirect, and PubMed. These indexes were chosen because they offer enough coverage and linkages to numerous papers in the biological field. A total of 65 articles were added to the final list. The inclusion and exclusion criteria were specified. Of the 65 publications, 42 are clinical applications of DL in omics data. Furthermore, 16 out of 65 articles comprised the review publications based on single- and multi-omics data from the proposed taxonomy. Finally, only a small number of articles (7/65) were included in papers focusing on comparative analysis and guidelines. The use of DL in studying omics data presented several obstacles related to DL itself, preprocessing procedures, datasets, model validation, and testbed applications. Numerous relevant investigations were performed to address these issues. Unlike other review papers, our study distinctly reflects different observations on omics with DL model areas. We believe that the result of this study can be a useful guideline for practitioners who look for a comprehensive view of the role of DL in omics data analysis. [ABSTRACT FROM AUTHOR]

In medical research and clinical applications, the utilization of MRI datasets from multiple centers has become increasingly prevalent. However, inherent variability between these centers presents challenges due to domain shift, which can impact the quality and reliability of the analysis. Regrettably, the absence of adequate tools for domain shift analysis hinders the development and validation of domain adaptation and harmonization techniques. To address this issue, this paper presents a novel Domain Shift analyzer for MRI (DSMRI) framework designed explicitly for domain shift analysis in multi-center MRI datasets. The proposed model assesses the degree of domain shift within an MRI dataset by leveraging various MRI-quality-related metrics derived from the spatial domain. DSMRI also incorporates features from the frequency domain to capture low- and high-frequency information about the image. It further includes the wavelet domain features by effectively measuring the sparsity and energy present in the wavelet coefficients. Furthermore, DSMRI introduces several texture features, thereby enhancing the robustness of the domain shift analysis process. The proposed framework includes visualization techniques such as t-SNE and UMAP to demonstrate that similar data are grouped closely while dissimilar data are in separate clusters. Additionally, quantitative analysis is used to measure the domain shift distance, domain classification accuracy, and the ranking of significant features. The effectiveness of the proposed approach is demonstrated using experimental evaluations on seven large-scale multi-site neuroimaging datasets. [ABSTRACT FROM AUTHOR]

Suppressor of mother against decapentaplegic (SMAD) family proteins are central to one of the most versatile cytokine signalling pathways in metazoan biology, the transforming growth factor-β (TGF-β) pathway. The TGF-β pathway is widely known for its dual role in cancer progression as both an inhibitor of tumour cell growth and an inducer of tumour metastasis. This is mainly mediated through SMAD proteins and their cofactors or regulators. SMAD proteins act as transcription factors, regulating the transcription of a wide range of genes, and their rich post-translational modifications are influenced by a variety of regulators and cofactors. The complex role, mechanisms, and important functions of SMAD proteins in tumours are the hot topics in current oncology research. In this paper, we summarize the recent progress on the effects and mechanisms of SMAD proteins on tumour development, diagnosis, treatment and prognosis, and provide clues for subsequent research on SMAD proteins in tumours. [ABSTRACT FROM AUTHOR]

Epigenetic Features of cfDNA Progress in cfDNA research has been driven forward rapidly by systematic characterizations of specific DNA mutations across basic and clinical research settings. This momentum has promise to not only accelerate the advent of personalized cancer care based on cfDNA assays but to also unlock the potential of cfDNA as a biomarker for various other diseases and clinical conditions. Oberhofer et al. also discuss cfDNA fragmentomics, but they also explore exciting and rapidly expanding research showing that various other epigenetic and physico-chemical features of cfDNA, such as various types of DNA methylation patterns, post-translational histone modifications, and nucleosome compaction patterns, are often cell- and disease-specific, which can be leveraged to trace the origins of cfDNA molecules. They found a high concordance in the mutational profiles between cfDNA and tissue analysis, indicating that cfDNA may be an ideal biomarker and potentially an alternative method to tissue analysis for the management of PMBL cases [[20]]. [Extracted from the article]

