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Search Results (3,957)

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20 pages, 4870 KiB  
Article
Histological and Immunohistochemical Evidence in Hypothermia-Related Death: An Experimental Study
by Emina Dervišević, Nina Čamdžić, Edina Lazović, Adis Salihbegović, Francesco Sessa, Hajrudin Spahović and Stefano D’Errico
Int. J. Mol. Sci. 2025, 26(15), 7578; https://doi.org/10.3390/ijms26157578 (registering DOI) - 5 Aug 2025
Abstract
Hypothermia-related deaths present significant diagnostic challenges due to non-specific and often inconsistent autopsy findings. This study investigated the histological and immunohistochemical alterations associated with primary and secondary hypothermia in an experimental Rattus norvegicus model, focusing on the effects of benzodiazepine and alcohol ingestion. [...] Read more.
Hypothermia-related deaths present significant diagnostic challenges due to non-specific and often inconsistent autopsy findings. This study investigated the histological and immunohistochemical alterations associated with primary and secondary hypothermia in an experimental Rattus norvegicus model, focusing on the effects of benzodiazepine and alcohol ingestion. Twenty-one male rats were divided into three groups: control (K), benzodiazepine-treated (B), and alcohol-treated (A). After two weeks of substance administration, hypothermia was induced and multiple organ samples were analyzed. Histologically, renal tissue showed hydropic and vacuolar degeneration, congestion, and acute tubular injury across all groups, with no significant differences in E-cadherin expression. Lung samples revealed congestion, emphysema, and hemorrhage, with more pronounced vascular congestion in the alcohol and benzodiazepine groups. Cardiac tissue exhibited vacuolar degeneration and protein denaturation, particularly in substance-exposed animals. The spleen showed preserved architecture but increased erythrocyte infiltration and significantly elevated myeloperoxidase (MPO)-positive granulocytes in the intoxicated groups. Liver samples demonstrated congestion, focal necrosis, and subcapsular hemorrhage, especially in the alcohol group. Immunohistochemical analysis revealed statistically significant differences in MPO expression in both lung and spleen tissues, with the highest levels observed in the benzodiazepine group. Similarly, CK7 and CK20 expression in the gastroesophageal junction was significantly elevated in both alcohol- and benzodiazepine-treated animals compared to the controls. In contrast, E-cadherin expression in the kidney did not differ significantly among the groups. These findings suggest that specific histological and immunohistochemical patterns, particularly involving pulmonary, cardiac, hepatic, and splenic tissues, may help differentiate primary hypothermia from substance-related secondary hypothermia. The study underscores the value of integrating toxicological, histological, and molecular analyses to enhance the forensic assessment of hypothermia-related fatalities. Future research should aim to validate these markers in human autopsy series and explore additional molecular indicators to refine diagnostic accuracy in forensic pathology. Full article
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31 pages, 1811 KiB  
Article
Fractal-Inspired Region-Weighted Optimization and Enhanced MobileNet for Medical Image Classification
by Yichuan Shao, Jiapeng Yang, Wen Zhou, Haijing Sun and Qian Gao
Fractal Fract. 2025, 9(8), 511; https://doi.org/10.3390/fractalfract9080511 - 5 Aug 2025
Abstract
In the field of deep learning, the design of optimization algorithms and neural network structures is crucial for improving model performance. Recent advances in medical image analysis have revealed that many pathological features exhibit fractal-like characteristics in their spatial distribution and morphological patterns. [...] Read more.
