Diagn Pathol [JOURNAL]
Sun
200 papers
Comprehensive clinicopathological and prognostic analysis of primary pulmonary lymphoepithelial carcinoma: a retrospective cohort study.
Yao M, Li W, Wang Y … +7 more , Chen Z, Pan Y, Zhang K, Lu Z, Chen D, Zheng Y, Yang Y
Diagn Pathol · 2026 Mar · PMID 41862951 · Full text
BACKGROUND: Primary pulmonary lymphoepithelial carcinoma (PPLEC) is an extremely rare subtype of lung squamous cell carcinoma (LUSC). This study aims to comprehensively characterize clinicopathological and molecular char...
BACKGROUND: Primary pulmonary lymphoepithelial carcinoma (PPLEC) is an extremely rare subtype of lung squamous cell carcinoma (LUSC). This study aims to comprehensively characterize clinicopathological and molecular characteristics, evaluate treatment strategies, and identify prognostic factors of PPLEC. METHODS: This retrospective study was conducted on 152 pathologically confirmed PPLEC patients in our center between April 2012 and December 2024. Data on clinicopathological characteristics, driver gene mutations (n = 40), PD-L1 expression (n = 65), treatment regimens, and survival outcomes were collected. Survival analyses were performed with Kaplan-Meier analysis and Cox regression model. RESULTS: The median age at diagnosis in the PPLELC cohort was 55 years, with a slight female predominance (52.6%) and strong nonsmoking association (75.7%). Despite the presence of CYFRA21-1, most of the serum tumor marker levels were normal. Immunohistochemical (IHC) staining revealed characteristic epithelial differentiation with high expression of CK5/6 (100.0%), P40 (98.5%), P63 (96.9%), and pan-CK (95.5%). All patients (100%) were EBV-encoded RNA (EBER) -in situ hybridization (ISH) positive. Driver mutations were rare (2 of 40, 5.0%), while PD-L1 expression was prevalent (60 of 65, 92.3%). The TNM stage distributions were I (38.2%), II (17.8%), III (28.9%), and IV (14.5%). Early-stage patients who underwent surgical resection (n = 102) achieved a 5-year overall survival (OS) rate of 91%. For locally advanced PPLEC (n = 14), neoadjuvant therapy is a potential strategy with an objective response rate (ORR) of 50.0%. Compared with chemotherapy alone, combination therapies yielded superior outcomes in advanced-stage patients (n = 30). Multivariate survival analysis revealed TNM stage was the independent prognostic factor for progression-free survival (PFS). CONCLUSIONS: PPLEC is a distinct LUSC subtype characterized by an Epstein–Barr virus (EBV) association, a nonsmoking phenotype, epithelial differentiation, few driver mutations, and high PD-L1 expression. Surgical resection plays a pivotal role in the management of early-stage disease, whereas multimodal therapeutic approaches have considerable potential for advanced-stage cases. TNM stage was the independent prognostic factor for PFS. These findings provide valuable insights for optimizing management strategies for this rare malignant entity.
Clinicopathological and prognostic significance of stromal maturity, tumour-infiltrating lymphocytes, and systemic environment in breast cancer.
Guo Q, Chang Y, Cai Y … +3 more , Yang S, Liang J, Zhou Z
Diagn Pathol · 2026 Mar · PMID 41851799 · Full text
BACKGROUND: The tumour microenvironment and systemic inflammatory environment are related to the diagnosis, treatment and prognosis of various tumours. This study aimed to evaluate the clinicopathological significance an...
BACKGROUND: The tumour microenvironment and systemic inflammatory environment are related to the diagnosis, treatment and prognosis of various tumours. This study aimed to evaluate the clinicopathological significance and prognostic value of the tumour microenvironment and systemic environment in patients with breast invasive ductal carcinoma (IDC). METHODS: A total of 222 patients with breast IDC who underwent radical mastectomy were included. Stromal maturity and tumour-infiltrating lymphocytes (TILs), along with a series of systemic inflammatory cell indicators from venous blood, were evaluated. Chi-square tests were performed to explore the relationships between the parameters. Kaplan‒Meier analysis and Cox proportional hazards regression models were used for survival analysis. RESULTS: Stromal maturity was significantly correlated with tumour necrosis, lymphovascular invasion, axillary lymph node metastasis, and clinical stage (all P < 0.001). TILs were significantly associated with nuclear grade, histopathological grade, tumour necrosis, lymphovascular invasion, and clinical stage (all P < 0.001). High TIL numbers were often accompanied by more mature stroma. No significant correlations were detected between stromal maturity/TILs and systemic inflammatory markers. Multivariate Cox proportional hazards model analysis revealed that TILs, pathological grade, clinical stage, and molecular subtype were independent prognostic factors for patients with IDC. ROC curve analysis revealed that the accuracy of stromal maturity detection was greater than that of TILs alone, and the combined assessment of both parameters achieved the best predictive performance. CONCLUSIONS: Stromal maturity and TILs in patients with breast IDC have important clinicopathological and prognostic significance, providing clinical guidance and a theoretical basis for the precise diagnosis and prognostic evaluation of this disease.
Immunohistochemical expression of Stomatin-Like protein 2 and trophoblast cell surface antigen 2 in papillary thyroid carcinoma in comparison to other thyroid lesions.
Elmetwally AA, Khashaba MH, Wagih HM … +2 more , Zidan AHM, Farrag MS
Diagn Pathol · 2026 Mar · PMID 41845488 · Full text
BACKGROUND: Thyroid carcinoma is a common tumor affecting the Egyptian population accounting for 2% of newly diagnosed cases of cancer in Egypt yearly and constituting 7.73% of 5 year prevalence in Egypt. Stomatin-Like P...
