使用预处理 F-FDG PET/CT 和 MRI 放射组学预测接受放化疗的局部晚期宫颈癌的结局。
Prediction of outcome using pretreatment F-FDG PET/CT and MRI radiomics in locally advanced cervical cancer treated with chemoradiotherapy.
机构信息
Radiation Oncology Department, University Hospital, Brest, France.
Service de Radiothérapie, CHRU Morvan, 2 Avenue Foch, 29609, Cedex, Brest, France.
出版信息
Eur J Nucl Med Mol Imaging. 2018 May;45(5):768-786. doi: 10.1007/s00259-017-3898-7. Epub 2017 Dec 9.
PURPOSE
The aim of this study is to determine if radiomics features from fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) images could contribute to prognoses in cervical cancer.
METHODS
One hundred and two patients (69 for training and 33 for testing) with locally advanced cervical cancer (LACC) receiving chemoradiotherapy (CRT) from 08/2010 to 12/2016 were enrolled in this study. F-FDG PET/CT and MRI examination [T1, T2, T1C, diffusion-weighted imaging (DWI)] were performed for each patient before CRT. Primary tumor volumes were delineated with the fuzzy locally adaptive Bayesian algorithm in the PET images and with 3D Slicer™ in the MRI images. Radiomics features (intensity, shape, and texture) were extracted and their prognostic value was compared with clinical parameters for recurrence-free and locoregional control.
RESULTS
In the training cohort, median follow-up was 3.0 years (range, 0.43-6.56 years) and relapse occurred in 36% of patients. In univariate analysis, FIGO stage (I-II vs. III-IV) and metabolic response (complete vs. non-complete) were probably associated with outcome without reaching statistical significance, contrary to several radiomics features from both PET and MRI sequences. Multivariate analysis in training test identified Grey Level Non Uniformity in PET and Entropy in ADC maps from DWI MRI as independent prognostic factors. These had significantly higher prognostic power than clinical parameters, as evaluated in the testing cohort with accuracy of 94% for predicting recurrence and 100% for predicting lack of loco-regional control (versus ~50-60% for clinical parameters).
CONCLUSIONS
In LACC treated with CRT, radiomics features such as EntropyGLCM and GLNUGLRLM from functional imaging DWI-MRI and PET, respectively, are independent predictors of recurrence and loco-regional control with significantly higher prognostic power than usual clinical parameters. Further research is warranted for their validation, which may justify more aggressive treatment in patients identified with high probability of recurrence.
目的
本研究旨在确定氟代脱氧葡萄糖（FDG）正电子发射断层扫描/计算机断层扫描（PET/CT）和磁共振成像（MRI）图像的放射组学特征是否有助于宫颈癌的预后判断。
方法
本研究纳入了 2010 年 8 月至 2016 年 12 月期间接受放化疗（CRT）的 102 例局部晚期宫颈癌（LACC）患者（训练组 69 例，测试组 33 例）。每位患者在 CRT 前均行 F-FDG PET/CT 和 MRI 检查（T1、T2、T1C、弥散加权成像（DWI））。在 PET 图像中，采用模糊局部自适应贝叶斯算法，在 MRI 图像中，采用 3D Slicer 软件勾画原发肿瘤体积。提取放射组学特征（强度、形状和纹理），并与临床参数比较，以评估其对无复发生存和局部区域控制的预测价值。
结果
在训练队列中，中位随访时间为 3.0 年（范围 0.43-6.56 年），36%的患者发生复发。单因素分析显示，FIGO 分期（I-II 期 vs. III-IV 期）和代谢反应（完全缓解 vs. 非完全缓解）可能与预后相关，但无统计学意义，而 PET 和 MRI 序列的多个放射组学特征则相反。多因素分析在训练组中确定了 PET 中 Grey Level Non Uniformity 和 DWI-MRI 中 ADC 图中的 Entropy 为独立的预后因素。在测试组中，这些特征的预测准确性为 94%预测复发和 100%预测局部区域控制，而临床参数的预测准确性约为 50-60%。
结论
在接受 CRT 治疗的 LACC 患者中，来自功能成像 DWI-MRI 和 PET 的 EntropyGLCM 和 GLNUGLRLM 等放射组学特征是复发和局部区域控制的独立预测因素，其预测效能明显高于常规临床参数。需要进一步研究以验证其有效性，这可能为识别高复发风险患者提供更积极的治疗策略。
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