In the field of deep learning, the design of optimization algorithms and neural network structures is crucial for improving model performance. Recent advances in medical image analysis have revealed that many pathological features exhibit fractal-like characteristics in their spatial distribution and morphological patterns. This observation has opened new possibilities for developing fractal-inspired deep learning approaches. In this study, we propose the following: (1) a novel Region-Module Adam (RMA) optimizer that incorporates fractal-inspired region-weighting to prioritize areas with higher fractal dimensionality, and (2) an ECA-Enhanced Shuffle MobileNet (ESM) architecture designed to capture multi-scale fractal patterns through its enhanced feature extraction modules. Our experiments demonstrate that this fractal-informed approach significantly improves classification accuracy compared to conventional methods. On gastrointestinal image datasets, the RMA algorithm achieved accuracies of 83.60%, 81.60%, and 87.30% with MobileNetV2, ShuffleNetV2, and ESM networks, respectively. For glaucoma fundus images, the corresponding accuracies reached 84.90%, 83.60%, and 92.73%. These results suggest that explicitly considering fractal properties in medical image analysis can lead to more effective diagnostic tools. Full article
20 pages, 1291 KiB  
Review
Ultrasound Imaging Modalities in the Evaluation of the Dog’s Stifle Joint
by Anargyros T. Karatrantos, Aikaterini I. Sideri, Pagona G. Gouletsou, Christina G. Bektsi and Mariana S. Barbagianni
Vet. Sci. 2025, 12(8), 734; https://doi.org/10.3390/vetsci12080734 - 4 Aug 2025
Abstract
This review presents a comprehensive overview of various ultrasound imaging techniques employed in the evaluation of the canine knee joint. It critically analyzes studies conducted on both human and animal subjects, with a focus on the diagnostic accuracy of B-mode ultrasound, Doppler examination, [...] Read more.
This review presents a comprehensive overview of various ultrasound imaging techniques employed in the evaluation of the canine knee joint. It critically analyzes studies conducted on both human and animal subjects, with a focus on the diagnostic accuracy of B-mode ultrasound, Doppler examination, contrast-enhanced ultrasound, and elastography in both normal and pathological conditions. The review underscores the necessity of strict adherence to the protocols of each ultrasound modality and emphasizes the importance of a thorough understanding of the anatomical region to achieve optimal outcomes. The findings suggest that these ultrasound techniques can significantly enhance the diagnostic process, providing valuable insights into anatomy, size, blood supply, and tissue elasticity. Additionally, in cases where advanced imaging modalities such as computed tomography (CT) or magnetic resonance imaging (MRI) are cost-prohibitive or less accessible, ultrasound serves as a reliable alternative, delivering high diagnostic accuracy and critical information regarding mechanical changes in the joint and neovascularization. Full article
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19 pages, 286 KiB  
Review
Does the Anatomical Type of the Plantaris Tendon Influence the Management of Midportion Achilles Tendinopathy?
by Łukasz Olewnik, Ingrid C. Landfald, Bartosz Gonera, Łukasz Gołek, Aleksandra Szabert-Kajkowska, Andrzej Borowski, Marek Drobniewski, Teresa Vázquez and Kacper Ruzik
J. Clin. Med. 2025, 14(15), 5478; https://doi.org/10.3390/jcm14155478 - 4 Aug 2025
Abstract
Background: Midportion Achilles tendinopathy (Mid-AT) is a complex condition that may be exacerbated by anatomical variations of the plantaris tendon. Recent anatomical studies, particularly the classification proposed by Olewnik et al., have enhanced the understanding of plantaris–Achilles interactions and their clinical implications. Objective: [...] Read more.
Background: Midportion Achilles tendinopathy (Mid-AT) is a complex condition that may be exacerbated by anatomical variations of the plantaris tendon. Recent anatomical studies, particularly the classification proposed by Olewnik et al., have enhanced the understanding of plantaris–Achilles interactions and their clinical implications. Objective: This review aims to assess the anatomical types of the plantaris tendon, their imaging correlates, and the impact of the Olewnik classification on diagnosis, treatment planning, and surgical outcomes in patients with Mid-AT. Methods: We present an evidence-based analysis of the six anatomical types of the plantaris tendon and their relevance to Achilles tendinopathy, with emphasis on MRI and ultrasound (USG) evaluation. A diagnostic and therapeutic algorithm is proposed, and clinical outcomes of both conservative and operative management are compared across tendon types. Results: Types I and V were most strongly associated with symptomatic conflict and showed the highest benefit from surgical resection. Endoscopic approaches were effective in Types II and III, while Type IV typically responded to conservative treatment. Type VI, often misdiagnosed as tarsal tunnel syndrome, required combined neurolysis. The classification significantly improves surgical decision-making, reduces overtreatment, and enhances diagnostic precision. Conclusions: The Olewnik classification provides a reproducible, clinically relevant framework for individualized management of Mid-AT. Its integration into imaging protocols and treatment algorithms may improve therapeutic outcomes and guide future research in orthopaedic tendon pathology. Full article
(This article belongs to the Section Orthopedics)
30 pages, 3430 KiB  
Article
Stage-Specific Serum Proteomic Signatures Reveal Early Biomarkers and Molecular Pathways in Huntington’s Disease Progression
by Christiana C. Christodoulou, Christiana A. Demetriou and Eleni Zamba-Papanicolaou
Cells 2025, 14(15), 1195; https://doi.org/10.3390/cells14151195 - 4 Aug 2025
Abstract
Background: Huntington’s Disease (HD) is a monogenic neurodegenerative disease resulting in a CAG repeat expansion in the HTT gene. Despite this genetic simplicity, its molecular mechanisms remain highly complex. Methods: In this study, untargeted serum proteomics, bioinformatics analysis, biomarker filtering and ELISA validation [...] Read more.