BACKGROUND: Thyroid carcinoma is a common tumor affecting the Egyptian population accounting for 2% of newly diagnosed cases of cancer in Egypt yearly and constituting 7.73% of 5 year prevalence in Egypt. Stomatin-Like Protein 2 (SLP-2) and Trophoblast Cell Surface Antigen 2 (TROP-2) antibodies are both expressed in some types of thyroid carcinomas. AIM: To evaluate immunohistochemical expression of SLP-2 and TROP-2 in papillary thyroid carcinoma and other thyroid lesions, assess association of both immunohistochemical markers with variable demographic and histopathological parameters and assess the diagnostic utility of both markers in thyroid carcinomas. SUBJECTS AND METHODS: The current study is a cross-sectional study with analytical component, performed in the Pathology laboratory of Suez Canal University Hospital on 144 samples of formalin fixed paraffin embedded blocks of thyroid cases, including 79 cases of PTC and 65 cases of other thyroid lesions during the period from January 2016 to May 2019. RESULTS: SLP-2 and TROP-2 have shown positive expression in 91.1% and 82.3% respectively in PTC cases. Compared to positive expressions in 38.5% and 7.7% respectively in other thyroid cases. The positivity of both markers has a statistically significant association with PTC cases, compared to other thyroid lesions p-value < 0.05). The sensitivity of combined positively expressed markers is 79.75%, specificity is 98.46%, positive predictive value is 98.44, the negative predictive value is 80% and the test accuracy is raised to 88.19 for discrimination between PTC and other thyroid lesions. There was no statistically significant association between all histopathological parameters and the expression of SLP-2 and TROP-2. CONCLUSIONS: SLP-2 and TROP-2 may be promising diagnostic markers of PTC carcinoma. Further studies are needed to fully evaluate the prognostic significance of SLP-2 and TROP-2 expression in PTC and other thyroid lesions.
A novel multimodal framework integrating pathomics, deep learning, and machine learning for breast cancer histological grades classification.
Ding H, Dong Z
Diagn Pathol · 2026 Mar · PMID 41814294 · Full text
OBJECTIVE: The present study is aimed at developing and testing a strong, interpretable, and multi-scale computational pathology framework for the automated histologic grade (grade-based) grading of invasive ductal carci...
OBJECTIVE: The present study is aimed at developing and testing a strong, interpretable, and multi-scale computational pathology framework for the automated histologic grade (grade-based) grading of invasive ductal carcinoma (IDC) from hematoxylin and eosin (H&E) whole-slide images (WSIs). MATERIALS AND METHODS: A multi-center dataset consisting of 3,660 WSIs from 925 patients with IDC from five institutions was assembled and quality controls were very stringent. Images were captured at four magnifications (4X, 10X, 20X, 40X), in order to capture both a view of global tissue architecture and fine detail of the nuclei. Multi-modality features were extracted: low and high magnification deep features (DINOv2 ViT-S/16, ConvNeXt V2 Small), 71 handcrafted radiomics descriptors extracted from H&E channels and three pseudo-nuclei indices. Correlation filtering and four feature selection approaches (mutual information, recursive feature elimination, ANOVA, LASSO) were used on a modality per modality basis. An Attention MIL framework with a novel cross scale attention module and cross scale consistency loss was used for feature fusion and grading. Three strategies of fusion (early, late, hybrid) were compared. Model performance was evaluated using 5-folder cross-validation, internal, and external validation on an independent cohort (n = 922 WSIs). RESULTS: The hybrid fusion of LASSO selected features resulted in the best performance as the accuracy was found to be 92.5% (internal) and 90.9% (external) and the AUC were found to be 93.5% and 92.1% respectively. High magnitude deep features proved to be the most informative single modality and multi-modality fusion increased both the accuracy and robustness. The proposed framework was better than end-to-end baselines (p < 0.001), and the recall was balanced across all grades. Attention heatmaps identified regions of diagnostic interest which were consistent with pathologist annotations. CONCLUSIONS: The multi-scaled, multi modal Attention-MIL framework provides accurate, interpretable and generalizable grading of IDC, outperforming conventional and end-to-end methods. Its inter-institutional strength and biological interpretability make it an appealing candidate for a clinical decision-support tool.
Inverse expression of ubiquitin-specific peptidase 19 and caspase 7 correlates with gastric neoplastic transformation.
Kelemen P, Naumann M, Vieth M
Diagn Pathol · 2026 Mar · PMID 41808185 · Full text
BACKGROUND: Ubiquitin-specific protease 19 (USP19) is a deubiquitinylase (DUB) that is part of the USP family, the largest group of DUBs in humans. Growing evidence has indicated that USP19 is involved in tumor progressi...
