Academic Unit of Surgery, School of Medicine, University of Glasgow, Royal Infirmary, Glasgow G31 2ER, UK.
Academic Unit of Surgery, School of Medicine, University of Glasgow, Royal Infirmary, Glasgow G31 2ER, UK.
Eur J Cancer. 2014 Feb;50(3):544-52. doi: 10.1016/j.ejca.2013.11.003. Epub 2013 Dec 11.
BACKGROUND: Cancer-associated inflammation is increasingly recognised to be an important determinant of oncological outcome. In colorectal cancer, the presence of peri-tumoural inflammatory/lymphocytic infiltrates predicts improved survival. To date, these infiltrates, assessed visually on haematoxylin and eosin (H&E) stained sections, have failed to enter routine clinical practice, partly due to their subjective assessment and considerable inter-observer variation. The present study aims to develop an automated scoring method to enable consistent and reproducible assessment of tumour inflammatory infiltrates in colorectal cancer. METHODS: 154 colorectal cancer patients who underwent curative resection were included in the study. The local inflammatory infiltrate was assessed using the method described by Klintrup-Makinen. H&E tumour sections were uploaded to an image analysis programme (Slidepath, Leica Biosystems). An image analysis algorithm was developed to count the inflammatory cells at the invasive margin. The manual and automated assessments of the tumour inflammatory infiltrates were then compared. RESULTS: The automated inflammatory cell counts assessed using the freehand annotation method (p<0.001) and the rectangular box method (p<0.001) were significantly associated with both K-M score (p<0.001) and K-M grade (p<0.001). The inflammatory cell counts were divided using quartiles to group tumours with similar inflammatory cell densities. There was good agreement between the manual and automated scoring methods (intraclass correlation coefficient (ICC)=0.82). Similar to the visual K-M scoring system, the automated K-M classification of the inflammatory cell counts, using quartiles, was significantly associated with venous invasion (p<0.05) and modified Glasgow Prognostic Score (mGPS) (p⩽0.05). On univariate survival analysis, both automated K-M category (p<0.05) and automated K-M grade (p<0.005) were associated with cancer-specific survival. CONCLUSION: The results of the present study demonstrate that automated assessment effectively recapitulates the clinical value of visual assessment of the local inflammatory cell infiltrate at the invasive margin of colorectal tumours. In addition, it is possible to obtain an objective assessment of tumour inflammatory infiltrates using routinely stained H&E sections. An automated, computer-based scoring method is therefore a workable and cost-effective approach to clinical assessment of local immune cell infiltrates in colorectal cancer.
背景:越来越多的人认识到癌症相关炎症是影响肿瘤预后的重要决定因素。在结直肠癌中,肿瘤周围炎症/淋巴细胞浸润的存在预示着更好的生存。迄今为止,这些通过苏木精和伊红(H&E)染色切片进行评估的浸润物尚未进入常规临床实践,部分原因是它们的主观评估和相当大的观察者间差异。本研究旨在开发一种自动化评分方法,以实现结直肠癌肿瘤炎症浸润的一致和可重复评估。
方法:本研究纳入了 154 例接受根治性切除术的结直肠癌患者。使用 Klintrup-Makinen 描述的方法评估局部炎症浸润。将 H&E 肿瘤切片上传至图像分析程序(Slidepath,Leica Biosystems)。开发了一种图像分析算法来计算侵袭边缘的炎症细胞数。然后比较手动和自动评估肿瘤炎症浸润的结果。
结果:使用徒手注释法(p<0.001)和矩形框法(p<0.001)评估的自动炎症细胞计数与 K-M 评分(p<0.001)和 K-M 分级(p<0.001)均显著相关。将炎症细胞计数分为四分位组,以分组具有相似炎症细胞密度的肿瘤。手动和自动评分方法之间具有良好的一致性(组内相关系数(ICC)=0.82)。与视觉 K-M 评分系统相似,使用四分位法对炎症细胞计数进行的自动 K-M 分类与静脉侵犯(p<0.05)和改良格拉斯哥预后评分(mGPS)(p⩽0.05)显著相关。在单因素生存分析中,自动 K-M 分类(p<0.05)和自动 K-M 分级(p<0.005)均与癌症特异性生存相关。
结论:本研究结果表明,自动评估可有效重现结直肠肿瘤侵袭边缘局部炎症细胞浸润的临床价值。此外,使用常规染色的 H&E 切片可以对肿瘤炎症浸润进行客观评估。因此,基于计算机的自动评分方法是一种可行且具有成本效益的方法,可用于结直肠癌局部免疫细胞浸润的临床评估。
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