Search Results (47)

Assessment of Programmed Death-Ligand 1 (PD-L1) immunohistochemical (IHC) expression on tumor cells (TCs) and immune cells (ICs) in bladder cancer (BC) is challenging. Artificial Intelligence (AI) has potential for accurate PD-L1 IHC scoring, but its efficiency remains debatable. Our aim was to compare two AI protocols provided by the free QuPath software (v0.5.1) (Selected Area Interpretation (AI-SAI) and Whole Slide Imaging (AI-WSI)) with manual PD-L1 IHC scoring. A total of 43 BCs were included. PD-L1 IHC was performed using the SP263 clone. The IHC slides were digitized and further imported into QuPath. The PD-L1 positivity threshold was set at 25%. Statistically significant correlations were observed between AI-SAI and manual interpretation for both TCs (r = 0.85) and ICs (r = 0.57). AI-WSI yielded comparable results, with correlation coefficients of r = 0.82 for TCs and r = 0.56 for ICs. However, AI-SAI demonstrated stronger agreement with manual assessment (κ = 0.86) compared to AI-WSI (κ = 0.65). Receiver Operating Characteristic (ROC) analysis further supported the superiority of AI-SAI, with higher AUC values for both TCs (0.96 vs. 0.92) and ICs (0.92 vs. 0.90). Our findings indicate that AI-SAI is preferable to AI-WSI, particularly in BC cases with high PD-L1-positive TC content. Nevertheless, supervision by an experienced pathologist is mandatory. Full article

Whole-slide imaging (WSI) in cytopathology poses challenges related to segmentation accuracy, computational efficiency, and image acquisition artifacts. This study aims to evaluate the performance of deep-learning models for instance segmentation in cervical cytology, benchmarking them against state-of-the-art methods on both public and institutional datasets. We tested three architectures—U-Net, vision transformer (ViT), and Detectron2—and evaluated their performance on the ISBI 2014 and CNseg datasets using panoptic quality (PQ), dice similarity coefficient (DSC), and intersection over union (IoU). All models were trained on CNseg and tested on an independent institutional dataset. Data preprocessing involved manual annotation using QuPath, patch extraction guided by GeoJSON files, and exclusion of regions containing less than 60% cytologic material. Our models achieved superior segmentation performance on public datasets, reaching up to 98% PQ. Performance decreased on the institutional dataset, likely due to differences in image acquisition and the presence of blurred nuclei. Nevertheless, the models were able to detect blurred nuclei, highlighting their robustness in suboptimal imaging conditions. In conclusion, the proposed models offer an accurate and efficient solution for instance segmentation in cytology WSI. These results support the development of reliable AI-powered tools for digital cytology, with potential applications in automated screening and diagnostic workflows. Full article

Background and Objectives: Innate and adaptive immune responses serve a crucial role in neoplasms. The interaction of immune cells with the neoplastic tissue influences tumor behavior, resulting in either pro-tumorigenic or anti-tumorigenic effects. However, the prognostic significance of the tumor immune microenvironment (TIME) in synovial sarcoma (SS) remains poorly studied. This study aimed to analyze the TIME of SS to determine its impact on the prognosis by examining the intratumoral lymphocytic and macrophagic infiltrate and its potential correlation with survival and recurrence. Methods: We conducted a retrospective observational study of 49 fusion-confirmed SS cases collected from two different institutions. We obtained clinical and follow-up data, and SSs were histologically classified according to WHO criteria. Immunohistochemical analysis, including of CD163, CD68, CD3, CD8, and CD20, was conducted in tissue microarrays using an analog scale. We examined the whole-slide tissue for the 23 cases with sufficient material available and then assessed the positive area by scanning the slides and analyzing the images using QuPath (0.4.4, Belfast, Northern Ireland) to calculate the positive area in an immune hotspot. We correlated the expression of these markers with clinical outcomes. A log-rank test and Kaplan–Meyer curves were used as appropriate (significance: p ≤ 0.05). Results: The most frequent morphological subtype was monophasic (59.6%), followed by biphasic (26.9%) and undifferentiated (7%). The mean disease specific survival (DSS) was 55.3 months, with a median of 33 months. The median overall survival (OS) was 50 months (range: 2–336 months). Both evaluation methods showed a good correlation for all antibodies, with Chi-square values of p < 0.05. All cases showed variable amounts of CD163-positive macrophages. The cases that showed a higher density of CD163-positive macrophages in whole-slide images subjected to digital analysis demonstrated an improved OS and DSS on Kaplan–Meier curves. Cases with lower CD8 and CD3 positivity showed a tendency toward faster progression and a slightly worse prognosis. Conclusions: The tumor immune microenvironment in sarcomas is a complex system that requires further investigation to fully understand its impact on tumorigenesis and patient clinical outcomes. Our results demonstrate that a higher amount of intratumoral CD163-positive macrophage infiltrate is associated with an increased OS and DSS. Our findings show that digital pathology is more precise than subjective quantitative analysis. Full article