BACKGROUND: Ubiquitin-specific protease 19 (USP19) is a deubiquitinylase (DUB) that is part of the USP family, the largest group of DUBs in humans. Growing evidence has indicated that USP19 is involved in tumor progression and serves as a new prognostic marker for various malignant disorders. Interestingly, USP19 has been shown to have both promoting and inhibiting effects on the onset and development of different neoplasms, depending on the specific tissue type. DUBs including USP19 affect a variety of cell functions including apoptotic cell death. Herein, caspase 7 acts as a key executioner in apoptosis, and its expression levels serve as a prognostic and diagnostic marker in various cancers. This study analysed the expression of USP19 and caspase 7 in gastric pathology along the progression of stomach cells to gastric adenocarcinoma (Correa cascade). METHODS: We analysed the expression and subcellular localization of USP19 and caspase 7 by immunohistochemistry (IHC) in 296 paraffin-embedded human gastric tissue samples. The cohort included various gastric conditions such as autoimmune gastritis (A-gastritis), Helicobacter pylori gastritis (HP-gastritis), chemical gastropathy (C-gastritis), adenoma, and adenocarcinoma, using gastric mucosa without pathological changes as a reference point. RESULTS: We observed a significant upregulation of USP19 expression in HP-gastritis, adenoma and adenocarcinoma. In contrast, caspase 7 was significantly upregulated in A-gastritis and HP-gastritis and significantly downregulated in both adenoma and adenocarcinoma. CONCLUSIONS: USP19 and caspase 7 showed distinct expression patterns across different gastric pathologies. Both USP19 and caspase 7 overexpression maybe associated with inflammation, while USP19 overexpression and no caspase 7 expression could indicate neoplastic transformation. This inverse expression may help distinguish early and late neoplastic epithelial changes in chronic gastritis.
Diffuse co-expression of TTF-1 and p40 (ΔNp63) defines a distinct biphenotypic non-small cell lung carcinoma: clinicopathologic and molecular characterization of 19 cases.
Lin J, Li S, Chen W … +6 more , Wu W, Zhang W, Huang Y, Dong Z, Wu C, Hou L
Diagn Pathol · 2026 Mar · PMID 41776632 · Full text
BACKGROUND: The diffuse co-expression of thyroid transcription factor-1 (TTF-1) and p40 defines a rare and diagnostically challenging subtype of non-small cell lung carcinoma (NSCLC). Due to its extreme rarity, the clini...
BACKGROUND: The diffuse co-expression of thyroid transcription factor-1 (TTF-1) and p40 defines a rare and diagnostically challenging subtype of non-small cell lung carcinoma (NSCLC). Due to its extreme rarity, the clinicopathologic and molecular characteristics of this entity remain poorly characterized. METHODS: We conducted a comprehensive analysis of the largest single-institution cohort to date (n = 19) of NSCLCs with diffuse TTF-1/p40 co-expression. All cases underwent detailed histopathologic review. Immunohistochemistry (IHC) utilized specific antibody clones (TTF-1: 8G7G3/1; p40). Molecular profiling was performed via next-generation sequencing in a subset of cases, including multi-region analysis for select tumors. RESULTS: The cohort mainly consisted of elderly male smokers (median age 65; 84.2% male; 73.7% smokers). Anatomically, 84.2% of tumors were located in the right lung, mainly in the upper lobe, with no clear preference for central or peripheral distribution. Histologically, all were poorly differentiated NSCLCs, classifiable into two patterns: a basaloid/squamous-like pattern and an inflammatory/plasmacytoid pattern. Molecular profiling revealed a hybrid genomic landscape, with individual tumors harboring alterations linked to both adenocarcinoma and squamous cell carcinoma, along with a high prevalence(58.8%) of TP53 mutations. In an index case, multi-region sequencing revealed a shared EGFR mutation across regions, with a TP53 mutation confined to the high-grade TTF-1/p40-positive area. Most patients (66.7%) presented with Stage III or IV disease, and 61.1% developed metastases, including four with distant spread and seven involving thoracic or supraclavicular lymph nodes or the pleura. Three patients died from the disease within 10–64 months after diagnosis. However, all patients with Stage I or II disease who underwent resection remained disease-free. CONCLUSIONS: NSCLC with diffuse TTF-1/p40 co-expression constitutes a distinct biphenotypic entity with unique clinicopathologic and molecular features. We suggest specific diagnostic criteria to ensure proper identification. Given the presence of targetable drivers and frequent PD-L1 expression, an integrated diagnostic approach is crucial for guiding personalized therapy and enhancing patient outcomes.
Subclassification of atypical endometrial cells (Not Otherwise Specified vs favor neoplasia) on Pap tests: age-dependent risk of endometrial neoplasia.
Zhou X, Zhou Y, Huang S … +5 more , Wang Y, Zou Q, Yang X, Lin W, Zhou F
Diagn Pathol · 2026 Mar · PMID 41772681 · Full text
BACKGROUND: Atypical endometrial cells (AEMc) detected in cervical cytology are uncommon yet significantly associated with an elevated risk of precancerous and malignant lesions. Nevertheless, limited data are available...