Background: Huntington’s Disease (HD) is a monogenic neurodegenerative disease resulting in a CAG repeat expansion in the HTT gene. Despite this genetic simplicity, its molecular mechanisms remain highly complex. Methods: In this study, untargeted serum proteomics, bioinformatics analysis, biomarker filtering and ELISA validation were implemented to characterize the proteomic landscape across the three HD stages—asymptomatic, early symptomatic and symptomatic advanced—alongside gender/age-matched controls. Results: We identified 84 over-expressed and 118 under-expressed differentially expressed proteins. Enrichment analysis revealed dysregulation in pathways including the complement cascade, LXR/RXR activation and RHOGDI signaling. Biomarker analysis highlighted key proteins with diagnostic potential, including CAP1 (AUC = 0.809), CAPZB (AUC = 0.861), TAGLN2 (AUC = 0.886), THBS1 (AUC = 0.883) and CFH (AUC = 0.948). CAP1 and CAPZB demonstrated robust diagnostic potential in linear mixed-effects models. CAP1 decreased in the asymptomatic stage, suggesting early cytoskeletal disruption, while CAPZB was consistently increased across HD stages. Conclusions: Our findings illuminate the dynamic proteomic and molecular landscape of HD. Future studies should validate these candidates in larger, more diverse cohorts and explore their mechanistic roles in HD pathology and progression. Full article
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27 pages, 747 KiB  
Review
An Insight into the Disease Prognostic Potentials of Nanosensors
by Nandu K. Mohanan, Nandana S. Mohanan, Surya Mol Sukumaran, Thaikatt Madhusudhanan Dhanya, Sneha S. Pillai, Pradeep Kumar Rajan and Saumya S. Pillai
Inorganics 2025, 13(8), 259; https://doi.org/10.3390/inorganics13080259 - 4 Aug 2025
Abstract
Growing interest in the future applications of nanotechnology in medicine has led to groundbreaking developments in nanosensors. Nanosensors are excellent platforms that provide reliable solutions for continuous monitoring and real-time detection of clinical targets. Nanosensors have attracted great attention due to their remarkable [...] Read more.
