Prediction of outcome using pretreatment 18F-FDG PET/CT and MRI radiomics in locally advanced cervical cancer treated with chemoradiotherapy

被引:188
|
作者
Lucia, Francois [1 ,2 ]
Visvikis, Dimitris [3 ]
Desseroit, Marie-Charlotte [3 ]
Miranda, Omar [1 ]
Malhaire, Jean-Pierre [1 ]
Robin, Philippe [4 ]
Pradier, Olivier [1 ,3 ]
Hatt, Mathieu [3 ]
Schick, Ulrike [1 ,3 ]
机构
[1] Univ Hosp, Radiat Oncol Dept, Brest, France
[2] CHRU Morvan, Serv Radiotherapie, 2 Ave Foch, F-29609 Brest, France
[3] Univ Brest, INSERM, UMR 1101, LaTIM,UBL,UBO,ISBAM, Brest, France
[4] Univ Hosp, Nucl Med Dept, Brest, France
关键词
Chemoradiotherapy; Cervical cancer; Radiomics; Prediction; FDGPET; MRI; CLINICAL TARGET VOLUME; TEXTURAL FEATURES; HETEROGENEITY; RADIOTHERAPY; PARAMETERS; SURVIVAL; IMAGES; CHEMORADIATION; VARIABILITY; DELINEATION;
D O I
10.1007/s00259-017-3898-7
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose The aim of this study is to determine if radiomics features from (18)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-18-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 (TM) 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(GLRLM) in PET and Entropy(GLCM) 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 similar to 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.
引用
收藏
页码:768 / 786
页数:19
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