BACKGROUND: Atypical endometrial cells (AEMc) detected in cervical cytology are uncommon yet significantly associated with an elevated risk of precancerous and malignant lesions. Nevertheless, limited data are available on the histopathological correlation of AEMc cases. This study aims to evaluate the immediate histological outcomes in women diagnosed with AEMc and to assess how HPV status and patient age influence oncogenic potential. METHOD: A retrospective analysis was conducted on 163 women diagnosed with AEMc at the International Peace Maternity and Child Health Hospital between January 2019 and December 2023. Each patient underwent liquid-based cytology (LBC) and high-risk HPV (hrHPV) testing for 14 genotypes, followed by histological evaluation within six months after the cytological assessment. RESULT: Among the 163 AEMc patients, 86.5% (141/163) were classified as AEMc-not otherwise specified (NOS) and 13.5% (22/163) as AEMc-favor neoplasia (FN). Histological analysis indicated that 2.5% (4/163) had precancerous lesions and 12.9% (21/163) had cancer. Immediate pathological severity was significantly higher in AEMc-FN than in AEMc-NOS (p = 0.015), with endometrial carcinoma more prevalent in AEMc-FN (27.3% vs. 9.9%, p = 0.037; odds ratio 3.30, 95% CI: 1.11–9.79). The diagnostic accuracy of AEMc-FN for endometrial carcinoma was 81.6% (95% CI: 74.8%–87.3%). hrHPV status did not reliably predict cancer risk stratification in AEMc, however, age was significantly associated with disease severity. Compared with younger patients, those aged > 65 years showed a markedly higher prevalence of high-grade endometrial glandular abnormalities (AEH +) and adenocarcinoma (AC) (p = 0.001 and p = 0.000401, respectively). With an age cutoff of 45 years, older AEMc patients had an increased prevalence of AEH + and AC, a trend also evident in the AEMc-NOS subgroup. CONCLUSION: Women aged ≥ 45 years, especially those classified as AEMc-NOS, exhibit a substantially higher risk of high-grade endometrial glandular lesions, underscoring the need for more vigilant follow-up. Given the significantly higher prevalence of endometrial carcinoma in AEMc-FN patients compared to AEMc-NOS patients, it may be advisable for cytopathologists to annotate the presence or absence of “favor neoplasia” when diagnosing AEMc. Refining the diagnostic criteria for AEMc-FN may facilitate earlier detection of endometrial cancer.
PRDM1: a useful indicator of differentiation and prognosis in esophageal squamous cell carcinoma.
Huang A, Jiang X, Qi Y … +4 more , Chen J, Guo X, Lu J, Jin M
Diagn Pathol · 2026 Feb · PMID 41764566 · Full text
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the gastrointestinal tract with a high mortality rate. Although positive regulatory domain zinc finger protein 1 (PRDM1) has long been...
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the gastrointestinal tract with a high mortality rate. Although positive regulatory domain zinc finger protein 1 (PRDM1) has long been thought to play a key role especially in the differentiation of B cells, its role in ESCC has never been studied. This study aimed to examine the association between PRDM1 and ESCC clinical and pathological characteristics and prognosis. METHODS: Using immunohistochemical and reverse transcription quantitative polymerase chain reaction, we detected the expression level of PRDM1 in consecutive ESCC surgical resections from 163 patients. To interpret PRDM1 immunohistochemical positivity, we employed three methods: PRDM1 10 high-power field (HPF) positive cell count (PCC), PRDM1 1HPF PCC and PRDM1 positive hotspots (PPHs). Based on PPH assessment and histological morphology, we developed a novel histological grading scheme. To evaluate the relationship between PRDM1 differential expression and clinical–pathological parameters in ESCC, we used the chi-square test. To evaluate the relationship between PRDM1 expression and ESCC prognosis, we performed Kaplan–Meier survival analysis and Cox regression analysis. RESULTS: Immunohistochemical staining revealed that PRDM1 was expressed in tumor epithelium, stroma, and adjacent squamous epithelium in ESCC. And the expression level of PRDM1 in tumor epithelium significantly correlated with tumor differentiation (P < 0.05) and was closely related to the patient prognosis (P < 0.05). Moreover, survival analysis results indicated that our novel histological grading seem to be better than the traditional histological grading criteria in predicting the prognosis of ESCC patients. CONCLUSIONS: PRDM1 holds promise as a novel indicator for ESCC, with potential application value in the histological grading, diagnosis, and prognostic assessment of this disease.
Integrating histopathology and immune marker analysis for machine learning-based colorectal cancer prognostics.
Saadh MJ, Saeed TN, Alfarttoosi KH … +10 more , Ballal S, Nayak PP, Singh A, Kavitha V, Kubaev A, Taher WM, Alwan M, Jawad MJ, Ali Al-Nuaimi AM, Farhood B
Diagn Pathol · 2026 Feb · PMID 41731487 · Full text
OBJECTIVE: This study aims to create a machine-learning framework that integrates histopathological imaging, immune marker data, and clinical features to classify tumor types, determine histological grades, and predict s...
OBJECTIVE: This study aims to create a machine-learning framework that integrates histopathological imaging, immune marker data, and clinical features to classify tumor types, determine histological grades, and predict survival outcomes in CRC patients. MATERIALS AND METHODS: This study analyzed 650 CRC cases, divided into training (520 cases) and testing (130 cases) subsets. Preprocessing involved quality control, color normalization, and selecting tumor regions (tumor center and invasive margins) with uniform dimensions (224 × 224 pixels). Six immune markers (CD3, CD8, CD45RO, PD-1, LAG-3, Tim-3) were selected for their relevance to CRC progression and immune response. A fine-tuned EfficientNet model was used to extract high-dimensional features from the images. These imaging features were combined with clinical data. To refine the dataset, feature selection methods such as PCA, RFE, and LASSO were applied to include only the most relevant variables. Machine learning models (XGBoost, CatBoost, Random Forest) and ensemble models were developed for tumor type and grade prediction. For survival prediction, regression models such as SVR, Random Forest Regressor, and stacking regressors were used. Model performance was evaluated using metrics such as accuracy, AUC, MSE, and the C-index. RESULTS: The evaluation highlighted the value of feature selection and ensemble learning in CRC classification and survival prediction. For tumor type classification, XGBoost with RFE achieved a testing AUC of 86.15% and accuracy of 85.33%, while stacking-based models with RFE performed better, with a testing AUC of 96.73% and accuracy of 96.92%. Histological grade classification followed a similar trend, with stacking-based models achieving a testing AUC of 96.37% and accuracy of 96.92%. In survival prediction, the Stacking Regressor with RFE produced the best results, with testing MSEs of 132.87 for Disease-Free Survival (days) and 115.78 for Survival (days), along with the highest C-index of 0.84 for both tasks. CONCLUSIONS: The proposed framework demonstrates the potential of integrating histopathological imaging, immune markers, and machine learning to improve CRC prognosis and enable personalized treatment, setting a benchmark for future computational pathology research.
