Search Results (448)

Background: Desmoid tumors (DT) are rare, locally aggressive neoplasms characterized by an unpredictable clinical course. Although anatomical localization has been associated with tumor behavior, its relationship with systemic inflammatory response remains insufficiently explored. This study aimed to evaluate the impact of tumor localization on systemic inflammatory markers and to investigate CD47 expression in DT. Methods: This retrospective cohort study included 127 patients diagnosed with DT between 2010 and 2023. Demographic, clinicopathological, and laboratory data were collected. Systemic inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), prognostic nutritional index (PNI), HALP score, and pan-immune-inflammation value (PIV), were calculated. Tumor localization was categorized as trunk, extremity, or head and neck. CD47 expression was evaluated by immunohistochemistry. Results: Tumors were most frequently located in the trunk (50.4%), followed by extremities (40.9%) and head and neck region (8.7%). Significant differences in inflammatory markers were observed according to tumor localization. The head and neck group demonstrated lower neutrophil counts (p = 0.020), NLR (p = 0.009), PLR (p < 0.001), and PIV (p = 0.003), while showing higher PNI (p = 0.043) and HALP scores (p = 0.001) compared to trunk-localized tumors. Additionally, smaller tumors (<49 mm) were associated with lower NLR (p = 0.041) and neutrophil counts (p = 0.015). No detectable CD47 expression was observed in any tumor samples. Conclusions: Anatomical localization is closely associated with distinct systemic inflammatory profiles in patients with DT. These findings suggest that tumor location may influence host immune–inflammatory interactions and contribute to the biological heterogeneity of DT. The absence of CD47 expression indicates that alternative immune-related mechanisms may play a role in DT biology. Easily accessible inflammatory markers may provide valuable insights for risk stratification in clinical practice. Full article

Cryptorchidism is one of the most frequently diagnosed developmental disorders of the male canine reproductive system, defined as the failure of one or both testes to descend into the scrotum. Physiologically, testicular descent is typically completed by six to eight weeks of age, although some authors extend this period to sixteen weeks. Failure of testicular descent beyond this timeframe is considered pathological. The condition has multiple causes and affects between 1% and 10% of the canine population. Genetics is the most significant factor, indicating the hereditary basis of cryptorchidism. In addition, increasing attention has been directed toward the potential impact of environmental and epigenetic factors on the incidence of cryptorchidism, suggesting that the condition may result from complex interactions between genetic predisposition and external influences. The effect of hormones (such as INSL3 and testosterone), mechanical factors (including narrowing of the inguinal canal, abnormalities of the gubernaculum, and shortening of the spermatic cord), and environmental factors (for example, exposure to external estrogens and maternal stress during pregnancy) all contribute to the development of this disorder. Recent results have emphasized the role of the orexin system, particularly the OX2R receptor, in regulating endocrine and reproductive functions in cryptorchid testes. Computed tomography is increasingly utilized in complex cases due to its high precision in localizing retained testes. Clinically, cryptorchidism may present unilaterally or bilaterally. Unilateral cryptorchidism may preserve partial fertility, whereas bilateral cryptorchidism results in complete infertility. Undescended testes may be located in the abdominal cavity or inguinal canal. Major complications include an increased risk of testicular cancer (Sertoli cell tumors and seminomas) and endocrine disorders leading to feminization. Diagnosis is based on clinical examination and imaging modalities such as ultrasound. Orchiectomy, involving the removal of both the retained and normally descended testicles, is thought to be the gold standard for treatment. This method helps avoid complications and the transmission of the defect to offspring. According to Fédération Cynologique Internationale (FCI) standards, affected individuals should not be used for breeding or shows. Early detection, surgical intervention, and consistent exclusion from breeding programs are the primary strategies for reducing the incidence of this disorder in the canine population. Full article

