• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

数字病理学在非小细胞肺癌肿瘤百分比估计中的一致性。

Concordance in the estimation of tumor percentage in non-small cell lung cancer using digital pathology.

机构信息

Department of Pathology, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), 28034, Madrid, Spain.

Faculty of Medicine, Universidad de Alcalá, 28801, Alcalá de Henares, Spain.

出版信息

Sci Rep. 2024 Oct 15;14(1):24163. doi: 10.1038/s41598-024-75175-w.

DOI:10.1038/s41598-024-75175-w
PMID:39406837
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11480438/
Abstract

The incorporation of digital pathology in clinical practice will require the training of pathologists in digital skills. Our study aimed to assess the reliability among pathologists in determining tumor percentage in whole slide images (WSI) of non-small cell lung cancer (NSCLC) using digital image analysis, and study how the results correlate with the molecular findings. Pathologists from nine centers were trained to quantify epithelial tumor cells, tumor-associated stromal cells, and non-neoplastic cells from NSCLC WSI using QuPath. Then, we conducted two consecutive ring trials. In the first trial, analyzing four WSI, reliability between pathologists in the assessment of tumor cell percentage was poor (intraclass correlation coefficient (ICC) 0.09). After performing the first ring trial pathologists received feedback. The second trial, comprising 10 WSI with paired next-generation sequencing results, also showed poor reliability (ICC 0.24). Cases near the recommended 20% visual threshold for molecular techniques exhibited higher values with digital analysis. In the second ring trial reliability slightly improved and human errors were reduced from 5.6% to 1.25%. Most discrepancies arose from subjective tasks, such as the annotation process, suggesting potential improvement with future artificial intelligence solutions.

摘要

将数字病理学纳入临床实践将需要病理学家接受数字技能培训。我们的研究旨在评估病理学家使用数字图像分析确定非小细胞肺癌 (NSCLC) 全切片图像 (WSI) 中肿瘤百分比的可靠性,并研究结果与分子发现的相关性。来自九个中心的病理学家接受了使用 QuPath 定量分析 NSCLC WSI 上皮肿瘤细胞、肿瘤相关基质细胞和非肿瘤细胞的培训。然后,我们进行了两次连续的环试。在第一次试验中,分析了四个 WSI,病理学家评估肿瘤细胞百分比的可靠性较差(组内相关系数 (ICC) 0.09)。完成第一次环试后,病理学家收到了反馈。第二次试验包括 10 个具有配对下一代测序结果的 WSI,结果也显示可靠性较差(ICC 0.24)。接近推荐用于分子技术的 20%视觉阈值的病例,其数字分析结果较高。在第二次环试中,可靠性略有提高,人为错误从 5.6%降至 1.25%。大多数差异源于主观任务,例如注释过程,这表明未来的人工智能解决方案可能会有改进的空间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/86889df6dc14/41598_2024_75175_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/cfbf69171c82/41598_2024_75175_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/d0506ebd6b4e/41598_2024_75175_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/f30b63aec1f5/41598_2024_75175_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/7bff04247109/41598_2024_75175_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/0bdf361d0d3e/41598_2024_75175_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/86889df6dc14/41598_2024_75175_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/cfbf69171c82/41598_2024_75175_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/d0506ebd6b4e/41598_2024_75175_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/f30b63aec1f5/41598_2024_75175_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/7bff04247109/41598_2024_75175_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/0bdf361d0d3e/41598_2024_75175_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/982d/11480438/86889df6dc14/41598_2024_75175_Fig6_HTML.jpg

相似文献

1
Concordance in the estimation of tumor percentage in non-small cell lung cancer using digital pathology.数字病理学在非小细胞肺癌肿瘤百分比估计中的一致性。
Sci Rep. 2024 Oct 15;14(1):24163. doi: 10.1038/s41598-024-75175-w.
2
Validation of Whole Slide Imaging for primary surgical pathology diagnosis of prostate biopsies.全切片成像技术在前列腺活检初级手术病理诊断中的验证。
Indian J Pathol Microbiol. 2021 Jan-Mar;64(1):78-83. doi: 10.4103/IJPM.IJPM_855_19.
3
Digitized whole slides for breast pathology interpretation: current practices and perceptions.用于乳腺病理学解读的数字化全切片:当前的实践与认知。
J Digit Imaging. 2014 Oct;27(5):642-8. doi: 10.1007/s10278-014-9683-2.
4
Validating whole slide imaging for diagnostic purposes in pathology: guideline from the College of American Pathologists Pathology and Laboratory Quality Center.验证全切片成像在病理学诊断中的应用:美国病理学家学会病理学和实验室质量中心指南。
Arch Pathol Lab Med. 2013 Dec;137(12):1710-22. doi: 10.5858/arpa.2013-0093-CP. Epub 2013 May 1.
5
Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.利用人工智能赋能显微镜提高 Ki67 评估一致性:一项多机构环研究。
Histopathology. 2021 Oct;79(4):544-555. doi: 10.1111/his.14383. Epub 2021 Jun 24.
6
Interinstitutional whole slide imaging teleconsultation service development: assessment using internal training and clinical consultation cases.机构间全切片成像远程会诊服务的开发:基于内部培训和临床会诊病例的评估
Arch Pathol Lab Med. 2015 May;139(5):627-35. doi: 10.5858/arpa.2014-0133-OA. Epub 2014 Nov 21.
7
A new AI-assisted scoring system for PD-L1 expression in NSCLC.一种用于 NSCLC 中 PD-L1 表达的新型 AI 辅助评分系统。
Comput Methods Programs Biomed. 2022 Jun;221:106829. doi: 10.1016/j.cmpb.2022.106829. Epub 2022 Apr 23.
8
Quantitative image analysis for CD8 score in lung small biopsies and cytology cell-blocks.肺小活检组织和细胞学细胞块中CD8评分的定量图像分析。
Cytopathology. 2020 Sep;31(5):393-401. doi: 10.1111/cyt.12812. Epub 2020 Apr 6.
9
Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.人工智能评估 NSCLC 患者新辅助阿替利珠单抗的病理缓解:LCMC3 研究结果。
J Thorac Oncol. 2024 May;19(5):719-731. doi: 10.1016/j.jtho.2023.12.010. Epub 2023 Dec 7.
10
Whole-slide imaging at primary pathological diagnosis: Validation of whole-slide imaging-based primary pathological diagnosis at twelve Japanese academic institutes.原发性病理诊断中的全切片成像:日本十二家学术机构基于全切片成像的原发性病理诊断的验证
Pathol Int. 2017 Nov;67(11):547-554. doi: 10.1111/pin.12590. Epub 2017 Oct 5.

