Search Results (797)

Background and Clinical Significance: Angioleiomyoma (ALM) is a benign tumor that generally presents as a single lesion and, according to the updated WHO classification, includes the following three histological subtypes: solid (or capillary), cavernous, and venous. Typically, ALMs are described as well-defined nodules in the lower extremities but are unusually located in the acral locations and toes. We summarize two cases of ALM and perform a systematic review to provide foot surgeons with the most up-to-date and useful information on the epidemiological aspects, anatomical distribution, and specific histological subtypes of ALM in the foot. Materials and Methods: A systematic review was carried out according to the criteria of a PICO framework, and a systematic search and data processing were carried out according to the PRISMA guidelines. We analyzed patient demographics, clinical characteristics, diagnostic workup, treatment, and clinical outcomes. Each one of the included articles was independently assessed for methodological quality and risk of bias by an independent evaluator. The risk of bias of the included studies was assessed based on their characteristics. Results: This systematic review included 14 case series with 172 reported cases of ALM. One hundred and seventy-two (18.57%) were cases of ALM located on foot, excluding the ankle region. The female-to-male ratio was 1.48. The most common location was the hindfoot (41.5%), followed by the forefoot (20.2%) and the midfoot (8.9%). In 29.4% of cases, the location of the lesions could not be determined. The most frequent location of the lesions was subcutaneous (69%), followed by subaponeurotic (16.5%) and skin (14.5%) locations. The most frequent histological presentation was the solid histologic subtype (65%), followed by the venous subtype (21%) and the cavernous subtype (14%), respectively. Of the total reported cases of ALM located in foot, 63.1% presented as solid painful lesions. Calcified presentations occurred in 7% of cases, with more than half of the cases located in the hindfoot. Surgical excision was the treatment of choice in the two herein reported cases of solid ALM located in the hindfoot, one of them with a calcified presentation. No recurrence was observed in either case after two and five years of follow-up, respectively. All cases reviewed after surgical excision showed a low recurrence rate with a favorable prognosis regardless of the histological subtype and a very rare tendency toward malignancy. Conclusions: ALMs of the foot present as well-defined, painful nodules in the subcutaneous tissue of middle-aged women. Solid histological subtypes are the most prevalent. Histopathological analysis is usually essential for confirmation. Treatment consists primarily of direct excision, with remarkably low recurrence rates. Full article

Background: Anti-synthetase Syndrome (ASyS) is an idiopathic inflammatory myopathy characterized by muscle weakness and inflammatory infiltrates in muscles. Sjogren’s disease (SD) is an autoimmune condition primarily affecting exocrine glands. Both these conditions may present lung involvement. We describe a female patient with anti-synthetase/SD overlap syndrome and review the literature to identify published cases describing this overlap, aiming to better define its clinical, radiological, and serological features. Methods: The case description was based on a retrospective collection of clinical, laboratory, and imaging data related to the patient’s diagnostic process and clinical course. Data were anonymized and handled in accordance with the competent territorial Ethics Committee. A literature review was performed using the MEDLINE and Scopus databases by combining the keywords “Anti-Synthetase syndrome”, “Sjögren disease”, “Sjögren syndrome”, “Myositis”, and “Interstitial lung disease” (ILD). Published cases were selected if they met the 2016 EULAR/ACR criteria for SD and at least one of the currently proposed classification criteria for ASyS. Results: The described case concerns a 68-year-old woman with rapidly progressive ILD. The diagnosis of anti-synthetase/SD overlap syndrome was based on clinical, serological (anti-Ro52 and anti-PL7 antibodies), histological, and radiological findings. Despite immunosuppressive and antifibrotic treatment, the clinical course worsened, leading to a poor outcome. In addition, six relevant cases were identified in the literature. Clinical presentations, autoantibody profiles, radiological findings, and outcomes were highly heterogeneous. Among the reported cases, no standardized treatment protocols were adopted, reflecting the lack of consensus in managing this rare condition. Conclusions: In anti-synthetase/SD overlap syndrome, ILD may follow a rapidly progressive course. Early recognition can be challenging, especially in the absence of muscular involvement. This case-based review highlights the need for more standardized approaches to the diagnosis and management of this rare and complex overlap syndrome. Full article