Assessing the influence of two deep-learning assistance modes on pathologists in cancer identification.
Chuang WY, Yu WH, Liu YJ … +17 more , Huang CC, Lee KF, Hwang CC, Chang LC, Ueng SH, Yeh CJ, Chuang HC, Lan J, Huang HS, Chang SH, Wang TH, Lin TC, Wu CT, Yu JS, Hsueh C, Kuo CF, Yeh CY
Diagn Pathol · 2026 Feb · PMID 41689116 · Full text
BACKGROUND: Artificial intelligence (AI) has achieved good performance in image recognition, including identifying cancer cells in pathology images. However, the best mode of AI assistance in diagnostic pathology remains...
BACKGROUND: Artificial intelligence (AI) has achieved good performance in image recognition, including identifying cancer cells in pathology images. However, the best mode of AI assistance in diagnostic pathology remains to be explored. METHODS: We compared the influence of two deep-learning assistance modes on pathologists in cancer identification. Ten board-certified pathologists classified 60 cases of nasopharyngeal biopsy as carcinoma or benign with or without AI assistance, which was either a heatmap of cancer probability accompanying a whole-slide image (AI-heatmap mode) or ten high-power field images with the highest cancer probability (AI-HPF mode). RESULTS: Both assisting modes significantly accelerated the diagnostic process, lowered the subjective difficulty, and maintained high accuracy compared to the unassisted mode. Notably, the acceleration of diagnosis was more significant in AI-HPF mode than in AI-heatmap mode (time reduction: 35.1% vs. 28.1%; P = 0.040), especially for benign cases (time reduction: 49.4% vs. 32.9%; P = 0.0000072). For benign cases, an increased area proportion of false-positive AI prediction slowed down the diagnostic process in AI-heatmap mode (P = 0.00000084) but not in AI-HPF mode (P = 0.62). CONCLUSIONS: We show for the first time that an AI-HPF assistance mode was superior to the commonly used AI-heatmap mode in accelerating cancer identification by pathologists. In our scenario, the AI-HPF mode maintained high diagnostic accuracy and was robust to the influence of false-positive AI prediction. The potential risk caused by AI assistance is also discussed.
Pathomic model to predict the expression of UQCRH and overall survival of lung adenocarcinoma patients.
Chen Y, Liu J, Li G … +1 more , Huang H
Diagn Pathol · 2026 Feb · PMID 41689104 · Full text
BACKGROUND: Ubiquinol-cytochrome c reductase hinge protein (UQCRH) is a component of mitochondrial respiratory chain complex CIII. Its relationship with human cancer has been less studied. Pathomics uses artificial intel...
BACKGROUND: Ubiquinol-cytochrome c reductase hinge protein (UQCRH) is a component of mitochondrial respiratory chain complex CIII. Its relationship with human cancer has been less studied. Pathomics uses artificial intelligence algorithms to collect histopathological image features and perform joint analysis by combining gene and transcriptome data. In this study, a pathomics prediction model was established based on UQCRH expression and histopathological images of lung adenocarcinoma (LUAD). Prognostic value and other analyses were conducted based on this model. METHODS: The expression level of UQCRH in 33 types of human cancers was measured. Its relationship with the survival of the primary LUAD samples with complete pathological images, gene expression data, and clinical information were divided into high and low expression groups based on the expression level threshold of the UQCRH gene (Table S1). LUAD patients was studied. Pathomic prediction model was established by using machine learning algorithms according to the UQCRH expression level and the characteristics of LUAD histopathological images. Based on this prediction model, survival analysis, molecular pathways, immune infiltration, immunological subtypes, ICI treatment prediction, and drug sensitivity analyses were performed. RESULTS: UQCRH is highly expressed in various cancers, including LUAD. In addition, we verified that UQCRH is overexpressed in human LUAD tissues. High expression of UQCRH is worse prognostic factor for LUAD patients. A pathomic prediction model was constructed based on the UQCRH expression level and histopathology image features. The pathomic score showed good correlation with the UQCRH expression level. Patients in the high-risk group of the pathomic prediction model had worse prognosis and higher tumor proliferation ability, but may have better response to immune checkpoint inhibitors (ICIs) therapy. CONCLUSION: We have established a pathomic prediction model for LUAD based on gene expression values and according to histopathological image features, which can predict patient survival prognosis and has potential guiding value for ICIs therapy.
"Clinicopathological profile of paragangliomas: A 5-Year retrospective analysis from a single tertiary Centre".
V G, Murali M, Nayal B … +9 more , Nayak D, Monappa V, Garg S, Priya PS, Menon G, Nayak R, Pujary K, Balakrishnan R, Pillai S
Diagn Pathol · 2026 Feb · PMID 41689042 · Full text
INTRODUCTION: Paragangliomas are rare neuroendocrine tumours arising from neural crest–derived paraganglionic cells and form part of the pheochromocytoma–paraganglioma (PPGL) spectrum. The World Health Organization (WHO)...