Macrophages play a crucial role in health and disease. Currently, reporter mice for tracking alternatively activated macrophages in vivo are lacking. We designed a transgenic mouse model in which luminescence and fluorescence proteins, click beetle red luciferase (CBRED2) and mKate2, report on the expression of the Mrc1/Cd206 promoter, active in the monocyte/macrophage population. The mouse line was named B6Mrc1-mKate2-CBRED2. Using this novel mouse model, we were able to develop in vitro assays to validate transgenic macrophage polarization and test them with compounds of repolarization potency. Furthermore, in the in vivo assays, we exploited the migratory and infiltrative potency of macrophages for detecting tumor locations via optical imaging. In fact, macrophages can act as universal cancer markers, as they infiltrate primary and secondary tumors, stimulating or suppressing tumor growth. We first characterized transgenic mice for reporter expression ex vivo, followed by the generation of luminescence-based assays to reflect the polarity of differentiated macrophages, and lastly, we visualized reporter macrophages accumulating and infiltrating the tumor microenvironment (TME) of murine pancreatic ductal adenocarcinoma (PDAC) at multiple time points. We found that the extent of macrophage recruitment and retention was dependent on the infiltrative T-cell and dendritic cell populations present in the TME, reflecting the immunologically hot or cold nature of the PDAC clones, respectively. In conclusion, the ability to optically detect light-emitting macrophages can be applied not only for cancer studies but also in the context of inflammatory diseases. Full article

Background/Objectives: Seromucinous hamartoma (SH) is an extremely rare benign glandular lesion arising in the nasal cavity and paranasal sinuses, characterized by proliferation of serous and mucinous glands. Preoperative diagnosis by biopsy is extremely uncommon, making it a diagnostic challenge. We report a case of SH and discuss its diagnostic difficulties and management. Case Presentation: A 52-year-old man presented with right-sided nasal obstruction. A lobulated mass in the posterior right nasal cavity was incidentally detected during transnasal endoscopy. The lesion persisted for one year without reduction. CT, MRI, and biopsy failed to provide a definitive diagnosis. The patient was referred to our department, and endoscopic surgery under general anesthesia was performed. The tumor was removed en bloc. Histopathological examination revealed glandular proliferation of mixed serous and mucinous glands within the subepithelial stroma, consistent with SH. Discussion: Preoperative diagnosis is difficult due to insufficient biopsy depth and limited recognition of this rare entity. Since the surface epithelium shows no atypia, identification of subepithelial glandular proliferation is essential. Larger and deeper biopsy specimens and communication with pathologists may improve diagnostic yield. Surgical excision is the treatment of choice. As SH often arises in the posterior nasal cavity and is highly vascular, en bloc resection under general anesthesia is recommended. Conclusions: Recognition of SH is important to improve diagnostic accuracy. Appropriate biopsy strategy and surgical planning based on tumor location are essential. Full article

Background/Objectives: This prospective study used a standardized preoperative assessment to characterize the full spectrum of pain in patients with peripheral nerve tumors, addressing the lack of structured pain phenotyping in this population. Methods: Between June 2024 and October 2025, preoperative pain symptoms were assessed in 91 patients, representing 16% of the Peripheral Nerve Tumor Registry (PNTR) cohort, using the PainDETECT questionnaire (0–38) at two centers: University Hospital Ulm, Günzburg (n = 72), and University Hospital Essen (n = 19). Results: Ninety-one patients (61.5% male; mean age, 49 years) were included. Most tumors were located in the lower extremity (54.9%). PainDETECT scores were ≤12 in 51.6%, 13–18 in 24.1%, and ≥19 in 21.9% of patients. Malignant tumors (6.5%) had the highest mean score (17), but benign tumors also showed a relevant pain burden (mean 11.9). Hybrid peripheral nerve sheath tumors and neurofibromas had numerically higher mean scores than schwannomas, although the difference was not statistically significant. Pain severity was not associated with tumor size, depth, or affected nerve. The most common sensory features were electric-shock-like and pressure-related pain, as reflected by a positive Tinel sign in 86.8% of patients. The most frequent pain pattern was intermittent attacks with pain-free intervals (46%). Conclusions: These interim results indicate that pain is common even in benign peripheral nerve tumors, challenging the assumption that these lesions are often asymptomatic. Malignant tumors showed the highest pain scores. The heterogeneous pain phenotypes highlight the need for individualized assessment and management. Expansion to a multicenter evaluation within the framework of the PNTR is planned. Full article