Background/Objectives: Purinergic signaling, which involves extracellular ATP (eATP), its metabolites, purinergic receptors and ectonucleotidases, plays a pivotal role in the tumor microenvironment (TME), impacting tumor progression and the antineoplastic immune response. In this study, the CD39, CD73, P2X4, and P2X7 expression in NSCLC tumor cells and the surrounding stroma of 139 resected patients was examined. Methods: The study included tissue samples from 139 NSCLC patients. Tissue microarrays (TMAs) were constructed using 1.0 mm cores from annotated tumor regions. Immunohistochemical staining for CD39, CD73, P2X4, and P2X4 was performed on 2 µm sections. TMA slides were digitized and analyzed with QuPath, where staining intensity was evaluated using a semi-quantitative H-score. Statistical analysis, including survival analysis, was performed using R, to assess the impact of biomarker expression on patient outcomes. Results: High CD39 expression in both tumor and stromal cells was significantly associated with prolonged PFS (respectively: p = 0.0058 and p = 0.0067), particularly in adenocarcinoma (ADC) patients (respectively: p = 0.01 and p = 0.023). In the multivariable Cox model, low CD73 expression in tumor cells correlated with longer PFS (HR: 0.47; 95% CI: [0.28, 0.8], p = 0.005), while low CD73 expression in stromal cells was linked to increased progression risk (HR: 4.81; 95% CI: [1.61, 14.4], p = 0.001). Neither P2X7 nor P2X4 demonstrated a consistent effect on PFS in univariable analyses; however, multivariable analyses suggested that P2X4 might play a prognostic role in NSCLCs (HR: 0.37; 95% CI: [0.19, 0.73], p = 0.003). Conclusions: These findings underscore the importance of purinergic signaling in NSCLC prognosis and highlight the role of the ectonucleotidases CD39 and CD73 as potential therapeutic targets to enhance antineoplastic immune responses. Full article

Background/Objectives: Alzheimer’s disease (AD) severely hinders cognitive function in the hippocampus (HP) and subiculum (SUB), impacting the expression of nicotinic acetylcholine receptors (nAChRs) such as the α7-subtype. To investigate α7 nAChRs as a potential PET imaging biomarker, we report the quantitative binding of [¹²⁵I]α-Bungarotoxin ([¹²⁵I]α-Bgtx) for binding to postmortem human AD (n = 29; 13 males, 16 females) HP compared to cognitively normal (CN) (n = 28; 13 male, 15 female) HP. Methods: For comparisons with common AD biomarkers, adjacent slices were anti-Aβ and anti-Tau immunostained for analysis using QuPath. Results: The [¹²⁵I]α-Bgtx average SUB/HP ratio was 0.5 among the CN subjects, suggesting higher [¹²⁵I]α-Bgtx binding in the HP gray matter regions. The AD subjects showed overall less binding than the CN subjects, with no statistical significance. A positive correlation was found in the [¹²⁵I]α-Bgtx binding in the AD subjects as the age increased. The Braak stage comparisons of [¹²⁵I]α-Bgtx were made with [¹⁸F]flotaza binding to Aβ plaques and [¹²⁵I]IPPI binding to Tau. A positive correlation was found between [¹²⁵I]α-Bgtx and [¹⁸F]flotaza and there was a negative correlation between [¹²⁵I]α-Bgtx and [¹²⁵I]IPPI, implicating intricate relationships between the different AD biomarkers. Conclusions: [¹²⁵I]α-Bgtx shows complimentary potential as a α7 nAChR imaging agent but needs more preclinical assessments to confirm effectiveness for translational PET studies using α7 nAChR radioligands. Full article