INTRODUCTION: Paragangliomas are rare neuroendocrine tumours arising from neural crest–derived paraganglionic cells and form part of the pheochromocytoma–paraganglioma (PPGL) spectrum. The World Health Organization (WHO) 5th edition classification emphasizes autonomic origin, distinguishing sympathetic from parasympathetic paragangliomas, and recognizes that all paragangliomas possess metastatic potential. OBJECTIVES: To evaluate the clinicopathological features of paragangliomas diagnosed over a 5-year period at a single tertiary care centre. METHODS: Twenty histologically confirmed cases of paraganglioma resected between 2018 and 2023 were retrospectively reviewed. Hematoxylin and eosin (H&E) and immunohistochemistry (IHC) slides were re-evaluated, and relevant clinical and radiological data were extracted from hospital records. RESULTS: The cohort showed a female predominance (male-to-female ratio 1:1.8) with a median age of 49 years. The most common tumour site was the jugulotympanic region (30%), followed by intradural extramedullary (IDEM) locations (15%) and the retroperitoneum (15%). Two patients (10%) had metastatic disease involving the spine. Radiological findings were concordant with histology in 50% of cases. IHC was performed in 75% of cases and aided differentiation from histologic mimics. The Ki-67 proliferation index ranged from 1 to 2% in most cases, with one exception (4%). Follow-up data were available for 13 patients; one case showed local recurrence, and no syndromic associations were identified. CONCLUSION: Histological features alone are insufficient to predict tumour behaviour. Metastasis remains the only definitive criterion for malignancy, particularly when identified at sites lacking normal chromaffin tissue. Comprehensive clinicopathological assessment, incorporating radiology and immunohistochemistry, is essential for accurate diagnosis and management, and integration of molecular markers may further refine risk stratification in future studies.
Sjögren's syndrome-focusassist: lymphocytic focus assessment in Sjögren's syndrome: a deep learning and spatial analysis approach.
Zhang J, Yang Y, Wang X … +12 more , Zhang Y, Wang B, Zong Y, Wu T, Zhao J, Zhao X, Tang W, He Y, Da Q, Jiang L, Guan T, He Q
Diagn Pathol · 2026 Feb · PMID 41668096 · Full text
Sjögren’s syndrome (SS) is a chronic autoimmune disease whose clinical gold standard relies on precise quantification of lymphocyte foci and lymphocyte density in salivary gland biopsies. However, traditional manual asse...
Sjögren’s syndrome (SS) is a chronic autoimmune disease whose clinical gold standard relies on precise quantification of lymphocyte foci and lymphocyte density in salivary gland biopsies. However, traditional manual assessment is time-consuming, highly subjective, and lacks consistency. To address these challenges, we propose Sjögren’s syndrome-FocusAssist (SS-FocusAssist), an end-to-end AI-assisted pathology framework for automated focus detection and quantification. At the cell-level detection stage, the system adopts an anchor-free single-stage detector enhanced with Coordinate Attention, improving the model’s ability to capture long-range spatial dependencies and identify minute lymphocytes. This design yields a precision of 95.9% and an mAP@0.5 of 99.1%, representing improvements of 11.1% and 7.3% over the baseline model. At the lesion-level aggregation stage, we introduce Filter-guided Adaptive Clustering (FAC): KDTree is first used to suppress spatial outliers, followed by DBSCAN with adaptive thresholds to form density-consistent lymphocytic foci; Finally, in the quantification stage, we develop an iterative expert-algorithm threshold optimization framework, guided by clinical diagnostic criteria, to achieve an optimal balance between lesion detection fidelity and pathological interpretability. In an independent cohort of 298 cases, SS-FocusAssist achieved a Cohen’s κ of 0.793 compared with dual-expert annotations—a 39% improvement over cell-detection-only methods. These results demonstrate that SS-FocusAssist substantially enhances the accuracy, consistency, and efficiency of SS biopsy interpretation, offering a clinically practical pathway for scalable digital pathology deployment.
Clinicopathological and prognostic insights into Embryonal Tumors with Multilayered Rosettes (ETMRs).
Ebrahim NAA, Abdelbaky HA, Elsalam AMA … +2 more , Hussein MA, Amin NH
Diagn Pathol · 2026 Feb · PMID 41664204 · Full text
BACKGROUND: Embryonal tumors with multilayered rosettes (ETMRs) are rare, highly aggressive pediatric brain neoplasms characterized by early onset and dismal prognosis. This study presents a comprehensive clinicopatholog...
BACKGROUND: Embryonal tumors with multilayered rosettes (ETMRs) are rare, highly aggressive pediatric brain neoplasms characterized by early onset and dismal prognosis. This study presents a comprehensive clinicopathological and molecular analysis of ETMR cases diagnosed over a 14-year period at National Cancer Institute, Cairo University, with a focus on diagnostic features, clinical presentation, and survival outcomes. METHODS: A retrospective review of 35 patients with histopathologically confirmed ETMRs was conducted. Demographic data, clinical symptoms, neuroimaging findings, histopathologic features-including rosette formation, mitotic activity, necrosis, and Ki67 proliferation index-as well as molecular analyses for C19MC amplification and LIN28A expression were evaluated. Kaplan-Meier survival curves and univariable Cox regression were used to assess prognostic associations. RESULTS: The cohort comprised 17 females and 18 males, with a median age of 36 months. Common presenting symptoms included signs of raised intracranial pressure, seizures, and motor deficits. Gross total resection was achieved in 43% of patients, and 48% received adjuvant chemoradiotherapy.Histopathologic examination consistently revealed ependymoblastic rosettes (true multilayered rosettes) and high mitotic activity. LIN28A was diffusely expressed in all assessable cases. Molecular confirmation by PCR testing was done in 20 cases. The median overall survival was 19 months. Factors associated with inferior survival included incomplete surgical resection, absence of adjuvant therapy, and presence of necrosis and high mitotic index. CONCLUSION: ETMRs demonstrate consistent histological and immunohistochemical features that can guide diagnosis in resource-limited settings. Despite therapeutic advances, prognosis remains poor, underscoring the urgent need for novel therapeutic strategies. Molecular testing for C19MC amplification and LIN28A expression supports diagnostic confirmation and may hold future prognostic or therapeutic relevance.
