مورد إلكتروني
Automated detection of vascular remodeling in human tumor draining lymph nodes by the deep learning tool HEV-finder
| العنوان: | Automated detection of vascular remodeling in human tumor draining lymph nodes by the deep learning tool HEV-finder |
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| بيانات النشر: | Uppsala universitet, Vaskulärbiologi Uppsala universitet, Avdelningen för visuell information och interaktion Uppsala universitet, Bildanalys och människa-datorinteraktion Uppsala universitet, Institutionen för immunologi, genetik och patologi Uppsala universitet, Science for Life Laboratory, SciLifeLab Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden 2022 |
| تفاصيل مُضافة: | Bekkhus, Tove Avenel, Christophe Hanna, Sabella Franzén Boger, Mathias Klemm, Anna H Vasiliu-Bacovia, Daniel Wärnberg, Fredrik Wählby, Carolina Ulvmar, Maria H. |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. |
| مصطلحات الفهرس: | HEV-finder, artificial intelligence (AI), breast cancer, deep learning, high endothelial venules (HEVs), tumor-draining lymph nodes (TDLNs), vascular remodeling, Cancer and Oncology, Cancer och onkologi, Article in journal, info:eu-repo/semantics/article, text |
| DOI: | 10.1002.path.5981 |
| URL: | Journal of Pathology, 0022-3417, 2022, 258:1, s. 4-11 |
| الإتاحة: | Open access content. Open access content info:eu-repo/semantics/openAccess |
| ملاحظة: | application/pdf English |
| أرقام أخرى: | UPE oai:DiVA.org:uu-469951 0000-0002-2868-2483 0000-0002-1835-921X 0000-0002-3466-1320 0000-0002-9050-0978 0000-0002-0130-7296 0000-0002-4139-7003 0000-0002-9050-0978 doi:10.1002/path.5981 PMID 35696253 ISI:000823061100001 1387014636 |
| المصدر المساهم: | UPPSALA UNIV LIBR From OAIster®, provided by the OCLC Cooperative. |
| رقم الأكسشن: | edsoai.on1387014636 |
| قاعدة البيانات: | OAIster |
| DOI: | 10.1002.path.5981 |
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