医学
宫颈癌
阶段(地层学)
单变量分析
多元分析
磁共振成像
近距离放射治疗
放化疗
肿瘤科
无进展生存期
顺铂
放射治疗
子宫颈
内科学
化疗
放射科
癌症
核医学
生物
古生物学
作者
Concetta Laliscia,Angiolo Gadducci,Roberto Mattioni,Francesca Orlandi,Sabina Giusti,Amelia Barcellini,Michela Gabelloni,Riccardo Morganti,Emanuele Neri,Fabiola Paiar
出处
期刊:Tumori Journal
[SAGE Publishing]
日期:2021-07-08
卷期号:108 (4): 376-385
被引量:14
标识
DOI:10.1177/03008916211014274
摘要
To assess prognostic factors by analyzing clinical and radiomic data of patients with locally advanced cervical cancer (LACC) treated with definitive concurrent cisplatin-based chemoradiotherapy (CCRT) using magnetic resonance imaging (MRI).We analyzed radiomic features from MRI in 60 women with FIGO (International Federation of Gynecology and Obstetrics) stage IB2-IVA cervical cancer who underwent definitive CCRT 45-50.4 Gy (in 25-28 fractions). Thirty-nine (65.0%) received EBRT sequential boost (4-20 Gy) on primary tumor site and 56 (93.3%) received high-dose-rate brachytherapy boost (6-28 Gy) (daily fractions of 5-7 Gy). Moreover, 71.7% of patients received dose-dense neoadjuvant chemotherapy for 6 cycles. The gross tumor volume was defined on T2-weighted sequences and 29 features were extracted from each MRI performed before and after CCRT, using dedicated software, and their prognostic value was correlated with clinical information.In univariate analysis, age ⩾60 years and FIGO stage IB2-IIB had significantly better progression-free survival (PFS) (p = 0.022 and p = 0.009, respectively). There was a trend for significance for worse overall survival (OS) in patients with positive nodes (p = 0.062). In multivariate analysis, only age ⩾60 years and FIGO stage IB2-IIB reached significantly better PFS (p = 0.020 and p = 0.053, respectively). In radiomic dataset, in multivariate analysis, pregray level p75 was significantly associated with PFS (p = 0.047), pre-D3D value with OS (p = 0.049), and preinformation measure of correlation value with local control (p = 0.031).The combination of clinical and radiomics features can provide information to predict behavior and prognosis of LACC and to make more accurate treatment decisions.
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