Growing interest in the future applications of nanotechnology in medicine has led to groundbreaking developments in nanosensors. Nanosensors are excellent platforms that provide reliable solutions for continuous monitoring and real-time detection of clinical targets. Nanosensors have attracted great attention due to their remarkable sensitivity, portability, selectivity, and automated data acquisition. The exceptional nanoscale properties of nanomaterials used in the nanosensors boost their sensing potential even at minimal concentrations of analytes present in a clinical sample. Along with applications in diverse sectors, the beneficial aspects of nanosensors have been exploited in healthcare systems to utilize their applications in diagnosing, treating, and preventing diseases. Hence, in this review, we have presented an overview of the disease-prognostic applications of nanosensors in chronic diseases through a detailed literature analysis. We focused on the advances in various nanosensors in the field of major diseases such as cancer, cardiovascular diseases, diabetes mellitus, and neurodegenerative diseases along with other prevalent diseases. This review demonstrates various categories of nanosensors with different nanoparticle compositions and detection methods suitable for specific diagnostic applications in clinical settings. The chemical properties of different nanoparticles provide unique characteristics to each nanosensors for their specific applications. This will aid the detection of potential biomarkers or pathological conditions that correlate with the early detection of various diseases. The potential challenges and possible recommendations of the applications of nanosensors for disease diagnosis are also discussed. The consolidated information present in the review will help to better understand the disease-prognostic potentials of nanosensors, which can be utilized to explore new avenues in improved therapeutic interventions and treatment modalities. Full article
(This article belongs to the Section Bioinorganic Chemistry)
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10 pages, 1055 KiB  
Article
Artificial Intelligence and Hysteroscopy: A Multicentric Study on Automated Classification of Pleomorphic Lesions
by Miguel Mascarenhas, Carla Peixoto, Ricardo Freire, Joao Cavaco Gomes, Pedro Cardoso, Inês Castro, Miguel Martins, Francisco Mendes, Joana Mota, Maria João Almeida, Fabiana Silva, Luis Gutierres, Bruno Mendes, João Ferreira, Teresa Mascarenhas and Rosa Zulmira
Cancers 2025, 17(15), 2559; https://doi.org/10.3390/cancers17152559 - 3 Aug 2025
Viewed by 126
Abstract
Background/Objectives: The integration of artificial intelligence (AI) in medical imaging is rapidly advancing, yet its application in gynecologic use remains limited. This proof-of-concept study presents the development and validation of a convolutional neural network (CNN) designed to automatically detect and classify endometrial [...] Read more.
Background/Objectives: The integration of artificial intelligence (AI) in medical imaging is rapidly advancing, yet its application in gynecologic use remains limited. This proof-of-concept study presents the development and validation of a convolutional neural network (CNN) designed to automatically detect and classify endometrial polyps. Methods: A multicenter dataset (n = 3) comprising 65 hysteroscopies was used, yielding 33,239 frames and 37,512 annotated objects. Still frames were extracted from full-length videos and annotated for the presence of histologically confirmed polyps. A YOLOv1-based object detection model was used with a 70–20–10 split for training, validation, and testing. Primary performance metrics included recall, precision, and mean average precision at an intersection over union (IoU) ≥ 0.50 (mAP50). Frame-level classification metrics were also computed to evaluate clinical applicability. Results: The model achieved a recall of 0.96 and precision of 0.95 for polyp detection, with a mAP50 of 0.98. At the frame level, mean recall was 0.75, precision 0.98, and F1 score 0.82, confirming high detection and classification performance. Conclusions: This study presents a CNN trained on multicenter, real-world data that detects and classifies polyps simultaneously with high diagnostic and localization performance, supported by explainable AI features that enhance its clinical integration and technological readiness. Although currently limited to binary classification, this study demonstrates the feasibility and potential of AI to reduce diagnostic subjectivity and inter-observer variability in hysteroscopy. Future work will focus on expanding the model’s capabilities to classify a broader range of endometrial pathologies, enhance generalizability, and validate performance in real-time clinical settings. Full article
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20 pages, 1383 KiB  
Review
The Multifaceted Role of miR-211 in Health and Disease
by Juan Rayo Parra, Zachary Grand, Gabriel Gonzalez, Ranjan Perera, Dipendra Pandeya, Tracey Weiler and Prem Chapagain
Biomolecules 2025, 15(8), 1109; https://doi.org/10.3390/biom15081109 - 1 Aug 2025
Viewed by 217
Abstract
MicroRNA-211 (miR-211) is a versatile regulatory molecule that plays critical roles in cellular homeostasis and disease progression through the post-transcriptional regulation of gene expression. This review comprehensively examines miR-211’s multifaceted functions across various biological systems, highlighting its context-dependent activity as both a tumor [...] Read more.