Cardiac magnetic resonance imaging (MRI) is widely used for non-invasive assessment of cardiac morphology, function, and tissue characteristics due to its exquisite soft-tissue contrast. However, it remains time-consuming and requires proficiency, making it costly and limiting its widespread use. Traditional cardiac MRI is inefficient as signal acquisition is often limited to specific cardiac phases and requires complex view planning, parameter adjustments, and management of both respiratory and cardiac motion. Recent efforts have aimed to make cardiac MRI more efficient and accessible. Among these innovations, the free-running framework enables 5D whole-heart imaging without the need for an electrocardiogram signal, respiratory breath-holding, or complex planning. It uses a fully self-gated approach to extract cardiac and respiratory signals directly from the acquired image data, allowing for more efficient coverage in time and space without the need for electrocardiogram gating, triggering, navigators, or breath-holds. This review provides a comprehensive overview of the free-running framework, detailing its history, concepts, recent improvements, and clinical applications. [ABSTRACT FROM AUTHOR]

Background: The HHUS market is very complex due to a multitude of equipment variants and several different device manufacturers. Only a few studies have compared different HHUS devices under clinical conditions. We conducted a comprehensive prospective observer study with a direct comparison of nine different HHUS devices in terms of B-scan quality, device handling, and software features under abdominal imaging conditions. Methods: Nine different HHUS devices (Butterfly iQ+, Clarius C3HD3, D5CL Microvue, Philips Lumify, SonoEye Chison, SonoSite iViz, Mindray TE Air, GE Vscan Air, and Youkey Q7) were used in a prospective setting by a total of 12 experienced examiners on the same subjects in each case and then assessed using a detailed questionnaire regarding B-scan quality, handling, and usability of the software. The evaluation was carried out using a point scale (5 points: very good; 1 point: insufficient). Results: In the overall evaluation, Vscan Air and SonoEye Chison achieved the best ratings. They achieved nominal ratings between "good" (4 points) and "very good" (5 points). Both devices differed significantly (p < 0.01) from the other seven devices tested. Among the HHUS devices, Clarius C3HD3 and Vscan Air achieved the best results for B-mode quality, D5CL Microvue achieved the best results for device handling, and SonoEye Chison and Vscan Air achieved the best results for software. Conclusions: This is the first comprehensive study to directly compare different HHUS devices in a head-to-head manner. While the majority of the tested devices demonstrated satisfactory performance, notable discrepancies were observed between them. In particular, the B-scan quality exhibited considerable variation, which may have implications for the clinical application of HHUS. The findings of this study can assist in the selection of an appropriate HHUS device for specific applications, considering the clinical objectives and acknowledging the inherent limitations. [ABSTRACT FROM AUTHOR]

For antinuclear antibody (ANA) screening, the gold standard method is an indirect immunofluorescence assay (IIFA) using HEp-2 cells, and a serial dilution test is needed to determine the endpoint titer. We aimed to evaluate the accuracy of the estimated endpoint titer (eEPT) by the NOVA View system, by comparing it with the EPT by the serial dilution method (dEPT). The endpoint titers of a total of 1518 ANA positive cases with five major patterns including speckled, homogeneous, centromere, nucleolar, and nuclear dots patterns were determined using both the estimation function and the serial dilution method by the NOVA View system. A significant correlation between the light intensity unit (LIU) values and dEPTs was identified in all five patterns with high ρ values, ranging from 0.666 to 0.832. However, the overall exact match rate between dEPT and eEPT was 22.1% (336/1518), with the ±one-titer match rate being highest in the centromere pattern (62.8%, 81/129), and lowest in the homogeneous pattern (37.6%, 200/532). This suggests that while LIU values correlate well with dEPT, there are discrepancies in numerical agreement. Most cases that did not show an exact match, showed one-to-three-titer overestimations by eEPT. Therefore, adjusting eEPT downward significantly improved the concordance rates with dEPTs. Further investigation for an appropriate cutoff of LIU values for determining eEPT should be performed for clinical application and contribution to the standardization of the ANA titer. [ABSTRACT FROM AUTHOR]