Variants in ELAC2, a gene encoding the mitochondrial RNase Z enzyme essential for mitochondrial tRNA processing, have been associated with severe pediatric-onset mitochondrial dysfunction, primarily presenting with developmental delay, hypertrophic cardiomyopathy (HCM), and lactic-acidosis. We hereby report the case of a 25-year-old young woman presenting with dilated cardiomyopathy (DCM) and peripheral sensorimotor polyneuropathy, harboring a homozygous variant in ELAC2. The same variant has been reported only once so far in a case of severe infantile-onset form of HCM and mitochondrial respiratory chain dysfunction, with in vitro data showing a moderate reduction in the RNase Z activity and supporting the current classification as C4 according to the American College of Medical Genetics (ACMG) criteria (PS3, PM2, PM3, PP4). Our extensive clinical, imaging, histological, and genetic investigations support a causal link between the identified variant and the patient’s phenotype, despite the fact that the latter might be considered atypical according to the current state of knowledge. A detailed review of the existing literature on ELAC2-related disease is also provided, highlighting the molecular mechanisms underlying tRNA maturation, mitochondrial dysfunction, and the variable phenotypic expression. Our case further expands the clinical spectrum of ELAC2-related cardiomyopathies to include a relatively late onset in young adulthood and underscores the importance of comprehensive genetic testing in unexplained cardiomyopathies with multisystem involvement. Full article

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

Rationale: The ProMisE molecular classification improves risk assessment in endometrial cancer (EC), but 3–11% of cases exhibit overlapping molecular features, complicating clinical decisions. We analyzed the prevalence and clinicopathological profiles of multiple-classifier ECs in a large Polish cohort. Methods: In this retrospective study (2022–2025), 1075 ECs from four institutions were classified by MMR and p53 immunohistochemistry and POLE exon sequencing. Tumors showing ≥2 molecular features (e.g., MMRd–p53abn, POLEmut–p53abn) were categorized as multiple-classifier ECs. Results: Multiple-classifier ECs comprised 6.9% (74/1075), with MMRd–p53abn (3.9%) being most common. These tumors exhibited more aggressive features vs. MMRd-only: G3 (28.57% vs. 11.79%, p = 0.002), non-endometrioid histology (11.9% vs. 2.85%, p = 0.018), and high–intermediate/high-risk (HIR/HR) groups (59.52% vs. 37.80%, p = 0.001). POLEmut–p53abn (N = 4) and POLEmut–MMRd–p53abn (N = 10) tumors showed advanced stages (75% and 40% FIGO III–IV, respectively), in contrast to classical POLEmut tumors (6.7% FIGO III–IV), and higher rates of nodal metastases. Conclusions: Co-occurrence of molecular classifiers, including triple-classifier tumors, correlates with more adverse profiles and may undermine current stratification paradigms. This study emphasizes the need to further investigate and refine molecular risk models to account for overlapping profiles. Full article

Cardiac fibrosis following myocardial infarction plays a critical role in the formation of scar tissue and contributes to ventricular arrhythmias, including ventricular tachycardia and sudden cardiac death. Current clinical diagnostics use electrical and structural markers, but lack precision due to low spatial resolution and absence of molecular information. In this paper, we employed line scan Raman microspectroscopy to classify sheep myocardial tissue into muscle, necrotic, granulated, and fibrotic tissue types, using collagen as a molecular biomarker. Three spectral regions were evaluated: region A (600–2960 cm⁻¹), region B (600–1399 cm⁻¹ and 1751–2960 cm⁻¹), and region C (1400–1750 cm⁻¹), which includes the prominent collagen-associated peaks at 1448 cm⁻¹ and 1652 cm⁻¹. Linear and nonlinear principal component analysis (PCA) and support vector machines (SVMs) were applied for dimensionality reduction and classification, with nonlinear models specifically addressing the nonlinearity of collagen formation during fibrogenesis. Histological validation was performed using Masson’s trichrome staining. Raman bands associated with collagen in region C consistently outperformed regions A and B, achieving the highest explained variance and best class separation in both binary and multiclass PCA models for both linear and nonlinear approaches. The ratio of collagen-related peaks enabled stage-dependent tissue characterization, confirming the nonlinear nature of fibrotic remodeling. Our findings highlight the diagnostic potential of collagen-associated Raman bands for characterizing myocardial fibrosis. The proposed PCA-SVM framework demonstrates robust performance even with limited sample size and has the potential to lay the foundation for real-time intraoperative diagnostics. Full article

