WhARIO:对接受免疫疗法的患者进行基于全滑动图像的生存分析。

IF 1.9 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Medical Imaging Pub Date : 2024-05-01 Epub Date: 2024-05-11 DOI:10.1117/1.JMI.11.3.037502
Paul Tourniaire, Marius Ilie, Julien Mazières, Anna Vigier, François Ghiringhelli, Nicolas Piton, Jean-Christophe Sabourin, Frédéric Bibeau, Paul Hofman, Nicholas Ayache, Hervé Delingette
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引用次数: 0

摘要

目的:免疫检查点抑制剂(ICIs)现已成为肺癌患者的治疗标准之一,大大提高了患者的无进展生存期和总生存期,但仍有20%的患者对治疗有反应,部分患者面临急性不良反应。虽然有一些预测性生物标志物已融入临床工作流程,但它们需要在全切片图像基础上增加其他模式,而且缺乏效率或稳健性。在这项工作中,我们提出了一种仅从组织学切片分析中得出的免疫疗法结果生物标志物:我们开发了一个三步框架,结合对比学习和非参数聚类来区分切片中的组织模式,然后利用之前定义的区域的邻接性来得出特征,并训练一个用于生存分析的比例危险模型。我们在来自 5 个医疗中心的 193 名患者的内部数据集上测试了我们的方法,并将其与金标准肿瘤比例评分(TPS)生物标志物进行了比较:在对整个数据集进行的五倍交叉验证(CV)中,基于全滑动图像的免疫疗法患者生存分析(WhARIO)特征能够区分低风险和高风险患者群体,其危险比(HR)为2.29(CI95=1.48至3.56),而TPS 1%参考阈值的危险比仅为1.81(CI95=1.21至2.69)。将二者结合则可得出更高的 HR,即 2.60(CI95=1.72 至 3.94)。在同一数据集上进行的其他实验证实了这些趋势:我们独特设计的 WhARIO 特征能有效预测接受 ICI 治疗的肺癌患者的生存率。我们取得了与当前金标准生物标志物相似的性能,而无需使用其他成像模式,并表明两者结合使用可取得更好的效果。
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WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy.

Purpose: Immune checkpoint inhibitors (ICIs) are now one of the standards of care for patients with lung cancer and have greatly improved both progression-free and overall survival, although <20% of the patients respond to the treatment, and some face acute adverse events. Although a few predictive biomarkers have integrated the clinical workflow, they require additional modalities on top of whole-slide images and lack efficiency or robustness. In this work, we propose a biomarker of immunotherapy outcome derived solely from the analysis of histology slides.

Approach: We develop a three-step framework, combining contrastive learning and nonparametric clustering to distinguish tissue patterns within the slides, before exploiting the adjacencies of previously defined regions to derive features and train a proportional hazards model for survival analysis. We test our approach on an in-house dataset of 193 patients from 5 medical centers and compare it with the gold standard tumor proportion score (TPS) biomarker.

Results: On a fivefold cross-validation (CV) of the entire dataset, the whole-slide image-based survival analysis for patients treated with immunotherapy (WhARIO) features are able to separate a low- and a high-risk group of patients with a hazard ratio (HR) of 2.29 (CI95=1.48 to 3.56), whereas the TPS 1% reference threshold only reaches a HR of 1.81 (CI95=1.21 to 2.69). Combining the two yields a higher HR of 2.60 (CI95=1.72 to 3.94). Additional experiments on the same dataset, where one out of five centers is excluded from the CV and used as a test set, confirm these trends.

Conclusions: Our uniquely designed WhARIO features are an efficient predictor of survival for lung cancer patients who received ICI treatment. We achieve similar performance to the current gold standard biomarker, without the need to access other imaging modalities, and show that both can be used together to reach even better results.

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来源期刊
Journal of Medical Imaging
Journal of Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.10
自引率
4.20%
发文量
0
期刊介绍: JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.
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