Extramammary Paget disease (EMPD) is an uncommon adenocarcinoma of apocrine gland-rich areas, presenting significant diagnostic challenges due to its nonspecific clinical appearance and frequent misidentification as benign, inflammatory skin conditions. Traditional diagnostic methods such as biopsy are invasive and uncomfortable, often required repeatedly due to high recurrence rates. Dermoscopy and non-invasive imaging techniques have been used but provide limited diagnostic accuracy due to their constraints in depth penetration and resolution. Recent advancements in imaging technologies, such as line-field confocal optical coherence tomography (LC-OCT), show promise in enhancing diagnostic precision while minimizing invasive procedures. LC-OCT merges high-resolution imaging with deep penetration capabilities, capturing detailed horizontal and vertical skin images akin to histopathology. This study evaluated the diagnostic performance of LC-OCT in detecting EMPD and its recurrence in 17 clinically suspicious anogenital regions, belonging to six patients. Data were collected prospectively at the patient's bedside by an LC-OCT expert with poor training for EMPD, and, then, reviewed retrospectively by an independent LC-OCT expert with adequate training for EMPD and no concerns about time. The prospective examination yielded 64.7% accuracy (11 true results out of 17 total cases), 71.4% sensitivity (10 true positives out of 14 actual positives), and 33.3% specificity (1 true negative out of 3 actual negatives). The retrospective analysis achieved 94.1% accuracy (16 true results out of 17 total cases), 100% sensitivity (14 true positives out of 14 actual positives), and 66.7% specificity (2 true positives out of 3 actual positives), with the only false positive case being a difficult-to-diagnose concomitant presentation of a lichen sclerosus et atrophicus. Despite the need for specialized training, our results suggest that LC-OCT represents a valuable tool for accurately identifying EMPD and improving its management by reducing unnecessary biopsies. Further studies are needed to standardize its clinical application. [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]

This review aims to analyze different strategies that make use of artificial intelligence to enhance diagnosis, treatment planning, and monitoring in orthodontics. Orthodontics has seen significant technological advancements with the introduction of digital equipment, including cone beam computed tomography, intraoral scanners, and software coupled to these devices. The use of deep learning in software has sped up image processing processes. Deep learning is an artificial intelligence technology that trains computers to analyze data like the human brain does. Deep learning models are capable of recognizing complex patterns in photos, text, audio, and other data to generate accurate information and predictions. Materials and Methods: Pubmed, Scopus, and Web of Science were used to discover publications from 1 January 2013 to 18 October 2023 that matched our topic. A comparison of various artificial intelligence applications in orthodontics was generated. Results: A final number of 33 studies were included in the review for qualitative analysis. Conclusions: These studies demonstrate the effectiveness of AI in enhancing orthodontic diagnosis, treatment planning, and assessment. A lot of articles emphasize the integration of artificial intelligence into orthodontics and its potential to revolutionize treatment monitoring, evaluation, and patient outcomes. [ABSTRACT FROM AUTHOR]

Background: this study aims to validate two occlusal-force-measuring devices by comparing them to a universal testing machine and assessing their reliability across various dental and prosthetic groups. The research comprised two parts: part 1 assessed the measurement accuracy of the Occlusal Force Meter GM 10® (OFM) (Morita, Nagano Keiki, Higashimagome, Ohta-ku, Tokyo, Japan) and a prototype (PRO) by comparing them to a calibrated universal testing machine (ZWICK). Part 2 involved analyzing the devices' reliability based on clinical bite force measurements from study participants. Results: both devices become more accurate and reliable compared to the ZWICK over time of usage. Additionally, higher deviation from the ZWICK can be observed for higher values of forces applied and vice versa for both devices. The PRO's intraoral alignment influences its mean values compared to the OFM in different dental and prosthetic groups. Conclusion: both devices had limitations and required quadratic function calibration, making them suitable only for progression measurements. The study concludes that both the OFM and PRO devices can measure occlusal forces with improved accuracy over time. Intraoral alignment should be considered. Their easy-to-use clinical application would allow a more widespread use of masticatory function diagnosis, which could indicate the need for treatment and improve treatment planning. [ABSTRACT FROM AUTHOR]