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are rare tumors with different clinical and biological characteristics. Ki-67 staining and mitotic counts are the most commonly used prognostic markers, but these methods are time-consuming and lack reproducibility, highlighting the need for innovative approaches that improve histological evaluation and prognosis. In our previous study, we observed that the microRNA (miRNA) expression profile of GEP-NENs correlates with the three grades of GEP-NENs. This study aimed to characterize a group of miRNAs that discriminate well-differentiated GEP-NENs grading 1 (G1) and grading (G2). Fifty formalin-fixed and paraffin-embedded tissue specimens from well-differentiated GEP-NENs G1 and G2 tissues were used for this study. The expression levels of 21 miRNAs were examined using qRT-PCR, while FGFR2 and FGF1 protein expression were evaluated through immunohistochemistry (IHC). We identified four miRNAs (hsa-miR-133, hsa-miR-150-5p, hsa-miR-143-3p and hsa-miR-378a-3p) that are downregulated in G2 GEP-NENs compared to G1. Bioinformatic analysis revealed that these miRNAs play a key role in modulating the FGF/FGFR signaling pathway. Consistent with this observation, we found that fibroblast growth factor receptor 2 (FGFR2) expression is markedly higher in G2 NENs patients, whereas its expression remains low in G1 NENs. Our findings highlight the potential use of miRNAs to confirm the histological evaluation of GEP-NENs by employing them as biomarkers for improving histological evaluation and tumor classification. Full article

Aquilaria sinensis (Lour.) Gilg, the exclusive botanical source of Chinese agarwood, holds significant medicinal value. This study investigated the agarwood-inducing potential of a Fusarium strain obtained through prior isolation work. Through integrated morphological characterization and molecular phylogenetic analysis, the strain was conclusively identified as Fusarium equiseti. GC-MS analysis revealed that fungal inoculation induced the synthesis of characteristic sesquiterpenes and aromatic compounds consistent with natural agarwood profiles. Quantitative determination demonstrated progressive accumulation of agarotetrol, a key quality marker, reaching 0.034%, 0.039%, and 0.038% at 2, 4, and 6 months post-inoculation, respectively—significantly exceeding levels from physical wounding (p < 0.05) and PDA control treatments. Histological examination showed characteristic yellow-brown oleoresin deposits concentrated in the inner phloem, mirroring the anatomical features of wild-type agarwood. Critical quality parameters measured in December-harvested samples included ethanol extractives (17.69%), chromone derivatives 2-[2-(4-methoxyphenyl) ethyl] chromone, and 2-(2-phenylethyl) chromone (2.13%), all meeting or surpassing the specifications outlined in the National Standard for Agarwood Classification (LY/T 3223-2020). These comprehensive findings establish F. equiseti as a promising microbial agent for sustainable agarwood production in A. sinensis plantations. Full article

Background: Pathological complete response (pCR) serves as a prognostic surrogate endpoint for long-term clinical outcomes in breast cancer patients receiving neoadjuvant systemic therapy (NAST). This study aims to develop and evaluate machine learning-based biomarkers for predicting pCR and recurrence-free survival (RFS). Methods: This retrospective monocentric study included 235 women (mean age 46 ± 11 years) with non-metastatic breast cancer treated with NAST. We developed various machine learning models using clinical features (age, genetic mutations, TNM stage, hormonal receptor expression, HER2 status, and histological grade), along with morphological features (size, T2 signal, and surrounding edema) and radiomics data extracted from pre-treatment MRI. Patients were divided into training and test groups with different MRI models. A customized machine learning pipeline was implemented to handle these diverse data types, consisting of feature selection and classification components. Results: The models demonstrated superior prediction ability using radiomics features, with the best model achieving an AUC of 0.72. Subgroup analysis revealed optimal performance in triple-negative breast cancer (AUC of 0.80) and HER2-positive subgroups (AUC of 0.65). Conclusion: Machine learning models incorporating clinical, qualitative, and radiomics data from pre-treatment MRI can effectively predict pCR in breast cancer patients receiving NAST, particularly among triple-negative and HER2-positive breast cancer subgroups. Full article