In the field of histological analysis, one of the typical issues is the analysis of single cells contained in regions of interest (i.e., ROIs). Today, several commercial, freely available, and open-source software options are accessible for this task. However, the literature lacks recent extensive reviews that summarise the functionalities of the opportunities currently available and provide guidance on selecting the most suitable option for analysing specific cases, for instance, irregular freehand-defined ROIs on brightfield images. In this work, we reviewed and compared 14 software tools tailored for single-cell analysis within a 2D histological freehand-defined image ROI. Precisely, six open-source tools (i.e., CellProfiler, Cytomine, Digital Slide Archive, Icy, ImageJ/Fiji, QuPath), four freely available tools (i.e., Aperio ImageScope, NIS Elements Viewer, Sedeen, SlideViewer), and four commercial tools (i.e., Amira, Arivis, HALO, Imaris) were considered. We focused on three key aspects: (a) the capacity to handle large file formats such as SVS, DICOM, and TIFF, ensuring compatibility with diverse datasets; (b) the flexibility in defining irregular ROIs, whether through automated extraction or manual delineation, encompassing square, circular, polygonal, and freehand shapes to accommodate varied research needs; and (c) the capability to classify single cells within selected ROIs on brightfield images, ranging from fully automated to semi-automated or manual approaches, requiring different levels of user involvement. Thanks to this work, a deeper understanding of the strengths and limitations of different software platforms emerges, facilitating informed decision making for researchers looking for a tool to analyse histological brightfield images. Full article

Background: Merkel cell carcinoma (MCC) is a rare and frequently fatal form of skin cancer. Apart from Programmed Cell Death Protein 1 (PD-1)/Programmed Death-Ligand 1 (PD-L1) signaling, there is a lack of knowledge regarding other immune checkpoint molecules. Recent studies have observed elevated glycoprotein CD200 (also known as OX-2) mRNA expression in in different types of tumors, with CD200R-expressing myeloid cells present in the tumor microenvironment. However, the potential role of the CD200/CD200 axis as an additional checkpoint modulator remains widely unexplored. The aim of this study was to determine the intratumoral protein expression of CD200 as well as CD200R in a larger cohort of MCC patients and to correlate the expression levels with patients’ outcomes. Methods: In this multicenter study, we investigated 68 patients with MCC (68 primary tumors and 15 corresponding metastases). Immunohistochemistry (IHC) was performed for CD200 as well as CD200R. Digital quantification and analysis of IHC were performed using QuPath-0.2.3. Results: CD200 and CD200R expression was observed in 100% of cases. Univariate analysis revealed that low CD200 expression in primary tumors (p = 0.0007, HR 9.35), male sex (p = 0.045, HR 2.41), and immunosuppression (p = 0.0031, HR 6.36) were significantly associated with MCC relapse. Low CD200 expression was also linked to prior immune checkpoint inhibitors (ICI) and/or chemotherapy treatment (p = 0.037). Multivariable analysis confirmed that low CD200 expression (p = 0.0012, HR 5.25) and immunosuppression (p = 0.0056, HR 4.11) were independent predictors of MCC relapse. Conclusions: Expression of CD200/CD200R proteins is very high in MCC and may thus be of diagnostic value. More importantly, low intratumoral CD200 protein expression in primary MCC represents a robust independent predictor of MCC relapse. Full article