Ultrasound elastography is gaining attention for its diagnostic potential across various medical fields, and its physical properties make it valuable in modern clinical medicine. However, its specific attributes, especially in the context of recent medical advancements, remain relatively unexplored. This study aimed to identify instrument-specific characteristics and applications of real-time ultrasound elastography, shear wave elastography, and strain elastography, particularly within gastroenterology. Following PRISMA guidelines, the study examined elastography articles on databases like PubMed, resulting in 78 included articles. Data on patient demographics, organ involvement, specificity, sensitivity, accuracy, positive predictive value, and negative predictive value were extracted. Statistical analysis involved SPSS version 21, with significance set at p < 0.05. The majority of patients were male (50.50%), with a mean age of 42.73 ± 4.41 years. Shear wave elastography was the most prevalent technique (48.7%), and liver investigations were predominant in gastroenterology (34.6%). Gastrointestinal applications showed higher sensitivity, positive predictive value, and negative predictive values (p < 0.05) but lower specificity (p < 0.05). Real-time ultrasound elastography exhibited increased specificity, accuracy, and predictive values (p < 0.05). Ultrasound elastography appears more accurate and effective in gastroenterological settings. Nonetheless, its performance depends on instrument-specific and operator-dependent factors. While promising, further studies are necessary to ascertain optimal utilization in both gastrointestinal and non-gastrointestinal conditions. [ABSTRACT FROM AUTHOR]

Immunotherapy has greatly improved the outcomes of patients with metastatic melanoma. However, it has also led to new patterns of response and progression, creating an unmet need for better biomarkers to identify patients likely to achieve a lasting clinical benefit or experience immune-related adverse events. In this study, we performed a focused literature survey covering the application of artificial intelligence (AI; in the form of radiomics, machine learning, and deep learning) to patients diagnosed with melanoma and treated with immunotherapy, reviewing 12 studies relevant to the topic published up to early 2022. The most commonly investigated imaging modality was CT imaging in isolation (n = 9, 75.0%), while patient cohorts were most frequently recruited retrospectively and from single institutions (n = 7, 58.3%). Most studies concerned the development of AI tools to assist in prognostication (n = 5, 41.7%) or the prediction of treatment response (n = 6, 50.0%). Validation methods were disparate, with two studies (16.7%) performing no validation and equal numbers using cross-validation (n = 3, 25%), a validation set (n = 3, 25%), or a test set (n = 3, 25%). Only one study used both validation and test sets (n = 1, 8.3%). Overall, promising results have been observed for the application of AI to immunotherapy-treated melanoma. Further improvement and eventual integration into clinical practice may be achieved through the implementation of rigorous validation using heterogeneous, prospective patient cohorts. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has been increasing, with more than 30 FDA-approved algorithms now available for applications in the abdomen and pelvis. In this manuscript, we explore some of the fundamentals of artificial intelligence and machine learning, review major functions that AI algorithms may perform, introduce current and potential future applications of AI in abdominal imaging, provide a basic understanding of the pathways by which AI algorithms can receive FDA approval, and explore some of the challenges with the implementation of AI in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Optical coherence tomography angiography (OCTA) is a noninvasive imaging modality used to analyze the retinochoroidal vasculature and detect vascular flow. The resulting images can be segmented to view each vascular plexus individually. While fluorescein angiography is still the gold standard for the diagnosis of posterior uveitis, it has limitations, and can be replaced by OCTA in some cases. Methods: This case series describes five patients with posterior noninfectious uveitis and their description by OCTA. Results: Cases included lupus retinopathy (n = 1) for which OCTA showed ischemic maculopathy as areas of flow deficit at the superficial and deep capillary plexus; choroidal granulomas (n = 1) with a non-detectable flow signal in the choroid; active punctate inner choroiditis and multifocal choroiditis (n = 1) with OCTA that showed active inflammatory chorioretinal lesions as non-detectable flow signals in choriocapillaris and choroid; dense type 2 inflammatory secondary neovascularization (n = 1) associated with active choroiditis; and acute posterior multifocal placoid pigment epitheliopathy (APMPPE) (n = 1) without flow abnormalities at the superficial and deep retinal plexuses but non-detectable flow at the levels of the choriocapillaris and choroid. Conclusions: Ophthalmologists can use OCTA to identify inflammatory changes in retinal and choroidal vasculature, aiding in the diagnosis, management, and monitoring of posterior uveitis. [ABSTRACT FROM AUTHOR]

CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation. [ABSTRACT FROM AUTHOR]

Cardiac complications are common in antiretroviral therapy-treated (ART-treated) acquired immune deficiency syndrome (AIDS) patients, and the incidence increases with age. Myocardial injury in ART-treated AIDS patients with a relatively longer disease duration has been evaluated. However, there is no relevant study on whether patients with a short AIDS duration have cardiac dysfunction. Thirty-seven ART-treated males with AIDS and eighteen healthy controls (HCs) were prospectively included for CMR scanning. Clinical data and laboratory examination results were collected. The ART-treated males with AIDS did not have significantly reduced biventricular ejection fraction, myocardial edema, or late gadolinium enhancement. Compared with the HCs, the biventricular volume parameters and left ventricle myocardial strain indices in ART-treated males with AIDS were not significantly reduced (all p > 0.05). ART-treated males with AIDS were divided into subgroups according to their CD4+ T-cell counts (<350 cells/μL and ≥350 cells/μL) and duration of disease (1–12 months, 13–24 months, and 25–36 months). There was no significant decrease in left or right ventricular volume parameters or myocardial strain indices among the subgroups (all p > 0.05). In Pearson correlation analysis, CD4+ T-cell counts were not significantly correlated with biventricular volume parameters or left ventricular myocardial strain indices. In conclusion, ART-treated males with AIDS receiving ART therapy with a short disease duration (less than 3 years) might not develop obvious cardiac dysfunction as evaluated by routine CMR, so it is reasonable to appropriately extend the interval between cardiovascular follow-ups to more than 3 years. [ABSTRACT FROM AUTHOR]

The superimposition of sequential radiographs of the head is commonly used to determine the amount and direction of orthodontic tooth movement. A harmless method includes the timely unlimited superimposition on the relatively stable palatal rugae, but the method is performed manually and, if automated, relies on the best fit of surfaces, not only rugal structures. In the first step, motion estimation requires segmenting and detecting the location of teeth and rugae at any time during the orthodontic intervention. Aim: to develop a process of tooth segmentation that eliminates all manual steps to achieve an autonomous system of assessment of the dentition. Methods: A dataset of 797 occlusal views from photographs of teeth was created. The photographs were manually semantically segmented and labeled. Machine learning methods were applied to identify a robust deep network architecture able to semantically segment teeth in unseen photographs. Using well-defined metrics such as accuracy, precision, and the average mean intersection over union (mIoU), four network architectures were tested: MobileUnet, AdapNet, DenseNet, and SegNet. The robustness of the trained network was additionally tested on a set of 47 image pairs of patients before and after orthodontic treatment. Results: SegNet was the most accurate network, producing 95.19% accuracy and an average mIoU value of 86.66% for the main sample and 86.2% for pre- and post-treatment images. Conclusions: Four architectural tests were developed for automated individual teeth segmentation and detection in two-dimensional photos that required no post-processing. Accuracy and robustness were best achieved with SegNet. Further research should focus on clinical applications and 3D system development. [ABSTRACT FROM AUTHOR]

Background: Accurate neonatal pain assessment (NPA) is the key to neonatal pain management, yet it is a challenging task for medical staff. This study aimed to analyze the clinical practicability of the artificial intelligence based NPA (AI-NPA) tool for real-world blood sampling. Method: We performed a prospective study to analyze the consistency of the NPA results given by a self-developed automated NPA system and nurses' on-site NPAs (OS-NPAs) for 232 newborns during blood sampling in neonatal wards, where the neonatal infant pain scale (NIPS) was used for evaluation. Spearman correlation analysis and the degree of agreement of the pain score and pain grade derived by the NIPS were applied for statistical analysis. Results: Taking the OS-NPA results as the gold standard, the accuracies of the NIPS pain score and pain grade given by the automated NPA system were 88.79% and 95.25%, with kappa values of 0.92 and 0.90 (p < 0.001), respectively. Conclusion: The results of the automated NPA system for real-world neonatal blood sampling are highly consistent with the results of the OS-NPA. Considering the great advantages of automated NPA systems in repeatability, efficiency, and cost, it is worth popularizing the AI technique in NPA for precise and efficient neonatal pain management. [ABSTRACT FROM AUTHOR]

