Search Results (145)

Melanoma subtyping plays a vital role in histopathological diagnosis, informing prognosis and, in some cases, guiding targeted therapy. However, conventional histologic classification is constrained by inter-rater reliability, morphologic overlap, and the underrepresentation of rare subtypes. Deep learning (DL)—particularly convolutional neural networks (CNNs)—presents a compelling opportunity to enhance diagnostic precision and reproducibility through automated analysis of histopathologic slides. This review examines the clinical importance and diagnostic challenges of melanoma subtyping, outlines core DL methodologies in dermatopathology, and synthesizes current advances in applying DL to subtype classification. Pertinent limitations including dataset imbalance, a lack of interpretability, and domain generalizability are discussed. Additionally, emerging directions such as multimodal integration, synthetic data generation, federated learning, and explainable AI are highlighted as potential solutions. As these technologies mature, DL holds considerable promise in advancing melanoma diagnostics and supporting more personalized, accurate, and equitable patient care. Full article

Undifferentiated pleomorphic sarcoma (UPS) is the most morphologically and genetically heterogeneous form of soft tissue sarcoma. UPS tumors can exhibit a wide range of genetic abnormalities, including activating and inactivating mutations, gene amplifications, chromosomal translocations, and copy number variations. Owing to this extensive genetic heterogeneity, no UPS-specific therapeutic targets have yet been validated, complicating diagnosis, prognosis, and the selection of targeted treatment strategies. Currently, immune checkpoint inhibitors (targeting PD-1, PD-L1, and CTLA-4) are the only validated targeted therapy for UPS, reflecting the frequent mutational events that activate immune response pathways. Because molecular genetic profiling alone provides limited prognostic value for chemoresistance in UPS, the development of experimental ex vivo and in vitro testing approaches may help to identify and exclude potentially ineffective targeted therapies. Full article

Current histological staining methods for intestinal tissue analysis face limitations in simultaneously visualizing multiple tissue components, often requiring multiple sequential stains that increase processing time and tissue consumption. This proof-of-concept study aimed to define and develop a pentachromatic staining method for enhanced visualization of gastrointestinal tissue architecture. We developed the Pentachroma O-H method, an original protocol using readily available histological reagents (Alcian Blue pH 2.5, Weigert’s resorcin–fuchsin, Mayer’s hematoxylin, and Van Gieson’s solution) applied in an optimized sequence. The protocol was tested on healthy human ileum tissue obtained from surgical specimens as proof of concept. Thirty serial sections were stained with Pentachroma O-H and compared to adjacent sections stained with conventional hematoxylin–eosin (H&E) to document the emerging morphological characteristics of this original stain. Pentachroma O-H achieved distinct five-color differentiation in approximately 45 min: acidic mucins appeared turquoise–blue, collagen fibers red, elastic fibers black–purple, smooth muscle and erythrocyte cytoplasm yellow, and nuclei blue–black. The method clearly delineated intestinal architecture, including mucosal goblet cells, muscularis mucosae, connective tissue vasculature (parietal smooth muscle and elastic laminae), fibers, and cellular components, as well as lymphoid tissue aggregates and infiltrates, with improved contrast compared to H&E. All tissue components were simultaneously visualized in single sections with excellent morphological preservation. This first description of Pentachroma O-H demonstrates its capability to provide comprehensive ileum tissue visualization equivalent to multiple traditional special stains in a single, efficient protocol, offering significant potential advantages for gastrointestinal pathology assessment and warranting future validation studies across diverse tissue types and pathological conditions. Full article