Primary and post-primary TB are distinct entities. Primary TB occurs when the patient is infected with Mycobacterium tuberculosis (MTB) for the first time without prior immunity, and post-primary TB occurs when the patient has developed immunity against the primary infection. Post-primary TB occurs only in humans. It accounts for 80% of all clinical cases and nearly 100% of transmissions of infection. Early lesions of post-primary TB are reversible, and studying it using modern immunological tools holds the key to developing preventive or treatment strategies. Human lung tissue from untreated TB patients was acquired from pathology archives stored at the Gades Institute of Pathology, Haukeland University Hospital, Bergen, Norway, from 1931 to 1947. Manual immunohistochemistry was performed for macrophage (CD68, CD64 and CD163), T cells (CD3 and CD8), matrix metalloproteinases (MMP-9), and markers for programmed death-pathway PD/PDL-1. Digital quantification was performed using Qupath software. In early lesions of post-primary TB, macrophages showed mixed-phenotype M1 and M2, expressed PDL-1, and were compartmentalized in the alveolar space. T-cells expressed PD-1 and were compartmentalized in the interstitial wall surrounding early lesions. MTB antigens and MMP-9 were also found in early lesions. As the lesion progressed towards necrosis, macrophages showed predominant M1 morphology, and expressions of PDL-1, PD-1, CD8⁺ cells, and MTB antigens increased. In the early lesions of post-primary TB, the compartmentalization of macrophages in the alveoli and T cells in the interstitium was shown. The PDL-PD1 pathway probably facilitated the mycobacterial growth by evading host immunity. Full article

The purpose of this study was to evaluate the suitability of formalin-fixed and paraffin-embedded (FFPE) samples and fixed fresh (FF) samples for single-cell RNA sequencing (scRNAseq). To this end, we compared single-cell profiles from FFPE and matched FF tissue samples of one invasive carcinoma of no special type carcinoma (invasive ductal carcinoma–IDC) and one invasive lobular carcinoma (ILC) to assess consistency in cell type distribution and molecular profiles. The results were validated using immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and electron microscopy. Additionally, immune cell proportions identified by IHC were quantified using QuPath and compared to the scRNAseq results. FFPE- and FF-derived libraries demonstrated high-quality sequencing metrics, and cellular heterogeneity was similar. No exclusive cell populations were identified by either approach. The four samples analysis identified six types of epithelial cells, as well as tumoral microenvironment populations. The scRNAseq results from epithelial neoplastic cells were concordant with common IHC markers. The proportion of immune cells identified by IHC in FFPE sections were similar to those obtained by scRNAseq. We identified and validated a previously poorly recognized subpopulation of neoplastic multi-ciliated cells (MCCs) (FOXJ1, ROPN1L). Analysis of FOXJ1 in 214 ER-positive invasive carcinomas demonstrated protein expression in one third of tumors, suggesting frequent focal MCC differentiation. Our results support the suitability of scRNAseq analysis using FFPE tissue, and identified a subpopulation of neoplastic MCC in breast cancer. Full article

Immunohistochemical (IHC) studies of formalin-fixed paraffin-embedded (FFPE) samples are a gold standard in oncology for tumor characterization, and the identification of prognostic and predictive markers. However, despite the abundance of archived FFPE samples, their research use is limited due to the labor-intensive nature of IHC on large cohorts. This study aimed to create a high-throughput workflow using modern technologies to facilitate IHC biomarker studies on large patient groups. Semiautomatic constructed tissue microarrays (TMAs) were created for two tumor patient cohorts and IHC stained for seven antibodies (ABs). AB expression in the tumor and surrounding stroma was quantified using the AI-supported image analysis software QuPath. The data were correlated with clinicopathological information using an R-script, all results were automatically compiled into formatted reports. By minimizing labor time to 7.7%—compared to whole-slide studies—the established workflow significantly reduced human and material resource consumption. It successfully correlated AB expression with overall patient survival and additional clinicopathological data, providing publication-ready figures and tables. The AI-assisted high-throughput TMA workflow, validated on two patient cohorts, streamlines modern histopathological research by offering cost and time efficiency compared to traditional whole-slide studies. It maintains research quality and preserves patient tissue while significantly reducing material and human resources, making it ideal for high-throughput research centers and collaborations. Full article