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens. [ABSTRACT FROM AUTHOR]

Brachial plexus injuries are commonly diagnosed clinically, as conventional imaging has a low sensitivity. In recent years, diffusion tensor imaging has established a clinical role in the study of the central nervous system and, while still presenting some limitations due to the technical complexity of the acquisition method, is showing promising results when applied to peripheral nerves. Moreover, deterministic fiber tracking with the Euler's method and multishell acquisition are two novel advances in the field which contribute to enhancing the reliability of the technique reducing the respiratory and inhomogeneity artifacts in this "magnetically complex" region, and better isolating the fibers in a heterogeneous territory. Here, we report a case of brachial plexus traumatic injury, a healthy reference subject, and details on the acquisition protocol of the reconstruction algorithm. [ABSTRACT FROM AUTHOR]

We discuss the early history of the structure of DNA and its involvement in gene structure as well as its mobility in and between cells and between tissues in the form of circulating cell-free DNA (cfDNA). This is followed by a view of the present status of the studies on cfDNA and clinical applications of circulating cell-free tumor DNA (ctDNA). The future developments and roles of ctDNA are also considered. [ABSTRACT FROM AUTHOR]

Classic Hodgkin lymphoma (cHL) constitutes a B cell-derived neoplasm defined by a scarce tumoral population, termed Hodgkin and Reed–Sternberg (HRS) cells, submerged into a histologically heterogeneous microenvironment. The paucity of HRS cells has historically hampered genetic studies, rendering the identification of the recurrent genetic lesions and molecular pathways deregulated in this lymphoma difficult. The advent of high-throughput sequencing methods such as next-generation sequencing (NGS) could sensibly optimize the identification of the mutational landscape of cHL. However, there is no current consensus either in the design of panels for targeted NGS or in its most relevant clinical applications. In this work, we systematically review the current state of NGS studies of cHL, stressing the need for standardization both in the candidate genes to be analyzed and the bioinformatic pipelines. As different institutions have developed and implemented their own customized NGS-based protocols, to compare and systematically review the major findings of this ongoing research area could be of added value for centers that routinely perform diagnostic, monitoring and genotyping strategies in cHL samples. The results of this systematic review should contribute to the interdepartmental harmonization and achievement of a consensus in the current clinical applications of NGS studies of cHL. [ABSTRACT FROM AUTHOR]

For over 15 years, thoracic ultrasound has been applied in the evaluation of numerous lung diseases, demonstrating a variable diagnostic predictive power compared to traditional imaging techniques such as chest radiography and CT. However, in unselected pulmonary patients, there are no rigorous scientific demonstrations of the complementarity of thoracic ultrasound with traditional and standardized imaging techniques that use radiation. In this study 101 unselected pulmonary patients were evaluated blindly with ultrasound chest examinations during their hospital stay. Other instrumental examinations, carried out during hospitalization, were standard chest radiography, computed tomography (CT), and, when needed, radioisotopic investigation and cardiac catheterization. The operator who performed the ultrasound examinations was unaware of the anamnestic and clinical data of the patients. Diffuse fibrosing disease was detected with a sensitivity, specificity and diagnostic accuracy of 100%, 95% and 97%, respectively. In pleural effusions, ultrasound showed a sensitivity, specificity and diagnostic accuracy of 100%. In consolidations, the sensitivity, specificity and diagnostic accuracy were 83%, 98% and 93%, respectively. Low values of sensitivity were recorded for surface nodulations of less than one centimeter. Isolated subpleural ground glass densities were identified as White Lung with a sensitivity of 72% and a specificity of 86%. Only the associations Diffuse ultrasound findings/Definitive fibrosing disease, Ultrasound Consolidation/Definitive consolidation and non-diffuse ultrasound artefactual features/Definitive vascular pathology (pulmonary hypertension, embolism) were statistically significant with adjusted residuals of 7.9, 7 and 4.1, respectively. The obtained results show how chest ultrasound is an effective complementary diagnostic tool for the pulmonologist. When performed, as a complement to the patient's physical examination, it can restrict the diagnostic hypothesis in the case of pleural effusion, consolidation and diffuse fibrosing disease of the lung. [ABSTRACT FROM AUTHOR]

