Wu Shiman, Zhang Xi, Rui Wenting, Sheng Yaru, Yu Yang, Zhang Yong, Yao Zhenwei, Qiu Tianming, Ren Yan
Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China.
Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Eur Radiol. 2022 May;32(5):3187-3198. doi: 10.1007/s00330-021-08444-1. Epub 2022 Feb 8.
To construct a radiomics nomogram based on multiparametric MRI data for predicting isocitrate dehydrogenase 1 mutation (IDH +) and loss of nuclear alpha thalassemia/mental retardation syndrome X-linked expression (ATRX -) in patients with lower-grade gliomas (LrGG; World Health Organization [WHO] 2016 grades II and III).
A total of 111 LrGG patients (76 mutated IDH and 35 wild-type IDH) were enrolled, divided into a training set (n = 78) and a validation set (n = 33) for predicting IDH mutation. IDH + LrGG patients were further stratified into the ATRX - (n = 38) and ATRX + (n = 38) subtypes. A total of 250 radiomics features were extracted from the region of interest of each tumor, including that from T fluid-attenuated inversion recovery (T FLAIR), contrast-enhanced T WI, ASL-derived cerebral blood flow (CBF), DWI-derived ADC, and exponential ADC (eADC). A radiomics signature was selected using the Elastic Net regression model, and a radiomics nomogram was finally constructed using the age, gender information, and above features.
The radiomics nomogram identified LrGG patients for IDH mutation (C-index: training sets = 0.881, validation sets = 0.900) and ATRX loss (C-index: training sets = 0.863, validation sets = 0.840) with good calibration. Decision curve analysis further confirmed the clinical usefulness of the two nomograms for predicting IDH and ATRX status.
The nomogram incorporating age, gender, and the radiomics signature provided a clinically useful approach in noninvasively predicting IDH and ATRX mutation status for LrGG patients. The proposed method could facilitate MRI-based clinical decision-making for the LrGG patients.
• Non-invasive determination of IDH and ATRX gene status of LrGG patients can be obtained with a radiomics nomogram. • The proposed nomogram is constructed by radiomics signature selected from 250 radiomics features, combined with age and gender. • The proposed radiomics nomogram exhibited good calibration and discrimination for IDH and ATRX gene mutation stratification of LrGG patients in both training and validation sets.
基于多参数磁共振成像（MRI）数据构建一个列线图，用于预测低级别胶质瘤（LrGG；世界卫生组织[WHO]2016年II级和III级）患者的异柠檬酸脱氢酶1突变（IDH +）和核α地中海贫血/智力发育迟缓综合征X连锁表达缺失（ATRX -）。
共纳入111例LrGG患者（76例IDH突变型和35例IDH野生型），分为训练集（n = 78）和验证集（n = 33）用于预测IDH突变。IDH +的LrGG患者进一步分为ATRX -（n = 38）和ATRX +（n = 38）亚型。从每个肿瘤的感兴趣区域提取总共250个影像组学特征，包括来自T2液体衰减反转恢复序列（T2 FLAIR）、对比增强T1加权成像（T1WI）、动脉自旋标记（ASL）衍生的脑血流量（CBF）、扩散加权成像（DWI）衍生的表观扩散系数（ADC）和指数ADC（eADC）的特征。使用弹性网络回归模型选择影像组学特征，最终结合年龄、性别信息和上述特征构建影像组学列线图。
影像组学列线图对LrGG患者的IDH突变（C指数：训练集 = 0.881，验证集 = 0.900）和ATRX缺失（C指数：训练集 = 0.863，验证集 = 0.840）具有良好的校准度。决策曲线分析进一步证实了这两个列线图在预测IDH和ATRX状态方面的临床实用性。
结合年龄、性别和影像组学特征的列线图为非侵入性预测LrGG患者的IDH和ATRX突变状态提供了一种临床有用的方法。所提出的方法可以促进基于MRI的LrGG患者临床决策制定。
• 可通过影像组学列线图对LrGG患者的IDH和ATRX基因状态进行非侵入性测定。• 所提出的列线图由从250个影像组学特征中选择的影像组学特征结合年龄和性别构建而成。• 所提出的影像组学列线图在训练集和验证集对LrGG患者的IDH和ATRX基因突变分层均表现出良好的校准度和区分度。