Our prior findings showed that BCL2A1 in neutrophils is highly expressed in the extra-placental membranes (EPMs) of both the human spontaneous preterm-birth (PTB) (i.e., PTL or preterm PROM) and nonhuman-primate PTB model. However, no data exist on whether the intensity of BCL2A1 expression quantitatively increases according to the stage progression of acute histologic chorioamnionitis (acute HCA) in EPM. The objective is to investigate whether the intensity of BCL2A1 expression quantitatively increases according to the stage progression of acute HCA in EPM among spontaneous PTB cases, as measured using QuPath. The study population included 121 singleton PTBs (gestational age [GA] at delivery < 34 weeks) due to either preterm labor or preterm PROM. With digital image analysis, we calculated the percentage of BCL2A1-positive cells in immunohistochemistry according to the stage progression of acute HCA in EPMs as the primary outcome and examined the relationship between the percentage of BCL2A1-positive cells and either the GA at delivery or the amniotic-fluid (AF) WBC count as the secondary outcome. The median percentage of BCL2A1-positive cells progressively increases with the stage progression of acute HCA in EPM (group-1 vs. group-2 vs. group-3 vs. group-4 vs. group-5; 7.62 vs. 5.15 vs. 43.57 vs. 71.07; γ = 0.552, p < 0.000001). The percentage of BCL2A1-positive cells in EPMs and the AFWBC count shows a positive correlation (γ = 0.492, p = 0.000385). Moreover, the percentage of BCL2A1-positive cells in EPMs continuously decreased with increasing GA at delivery (γ = −0.253, p = 0.005148). In conclusion, the intensity of BCL2A1 expression increases according to the stage progression of acute HCA in EPMs and the elevation of AFWBC among spontaneous PTB cases. This finding suggests BCL2A1 in EPMs may be a promising marker and target for acute HCA. Full article

The emerging usage of digitalized histopathological images is leading to a novel possibility for data analysis. With the help of artificial intelligence algorithms, it is now possible to detect certain structures and morphological features on whole slide images automatically. This enables algorithms to count, measure, or evaluate those areas when trained properly. To achieve suitable training, datasets must be annotated and curated by users in programs like QuPath. The extraction of this data for artificial intelligence algorithms is still rather tedious and needs to be saved on a local hard drive. We developed a toolkit for integration into existing pipelines and tools, like U-net, for the on-the-fly extraction of annotation tiles from existing QuPath projects. The tiles can be directly used as input for artificial intelligence algorithms, and the results are directly transferred back to QuPath for visual inspection. With the toolkit, we created a convenient way to incorporate QuPath into existing AI workflows. Full article

Background: Coronary artery disease (CAD) underlies most cases of myocardial infarction (MI), causing or at least contributing to oxygen supply–demand mismatch and myocardial injury, so a careful and reliable evaluation of the main coronary arteries and large branches is a key moment of autopsy in order to establish the cause of death. The aim of this study is to evaluate the application of digital image analysis in the assessment of coronary artery sub-occlusions. Methods: A total of 50 coronary sections sampled during 11 consecutive autopsies, regardless of the cause of death, were analyzed. The ideal lumen and the percentage of the residual lumen were evaluated by digital pathology using QuPath v 4.3 and by an expert pathologist. The evaluations performed were compared using Lin’s concordance correlation coefficient. Results: The Lin agreement index between the two evaluation methods for all measurements showed an excellent agreement rate [0.923, with confidence interval (0.866, 0.956)]. However, in the case of critical stenosis, from 60% to 80% and from 65% to 75%, the Lin agreement index between the two evaluation methods was, respectively, 0.798 [0.603, 0.904], corresponding to good agreement, and 0.516 [0.071, 0.725], corresponding to slight agreement. The digital system has superior performance in cases where lumen occlusion falls between 60% and 80% and provides an objective assessment of the residual lumen area. Conclusions: According to the widespread availability and ease of use of these technologies, we suggest that image analysis should be considered a routine tool and established as the diagnostic gold standard in this field. Full article