Brain tumors (BTs) arise from the abnormal growth of cells within brain tissue and may spread rapidly, making them a major cause of mortality worldwide. Early detection of BTs remains highly challenging due to the brain’s complex structure and the heterogeneous nature of tumors. Magnetic Resonance Imaging (MRI) provides detailed information about tumor size, location, and shape, thereby supporting clinical decision-making for treatments such as chemotherapy, radiation therapy, and surgery. Traditional machine learning (ML) approaches mainly rely on manual feature extraction, whereas recent advances in Computer-Aided Diagnosis (CAD) and deep learning (DL) have enabled more accurate detection of small and complex tumor regions. To improve automated tumor detection, we propose a hybrid Swin–YOLO framework that combines the Swin Transformer (ST) with the latest CNN-based YOLOv12 model. In this framework, the Swin Transformer serves as the main backbone for feature extraction, while the Feature Pyramid Network (FPN) and Path Aggregation Network (PANet) are employed in the neck to better capture multi-scale features. For training, we used the publicly available Br35H dataset and applied data augmentation to enhance the model’s robustness and generalization capability. The experimental results show that the proposed framework achieved 99.7% accuracy, 99.4% mAP@50, and 87.2% mAP@50:95. Furthermore, we incorporated Explainable Artificial Intelligence (XAI) techniques, including Grad-CAM and SHAP, to improve the interpretability of the model by visually highlighting the tumor regions that contributed most to the prediction. In addition, we developed NeuroVision AI, a web-based application designed to support faster and more accurate clinical decision-making. Although the proposed model demonstrated strong performance on the dataset, these results should be interpreted within the context of the current experimental setting. Full article

Background: Magnetic Particle Imaging (MPI) is an emerging biomedical imaging modality that detects superparamagnetic iron oxide nanoparticles (SPIONs), providing high contrast, sensitivity, and quantification capabilities without ionizing radiation, making it particularly suitable for cancer diagnostics. Considerable engineering efforts are underway to translate MPI technology to clinical settings. Most of these MPI scanners feature a cylindrical bore geometry similar to that of other clinical imaging modalities, which limits their potential application primarily to head scanning. Methods: We have developed a single-sided MPI scanner designed to expand the modality’s applicability to other regions of the human body through a unique hardware design developed in our previous work. Imaging experiments were performed on an anatomical breast phantom containing implanted SPION point sources placed at anatomically plausible locations for breast tumors. These point sources served as artificial tumors for evaluating the system’s suitability for breast imaging applications. Results: The scanner successfully detected and clearly resolved the implanted SPION tumors in two orthogonal imaging planes. Tumor positioning was independently validated by ultrasound imaging, confirming MPI’s accurate localization. In addition, sensitivity measurements demonstrated a detection limit of 4.0 $\mathsf{\mu }\mathrm{g}$ of iron, below the estimated 4.8 $\mathsf{\mu }\mathrm{g}$ sensitivity threshold required for breast tumor detection with electronic depth scanning up to 3.5 cm deep. Conclusions: Together, these results demonstrate the capability of a single-sided MPI geometry for breast imaging applications. Imaging an anatomical breast-shaped volume presents significant challenges for MPI due to the size and accessibility constraints of conventional hardware. The results presented highlight the advantages of this approach and support its potential to extend MPI from small-animal imaging to clinically relevant applications. Full article