Objectives: Oncocyte-rich indeterminate thyroid nodules (O-ITNs) present diagnostic and management challenges due to overlapping features between benign and malignant lesions and differing cytological classifications. This study aimed primarily to assess the ultrasound (US) characteristics and US-based risk of O-ITNs using the American College of Radiology Thyroid Imaging Reporting And Data Systems (ACR TI-RADS). A secondary objective was to compare the Bethesda System for Reporting Thyroid Cytopathology (BSRTC) and Italian Consensus for the Classification and Reporting of Thyroid Cytology (ICCRTC) cytological systems regarding classification and clinical management implications for O-ITNs. Methods: A retrospective study was conducted on 177 ITNs (TIR3A and TIR3B) evaluated between June 2023 and December 2024 at CTO-Alesini, Rome (Italy). Nodules were assessed with US, cytology, and histology. Oncocyte predominance was defined as >70% oncocytes on fine-needle aspiration (FNA). US features were analyzed according to ACR TI-RADS. Nodules were reclassified by BSRTC, and potential differences in clinical case management (CCM) were analyzed. Results: O-ITNs comprised 47.5% of the sample. Compared to non-O-ITNs, O-ITNs were larger and more frequently showed low-risk US features, including a higher prevalence of ACR TI-RADS 3 nodules. However, no progressive increase in the risk of malignancy (ROM) was observed across ACR TI-RADS classes within O-ITNs. Histological malignancy was identified in 47.1% of O-ITNs, a lower proportion compared to non-O-ITNs, though the difference was not statistically significant. Classification discordance with potential management impact was lower in O-ITNs (20.2%) than in non-O-ITNs (38.7%). Conclusions: O-ITNs typically exhibit benign-appearing US features and lower classification discordance between BSRTC and ICCRTC, yet US risk stratification fails to differentiate malignancy risk within O-ITNs. A tailored approach integrating cytology and cautious US interpretation is essential for optimal O-ITN management. Full article

Background: This study aimed to develop a nomogram based on the most relevant clinical, CT, and radiomic features comprising 11 key signatures (2 clinical, 2 CT-based, and 7 radiomic) for the non-invasive prediction of the EGFR mutation status and to support the timely initiation of tyrosine kinase inhibitor (TKI) therapy in patients with non-small cell lung cancer (NSCLC) adenocarcinoma. Methods: Retrospective real-world data were collected from 521 patients with histologically confirmed NSCLC adenocarcinoma who underwent CT imaging and either surgical resection or pathological biopsy for EGFR mutation testing. Five Random Forest classification models were developed and trained on various datasets constructed by combining clinical, CT, and radiomic features extracted from CT image regions of interest (ROIs), with and without feature preselection. Results: The model trained exclusively on the most relevant clinical, CT, and radiomic features demonstrated superior predictive performance compared to the other models, with strong discrimination between EGFR-mutant and wild-type cases (AUC = 0.88; macro-average = 0.90; micro-average = 0.89; precision = 0.90; recall = 0.94; F1-score = 0.91; and accuracy = 0.87). Conclusions: A nomogram constructed using a Random Forest model trained solely on the most informative clinical, CT, and radiomic features outperformed alternative approaches in the non-invasive prediction of the EGFR mutation status, offering a promising decision-support tool for precision treatment planning in NSCLC. Full article

Background/Objectives: The major question that confronts a pathologist when evaluating a lymph node biopsy is whether the process is benign or malignant, and the differential diagnosis between follicular lymphoma and reactive lymphoid tissue can be challenging. Methods: This study designed a convolutional neural network based on ResNet architecture to classify a large series of 221 cases, including 177 follicular lymphoma and 44 reactive lymphoid tissue/lymphoid hyperplasia, which were stained with hematoxylin and eosin (H&E). Explainable artificial intelligence (XAI) methods were used for interpretability. Results: The series included 1,004,509 follicular lymphoma and 490,506 reactive lymphoid tissue image-patches at 224 × 244 × 3, and was partitioned into training (70%), validation (10%), and testing (20%) sets. The performance of the training (training and validation sets) had an accuracy of 99.81%. In the testing set, the performance metrics achieved an accuracy of 99.80% at the image-patch level for follicular lymphoma. The other performance parameters were precision (99.8%), recall (99.8%), false positive rate (0.35%), specificity (99.7%), and F1 score (99.9%). Interpretability was analyzed using three methods: grad-CAM, image LIME, and occlusion sensitivity. Additionally, hybrid partitioning was performed to avoid information leakage using a patient-level independent validation set that confirmed high classification performance. Conclusions: Narrow artificial intelligence (AI) can perform differential diagnosis between follicular lymphoma and reactive lymphoma tissue, but it is task-specific and operates within limited constraints. The trained ResNet convolutional neural network (CNN) may be used as transfer learning for larger series of cases and lymphoma diagnoses in the future. Full article

