Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA.
J Neurooncol. 2020 Sep;149(2):325-335. doi: 10.1007/s11060-020-03611-8. Epub 2020 Sep 9.
The prognosis of lower grade glioma (LGG) patients depends (in large part) on both isocitrate dehydrogenase (IDH) gene mutation and chromosome 1p/19q codeletion status. IDH-mutant LGG without 1p/19q codeletion (IDHmut-Noncodel) often exhibit a unique imaging appearance that includes high apparent diffusion coefficient (ADC) values not observed in other subtypes. The purpose of this study was to develop an ADC analysis-based approach that can automatically identify IDHmut-Noncodel LGG.
Whole-tumor ADC metrics, including fractional tumor volume with ADC > 1.5 × 10mm/s (V), were used to identify IDHmut-Noncodel LGG in a cohort of N = 134 patients. Optimal threshold values determined in this dataset were then validated using an external dataset containing N = 93 cases collected from The Cancer Imaging Archive. Classifications were also compared with radiologist-identified T2-FLAIR mismatch sign and evaluated concurrently to identify added value from a combined approach.
V classified IDHmut-Noncodel LGG in the internal cohort with an area under the curve (AUC) of 0.80. An optimal threshold value of 0.35 led to sensitivity/specificity = 0.57/0.93. Classification performance was similar in the validation cohort, with V ≥ 0.35 achieving sensitivity/specificity = 0.57/0.91 (AUC = 0.81). Across both groups, 37 cases exhibited positive T2-FLAIR mismatch sign-all of which were IDHmut-Noncodel. Of these, 32/37 (86%) also exhibited V ≥ 0.35, as did 23 additional IDHmut-Noncodel cases which were negative for T2-FLAIR mismatch sign.
Tumor subregions with high ADC were a robust indicator of IDHmut-Noncodel LGG, with V achieving > 90% classification specificity in both internal and validation cohorts. V exhibited strong concordance with the T2-FLAIR mismatch sign and the combination of both parameters improved sensitivity in detecting IDHmut-Noncodel LGG.
低级别胶质瘤 (LGG) 患者的预后在很大程度上取决于异柠檬酸脱氢酶 (IDH) 基因突变和染色体 1p/19q 联合缺失状态。无 1p/19q 联合缺失的 IDH 突变型 LGG (IDHmut-Noncodel) 常表现出独特的影像学表现，包括在其他亚型中观察不到的高表观扩散系数 (ADC) 值。本研究旨在开发一种基于 ADC 分析的方法，能够自动识别 IDHmut-Noncodel LGG。
使用全肿瘤 ADC 指标，包括 ADC 值>1.5×10mm/s 的肿瘤体积分数 (V)，对 N=134 例患者的队列进行 IDHmut-Noncodel LGG 的识别。在该数据集确定的最佳阈值值随后在包含从癌症成像档案中收集的 N=93 例的外部数据集中进行验证。分类还与放射科医生识别的 T2-FLAIR 不匹配征进行了比较，并同时评估以确定联合方法的附加价值。
V 在内部队列中对 IDHmut-Noncodel LGG 的分类，曲线下面积 (AUC) 为 0.80。最佳阈值值为 0.35，灵敏度/特异性=0.57/0.93。验证队列中的分类性能相似，V≥0.35 的灵敏度/特异性=0.57/0.91 (AUC=0.81)。在两组中，有 37 例表现出阳性 T2-FLAIR 不匹配征-均为 IDHmut-Noncodel。其中 32/37 (86%) 也表现出 V≥0.35，而 23 例 IDHmut-Noncodel 病例 T2-FLAIR 不匹配征阴性也表现出 V≥0.35。
高 ADC 的肿瘤亚区是 IDHmut-Noncodel LGG 的一个可靠指标，V 在内部和验证队列中的分类特异性均超过 90%。V 与 T2-FLAIR 不匹配征具有很强的一致性，两者参数的结合提高了检测 IDHmut-Noncodel LGG 的灵敏度。