MicroRNA-211 (miR-211) is a versatile regulatory molecule that plays critical roles in cellular homeostasis and disease progression through the post-transcriptional regulation of gene expression. This review comprehensively examines miR-211’s multifaceted functions across various biological systems, highlighting its context-dependent activity as both a tumor suppressor and oncogene. In physiological contexts, miR-211 regulates cell cycle progression, metabolism, and differentiation through the modulation of key signaling pathways, including TGF-β/SMAD and PI3K/AKT. miR-211 participates in retinal development, bone physiology, and protection against renal ischemia–reperfusion injury. In pathological conditions, miR-211 expression is altered in various diseases, particularly cancer, where it may be a useful diagnostic and prognostic biomarker. Its stability in serum and differential expression in various cancer types make it a promising candidate for non-invasive diagnostics. The review also explores miR-211’s therapeutic potential, discussing both challenges and opportunities in developing miRNA-based treatments. Understanding miR-211’s complex regulatory interactions and context-dependent functions is crucial for advancing its clinical applications for diagnosis, prognosis, and targeted therapy in multiple diseases. Full article
(This article belongs to the Special Issue DNA Damage, Mutagenesis, and Repair Mechanisms)
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15 pages, 1566 KiB  
Systematic Review
Diagnostic Accuracy of Insulinoma-Associated Protein 1 in Pulmonary Neuroendocrine Carcinomas: A Systematic Review and Meta-Analysis
by Risa Waki, Saya Haketa, Riona Aburaki and Nobuyuki Horita
Cancers 2025, 17(15), 2544; https://doi.org/10.3390/cancers17152544 - 31 Jul 2025
Viewed by 130
Abstract
Background and Objective: Insulinoma-associated protein 1 (INSM1) is a novel immunohistochemical marker with potential utility in identifying neuroendocrine differentiation in lung cancer. Unlike conventional neuroendocrine (NE) markers, INSM1 can potentially serve as a standalone diagnostic biomarker. This study presents the first meta-analysis assessing [...] Read more.
Background and Objective: Insulinoma-associated protein 1 (INSM1) is a novel immunohistochemical marker with potential utility in identifying neuroendocrine differentiation in lung cancer. Unlike conventional neuroendocrine (NE) markers, INSM1 can potentially serve as a standalone diagnostic biomarker. This study presents the first meta-analysis assessing the diagnostic accuracy of using INSM1 to distinguish LCNEC and SCLC from other lung cancer subtypes, addressing the variability across individual studies. Methods: A systematic review and meta-analysis were conducted to comprehensively evaluate the diagnostic performance of INSM1 in the pathological classification of lung cancer. The online databases PubMed, Web of Science, and Embase were systematically searched for data collection. Studies reporting the sensitivity and specificity of INSM1 in diagnosing LCNEC and SCLC were included. Pooled estimates were calculated using two models: the NSCLC model, which distinguishes LCNEC from other non-small cell lung cancers (NSCLCs), and the lung cancer model, which differentiates both LCNEC and SCLC from non-neuroendocrine (non-NE) lung cancer. Results: Fourteen studies comprising 3,218 specimens were included in this systematic review and meta-analysis. In the NSCLC model, INSM1 demonstrated a pooled sensitivity of 0.67 (95% CI: 0.61–0.73) and specificity of 0.97 (95% CI: 0.96–0.98), with an area under the curve (AUC) of 0.943. In the lung cancer model, the pooled sensitivity and specificity were 0.86 (95% CI: 0.84–0.88) and 0.97 (95% CI: 0.96–0.98), respectively, with an AUC of 0.974. Conclusions: INSM1 demonstrated excellent diagnostic accuracy and consistently high specificity for pulmonary neuroendocrine carcinomas, supporting its utility as a reliable standalone immunohistochemical marker with the potential to replace conventional NE markers in the pathological diagnosis of LCNEC and SCLC. Full article
(This article belongs to the Section Systematic Review or Meta-Analysis in Cancer Research)
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8 pages, 9195 KiB  
Case Report
Fatal Case of Viral Pneumonia Associated with Metapneumovirus Infection in a Patient with a Burdened Medical History
by Parandzem Khachatryan, Naira Karalyan, Hasmik Petunts, Sona Hakobyan, Hranush Avagyan, Zarine Ter-Pogossyan and Zaven Karalyan
Microorganisms 2025, 13(8), 1790; https://doi.org/10.3390/microorganisms13081790 - 31 Jul 2025
Viewed by 186
Abstract
Background: Human metapneumovirus (hMPV) is a respiratory pathogen that causes illness ranging from mild upper respiratory tract infections to severe pneumonia, particularly in individuals with comorbidities. Fatal cases of hMPV-induced hemorrhagic pneumonia are rare and likely under-reported. Diagnosis is often delayed due to [...] Read more.