Oral cancer is typically diagnosed through histological examination; however, the primary issue with this type of procedure is tumor heterogeneity, where a subjective aspect of the examination may have a direct effect on the treatment plan for a patient. To reduce inter- and intra-observer variability, artificial intelligence algorithms are often used as computational aids in tumor classification and diagnosis. This research proposes a two-step approach for automatic multiclass grading using oral histopathology images (the first step) and Grad-CAM visualization (the second step) to assist clinicians in diagnosing oral squamous cell carcinoma. The Xception architecture achieved the highest classification values of 0.929 (±σ = 0.087) AUC_macro and 0.942 (±σ = 0.074) AUC_micro. Additionally, Grad-CAM provided visual explanations of the model’s predictions by highlighting the precise areas of histopathology images that influenced the model’s decision. These results emphasize the potential of integrated AI algorithms in medical diagnostics, offering a more precise, dependable, and effective method for disease analysis. Full article

Background and Objectives: The accuracy of breast cancer diagnosis depends on the concordance between imaging features and pathological findings. While BI-RADS (Breast Imaging Reporting and Data System) provides standardized risk stratification, its correlation with histologic grade and immunohistochemical markers remains underexplored. This study assessed the diagnostic performance of BI-RADS 3, 4, and 5 classifications and their association with tumor grade and markers such as ER, PR, HER2, and Ki-67. Materials and Methods: In this prospective study, 67 women aged 33–82 years (mean 56.4) underwent both mammography and ultrasound. All lesions were biopsied using ultrasound-guided 14G core needles. Imaging characteristics (e.g., margins, echogenicity, calcifications), histopathological subtype, and immunohistochemical data were collected. Statistical methods included logistic regression, Chi-square tests, and Spearman’s correlation to assess associations between BI-RADS, histology, and immunohistochemical markers. Results: BI-RADS 5 lesions showed a 91% malignancy rate. Evaluated features included spiculated margins, pleomorphic microcalcifications, and hypoechoic masses with posterior shadowing, and were correlated with histological and immunohistochemical results. Invasive tumors typically appeared as irregular, hypoechoic masses with posterior shadowing, while mucinous carcinomas mimicked benign features. Higher BI-RADS scores correlated significantly with increased Ki-67 index (ρ = 0.76, p < 0.001). Logistic regression yielded an AUC of 0.877, with 93.8% sensitivity and 80.0% specificity. Conclusions: BI-RADS scoring effectively predicts malignancy and correlates with tumor proliferative markers. Integrating imaging, histopathology, and molecular profiling enhances diagnostic precision and supports risk-adapted clinical management in breast oncology. Full article

Background/Objectives: Skin adnexal tumors (SATs) are rare neoplasms originating from sebaceous glands, hair follicles, and sweat glands, often presenting diagnostic challenges due to their histopathological diversity and clinical resemblance to other lesions. This epidemiological and clinicopathological study aimed to evaluate SATs diagnosed between January 2018 and October 2024 across two medical centers in Turkey. Methods: A total of 652 cases were analyzed based on demographic features, tumor size, anatomical localization, and histological subtypes per the 2018 WHO classification. The study also explored the predictors of malignancy, including tumor size and multifocality. Results: Among the cases, 98% were benign and 2% malignant. Sebaceous tumors were the most common (34.5%), followed by eccrine/apocrine (34.2%) and follicular tumors (31.3%). Benign tumors showed a slight female predominance (56.6%), while malignant tumors were more frequent in males (61.5%). The majority of tumors were located in the head and neck region (84.6%), and a tumor size >20 mm was significantly associated with malignancy. Conclusions: This study, one of the largest series from Turkey, highlights the importance of clinicopathological correlation in SATs. It contributes to the literature by identifying size-based cut-off values for malignancy prediction and by assessing interobserver agreement, multifocality, and tumor subtype distribution. Full article