低级别胶质瘤的 MRI 特征与基于 mRNA 的亚型的放射组基因组相关性。
Radiogenomics correlation between MR imaging features and mRNA-based subtypes in lower-grade glioma.
机构信息
Department of Medical Imaging, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou City, 510623, PR China.
出版信息
BMC Neurol. 2020 Jun 29;20(1):259. doi: 10.1186/s12883-020-01838-6.
BACKGROUND
To investigate associations between lower-grade glioma (LGG) mRNA-based subtypes (R1-R4) and MR features.
METHODS
mRNA-based subtyping was obtained from the LGG dataset in The Cancer Genome Atlas (TCGA). We identified matching patients (n = 145) in The Cancer Imaging Archive (TCIA) who underwent MR imaging. The associations between mRNA-based subtypes and MR features were assessed.
RESULTS
In the TCGA-LGG dataset, patients with the R2 subtype had the shortest median OS months (P < 0.05). The time-dependent ROC for the R2 subtype was 0.78 for survival at 12 months, 0.76 for survival at 24 months, and 0.76 for survival at 36 months. In the TCIA-LGG dataset, 41 (23.7%) R1 subtype, 40 (23.1%) R2 subtype, 19 (11.0%) R3 subtype and 45 (26.0%) R4 subtype cases were identified. Multivariate analysis revealed that enhancing margin (ill-defined, OR: 9.985; P = 0.003) and T1 + C/T2 mismatch (yes, OR: 0.091; P = 0.023) were associated with the R1 subtype (AUC: 0.708). The average accuracy of the ten-fold cross validation was 71%. Proportion of contrast-enhanced (CE) tumour (> 5%, OR: 14.733; P < 0.001) and necrosis/cystic changes (yes, OR: 0.252; P = 0.009) were associated with the R2 subtype (AUC: 0.832). The average accuracy of the ten-fold cross validation was 82%. Haemorrhage (yes, OR: 8.55; P < 0.001) was positively associated with the R3 subtype (AUC: 0.689). The average accuracy of the ten-fold cross validation was 87%. Proportion of CE tumour (> 5%, OR: 0.14; P < 0.001) was negatively associated with the R4 subtype (AUC: 0.672). The average accuracy of the ten-fold cross validation was 71%. For the prediction of the R2 subtype, the nomogram showed good discrimination and calibration. Decision curve analysis demonstrated that prediction with the R2 model was clinically useful.
CONCLUSIONS
Patients with the R2 subtype had the worst prognosis. We demonstrated that MRI features can identify distinct LGG mRNA-based molecular subtypes.
背景
本研究旨在探讨低级别胶质瘤（LGG）mRNA 亚型（R1-R4）与磁共振（MR）特征之间的关联。
方法
从癌症基因组图谱（TCGA）的 LGG 数据集获取基于 mRNA 的分型。我们在癌症成像档案（TCIA）中匹配了进行 MR 成像的患者（n=145）。评估基于 mRNA 的亚型与 MR 特征之间的关联。
结果
在 TCGA-LGG 数据集，R2 亚型患者的中位 OS 月数最短（P<0.05）。R2 亚型的时间依赖性 ROC 曲线在 12 个月时的生存率为 0.78，在 24 个月时的生存率为 0.76，在 36 个月时的生存率为 0.76。在 TCIA-LGG 数据集中，鉴定出 41 例 R1 亚型（23.7%）、40 例 R2 亚型（23.1%）、19 例 R3 亚型（11.0%）和 45 例 R4 亚型（26.0%）。多变量分析显示，增强边界（不清晰，OR：9.985；P=0.003）和 T1+C/T2 不匹配（是，OR：0.091；P=0.023）与 R1 亚型相关（AUC：0.708）。十折交叉验证的平均准确率为 71%。增强肿瘤的比例（>5%，OR：14.733；P<0.001）和坏死/囊性改变（是，OR：0.252；P=0.009）与 R2 亚型相关（AUC：0.832）。十折交叉验证的平均准确率为 82%。出血（是，OR：8.55；P<0.001）与 R3 亚型呈正相关（AUC：0.689）。十折交叉验证的平均准确率为 87%。增强肿瘤的比例（>5%，OR：0.14；P<0.001）与 R4 亚型呈负相关（AUC：0.672）。十折交叉验证的平均准确率为 71%。对于 R2 亚型的预测，列线图显示出良好的区分度和校准度。决策曲线分析表明，R2 模型的预测具有临床意义。
结论
R2 亚型患者的预后最差。本研究表明，MR 特征可识别不同的 LGG mRNA 分子亚型。
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