引用本文的文献

1
Tumor Cell Proportion Assessment in Advanced Non-Squamous Non-Small Cell Lung Cancer Tissue Samples in Real-World Settings in Japan: The ASTRAL Study.日本真实世界环境中晚期非鳞状非小细胞肺癌组织样本的肿瘤细胞比例评估:ASTRAL研究
Diagnostics (Basel). 2025 Aug 26;15(17):2165. doi: 10.3390/diagnostics15172165.

本文引用的文献

1
Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.用于分子分析的组织细胞数字计数:量子工作流程。
Virchows Arch. 2025 Feb;486(2):277-286. doi: 10.1007/s00428-024-03794-9. Epub 2024 Mar 26.
2
International Association for the Study of Lung Cancer Study of Reproducibility in Assessment of Pathologic Response in Resected Lung Cancers After Neoadjuvant Therapy.国际肺癌研究协会:新辅助治疗后切除肺癌病理反应评估重复性研究。
J Thorac Oncol. 2023 Oct;18(10):1290-1302. doi: 10.1016/j.jtho.2023.07.017. Epub 2023 Sep 12.
3
Oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up.
癌基因成瘾性转移性非小细胞肺癌:ESMO诊断、治疗及随访临床实践指南
Ann Oncol. 2023 Apr;34(4):339-357. doi: 10.1016/j.annonc.2022.12.009. Epub 2023 Jan 23.
4
QuPath Analysis for CD30+ Cutaneous T-Cell Lymphoma.CD30+ 皮肤 T 细胞淋巴瘤的 QuPath 分析。
Am J Dermatopathol. 2023 Feb 1;45(2):93-98. doi: 10.1097/DAD.0000000000002330.
5
Defining Morphologic Features of Invasion in Pulmonary Nonmucinous Adenocarcinoma With Lepidic Growth: A Proposal by the International Association for the Study of Lung Cancer Pathology Committee.定义以鳞屑样生长为主型肺非黏液性腺癌侵袭的形态学特征:国际肺癌研究协会病理委员会的提议
J Thorac Oncol. 2023 Apr;18(4):447-462. doi: 10.1016/j.jtho.2022.11.026. Epub 2022 Dec 9.
6
Assessing the prognostic value of tumor-infiltrating CD57+ cells in advanced stage head and neck cancer using QuPath digital image analysis.使用 QuPath 数字图像分析评估晚期头颈部癌症中肿瘤浸润性 CD57+细胞的预后价值。
Virchows Arch. 2022 Aug;481(2):223-231. doi: 10.1007/s00428-022-03323-6. Epub 2022 Apr 22.
7
Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.胰腺神经内分泌肿瘤的 Ki-67 评估:手动与数字病理学评分的系统评价和荟萃分析。
Mod Pathol. 2022 Jun;35(6):712-720. doi: 10.1038/s41379-022-01055-1. Epub 2022 Mar 5.
8
Automated PD-L1 Scoring for Non-Small Cell Lung Carcinoma Using Open-Source Software.使用开源软件对非小细胞肺癌进行自动化程序性死亡配体1(PD-L1)评分
Pathol Oncol Res. 2021 Mar 26;27:609717. doi: 10.3389/pore.2021.609717. eCollection 2021.
9
Conventional and semi-automatic histopathological analysis of tumor cell content for multigene sequencing of lung adenocarcinoma.用于肺腺癌多基因测序的肿瘤细胞含量的传统及半自动组织病理学分析。
Transl Lung Cancer Res. 2021 Apr;10(4):1666-1678. doi: 10.21037/tlcr-20-1168.
10
Recommendations for Specimen and Therapy Selection in Colorectal Cancer.结直肠癌标本及治疗选择的建议
Oncol Ther. 2021 Dec;9(2):451-469. doi: 10.1007/s40487-021-00151-7. Epub 2021 Apr 25.