Christina Neppl

MetAssist 2.0: A Generalizable AI Framework for Lymph Node Metastasis Detection Across Multiple Cancer Types.

Javier García-Baroja, Bastian Dislich, Philipp Zens, Branislav Zagrapan et autres

Lymph node metastasis assessment is critical for cancer staging, yet the process is labor-intensive and prone to variability, particularly when evaluating micro-metastases or isolated tumor cells that can directly alter treatment decisions. We present MetAssist 2.0, a modular AI system that combines …

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MetAssist 2.0: A Generalizable Artificial Intelligence Framework for Lymph Node Metastasis Detection Across Multiple Cancer Types

Javier García-Baroja, Bastian Dislich, Philipp Zens, Branislav Zagrapan et autres

Lymph node metastasis assessment is critical for cancer staging, yet the process is labor intensive and prone to variability, particularly when evaluating micrometastases or isolated tumor cells that can directly alter treatment decisions. We present MetAssist 2.0, a modular artificial intelligence system …

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Clear Cell Renal Cell Carcinoma: Rare and Atypical Metastatic Localizations—A Case Series

Roosvelt Tessa Djambong, Bril Laurel Follah Feudjio, Stéphane Rysselinck, Emmanuel Seront et autres

Introduction: Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer, characterized by its high degree of vascularity and metastatic potential. Although common metastatic sites include the lungs, lymph nodes, bones, liver, adrenal glands, and brain, rare localizations, …

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Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer

Gesa Mittmann, Sara Laiouar-Pedari, Hendrik A. Mehrtens, Sarah Haggenmüller et autres

Abstract The aggressiveness of prostate cancer is primarily assessed from histopathological data using the Gleason scoring system. Conventional artificial intelligence (AI) approaches can predict Gleason scores, but often lack explainability, which may limit clinical acceptance. Here, we present an alternative, inherently explainable …

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GrEp: Graph-based epithelial cell classification refinement in histopathology H&E images

Ana Leni Frei, Javier García-Baroja, Tilman T. Rau, Christina Neppl et autres

The automatic cell segmentation and classification from whole slide images plays an important role in digital pathology, unlocking new opportunities for biomarker discovery. Despite extensive research, this task faces persistent challenges such as the differentiation of epithelial cells into normal and malignant. …

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Pathologist-Read vs AI-Driven Assessment of Tumor-Infiltrating Lymphocytes in Melanoma

Thazin Nwe Aung, Matthew Liu, David G. Su, Saba Shafi et autres

Importance: Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin-stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring …

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Immunopathogenic and clinical implications of advanced tissue analysis in non-tuberculous mycobacterial infections in children

Maximilian Seidl, Elham Bavafaye Haghighi, Anne Kathrin Lößlein, Markus Hufnagel et autres

Objectives: Infections with non-tuberculous mycobacteria (NTM) in children usually affect the lymph nodes and surrounding tissue. Although the infection is typically self-limiting, it carries a substantial risk of complications due to persistent inflammation and invasive therapeutic interventions. Yet, the immunopathogenesis of the …

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Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer

Gesa Mittmann, Sara Laiouar-Pedari, Hendrik A. Mehrtens, Sarah Haggenmüller et autres

The aggressiveness of prostate cancer, the most common cancer in men worldwide, is primarily assessed based on histopathological data using the Gleason scoring system. While artificial intelligence (AI) has shown promise in accurately predicting Gleason scores, these predictions often lack inherent explainability, …

Chemotherapy increases CDA expression and sensitizes malignant pleural mesothelioma cells to capecitabine treatment

Darya Karatkevich, Tereza Losmanová, Philipp Zens, Haibin Deng et autres

The combination of cisplatin and pemetrexed remains the gold standard chemotherapy for malignant pleural mesothelioma (MPM), although resistance and poor response pose a significant challenge. Cytidine deaminase (CDA) is a key enzyme in the nucleotide salvage pathway and is involved in the …

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Multicenter Study on Tumor Budding in Lung Squamous Cell Carcinoma: Comparison Between Biopsy and Resection With Interobserver Variability Assessment

Marie Maillard, Christina Neppl, Philipp Zens, Julie Anex et autres

Grading lung squamous cell carcinoma (LUSC) is controversial and not universally accepted. The histomorphologic feature of tumor budding (TB) is an established independent prognostic factor in colorectal cancer, and its importance is growing in other solid cancers, making it a candidate for …

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Herausforderungen der zytopathologischen Pankreasdiagnostik

Martin Schramm, Christina Neppl

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1305 Agreement and reliability of an automated PD-L1 tumor proportion scoring algorithm in non-small cell lung cancer (NSCLC)

Daniela F Rodrigues, Christina Neppl, David W. Dorward, Tereza Losmanová et autres

Background Immunotherapy has revolutionized the treatment paradigm of advanced non-small cell lung cancer (NSCLC), opening possibilities for long-term survival outcomes with superior tolerability.1 Eligibility for immune checkpoint inhibitors is set by estimating the tumor proportion score (TPS) in programmed cell death ligand …

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