异柠檬酸脱氢酶
胶质瘤
有效扩散系数
医学
核医学
磁共振弥散成像
百分位
体素
IDH1
体内磁共振波谱
曲线下面积
磁共振成像
放射科
内科学
突变
核磁共振
生物
数学
遗传学
统计
癌症研究
物理
基因
酶
作者
Xiaorui Su,Xibiao Yang,Huaiqiang Sun,Yan‐Hui Liu,Ni Chen,Shuang Li,Zongyao Huang,Hanbing Shao,Simin Zhang,Qiyong Gong,Qiang Yue
摘要
Background Preoperative identification of isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status could help clinicians select the optimal therapy in patients with diffuse glioma. Although, the value of multimodal intersection was underutilized. Purpose To evaluate the value of quantitative MRI biomarkers for the identification of IDH mutation and 1p/19q codeletion in adult patients with diffuse glioma. Study Type Retrospective. Population Two hundred sixteen adult diffuse gliomas with known genetic test results, divided into training (N = 130), test (N = 43), and validation (N = 43) groups. Sequence/Field Strength Diffusion/perfusion‐weighted‐imaging sequences and multivoxel MR spectroscopy (MRS), all 3.0 T using three different scanners. Assessment The apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) of the core tumor were calculated to identify IDH‐mutant and 1p/19q‐codeleted statuses and to determine cut‐off values. ADC models were built based on the 30th percentile and lower, CBV models were built based on the 75th centile and higher (both in five centile steps). The optimal tumor region was defined and the metabolite concentrations of MRS voxels that overlapped with the ADC/CBV optimal region were calculated and added to the best‐performing diagnostic models. Statistical Tests DeLong's test, diagnostic test, and decision curve analysis were performed. A P value <0.05 was considered to be statistically significant. Results Almost all ADC models achieved good performance in identifying IDH mutation status, among which ADC_15th was the most valuable parameter (threshold = 1.186; Youden index = 0.734; AUC_train = 0.896). The differential power of CBV histogram metrics for predicting 1p/19q codeletion outperformed ADC histogram metrics, and the CBV_80th‐related model performed best (threshold = 1.435; Youden index = 0.458; AUC_train = 0.724). The AUCs of ADC_15th and CBV_80th models in the validation set were 0.857 and 0.733. These models tended to improve after incorporation of N‐acetylaspartate/total_creatine and glutamate‐plus‐glutamine/total_creatine, respectively. Data Conclusion The intersection of ADC‐, CBV‐based histogram and MRS provide a reliable paradigm for identifying the key molecular markers in adult diffuse gliomas. Evidence Level 3 Technical Efficacy Stage 3
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