Extrahepatic cholangiocarcinoma (eCCA) is a highly aggressive malignancy arising from the biliary epithelium, with surgical resection representing the only potentially curative treatment. The predominant periductal infiltrating growth pattern, characterized by subepithelial tumor spread and desmoplastic stromal reaction, severely limits the diagnostic sensitivity of conventional endoscopic sampling techniques, which primarily assess the luminal mucosal surface. This review provides a histomorphology-oriented diagnostic framework for indeterminate extrahepatic biliary strictures, integrating advanced endoscopic technologies with emerging optical diagnostic approaches. ERCP combined with cholangioscopy demonstrates superior sensitivity for perihilar strictures, while EUS-guided tissue acquisition shows higher diagnostic yield in distal cholangiocarcinoma, also providing locoregional staging. Advanced EUS technologies—including elastography, contrast harmonic EUS, and Detective Flow Imaging—further improve characterization of indeterminate strictures by evaluating tissue stiffness, microvascular architecture, and periductal infiltration. Ex vivo fluorescence confocal laser microscopy (FCM) enables real-time microscopic evaluation of biopsy specimens, reducing diagnostic turnaround time and minimizing inadequate sampling. A location-adapted diagnostic algorithm integrating cross-sectional imaging, ERCP, cholangioscopy, and EUS is proposed. An integrated, biology-informed endoscopic approach tailored to tumor location and ductal wall involvement may significantly improve early eCCA detection and guide patient selection for curative treatment. Full article

Objective: Primary extranodal lymphomas of the head and neck region are relatively rare and represent a biologically distinct subset. The diagnosis and differential diagnosis of head and neck lymphomas are important and deserve special attention. The aim of the present study was to retrospectively evaluate patients diagnosed with primary head and neck lymphomas at the Department of Pathology between January 2020 and January 2026. Histopathological subtypes, localization, relative frequencies, and overall survival were analyzed. Materials and Methods: This retrospective study included 31 cases diagnosed with lymphoma involving the head and neck region. Medical records were reviewed. Histopathological slides were re-evaluated under light microscopy by experienced pathologists. All cases were classified according to the current World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues. An extensive immunohistochemical panel was applied. Statistical analysis was performed using SPSS statistical software (version 27.0; IBM Corp., Armonk, NY, USA). Results: The study group included 31 patients with head and neck lymphoma. The most common histological type was diffuse large B-cell lymphoma (DLBCL) (54.8%). Other histological subtypes included follicular lymphoma (FL), mantle cell lymphoma (MCL), extranodal NK/T-cell lymphoma (NKTCL), anaplastic large cell lymphoma (ALCL), and Hodgkin lymphoma (HL). The most common location was the tonsil (38.7%). Other locations included the nasopharynx, oral cavity, nasal cavity, salivary glands, and thyroid. Epstein–Barr virus (EBV) positivity was detected in two patients (6.5%), and human immunodeficiency virus (HIV) infection was identified in two patients (6.5%). At the time of the last follow-up, 27 patients (87.1%) were alive, whereas four patients (12.9%) had died. The mortality rate was 12.9%. The median overall survival was 28 months (95% CI: 10–45). Conclusions: Malignant lymphoma should be considered when evaluating head and neck masses, and histopathological assessment of the affected tissue remains the cornerstone of diagnosis. Full article

Background: Breast cancer is the most common malignancy in women, and sentinel lymph node (SLN) biopsy is essential for accurate nodal staging while avoiding unnecessary axillary dissection. Aim: This study aimed to compare SLN detection rates between two dual-tracer techniques: indocyanine green plus patent blue (ICG + PB) and technetium-99m plus patent blue (99mTc + PB), and to identify factors associated with detection failure for each tracer. Methods: All clinically node-negative breast cancer patients undergoing SLN biopsy between January 2014 and December 2024 were retrospectively evaluated. SLN detection was considered successful when at least one node was identified intraoperatively and confirmed histologically. Multivariate analysis assessed clinical and tumor-related predictors of failure. Results: A total of 269 procedures (258 patients) were analyzed, including 152 ICG + PB and 117 99mTc + PB procedures. Detection rates were comparable between groups (95.4% vs. 94.9%, p = 0.96), with no significant differences in the number of SLNs retrieved or nodal positivity. Multivariate analysis identified increasing patient age as the only independent predictor of PB failure, while no variables were associated with ICG failure. Tumor location in the upper-inner quadrant was the sole predictor of 99mTc failure. Conclusions: ICG + PB and 99mTc + PB provide equivalent and high SLN detection rates. ICG appears to be a robust, radiation-free alternative with no identifiable predictors of failure, supporting its role as an effective mapping strategy, particularly in centers aiming to optimize workflow and patient safety, despite the limited available data on its efficacy. Full article