Background: Human metapneumovirus (hMPV) is a respiratory pathogen that causes illness ranging from mild upper respiratory tract infections to severe pneumonia, particularly in individuals with comorbidities. Fatal cases of hMPV-induced hemorrhagic pneumonia are rare and likely under-reported. Diagnosis is often delayed due to overlapping symptoms with other respiratory viruses and the rapid progression of the disease. Case presentation: We report the case of a 55-year-old man with a complex medical history, including liver cirrhosis and diabetes mellitus, who developed acute viral pneumonia. Initial symptoms appeared three days before a sudden clinical deterioration marked by shortness of breath, hemoptysis, and respiratory failure. A nasopharyngeal swab taken on the third day of illness tested positive for hMPV by qRT-PCR. The patient died the following day. Postmortem molecular testing confirmed hMPV in lung tissue and alveolar contents. Autopsy revealed bilateral hemorrhagic pneumonia with regional lymphadenopathy. Histopathological examination showed alveolar hemorrhage, multinucleated cells, neutrophilic infiltration, activated autophagy in macrophages, and numerous cytoplasmic eosinophilic viral inclusions. Conclusions: This is the first documented case of fatal hMPV pneumonia in Armenia. It highlights the potential severity of hMPV in adults with chronic health conditions and emphasizes the need for timely molecular diagnostics. Postmortem identification of characteristic viral inclusions may serve as a cost-effective histopathological marker of hMPV-associated lung pathology. Full article
(This article belongs to the Section Virology)
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12 pages, 1990 KiB  
Article
Vaginal Intraepithelial Neoplasia (VaIN)—A Retrospective Cohort Analysis of Epidemiology, Risk Factors, and Management in an Academic Clinical Center
by Barbara Suchońska, Franciszek Ługowski, Magdalena Papież and Artur Ludwin
J. Clin. Med. 2025, 14(15), 5386; https://doi.org/10.3390/jcm14155386 - 30 Jul 2025
Viewed by 239
Abstract
Background: Vaginal intraepithelial neoplasia (VaIN) is a rare but potentially precancerous condition strongly associated with human papillomavirus (HPV) infection. Despite increased detection rates due to HPV screening and colposcopy, diagnosis and management remain challenging. This study aimed to evaluate the epidemiological characteristics, [...] Read more.
Background: Vaginal intraepithelial neoplasia (VaIN) is a rare but potentially precancerous condition strongly associated with human papillomavirus (HPV) infection. Despite increased detection rates due to HPV screening and colposcopy, diagnosis and management remain challenging. This study aimed to evaluate the epidemiological characteristics, risk factors, and outcomes of VaIN in patients referred to a tertiary academic center. Methods: We conducted a retrospective analysis of 48 patients who underwent colposcopy-directed vaginal biopsies between January 2019 and June 2024 at the Medical University of Warsaw. Data collected included patient demographics, HPV status, cytology, histopathology, and treatment outcomes. Patients were grouped based on the presence and grade of VaIN (VaIN 1 vs. VaIN 2/3). Statistical analyses were performed using SPSS software. Results: VaIN was diagnosed in 24 patients (50%), VaIN was confirmed in half of the cohort, VaIN 2 in 30%, and VaIN 3 in 18% of cases. HPV infection and prior cervical pathology were significantly associated with VaIN diagnosis (P = 0.03 and P = 0.05, respectively), and high-risk HPV infection correlated with higher-grade lesions (P = 0.04). Among VaIN 2+ cases, most patients required laser ablation or surgical excision, while VaIN 1 often regressed spontaneously. Regression occurred in 11 cases, and high-risk HPV infection was inversely associated with spontaneous regression (P = 0.04). Conclusions: This study confirms the central role of HPV, particularly high-risk subtypes, in VaIN pathogenesis. Conservative management may be appropriate for VaIN 1, while VaIN 2+ requires active intervention. HPV genotyping should be integrated into diagnostic workups, and long-term follow-up is essential due to the risks of persistence and recurrence. Full article
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12 pages, 456 KiB  
Article
From Variability to Standardization: The Impact of Breast Density on Background Parenchymal Enhancement in Contrast-Enhanced Mammography and the Need for a Structured Reporting System
by Graziella Di Grezia, Antonio Nazzaro, Luigi Schiavone, Cisternino Elisa, Alessandro Galiano, Gatta Gianluca, Cuccurullo Vincenzo and Mariano Scaglione
Cancers 2025, 17(15), 2523; https://doi.org/10.3390/cancers17152523 - 30 Jul 2025
Viewed by 428
Abstract
Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. [...] Read more.
Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the “A. Perrino” Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen’s kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R2 = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact. Full article
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12 pages, 1065 KiB  
Article
Clinico-Morphological Correlations with Ki-67 and p53 Immunohistochemical Expression in High-Grade Gastrointestinal Neuroendocrine Neoplasms
by Alexandra Dinu, Mariana Aşchie, Mariana Deacu, Anca Chisoi, Manuela Enciu, Oana Cojocaru and Sabina E. Vlad
Gastrointest. Disord. 2025, 7(3), 51; https://doi.org/10.3390/gidisord7030051 - 30 Jul 2025
Viewed by 188
Abstract
Background/Objectives: The 2019 WHO classification redefined high-grade gastrointestinal neuroendocrine neoplasms (GI NENs), encompassing not only poorly differentiated neuroendocrine carcinomas (NECs), but also well-differentiated grade 3 neuroendocrine tumors (NETs G3). Since both subtypes share a Ki-67 index > 20%, distinguishing them based solely on [...] Read more.
Background/Objectives: The 2019 WHO classification redefined high-grade gastrointestinal neuroendocrine neoplasms (GI NENs), encompassing not only poorly differentiated neuroendocrine carcinomas (NECs), but also well-differentiated grade 3 neuroendocrine tumors (NETs G3). Since both subtypes share a Ki-67 index > 20%, distinguishing them based solely on morphology is challenging. Prior studies have shown TP53 alterations in NECs but not in NETs. This study aimed to evaluate clinico-morphological parameters and the immunohistochemical (IHC) expression of p53 in high-grade GI NENs to identify relevant correlations. Methods: Tumors were stratified by Ki-67 index into two groups: >20–50% and >50%. p53 IHC expression was assessed as “wild-type” (1–20% positive tumor cells) or “non-wild-type” (absence or >20% positivity). Correlations were analyzed between Ki-67, p53 status, and various pathological features. Results: Significant correlations were found between the Ki-67 index and maximum tumor size, pT stage, lymphovascular invasion, perineural infiltration, and diagnostic classification. Similarly, p53 immunohistochemical status was significantly associated with lymphovascular invasion, lymph node metastasis, and tumor classification (NET G3 versus NEC, including NEC components of MiNENs). Conclusions: The findings support the value of Ki-67 and p53 as complementary biomarkers in the pathological evaluation of high-grade GI NENs. Their significant associations with key morphological parameters support their utility in differentiating NETs G3 from NECs, particularly in cases showing overlapping histological features. The immunohistochemical profile of p53 may serve as a useful diagnostic adjunct in routine practice. Full article
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13 pages, 311 KiB  
Article
Diagnostic Performance of ChatGPT-4o in Analyzing Oral Mucosal Lesions: A Comparative Study with Experts
by Luigi Angelo Vaira, Jerome R. Lechien, Antonino Maniaci, Andrea De Vito, Miguel Mayo-Yáñez, Stefania Troise, Giuseppe Consorti, Carlos M. Chiesa-Estomba, Giovanni Cammaroto, Thomas Radulesco, Arianna di Stadio, Alessandro Tel, Andrea Frosolini, Guido Gabriele, Giannicola Iannella, Alberto Maria Saibene, Paolo Boscolo-Rizzo, Giovanni Maria Soro, Giovanni Salzano and Giacomo De Riu
Medicina 2025, 61(8), 1379; https://doi.org/10.3390/medicina61081379 - 30 Jul 2025
Viewed by 218
Abstract
Background and Objectives: this pilot study aimed to evaluate the diagnostic accuracy of ChatGPT-4o in analyzing oral mucosal lesions from clinical images. Materials and Methods: a total of 110 clinical images, including 100 pathological lesions and 10 healthy mucosal images, were retrieved [...] Read more.
