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介入肿瘤学项目在活体内肝细胞癌中的大型数据库 - 初步基于 CT 的放射组学分析(POLAR Liver 1.1)。

Project for interventional Oncology LArge-database in liveR Hepatocellular carcinoma - Preliminary CT-based radiomic analysis (POLAR Liver 1.1).

机构信息

Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia - U.O.C. Radiologia Diagnostica e Interventistica Generale, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

出版信息

Eur Rev Med Pharmacol Sci. 2022 Apr;26(8):2891-2899. doi: 10.26355/eurrev_202204_28620.

Abstract

OBJECTIVE

The objective of this study is to find a contrast-enhanced CT-radiomic signature to predict clinical incomplete response in patients affected by hepatocellular carcinoma who underwent locoregional treatments.

PATIENTS AND METHODS

190 patients affected by hepatocellular carcinoma treated using focal therapies (radiofrequency or microwave ablation) from September 2018 to October 2020 were retrospectively enrolled. Treatment response was evaluated on a per-target-nodule basis on the 6-months follow-up contrast-enhanced CT or MR imaging using the mRECIST criteria. Radiomics analysis was performed using an in-house developed open-source R library. Wilcoxon-Mann-Whitney test was applied for univariate analysis; features with a p-value lower than 0.05 were selected. Pearson correlation was applied to discard highly correlated features (cut-off=0.9). The remaining features were included in a logistic regression model and receiver operating characteristic curves; sensitivity, specificity, positive and negative predictive value were also computed. The model was validated performing 2000 bootstrap resampling.

RESULTS

56 treated lesions from 42 patients were selected. Treatment responses were: complete response for 26 lesions (46.4%), 18 partial responses (32.1%), 10 stable diseases (17.9%), 2 progression diseases (3.6%). Area-Under-Curve value was 0.667 (95% CI: 0.527-0.806); accuracy, sensitivity, specificity, positive and negative predictive values were respectively 0.66, 0.85, 0.50, 0.59 and 0.79.

CONCLUSIONS

This contrast-enhanced CT-based model can be helpful to early identify poor responder's hepatocellular carcinoma patients and personalize treatments.

摘要

目的

本研究旨在寻找一种增强 CT 放射组学特征,以预测接受局部区域治疗的肝细胞癌患者的临床不完全反应。

方法

回顾性纳入 2018 年 9 月至 2020 年 10 月接受局部治疗(射频或微波消融)的 190 例肝细胞癌患者。根据 mRECIST 标准,在 6 个月的随访增强 CT 或磁共振成像上对每个靶结节进行治疗反应评估。使用内部开发的开源 R 库进行放射组学分析。采用 Wilcoxon-Mann-Whitney 检验进行单变量分析;选择 p 值小于 0.05 的特征。应用 Pearson 相关系数剔除高度相关特征(截止值=0.9)。剩余特征被纳入逻辑回归模型和受试者工作特征曲线;同时还计算了敏感性、特异性、阳性预测值和阴性预测值。采用 2000 次 bootstrap 重采样对模型进行验证。

结果

共纳入 42 例患者的 56 个治疗病灶。治疗反应为:26 个病灶完全缓解(46.4%),18 个部分缓解(32.1%),10 个稳定疾病(17.9%),2 个进展疾病(3.6%)。曲线下面积为 0.667(95%CI:0.527-0.806);准确性、敏感性、特异性、阳性预测值和阴性预测值分别为 0.66、0.85、0.50、0.59 和 0.79。

结论

该基于增强 CT 的模型有助于早期识别治疗反应不良的肝细胞癌患者,并实现个体化治疗。

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