Predictive value of T2-FLAIR signal suppression rate for 1p/19q molecular features in lower-grade gliomas

Hanwei WANG; Linlan ZENG; Mimi ZHAO; Xuan LI; Qisheng RAN; Jing TIAN; Jie SUN; Lizhao CHEN; Shunan WANG

doi:10.16016/j.2097-0927.202404029

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Predictive value of T2-FLAIR signal suppression rate for 1p/19q molecular features in lower-grade gliomas

Clinical Medicine | 更新时间：2026-01-09

- Predictive value of T2-FLAIR signal suppression rate for 1p/19q molecular features in lower-grade gliomas
- Journal of Army Medical University Vol. 46, Issue 18, Pages: 2121-2129(2024)
- 作者机构：
  
  1.400042 重庆，陆军特色医学中心：放射科，重庆市影像医学与核医学临床研究中心
  2.400042 重庆，陆军特色医学中心：神经外科
- 作者简介：
- 基金信息：
  
  the Joint Medical Research Project of Chongqing Science and Technology Commission and Chongqing Health Commission(2023MSXM009);the Project of Science and Technology Plan of Chongqing Clinical Research Centre of Imaging and Nuclear Medicine(CSTC2015YFPT-gcjsyjzx0175)
- DOI：10.16016/j.2097-0927.202404029
  CLC： R195.4;R445.2;R730.264
- Received：09 April 2024，
  
  Revised：2024-05-27，
  
  Published：30 September 2024
- 稿件说明：
移动端阅览
Hanwei WANG, Linlan ZENG, Mimi ZHAO, et al. Predictive value of T2-FLAIR signal suppression rate for 1p/19q molecular features in lower-grade gliomas[J]. Journal of Army Medical University, 2024, 46(18): 2121-2129.
DOI：

Hanwei WANG, Linlan ZENG, Mimi ZHAO, et al. Predictive value of T2-FLAIR signal suppression rate for 1p/19q molecular features in lower-grade gliomas[J]. Journal of Army Medical University, 2024, 46(18): 2121-2129. DOI： 10.16016/j.2097-0927.202404029.

摘要

目的

探讨T2-液体衰减反转恢复(fluid attenuated inversion recovery，FLAIR)信号抑制率对较低级别胶质瘤(lower-grade gliomas，LGG)患者1号染色体短臂和19号染色体长臂(1p/19q)分子特征的预测价值，基于磁共振成像(magnetic resonance imaging，MRI)肿瘤影像特征以及T2-FLAIR信号抑制率建立预测模型并验证效能。

方法

回顾性分析陆军特色医学中心2017-2021年术后病理证实为WHO 2~3级的幕上LGG患者临床以及影像资料。根据术后分子病理检测结果将患者分为1p/19q联合缺失(1p/19q-codeleted，1p/19q-Codel) 组与1p/19q未联合缺失(1p/19q-noncodeleted，1p/19q-Noncodel) 组。由2名神经影像医师分别在盲法情况下评价MRI肿瘤影像特征，并采用热点法在肿瘤区以及对侧正常半卵圆中心分别放置5个圆形感兴趣区域，计算T2-FLAIR信号抑制率。分析2组患者临床、MRI肿瘤影像特征及T2-FLAIR信号抑制率的差异。利用单因素及多因素Logistic回归分析筛选独立预测因素，建立预测模型并绘制列线图，采用受试者操作特征(receiver operating characteristic

ROC)曲线、校准图以及Hosmer-Lemeshow检验评估模型效能，并通过Bootstrap法进行内部验证。

结果

共纳入146例幕上LGG患者，其中1p/19q-Codel组68例，1p/19q-Noncodel组78例。1p/19q-Noncodel组T2-FLAIR信号抑制率为0.43(0.28

0.62)，高于1p/19q-Codel组[0.29(0.24

0.35)，

0.001

]

