Application of CT-based radiomics in predicting portal pressure and patient outcome in portal hypertension
Application of CT-based radiomics in predicting portal pressure and patient outcome in portal hypertension
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DOI：
10.1016/j.ejrad.2020.108927
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发表时间：
2020-05-01
影响因子：
3.3
通讯作者：
Chen, Shiyao
中科院分区：
文献类型：
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作者：
Tseng, Yujen;Ma, Lili;Chen, Shiyao
目的：门静脉压力（PVP）的测定具有重要的临床意义，尤其是对门静脉高压症患者。然而，侵入性和相关并发症限制了其应用。本研究的目的是提出一种基于CT提取的放射组学features.Methods：放射组学PVP（rPVP）模型的基础上肝，脾和组合功能的PVP值的无创预测模型建立在一个实验队列的169名受试者。从每个ROI中提取放射组学特征，并通过LASSO回归进行缩减，以获得最佳预测公式。使用62例接受胃食管静脉曲张（GOV）治疗的患者的验证队列来确认rPVP在预测静脉曲张复发方面的效用。结果：根据放射组学特征，推导出三个独立的PVP预测公式。rPVP与食管静脉曲张内镜治疗的反应显著相关。其中，包含肝脏和脾脏特征的模型对食管静脉曲张复发的预测性最高，最佳截断值为29.102 mmHg（AUC 0.866）。Kaplan Meier分析进一步证实了不同rPVP values.Conclusion患者之间的差异：PVP值可以准确预测的非侵入性，CT衍生的放射组学模型。rPVP可作为预测继发于门静脉高压的GOV治疗结果的无创和精确参考。
Purpose: Portal venous pressure (PVP) measurement is of clinical significance, especially in patients with portal hypertension. However, the invasive nature and associated complications limits its application. The aim of the study is to propose a noninvasive predictive model of PVP values based on CT-extracted radiomic features.Methods: Radiomics PVP (rPVP) models based on liver, spleen and combined features were established on an experimental cohort of 169 subjects. Radiomics features were extracted from each ROI and reduced via the LASSO regression to achieve an optimal predictive formula. A validation cohort of 62 patients treated for gastroesophageal varices (GOV) was used to confirm the utility of rPVP in predicting variceal recurrence. The association between rPVP and response to treatment was observed.Results: Three separate predictive formula for PVP were derived from radiomics features. rPVP was significantly correlated to patient response to endoscopic treatment for GOV. Among which, the model containing both liver and spleen features has the highest predictability of variceal recurrence, with an optimal cut-off value at 29.102 mmHg (AUC 0.866). A Kaplan Meier analysis further confirmed the difference between patients with varying rPVP values.Conclusion: PVP values can be accurately predicted by a non-invasive, CT derived radiomics model. rPVP serves as a non-invasive and precise reference for predicting treatment outcome for GOV secondary to portal hypertension.