The establishment of immunotherapy applying immune checkpoint inhibitors (ICI) has provided an important new option for the treatment of solid malignant diseases. However, different tumor entities show dramatically different responses to this therapy. BCC responds worse to anti-PD-1 ICIs as compared to cSCC. Differential immune checkpoint expression could explain this discrepancy and, therefore, the aim of this study was to analyze activating and inhibitory immune checkpoints in cSCC and BCC tissues. Tissue microarrays of the invasive front as well as the tumor core of BCC and cSCC samples were used to evaluate PD-1, PD-L1, CD28, and CD86 expression and their topographic distribution profiles by chromogenic immunohistochemistry. QuPath was used to determine the labeling index. The expression of PD-1, PD-L1, and CD28 was significantly higher in both the tumor core and the invasive front of cSCC samples as compared to BCC (p < 0.001). In addition, the ratios of PD-L1/CD86 (p < 0.001) and CD28/CD86 (p < 0.001) were significantly higher in cSCC. The invasive front of both tumor entities showed higher expression levels of all immune markers compared to the tumor core in both tumor entities. The significantly higher expression of PD-1, PD-L1, and CD28 in cSCC, along with the predominance of the inhibitory ligand PD-L1 as compared to the activating CD86 in cSCC, provide a potential explanation for the better objective response rates to anti-PD-1 immunotherapy as compared to BCC. Furthermore, the predominant site of interaction between the immune system and the tumor was within the invasive front in both tumor types. Full article

The diagnostic value of imaging Aβ plaques in Alzheimer’s disease (AD) has accelerated the development of fluorine-18 labeled radiotracers with a longer half-life for easier translation to clinical use. We have developed [¹⁸F]flotaza, which shows high binding to Aβ plaques in postmortem human AD brain slices with low white matter binding. We report the binding of [¹⁸F]flotaza in postmortem AD hippocampus compared to cognitively normal (CN) brains and the evaluation of [¹⁸F]flotaza in transgenic 5xFAD mice expressing Aβ plaques. [¹⁸F]Flotaza binding was assessed in well-characterized human postmortem brain tissue sections consisting of HP CA1-subiculum (HP CA1-SUB) regions in AD (n = 28; 13 male and 15 female) and CN subjects (n = 32; 16 male and 16 female). Adjacent slices were immunostained with anti-Aβ and analyzed using QuPath. In vitro and in vivo [¹⁸F]flotaza PET/CT studies were carried out in 5xFAD mice. Post-mortem human brain slices from all AD subjects were positively IHC stained with anti-Aβ. High [¹⁸F]flotaza binding was measured in the HP CA1-SUB grey matter (GM) regions compared to white matter (WM) of AD subjects with GM/WM > 100 in some subjects. The majority of CN subjects had no decipherable binding. Male AD exhibited greater WM than AD females (AD WM♂/WM♀ > 5; p < 0.001) but no difference amongst CN WM. In vitro studies in 5xFAD mice brain slices exhibited high binding [¹⁸F]flotaza ratios (>50 versus cerebellum) in the cortex, HP, and thalamus. In vivo, PET [¹⁸F]flotaza exhibited binding to Aβ plaques in 5xFAD mice with SUVR~1.4. [¹⁸F]Flotaza is a new Aβ plaque PET imaging agent that exhibited high binding to Aβ plaques in postmortem human AD. Along with the promising results in 5xFAD mice, the translation of [¹⁸F]flotaza to human PET studies may be worthwhile. Full article