Aging is an irreversible and natural phenomenon that occurs as a person ages. Anti-aging medicine applies advanced science and medical technology to early detection, prevention, treatment, and reversal of age-related dysfunctions, disorders, and diseases. Therefore, anti-aging diagnostic medicine and healthcare are important factors in helping the elderly population lead healthy and active lives. However, it is challenging to diagnose various aging and related diseases accurately through various forms of anti-aging diagnostic medicine and health management. It may not be treated appropriately, so many older people are making various efforts to prevent aging themselves in advance. Therefore, anti-aging medicine and health care have been developed in various forms, from health checkups to alternative medicine and biophysical technology beyond simple clinical medicine, and are being applied to demand the needs of the elderly. This review intends to explore and characterize various applications related to anti-aging medicine and healthcare in the elderly. In addition, economic, medical, and ethical considerations arising from the relationship between the increase in the elderly population and the continuous development of anti-aging medicine can be considered. [ABSTRACT FROM AUTHOR]

Somatostatin receptor (SSTR) agonist tracers used in nuclear medicine scans are classically used for neuroendocrine tumor diagnosis and staging. SSTR are however, expressed more widely in a variety of cells as seen in the distribution of physiological tracer uptake during whole body scans. This provides opportunities for using these tracers for applications other than NETs and meningiomas. In this qualitative systematic review, novel diagnostics in SSTR-PET imaging are reviewed. A total of 70 studies comprised of 543 patients were qualitatively reviewed. Sarcoidosis, atherosclerosis and phosphaturic mesenchymal tumors represent the most studied applications currently with promising results. Other applications remain in progress where there are many case reports but a relative dearth of cohort studies. [18F]FDG PET provides the main comparative method in many cases but represents a well-established general PET technique that may be difficult to replace, without prospective clinical studies. [ABSTRACT FROM AUTHOR]

Ultrasound (US)-based measurements of the inferior vena cava (IVC) diameter are widely used to estimate right atrial pressure (RAP) in a variety of clinical settings. However, the correlation with invasively measured RAP along with the reproducibility of US-based IVC measurements is modest at best. In the present manuscript, we discuss the limitations of the current technique to estimate RAP through IVC US assessment and present a new promising tool developed by our research group, the automated IVC edge-to-edge tracking system, which has the potential to improve RAP assessment by transforming the current categorical classification (low, normal, high RAP) in a continuous and precise RAP estimation technique. Finally, we critically evaluate all the clinical settings in which this new tool could improve current practice. [ABSTRACT FROM AUTHOR]

Micro-computed tomography (micro-CT) is a promising novel medical imaging modality that allows for non-destructive volumetric imaging of surgical tissue specimens at high spatial resolution. The aim of this study is to provide a comprehensive assessment of the clinical applications of micro-CT for the tissue-based diagnosis of lung diseases. This scoping review was conducted in accordance with the PRISMA Extension for Scoping Reviews, aiming to include every clinical study reporting on micro-CT imaging of human lung tissues. A literature search yielded 570 candidate articles, out of which 37 were finally included in the review. Of the selected studies, 9 studies explored via micro-CT imaging the morphology and anatomy of normal human lung tissue; 21 studies investigated microanatomic pulmonary alterations due to obstructive or restrictive lung diseases, such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and cystic fibrosis; and 7 studies examined the utility of micro-CT imaging in assessing lung cancer lesions (n = 4) or in transplantation-related pulmonary alterations (n = 3). The selected studies reported that micro-CT could successfully detect several lung diseases providing three-dimensional images of greater detail and resolution than routine optical slide microscopy, and could additionally provide valuable volumetric insight in both restrictive and obstructive lung diseases. In conclusion, micro-CT-based volumetric measurements and qualitative evaluations of pulmonary tissue structures can be utilized for the clinical management of a variety of lung diseases. With micro-CT devices becoming more accessible, the technology has the potential to establish itself as a core diagnostic imaging modality in pathology and to enable integrated histopathologic and radiologic assessment of lung cancer and other lung diseases. [ABSTRACT FROM AUTHOR]