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基于 MRI 的放射组学特征用于宫颈癌的术前预后预测。

MRI-based radiomic signatures for pretreatment prognostication in cervical cancer.

机构信息

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway.

Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.

出版信息

Cancer Med. 2023 Oct;12(20):20251-20265. doi: 10.1002/cam4.6526. Epub 2023 Oct 16.

Abstract

BACKGROUND

Accurate pretherapeutic prognostication is important for tailoring treatment in cervical cancer (CC).

PURPOSE

To investigate whether pretreatment MRI-based radiomic signatures predict disease-specific survival (DSS) in CC.

STUDY TYPE

Retrospective.

POPULATION

CC patients (n = 133) allocated into training (n  = 89)/validation (n  = 44) cohorts.

FIELD STRENGTH/SEQUENCE: T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) at 1.5T or 3.0T.

ASSESSMENT

Radiomic features from segmented tumors were extracted from T2WI and DWI (high b-value DWI and apparent diffusion coefficient (ADC) maps).

STATISTICAL TESTS

Radiomic signatures for prediction of DSS from T2WI (T2 ) and T2WI with DWI (T2 + DWI ) were constructed by least absolute shrinkage and selection operator (LASSO) Cox regression. Area under time-dependent receiver operating characteristics curves (AUC) were used to evaluate and compare the prognostic performance of the radiomic signatures, MRI-derived maximum tumor size ≤/> 4 cm (MAX ), and 2018 International Federation of Gynecology and Obstetrics (FIGO) stage (I-II/III-IV). Survival was analyzed using Cox model estimating hazard ratios (HR) and Kaplan-Meier method with log-rank tests.

RESULTS

The radiomic signatures T2 and T2 + DWI yielded AUC /AUC of 0.80/0.62 and 0.81/0.75, respectively, for predicting 5-year DSS. Both signatures yielded better or equal prognostic performance to that of MAX (AUC /AUC : 0.69/0.65) and FIGO (AUC /AUC : 0.77/0.64) and were significant predictors of DSS after adjusting for FIGO (HR /HR for T2 : 4.0/2.5 and T2 + DWI : 4.8/2.1). Adding T2 and T2 + DWI to FIGO significantly improved DSS prediction compared to FIGO alone in cohort (AUC 0.86 and 0.88 vs. 0.77), and FIGO with T2 + DWI tended to the same in cohort (AUC 0.75 vs. 0.64, p = 0.07). High radiomic score for T2 + DWI was significantly associated with reduced DSS in both cohorts.

DATA CONCLUSION

Radiomic signatures from T2WI and T2WI with DWI may provide added value for pretreatment risk assessment and for guiding tailored treatment strategies in CC.

摘要

背景

准确的术前预后预测对于宫颈癌(CC)的治疗方案制定非常重要。

目的

探讨基于治疗前 MRI 的放射组学特征是否可预测 CC 的疾病特异性生存(DSS)。

研究类型

回顾性研究。

人群

CC 患者(n=133)分为训练(n=89)/验证(n=44)队列。

场强/序列:1.5T 或 3.0T 的 T2 加权成像(T2WI)和弥散加权成像(DWI)。

评估

从 T2WI 和 DWI(高 b 值 DWI 和表观扩散系数(ADC)图)中提取分段肿瘤的放射组学特征。

统计检验

使用最小绝对收缩和选择算子(LASSO)Cox 回归构建 T2WI(T2)和 T2WI 联合 DWI(T2+DWI)预测 DSS 的放射组学特征。使用时间依赖性接收器工作特征曲线(ROC)下面积(AUC)评估并比较放射组学特征、MRI 最大肿瘤直径(MAX)≤/>4cm、2018 年国际妇产科联合会(FIGO)分期(I-II/III-IV)的预后性能。使用 Cox 模型估计风险比(HR)和 Kaplan-Meier 方法进行生存分析,并进行对数秩检验。

结果

T2 和 T2+DWI 预测 5 年 DSS 的 AUC/AUC 分别为 0.80/0.62 和 0.81/0.75。这两个特征的预后性能均优于或等于 MAX(AUC/AUC:0.69/0.65)和 FIGO(AUC/AUC:0.77/0.64),且在调整 FIGO 后是 DSS 的显著预测因子(T2:HR/HR 为 4.0/2.5,T2+DWI:4.8/2.1)。与 FIGO 相比,T2 和 T2+DWI 联合 FIGO 可显著提高两个队列的 DSS 预测能力(AUC 0.86 和 0.88 与 0.77),而 T2+DWI 联合 FIGO 的 AUC 与 FIGO 相近(AUC 0.75 与 0.64,p=0.07)。在两个队列中,T2+DWI 的高放射组学评分均与 DSS 降低显著相关。

数据结论

T2WI 和 T2WI 联合 DWI 的放射组学特征可为宫颈癌的术前风险评估和指导个体化治疗策略提供附加价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee8d/10652318/925a0d87790a/CAM4-12-20251-g002.jpg

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