Hobnail hemangioma-a systematic review and a case report of an intraoral lesion with Dabska tumor-like features.
Salasuo EMS, Pajukanta RH, Kelppe J … +4 more , Lohi J, Wilkman T, Ruokonen HMA, Salo TA
Diagn Pathol · 2026 Feb · PMID 41664184 · Full text
Hobnail hemangioma is a rare, benign vascular neoplasm. Intraoral lesions are extremely rare. To date, only seven intraoral cases of hobnail hemangiomas and two intraoral cases of Dabska tumors have been described in the...
Hobnail hemangioma is a rare, benign vascular neoplasm. Intraoral lesions are extremely rare. To date, only seven intraoral cases of hobnail hemangiomas and two intraoral cases of Dabska tumors have been described in the English-language literature. This article presents a hobnail hemangioma case with papillary intralymphatic angioendothelioma (Dabska tumor)-like features on the gingiva of a 7-year-old female. Hobnail hemangiomas are benign lesions, but they display worrisome features on microscopic examination and can be confused with malignant vascular neoplasms. Histologically hobnail hemangiomas demonstrate superficial dilated, vascular structures with prominent hobnail endothelial cells and deeper, collagen dissecting thinner neoplastic vessels which in some cases may raise a worrisome pseudoangiosarcomatous histologic view. It is important to set an accurate diagnosis of hobnail hemangioma to diminish the risk of diagnosing these lesions as malignant tumors thus avoiding unnecessarily aggressive therapy.
SOX17/PAX8 dual immunohistochemical expression in the diagnosis of Müllerian carcinomas.
Moustafa M, Abdalrahman MAM, Abdelgeleel HM
Diagn Pathol · 2026 Feb · PMID 41664069 · Full text
BACKGROUND: Metastatic Müllerian carcinomas, including endometrial and ovarian adenocarcinomas, are challenging to diagnose due to factors like similar malignancies, insufficient clinical history, multiorgan disseminatio...
BACKGROUND: Metastatic Müllerian carcinomas, including endometrial and ovarian adenocarcinomas, are challenging to diagnose due to factors like similar malignancies, insufficient clinical history, multiorgan dissemination, and small tumor specimens. Immunohistochemistry (IHC) stains are commonly used to identify these cancers. PAX8 is a widely used IHC marker with varying sensitivity levels for different types of gynecologic carcinomas. SOX17, a transcription factor involved in embryonic differentiation and development, has high specificity for ovarian and endometrial carcinomas but is weakly expressed in other epithelial neoplasms. METHODS: . 56 endometrial carcinomas cases,56 ovarian cancer case and 56 cases of non-gynecological cancer, were subjected to immunohistochemical (IHC) analysis of SOX17 and PAX8. RESULTS: In endometrial carcinomas, PAX8-high/SOX17-high co-expression strongly favored endometrioid histology (90% vs. 68.8%, p = 0.04), while ovarian high-grade serous carcinomas commonly expressed PAX8 (78.9% high) with heterogeneous SOX17 expression (47.4% high). Notably, double-negative PAX8/SOX17 status completely excluded Müllerian origin in metastases from colorectal, breast, and pulmonary primary tumors (100% specificity), though renal (all PAX8+) and thyroid neoplasms (63.6% PAX8+) required additional markers for distinction. Statistical analyses confirmed subtype-specific trends (p < 0.05 for all applicable comparisons) with loss of SOX17 associated with aggressive histotypes (25% negative in serous versus 10% in endometrioid). CONCLUSIONS: Müllerian carcinomas can be distinguished from non-gynecological metastases using PAX8 and SOX17 immunohistochemistry, with PAX8-high/SOX17-high patterns strongly indicating endometrioid differentiation and double-negative results excluding gynecologic origin with consistency in colorectal, breast, and pulmonary carcinomas. Renal and thyroid carcinomas are the diagnostic traps on the basis of PAX8 expression and require additional markers for final classification in metastatic workups.
Interobserver agreement among pathologists in the histopathological diagnosis and classification of colorectal polyps.
Jafari E, Lashkarizadeh M, Nezhad NZ … +1 more , Rahmani H
Diagn Pathol · 2026 Feb · PMID 41664056 · Full text
OBJECTIVE: To assess interobserver agreement among pathologists in the diagnosis and classification of colorectal polyps. METHODS: This cross-sectional study was conducted at Afzalipour Educational and Medical Center fro...