Background and Objectives: this pilot study aimed to evaluate the diagnostic accuracy of ChatGPT-4o in analyzing oral mucosal lesions from clinical images. Materials and Methods: a total of 110 clinical images, including 100 pathological lesions and 10 healthy mucosal images, were retrieved from Google Images and analyzed by ChatGPT-4o using a standardized prompt. An expert panel of five clinicians established a reference diagnosis, categorizing lesions as benign or malignant. The AI-generated diagnoses were classified as correct or incorrect and further categorized as plausible or not plausible. The accuracy, sensitivity, specificity, and agreement with the expert panel were analyzed. The Artificial Intelligence Performance Instrument (AIPI) was used to assess the quality of AI-generated recommendations. Results: ChatGPT-4o correctly diagnosed 85% of cases. Among the 15 incorrect diagnoses, 10 were deemed plausible by the expert panel. The AI misclassified three malignant lesions as benign but did not categorize any benign lesions as malignant. Sensitivity and specificity were 91.7% and 100%, respectively. The AIPI score averaged 17.6 ± 1.73, indicating strong diagnostic reasoning. The McNemar test showed no significant differences between AI and expert diagnoses (p = 0.084). Conclusions: In this proof-of-concept pilot study, ChatGPT-4o demonstrated high diagnostic accuracy and strong descriptive capabilities in oral mucosal lesion analysis. A residual 8.3% false-negative rate for malignant lesions underscores the need for specialist oversight; however, the model shows promise as an AI-powered triage aid in settings with limited access to specialized care. Full article
(This article belongs to the Section Dentistry and Oral Health)
16 pages, 2784 KiB  
Article
Development of Stacked Neural Networks for Application with OCT Data, to Improve Diabetic Retinal Health Care Management
by Pedro Rebolo, Guilherme Barbosa, Eduardo Carvalho, Bruno Areias, Ana Guerra, Sónia Torres-Costa, Nilza Ramião, Manuel Falcão and Marco Parente
Information 2025, 16(8), 649; https://doi.org/10.3390/info16080649 - 30 Jul 2025
Viewed by 194
Abstract
Background: Retinal diseases are becoming an important public health issue, with early diagnosis and timely intervention playing a key role in preventing vision loss. Optical coherence tomography (OCT) remains the leading non-invasive imaging technique for identifying retinal conditions. However, distinguishing between diabetic macular [...] Read more.
Background: Retinal diseases are becoming an important public health issue, with early diagnosis and timely intervention playing a key role in preventing vision loss. Optical coherence tomography (OCT) remains the leading non-invasive imaging technique for identifying retinal conditions. However, distinguishing between diabetic macular edema (DME) and macular edema resulting from retinal vein occlusion (RVO) can be particularly challenging, especially for clinicians without specialized training in retinal disorders, as both conditions manifest through increased retinal thickness. Due to the limited research exploring the application of deep learning methods, particularly for RVO detection using OCT scans, this study proposes a novel diagnostic approach based on stacked convolutional neural networks. This architecture aims to enhance classification accuracy by integrating multiple neural network layers, enabling more robust feature extraction and improved differentiation between retinal pathologies. Methods: The VGG-16, VGG-19, and ResNet50 models were fine-tuned using the Kermany dataset to classify the OCT images and afterwards were trained using a private OCT dataset. Four stacked models were then developed using these models: a model using the VGG-16 and VGG-19 networks, a model using the VGG-16 and ResNet50 networks, a model using the VGG-19 and ResNet50 models, and finally a model using all three networks. The performance metrics of the model includes accuracy, precision, recall, F2-score, and area under of the receiver operating characteristic curve (AUROC). Results: The stacked neural network using all three models achieved the best results, having an accuracy of 90.7%, precision of 99.2%, a recall of 90.7%, and an F2-score of 92.3%. Conclusions: This study presents a novel method for distinguishing retinal disease by using stacked neural networks. This research aims to provide a reliable tool for ophthalmologists to improve diagnosis accuracy and speed. Full article
(This article belongs to the Special Issue AI-Based Biomedical Signal Processing)
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