。多因素Logistic回归分析显示，T2-FLAIR信号抑制率

0.374(

0.001)、皮质浸润(

=0.001)、钙化(

=0.004)为预测1p/19q状态的独立因素。其中，T2-FLAIR信号抑制率

0.374预测1p/19q-Noncodel的AUC值为0.720，敏感性为60.26%，特异性为83.82%。DeLong检验结果表明，T2-FLAIR信号抑制率

0.374在预测1p/19q分子分型的效能比T2-FLAIR错配征好，差异具有统计学意义(

0.001)。ROC曲线分析显示，T2-FLAIR信号抑制率

0.374联合皮质浸润和钙化建立的预测模型效能良好，AUC值为0.808，经Bo

otstrap法进行内部验证的AUC值为0.807。同时，该模型的校准度以及拟合度均良好。

结论

T2-FLAIR信号抑制率能够作为术前预测1p/19q-Noncodel型LGG的定量影像标志物。T2-FLAIR信号抑制率>0.374联合皮质浸润、钙化建立的预测模型可有效预测1p/19q分子特征。

Abstract

Objective

To evaluate the predictive value of T2-fluid attenuated inversion recovery (FLAIR) signal suppression rate for the short arm of chromosome 1 and long arm of chromosome 19 (1p/19q) molecular features in lower-grade gliomas (LGG)

and to construct and verify the predictive model based on magnetic resonance imaging (MRI) tumor features and T2-FLAIR signal suppression rate.

Methods

Clincal and imaging data of the patients with pathologically confirmed supratentorial LGG (WHO grade 2~3) in our medical center from 2017 to 2021 were collected and retrospectively analyzed. According to the results of postoperative molecular pathology

they were divided into 1p/19q-codeleted (1p/19q-Codel) and 1p/19q-noncodeleted (1p/19q-Noncodel) groups. MRI tumor features were blindly assessed by 2 neuroradiologists. Five circular regions of interest were respectively delineated in the tumor area and the normal-appearing white matter in contralateral semioval center using the hot-spot method in order to calculate the T2-FLAIR signal suppression rate. The differences of clinical features

MRI tumor features and T2-FLAIR signal suppression rate were analyzed between the 2 groups. Univariate and multivariate logistic regression analyses were used to screen independent predictors and constructa predictive model and nomogram. Receiver operating characteristic (ROC) curve

calibration curve and Hosmer-Lemeshow test were applied to assess the model performance

and the model was internally validated by bootstrap method.

Results

A total of 146 supratentorial LGG patients were enrolled

including 68 being assigned into the 1p/19q-Codel group and 78 into the 1p/19q-Noncodel group. The T2-FLAIR si

gnal suppression rate was 0.43 (0.28

0.62) in the 1p/19q-Noncodel group

which was significantly higher than that in the 1p/19q-Codel group [0.29 (0.24

0.35)

0.001

]

. Multivariate logistic regression analysis showed that T2-FLAIR signal suppression rate

0.374 (

0.001)

cortex infiltration (

=0.001) and calcification (

=0.004) were independent predictors for 1p/19q status. The AUC value of T2-FLAIR signal suppression rate

0.374 in predicting 1p/19q-Noncodel was 0.720

the sensitivity was 60.26% and the specificity was 83.82%. DeLong test indicated that T2-FLAIR signal suppression rate

0.374 was more effective than T2-FLAIR mismatch sign in predicting 1p/19q molecular features (

0.001). ROC curve analysis suggested that the predictive model established by T2-FLAIR signal suppression rate

0.374 combined with cortex infiltration and calcification had good performance

with an AUC value of 0.808

and the AUC value verified internally by bootstrap method was 0.807. At the same time

the calibration and goodness of fit of the model were good.

Conclusion

T2-FLAIR signal suppression rate can be used as a quantitative imaging marker to predict 1p/19q-Noncodel LGG. The predictive model with T2-FLAIR signal suppression rate >0.374 combined with cortex infiltration and calcification can effectively predict 1p/19q molecular features.

关键词

Keywords

references

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