Cervical cancer is a major global health concern with serious implications for women’s health. It is most often caused by persistent infection with high-risk human papillomavirus (HPV) types. However, about 5–11% of cervical carcinoma cases are HPV-independent, entities with their own unique set of histopathological, molecular, and clinical features. The histopathological forms of HPV-independent cervical cancer include gastric-type adenocarcinoma, clear-cell, mesonephric, and endometrioid carcinoma. Unlike HPV-associated cervical cancers, which require E6 and E7 oncogenes for their expression, HPV-independent tumors exhibit specific mutations such as TP53, PIK3CA, KRAS, STK11, and PTEN. These mutations lead to alternative oncogenic pathways. Diagnosis of HPV-independent cervical adenocarcinoma is often delayed because of possible misclassification as endometrial adenocarcinomas, which frequently results from inadequate HPV testing. This often leads to advanced presentation stages, higher rates of lymphovascular invasion, and, in many cases, a reduced response to chemotherapy and immunotherapy—though outcomes can vary across histotypes and selected patient subgroups—due to the immune-cold tumor microenvironment. Although these morphologic and molecular characteristics describe tumors that are very difficult to manage, PI3K/mTOR and KRAS inhibitors may offer potential therapeutic options for selected patients. This review focuses on the pathogenic and molecular mechanisms, histopathological features, prognosis, and therapeutic difficulties of HPV-independent cervical cancers. Moreover, it provides a comprehension of contemporary issues in diagnostic methods and some new therapeutic approaches, suggesting the need for precision medicine in this aggressive type of cervical cancer. Further studies are necessary to enhance early detection, improve treatment results, and increase survival rates for patients with HPV-independent cervical cancer. Full article

Cutaneous leiomyosarcoma is a rare, malignant tumor that arises from smooth muscle cells, accounting for less than 3% of all cutaneous sarcomas. Our case report details a 63-year-old male patient who presented with a rapidly growing, painful nodule in the popliteal region. The patient underwent initial surgical excision in September 2021, followed by three subsequent resections until March 2022 due to local recurrence. Histopathological analysis of all specimens revealed a dermal neoplasm composed of spindle cells arranged in intersecting fascicles with storiform patterns. The immunohistochemistry profile showed strong positivity for the markers SMA and desmin, confirming the diagnosis. Despite early interventions, the deep surgical margins were positive, and further surgeries were required until tumor-free margins were achieved. This case emphasizes the morphological characteristics, clinical behavior, and therapeutic challenges in managing cutaneous leiomyosarcoma. A favorable prognosis is achieved with long-term follow-up and a multidisciplinary approach. Full article

Progress in clinical diagnosis increasingly relies on innovative technologies and advanced disease biomarker detection methods. While cell labeling remains a well-established technique, label-free approaches offer significant advantages, including reduced workload, minimal sample damage, cost-effectiveness, and simplified chip integration. These approaches focus on the morpho-biophysical properties of cells, eliminating the need for labeling and thus reducing false results while enhancing data reliability and reproducibility. Current label-free methods span conventional and advanced technologies, including phase-contrast microscopy, holographic microscopy, varied cytometries, microfluidics, dynamic light scattering, atomic force microscopy, and electrical impedance spectroscopy. Their integration with artificial intelligence further enhances their utility, enabling rapid, non-invasive cell identification, dynamic cellular interaction monitoring, and electro-mechanical and morphological cue analysis, making them particularly valuable for cancer diagnostics, monitoring, and prognosis. This review compiles recent label-free cancer cell detection developments within clinical and biotechnological laboratory contexts, emphasizing biophysical alterations pertinent to liquid biopsy applications. It highlights interdisciplinary innovations that allow the characterization and potential identification of cancer cells without labeling. Furthermore, a comparative analysis addresses throughput, resolution, and detection capabilities, thereby guiding their effective deployment in biomedical research and clinical oncology settings. Full article

Polycystic ovarian syndrome (PCOS) is one of the most common endocrine and metabolic conditions affecting women of reproductive age. This condition affects around 20% of this demographic and is characterized by polycystic ovarian morphology, hyperandrogenism, and chronic anovulation. Obesity, impacting 40–85% of women with PCOS, exacerbates insulin resistance, increases insulin levels, and intensifies low-grade inflammation. This exacerbates the reproductive and metabolic complications associated with the condition. Recent advancements in molecular biology have underscored the significance of non-coding RNAs, including as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), as crucial regulators of gene expression and prospective biomarkers for PCOS. Exosome-derived microRNAs (ex-miRNAs) have emerged as compelling candidates due to their stability in body fluids and their capacity to promote intercellular communication among adipose tissue, the ovary, and the endometrium. Research, encompassing both experimental and clinical studies, has shown that ex-miRNAs display differing expression levels in women with obesity-related PCOS. Several of these ex-miRNAs are associated with networks that govern inflammation, glucose metabolism, steroidogenesis, and folliculogenesis. Moreover, the encapsulation of these chemicals within exosomes safeguards them from enzymatic breakdown, hence augmenting their potential as non-invasive biomarkers for diagnosis, prognosis, and treatment monitoring. Despite the initial results being encouraging, challenges remain in standardising exosome separation, quantifying miRNA, and analyzing functional data within the complex pathophysiology of PCOS. This narrative review consolidates existing evidence regarding the molecular signatures of obesity-related infertility in PCOS, emphasising the growing significance of exosomal miRNAs and other non-coding RNAs, while examining their translational potential for early diagnosis and personalised therapeutic approaches. Full article