Avian reticuloendotheliosis (RE) caused by reticuloendotheliosis virus (REV) is an important tumor and immunosuppressive disease posing a serious threat to poultry development. The REV envelope protein, glycoprotein (gp)-90, not only participates in cell receptor binding and viral assembly and release but also induces neutralizing antibody production. However, the antigenic epitope structure of gp90 has not yet been systematically understood. Therefore, in this study, the gp90 envelope protein of a predominant REV strain was prepared using a prokaryotic expression system, and a hybridoma cell line stably secreting the REV gp90 monoclonal antibody was developed via cell fusion and flow cytometry. Notably, a novel linear B-cell epitope, ¹⁹⁵REESVRERL²⁰³, was identified for the first time in the gp90 of REV using peptide scanning. This epitope was located on the outer side of the gp90 midpiece and was conserved across REV strains. Overall, this study is of great significance for the systematic understanding of REV antigen structure and the development of virus detection methods. Full article

Background and Objectives: Melanoma is the leading cause of skin cancer-related mortality due to its high propensity for early metastasis, although survival rates have improved with the advent of targeted and immune-based therapies. Accurate detection of targetable mutations and assessment of tumor mutational burden are essential for informed therapeutic decision-making. Mutation profiling is routinely performed using next-generation sequencing (NGS). The Oncomine Focus Assay (OFA) detects common alterations in 52 genes across various tumor entities, whereas MelArray is a melanoma-specific NGS panel covering mutations in 190 melanoma-relevant genes and providing a genome-wide copy number analysis. Moreover, tumor mutational burden is being assessed. Materials and Methods: In this retrospective study, we analyzed the phenotypic characteristics of 100 patients with cutaneous melanoma who underwent NGS testing using either OFA or MelArray. The aims were to compare the diagnostic yield of the two panels and to investigate potential associations between mutational profiles and clinicopathological features of melanoma. Results: Tumor location, ulceration, and Breslow thickness showed significant correlations with the melanoma subtypes. BRAF mutations were the most frequent driver alterations across all cutaneous melanoma subtypes; however, no significant correlation between specific driver mutations and phenotypic characteristics was identified. MelArray detected a notably high number of alterations in the TERT promoter and CDKN2A genes, which were not captured by OFA and are of potential therapeutic relevance. Conclusions: In conclusion, MelArray enables a more comprehensive molecular characterization of cutaneous melanoma compared with a small generic cancer panel and may support more personalized therapeutic decision-making. Full article

Background/Objectives: Brain tumors are among the most severe neurological disorders, and their variability in size, morphology, and anatomical location complicates early and accurate diagnosis. Although magnetic resonance imaging (MRI) is the most reliable non-invasive modality for tumor detection, manual interpretation remains time-consuming, subjective, and susceptible to human error. This study aims to develop an optimization-driven hybrid machine learning framework for accurate and computationally efficient automatic brain tumor classification. Methods: The dataset includes 834 MRI images (583-training, 123-validation, 128-independent test). Because YOLOv11 detects tumor and non-tumor regions separately, the sample size doubled during region-based analysis, and all subsequent stages were conducted at the regions of interest (ROI) level. On the independent test set, YOLOv11 achieved 98.87% mAP@50, 98.54% precision, and 98.21% recall. The proposed framework combines automated tumor localization with image standardization using Gaussian noise reduction and bilinear interpolation. From the processed MR images, 39 entropy-based features were extracted. To enhance diagnostic performance and eliminate redundant information, the superb fairy-wren optimization algorithm (SFOA) was applied for feature selection and compared with particle swarm optimization (PSO), Harris hawk optimization (HHO), and puma optimization (PO). Final classification was primarily performed using k-nearest neighbors (kNN), while support vector machines (SVM) were used for comparative evaluation. Results: SFOA reduced the feature dimensionality from 39 to 5 features while achieving 99.20% classification accuracy on the independent test set. In comparison, PSO selected 10 features, HHO selected 6 features and PO selected 10 features, all achieving 98.45% accuracy. The best performance obtained with SVM was 98.45% accuracy (HHO-SVM), which remained lower than the 99.20% achieved by the proposed SFOA-kNN model. Conclusions: The results indicate that combining entropy-based feature extraction with SFOA-driven feature selection and kNN classification significantly enhances diagnostic accuracy while reducing computational complexity, highlighting the strong potential of the proposed framework for integration into computer-aided diagnosis systems to support clinical decision-making. Full article

