基于肝脏的肠道决策：一种提升结直肠癌筛查的影像组学方法
Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening
AI总结：
本研究利用常规腹部CT的肝脏影像组学特征预测结直肠肿瘤，XGBoost模型测试AUROC达0.810，优于临床模型，验证了肠-肝轴作为机会性筛查生物标志物来源的潜力。
摘要：
非侵入性结直肠癌（CRC）筛查是提高结肠镜检查参与率并降低CRC死亡率的关键机会。本研究探索了肠-肝轴在通过从常规CT图像中提取的肝脏源性影像组学特征预测结直肠肿瘤方面的潜力，作为一种新颖的机会性筛查方法。在这项回顾性研究中，我们分析了1,997名接受结肠镜检查和腹部CT的患者数据。患者要么没有结直肠肿瘤（n=1,189），要么患有结直肠肿瘤（n_total=808；腺瘤n=423，CRC n=385）。使用影像组学处理工具包（RPTK）从3D肝脏分割中提取影像组学特征，该工具包执行特征提取、过滤和分类。数据集被分为训练队列（n=1,397）和测试队列（n=600）。使用5折交叉验证在20个最具信息量的特征上训练了五种机器学习模型，并根据验证AUROC选择了最佳模型集成。基于影像组学的最佳XGBoost模型实现了测试AUROC为0.810，明显优于仅使用临床数据的最佳模型（测试AUROC：0.457）。结直肠癌和腺瘤之间的亚分类显示准确性较低（测试AUROC：0.674）。我们的发现确立了概念验证，即来自常规腹部CT的肝脏源性影像组学可以预测结直肠肿瘤。除了为CRC筛查提供一种实用且广泛可及的辅助手段外，这种方法还强调了肠-肝轴作为机会性筛查的新型生物标志物来源，并为未来的转化研究激发了新的机制假设。
英文摘要：
Non-invasive colorectal cancer (CRC) screening represents a key opportunity to improve colonoscopy participation rates and reduce CRC mortality. This study explores the potential of the gut-liver axis for predicting colorectal neoplasia through liver-derived radiomic features extracted from routine CT images as a novel opportunistic screening approach. In this retrospective study, we analyzed data from 1,997 patients who underwent colonoscopy and abdominal CT. Patients either had no colorectal neoplasia (n=1,189) or colorectal neoplasia (n_total=808; adenomas n=423, CRC n=385). Radiomics features were extracted from 3D liver segmentations using the Radiomics Processing ToolKit (RPTK), which performed feature extraction, filtering, and classification. The dataset was split into training (n=1,397) and test (n=600) cohorts. Five machine learning models were trained with 5-fold cross-validation on the 20 most informative features, and the best model ensemble was selected based on the validation AUROC. The best radiomics-based XGBoost model achieved a test AUROC of 0.810, clearly outperforming the best clinical-only model (test AUROC: 0.457). Subclassification between colorectal cancer and adenoma showed lower accuracy (test AUROC: 0.674). Our findings establish proof-of-concept that liver-derived radiomics from routine abdominal CT can predict colorectal neoplasia. Beyond offering a pragmatic, widely accessible adjunct to CRC screening, this approach highlights the gut-liver axis as a novel biomarker source for opportunistic screening and sparks new mechanistic hypotheses for future translational research.
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