ArticleVirchows Archiv : an international journal of pathology2025
Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.
Article in Virchows Archiv : an international journal of pathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 11 citations in OpenAlex.
- AI-based tumor cellularity assessment in digital pathology: A review of methods, datasets, and clinical translation.Journal of pathology informatics · 2026Review
- Tumour-Stroma Ratio as a Predictive Biomarker for Neoadjuvant Therapy Efficacy in Rectal Cancer.Cancers · 2026Review
- What practicing pathologists and oncologists should know about the new computational pathology-based companion diagnostic tools.The Journal of pathology · 2026Review
- The critical role of accurate neoplastic cell percentage (NCP) assessment: investigating targeted training strategies for pulmonary biopsy and cytology specimens.Virchows Archiv : an international journal of pathology · 2026Article
- Pre-analytical Best Practices for RNA Sequencing from Small Biopsies and Cytologic Specimens.Molecular diagnosis & therapy · 2026Review
- Validation of QuANTUM-derived tumor cell fraction for molecular testing in high-grade serous tubo-ovarian carcinoma.NPJ precision oncology · 2026Article
- The routine use of a digital tool for the tumor cell fraction quantification in molecular pathology: an international validation of QuANTUM.Pathologica · 2025Article
- Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysis.The Journal of pathology · 2025Article
- GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning.Computational and structural biotechnology journal · 2025Article
- Deep learning algorithm on H&E whole slide images to characterizeComputational and structural biotechnology journal · 2024Article
- Concordance in the estimation of tumor percentage in non-small cell lung cancer using digital pathology.Scientific reports · 2024Article
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
Abstract
The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.