Cancer is one of the global health problems that affects millions of people every year. Biopsies are among the standard methods for detecting and confirming a cancer diagnosis. Performing this study manually poses several challenges due to tissue movement and the difficulty of precisely locating the target, as is often the case in lung biopsies. This study presents the design and implementation of an autonomous image processing algorithm included in a closed-loop controller that drives the activity of a multi-degree-of-freedom (six) robotic manipulator that performs emulated tissue biopsies. A realistic lung motion emulator, based on a two-degree-of-freedom robotic device with a photon emitter (to simulate radiopharmaceutical identification of cancerous tissue), was used to test the proposed automatic biopsy collector. Applying image processing to detect cancer tissue enables the identification of the centroid and tumor boundaries. Using the detected centroid coordinates, the reference trajectory of the end effector (biopsy needle) was automatically determined. A finite-time convergent controller was implemented to guide the robotic manipulator’s motion towards the tumor position within a specified time window. The controller was evaluated using a digital twin representation of the entire robotic system and using an experimental device working on the simulated mobile tumor emulator. Evaluation of simulated tumor detection and reference trajectory tracking effectiveness was used to validate the operation of the proposed automatic robotic lung biopsy sampler. The application of the controller allows one to track the position of the emulated tumor with a deviation of 0.52 mm and a settling time of less than 1 s. Full article

Background/Objectives: Aggressive variants of prostate cancer pose significant diagnostic and prognostic challenges due to atypical imaging appearances, variable prostate-specific antigen behavior, and distinct molecular features. Conventional imaging may underestimate their biological aggressiveness. This review aimed to synthesize current evidence on imaging characteristics, biomarker dynamics, tumor localization, histology, and radiomic features of aggressive prostate cancer variants, and to evaluate the potential role of radiomics in early recognition and risk stratification. Methods: A structured narrative review was performed of studies reporting imaging, clinical, and molecular features of aggressive prostate cancer variants. Imaging modalities included multiparametric magnetic resonance imaging, positron emission tomography with prostate-specific membrane antigen or fluorodeoxyglucose, bone scintigraphy, and transrectal ultrasound. Data on prostate-specific antigen levels and kinetics, intraprostatic tumor location, tumor size, metastatic patterns, and molecular alterations were extracted. Evidence for rare entities such as basaloid and primary squamous carcinomas was derived from published case reports and series, while selected variants were complemented by institutional imaging and histopathologic observations. Results: Neuroendocrine and small cell carcinomas frequently showed low prostate-specific antigen levels, high fluorodeoxyglucose uptake, low prostate-specific membrane antigen expression, and central or transitional zone involvement with large tumor size at diagnosis. Ductal adenocarcinoma demonstrated marked diffusion restriction and elevated prostate-specific antigen, whereas basal cell carcinoma often appeared inconspicuous on conventional imaging. Radiomic analysis consistently captured tumor heterogeneity and spatial complexity beyond standard qualitative metrics. Conclusions: Aggressive prostate cancer variants represent a diagnostic blind spot in routine imaging. Radiomics offers complementary quantitative information that may improve early detection, subtype differentiation, and risk stratification when integrated into multimodal imaging workflows. Further prospective and radiogenomic studies are warranted to validate these findings. Full article