Cardiac magnetic resonance (CMR) imaging has become a key tool in evaluating myocardial injury secondary to coronary artery disease (CAD), providing detailed assessments of cardiac morphology, function, and tissue composition. The integration of artificial intelligence (AI), including machine learning and deep learning techniques, has enhanced the diagnostic capabilities of CMR by automating segmentation, improving image interpretation, and accelerating clinical workflows. Radiomics, through the extraction of quantitative imaging features, complements AI by revealing sub-visual patterns relevant to disease characterization. This systematic review analyzed AI applications in CMR for CAD. A structured search was conducted in MEDLINE, Web of Science, and Scopus up to 17 March 2025, following PRISMA guidelines and quality-assessed with the CLAIM checklist. A total of 106 studies were included: 46 on classification, 19 using radiomics, and 41 on segmentation. AI models were used to classify CAD vs. controls, predict major adverse cardiovascular events (MACE), arrhythmias, and post-infarction remodeling. Radiomics enabled differentiation of acute vs. chronic infarction and prediction of microvascular obstruction, sometimes from non-contrast CMR. Segmentation achieved high performance for myocardium (DSC up to 0.95), but scar and edema delineation were more challenging. Reported performance was moderate-to-high across tasks (classification AUC = 0.66–1.00; segmentation DSC = 0.43–0.97; radiomics AUC = 0.57–0.99). Despite promising results, limitations included small or overlapping datasets. In conclusion, AI and radiomics offer substantial potential to support diagnosis and prognosis of CAD through advanced CMR image analysis. Full article

Red blood cell (RBC), accounting for approximately 45% of total blood volume, are essential for oxygen delivery and carbon dioxide removal. Their unique biconcave morphology, high surface area-to-volume ratio, and remarkable deformability enable them to navigate microvessels narrower than their resting diameter, ensuring efficient microcirculation. RBC deformability is primarily determined by membrane viscoelasticity, cytoplasmic viscosity, and cell geometry, all of which can be altered under various physiological and pathological conditions. Reduced deformability is a hallmark of numerous diseases, including sickle cell disease, malaria, diabetes mellitus, sepsis, ischemia–reperfusion injury, and storage lesions in transfused blood. As these mechanical changes often precede overt clinical symptoms, RBC deformability is increasingly recognized as a sensitive biomarker for disease diagnosis, prognosis, and treatment monitoring. Over the past decades, diverse techniques have been developed to measure RBC deformability. These include single-cell methods such as micropipette aspiration, optical tweezers, atomic force microscopy, magnetic twisting cytometry, and quantitative phase imaging; bulk approaches like blood viscometry, ektacytometry, filtration assays, and erythrocyte sedimentation rate; and emerging microfluidic platforms capable of high-throughput, physiologically relevant measurements. Each method captures distinct aspects of RBC mechanics, offering unique advantages and limitations. This review synthesizes current knowledge on the pathophysiological significance of RBC deformability and the methods for its measurement. We discuss disease contexts in which deformability is altered, outline mechanical models describing RBC viscoelasticity, and provide a comparative analysis of measurement techniques. Our aim is to guide the selection of appropriate approaches for research and clinical applications, and to highlight opportunities for developing robust, clinically translatable diagnostic tools. Full article

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) diagnosis and treatment rely heavily on computed tomography (CT) imaging to evaluate tumor characteristics and lymph node (LN) involvement, crucial for staging, prognosis, and therapy planning. Conventional LN evaluation methods based on morphological criteria such as size, shape, and anatomical location often lack sensitivity for early metastasis detection. This study leverages radiomics to extract quantitative features from CT images, addressing the limitations of subjective assessment and aiming to enhance LN classification accuracy while potentially reducing reliance on invasive histopathology. Methods: We analyzed 234 LNs from 27 HNSCC patients, deriving 120 features per node, resulting in over 25,000 data points classified into reactive, pathologic, and pathologic with extracapsular spread classes. Considering the challenges of high dimensionality and limited dataset size, more than 44,000 experiments systematically optimized machine learning models, feature selection methods, and hyperparameters, including ensemble approaches to strengthen classification robustness. A Pareto front strategy was employed to balance diagnostic accuracy with significant feature reduction. Results: The optimal model, validated via 5-fold cross-validation, achieved a balanced accuracy of 0.90, an area under the curve (AUC) of 0.93, and an F1-score of 0.88 using only five radiomics features. Conclusions: This interpretable approach aligns well with clinical radiology practice, demonstrating strong potential for clinical application in noninvasive LN classification in HNSCC. Full article