OBJECTIVE: To assess interobserver agreement among pathologists in the diagnosis and classification of colorectal polyps. METHODS: This cross-sectional study was conducted at Afzalipour Educational and Medical Center from 2017 to 2018. Three experienced pathologists independently evaluated 253 colorectal polyp specimens, encompassing a spectrum of neoplastic and non-neoplastic lesions. Polyps were classified into six categories and dysplasia was graded. Interobserver agreement was assessed using weighted Cohen's kappa coefficient. RESULTS: The mean age of patients was 51.09 ± 20.11 years, with an average polyp size of 6.6 ± 0.6 mm. Most polyps (49.8%) were located in the colon, with 69.1% measuring 1-5 mm. Neoplastic polyps constituted 59.3% of the samples. Interobserver agreement for overall histopathological diagnosis was good (κ = 0.66). Agreement was very good for carcinoma in situ (κ = 0.87), good for adenomatous (κ = 0.78) and juvenile polyps (κ = 0.76), moderate for hyperplastic polyps (κ = 0.45), and poor for Inflammatory Polyps (κ = 0.16), solitary rectal ulcer (κ = 0.12), and sessile serrated polyps (κ = 0.14). Agreement on dysplasia grading was fair (κ = 0.32). CONCLUSION: While agreement was good for adenomatous polyps and carcinoma, considerable variability exists in diagnosing certain polyp types and grading dysplasia. These findings highlight the need for standardized criteria and additional training to improve consistency in colorectal polyp assessment, particularly for serrated lesions and dysplasia grading.
StainStyleSampler: clustering-based sampling of whole slide image appearances.
Silva MMB, Leh S, Weishaupt H
Diagn Pathol · 2026 Feb · PMID 41645270 · Full text
The appearance of whole slide biopsy images is greatly affected by various factors such as laboratory procedures or the choice of digital slide scanners. The resulting variations in image styles within and across batches...
The appearance of whole slide biopsy images is greatly affected by various factors such as laboratory procedures or the choice of digital slide scanners. The resulting variations in image styles within and across batches of histological images represent one of the major obstacles to the development of generalizable machine learning algorithms. To overcome this challenge, a lot of research has focused on stain normalization and stain augmentation techniques. While such approaches provide effective strategies to reduce stain variation or increase stain invariance, respectively, they typically involve only limited modelling or sampling of the underlying stain style distribution. Tools for a streamlined sampling of different aspects of such a distribution, which would be crucial e.g. for explicitly evaluating machine learning robustness across or with respect to major stain styles, remain largely missing. Here, we present the StainStyleSampler, a toolkit for (i) the exploration and modelling of stain style variations, and (ii) the automated sampling of images or styles capturing the core components of this variation. The tool enables the extraction of various colour features and deconvolved stain components, visualization of such features directly or after dimensionality reduction, modelling of style distributions using binning, clustering, and density mapping, and automated sampling of the most representative reference images. We believe that this software will equip pathologists and computer-scientists with a more versatile set of tools that can substantially aid in both the exploration and sampling of stain variation across whole slide images.
Quantification of interstitial fibrosis in digitized kidney biopsies using deep neural networks.
Soleimani N, Hajizadeh Z, Mohammadi M … +1 more , Mohammadzadeh S
Diagn Pathol · 2026 Feb · PMID 41639733 · Full text
INTRODUCTION: Interstitial fibrosis in kidney biopsy is an established marker of disease prognosis and chronicity. Conventional manual grading by pathologists is subjective and variable. Computational methods may reduce...
INTRODUCTION: Interstitial fibrosis in kidney biopsy is an established marker of disease prognosis and chronicity. Conventional manual grading by pathologists is subjective and variable. Computational methods may reduce this variability. METHODS: We developed a deep learning framework using a ResNet-50 architecture with transfer learning to classify interstitial fibrosis on trichrome-stained renal biopsy images. A total of 2000 biopsies were screened; 162 were excluded due to poor slide quality, leaving 1838 cases (1154 native, 684 transplant). A single expert nephropathologist provided ground-truth fibrosis scores, categorized as < 5% (minimal), 5–25% (mild), 26–50% (moderate), and > 50% (severe). RESULTS: The model achieved an overall accuracy of 73% (95% CI: 65–81%) with substantial agreement with the pathologist (κ = 0.68). Stratified analysis showed 78% accuracy for native kidneys and 67% for transplant biopsies. CONCLUSION: Our CNN-based framework shows promise for standardizing fibrosis assessment in kidney biopsies. However, the absence of external validation remains a key limitation, and further multi-center studies are required.
Guidelines for the adoption of digital pathology in clinical pathology units recommended by the polish society of pathologists.
Szylberg Ł, Durślewicz J, Chmura Ł … +3 more , Rezner W, Bartczak A, Marszałek A
Diagn Pathol · 2026 Jan · PMID 41618426 · Full text
These guidelines provide a clear and practical framework for the effective implementation of digital pathology (DP) in routine anatomical pathology practice. Digital pathology, defined as the digitization of microscope s...
These guidelines provide a clear and practical framework for the effective implementation of digital pathology (DP) in routine anatomical pathology practice. Digital pathology, defined as the digitization of microscope slide into high-resolution whole slide images, is transforming the diagnostic workflow by enabling remote access, improved image analysis, integration with artificial intelligence (AI), and enhanced data management. While digital systems are becoming increasingly integrated into pathology laboratories, the physical archiving of microscope slides remains a legal and procedural requirement in many countries, particularly for histological and cytological materials. As DP continues to evolve globally, the establishment of clear standards, technical requirements, validation procedures, and interoperability guidelines is essential to maintain diagnostic accuracy, patient safety, and system reliability. These recommendations address key technical, organizational, and legal aspects of DP implementation, with an emphasis on ensuring consistent quality and minimizing variability in diagnostic outcomes. The outlined approach supports the safe and effective adoption of DP as an integral element of modern digital healthcare.
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