Background: Melanoma is one of the most aggressive types of skin cancer. Its diagnosis appears to be challenging due to morphological similarities to benign melanocytic lesions. Even though histopathological evaluation is the diagnostic gold standard, immunohistochemistry (IHC) proves to be useful in challenging cases. Preferentially Expressed Antigen in Melanoma (PRAME) has emerged as a promising diagnostic, prognostic, and therapeutic marker in melanoma. Methods: This review critically examines the role of PRAME across clinical domains. It presents an evaluation of PRAME’s diagnostic utility in differentiating melanomas from benign nevi, its prognostic significance across melanoma subtypes, and therapeutic applications in emerging immunotherapy strategies. An extensive analysis of the current literature was conducted, with a focus on PRAME expression patterns in melanocytic lesions and various malignancies, along with its integration into IHC protocols and investigational therapies. Results: PRAME demonstrates high specificity and sensitivity in distinguishing melanoma from benign melanocytic proliferations, particularly in challenging subtypes such as acral, mucosal, and spitzoid lesions. Its overexpression correlates with poor prognosis in numerous malignancies. Therapeutically, PRAME’s HLA class I presentation enables T-cell-based targeting. Early-phase trials show promising results using PRAME-directed TCR therapies and bispecific ImmTAC agents. However, immune evasion mechanisms (i.e., heterogeneous antigen expression, immune suppression in the tumor microenvironment, and HLA downregulation) pose significant challenges to therapy. Conclusions: PRAME is a valuable biomarker for melanoma diagnosis and a promising target for immunotherapy. Its selective expression in malignancies supports its clinical utility in diagnostic precision, prognostic assessment, and precision oncology. Ongoing research aimed at overcoming immunological barriers will be essential for optimizing PRAME-directed therapies and establishing their place in the personalized management of melanoma. Full article

Neuroendocrine neoplasms (NENs) of the lung are a biologically and clinically diverse group of tumors that includes well-differentiated typical and atypical carcinoids (LNETs), as well as poorly differentiated large-cell neuroendocrine carcinoma and small-cell lung cancer. Despite their relative rarity, the incidence of LNETs is increasing, primarily due to advancements in diagnostic techniques and heightened clinical awareness. While the current World Health Organization (WHO) classification offers a morphological basis for diagnosis and prognosis, particularly for extrapulmonary neuroendocrine neoplasms (ep-NENs), it has limitations in predicting the clinical behavior of pulmonary carcinoids. Recent evidence highlights the inadequacy of traditional criteria in fully capturing the biological complexity and clinical heterogeneity of these tumors. This review explores the evolving landscape of LNETs, focusing on well-differentiated forms and analyzing current classification systems, clinicopathological features, and the emerging role of novel prognostic and predictive biomarkers. Advances in histopathology and molecular profiling have begun to elucidate distinct molecular subsets within carcinoids, offering potential avenues for improved risk stratification and therapeutic decision-making. Although there are limited treatment options for advanced disease, new insights into tumor biology could facilitate the development of personalized therapeutic strategies and pave the way for future innovations in LNET management. Full article

Objectives: This study sought to echocardiographic manifestations and the related risk factors affecting the prognosis of isolated congenitally corrected transposition of the great arteries (CCTGA). Methods: A total of 143 patients (≥18 years of age) were diagnosed with isolated CCTGA at Anzhen Hospital. The patients were classified as the operation group and the non-operation group depending on whether they had undergone tricuspid valve surgery. The echocardiographic data and follow-up were compared, and the primary outcomes examined were defined as death or heart transplantation. Results: The average age of 143 patients with isolated CCTGA was 39.93 ± 13.50 years. Tricuspid valve surgery was performed in 31 patients with isolated CCTGA, and 112 patients did not undergo tricuspid valve surgery. The incidence of tricuspid valve structural changes in the operation group was 39.1%, and this group had higher numbers of patients with right ventricular diastolic diameter, right ventricular systolic diameter, left atrial dimensions, and regurgitation before surgery compared with the non-operation group (p < 0.05). Follow-up results showed no significant difference in the number of death/heart transplantations, and the incidence of systemic ventricular ejection fraction (SVEF) < 40% between the two groups. The survival rate of the surgery group was higher than that of the non-surgery group, although not statistically significant (p = 0.123). Age, right ventricular end-diastolic diameter, and decreased SVEF at the first diagnosis are independent predictive risk factors for major adverse outcomes. Conclusions: Adult patients with isolated CCTGA may have structural abnormalities in their tricuspid valves. There were no significant differences in the incidence of adverse outcomes, morphological right ventricular systolic dysfunction, and survival between the surgery group and the non-surgery group. However, this study is a retrospective study, and the sample size of the surgical group is relatively small, which may limit the generalizability of the research conclusions. In the future, a prospective, large-scale study will be conducted to evaluate the therapeutic effect of tricuspid valve surgery on such patients. Full article

Posterior pituitary tumors (PPTs) are rare, non-neuroendocrine neoplasms derived from pituicytes of the neurohypophysis or infundibulum. According to the 2025 WHO classification, PPTs comprise four distinct but related low-grade entities: pituicytoma, granular cell tumor of the sellar region, spindle cell oncocytoma, and ependymal pituicytoma. All share nuclear TTF-1 expression, confirming their common origin, but differ in morphology, immunophenotype, and ultrastructure. Histologically, pituicytomas consist of bipolar spindle cells in fascicles; granular cell tumors show polygonal cells with PAS-positive, diastase-resistant cytoplasmic granules; spindle cell oncocytomas display oncocytic change and abundant mitochondria; and ependymal pituicytomas exhibit perivascular pseudorosettes and EMA positivity in apical or dot-like patterns. Immunohistochemically, all are S100 and vimentin positive, and negative for pituitary hormones and lineage-specific transcription factors. Clinically, PPTs are typically non-functioning but may be associated with corticotroph or somatotroph hyperfunction. Imaging features are nonspecific. Surgical resection is the treatment of choice, although hypervascularity and adherence—especially in spindle cell oncocytomas—can hinder complete excision. Radiotherapy is reserved for recurrences. Molecular analyses reveal recurrent alterations in MAPK/PI3K pathways (e.g., HRAS, BRAF, FGFR1, NF1, TSC1) and suggest a shared histogenesis. Copy number imbalances correlate with reduced progression-free survival in some subtypes. Despite a generally favorable prognosis, recurrence—particularly in spindle cell oncocytomas—necessitates long-term follow-up. The WHO 2025 update provides a unified framework for classification, diagnosis, and prognostic stratification of these rare tumors. Full article

In children without Down syndrome who have acute megakaryoblastic leukemia (AMKL), inv(16)(p13q24)/CBFA2T3::GLIS2 is the most frequent genetic aberration. Pediatric CBFA2T3::GLIS2-positive AMKL is strongly associated with a poor prognosis and a high cumulative incidence of relapse. One of the key laboratory signs of CBFA2T3::GLIS2-positive AMKL is the RAM immunophenotype, which looks very similar to that of solid-tumor bone marrow (BM) infiltration. For this reason, in cases of isolated extramedullary involvement of CBFA2T3::GLIS2-positive AMKL, excluding solid tumors may be challenging. We report a case of a girl with isolated extramedullary CBFA2T3::GLIS2-positive AMKL relapse, which was misdiagnosed as secondary Ewing sarcoma. The morphological differential diagnosis between Ewing sarcoma and AMKL presented significant challenges owing to their overlapping histological features (small, round blue-cell morphology and similar growth patterns). The tumor cells’ immunophenotype completely mirrored that at the initial diagnosis of AMKL. Additional cytogenetic and molecular studies confirmed the presence of the CBFA2T3::GLIS2 fusion, but no Ewing sarcoma-specific EWSR1, FUS and CIC fusion transcripts were found. Thus, extramedullary CBFA2T3::GLIS2-positive AMKL relapse was confirmed. The presented case demonstrates the difficulties in differential diagnosis between AMKL relapse and the development of a secondary tumor. Full article