Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, Switzerland.
Department of Nuclear Medicine and Molecular Imaging, Nancy University Hospital, Nancy, France.
PLoS One. 2018 Jun 28;13(6):e0199379. doi: 10.1371/journal.pone.0199379. eCollection 2018.
Aim was to develop a full automatic clustering approach of the time-activity curves (TAC) from dynamic 18F-FET PET and evaluate its association with IDH1 mutation status and survival in patients with gliomas.
Thirty-seven patients (mean age: 45±13 y) with newly diagnosed gliomas and dynamic 18F-FET PET before any histopathologic investigation or treatment were retrospectively included. Each dynamic 18F-FET PET was realigned to the first image and spatially normalized in the Montreal Neurological Institute template. A tumor mask was semi-automatically generated from Z-score maps. Each brain tumor voxel was clustered in one of the 3 following centroids using dynamic time warping and k-means clustering (centroid #1: slowly increasing slope; centroid #2: rapidly increasing followed by slowly decreasing slope; and centroid #3: rapidly increasing followed by rapidly decreasing slope). The percentage of each dynamic 18F-FET TAC within tumors and other conventional 18F-FET PET parameters (maximum and mean tumor-to-brain ratios [TBRmax and TBRmean], time-to-peak [TTP] and slope) was compared between wild-type and IDH1 mutant tumors. Their prognostic value was assessed in terms of progression free-survival (PFS) and overall survival (OS) by Kaplan-Meier estimates.
Twenty patients were IDH1 wild-type and 17 IDH1 mutant. Higher percentage of centroid #1 and centroid #3 within tumors were positively (P = 0.016) and negatively (P = 0.01) correlated with IDH1 mutated status. Also, TBRmax, TBRmean, TTP, and slope discriminated significantly between tumors with and without IDH1 mutation (P range 0.01 to 0.04). Progression occurred in 22 patients (59%) at a median of 13.1 months (7.6-37.6 months) and 13 patients (35%) died from tumor progression. Patients with a percentage of centroid #1 > 90% had a longer survival compared with those with a percentage of centroid #1 < 90% (P = 0.003 for PFS and P = 0.028 for OS). This remained significant after stratification on IDH1 mutation status (P = 0.029 for PFS and P = 0.034 for OS). Compared to other conventional 18F-FET PET parameters, TTP and slope were associated with PFS and OS (P range 0.009 to 0.04).
Based on dynamic 18F-FET PET acquisition, we developed a full automatic clustering approach of TAC which appears to be a valuable noninvasive diagnostic and prognostic marker in patients with gliomas.
目的是开发一种从动态 18F-FET PET 中提取时间-活性曲线（TAC）的全自动聚类方法，并评估其与 IDH1 突变状态和胶质瘤患者生存的关系。
回顾性纳入 37 名新诊断为胶质瘤的患者，这些患者在进行任何组织病理学检查或治疗前均进行了动态 18F-FET PET 检查。对每个动态 18F-FET PET 进行重新定位到第一个图像，并在蒙特利尔神经学研究所模板中进行空间归一化。使用 Z 分数图半自动生成肿瘤掩模。使用动态时间 warping 和 k-means 聚类（质心#1：斜率缓慢增加；质心#2：快速增加后缓慢减少斜率；质心#3：快速增加后快速减少斜率）将每个脑肿瘤体素聚类到以下 3 个质心之一。比较野生型和 IDH1 突变型肿瘤内的每个动态 18F-FET TAC 百分比以及其他常规 18F-FET PET 参数（最大和平均肿瘤与脑比值[TBRmax 和 TBRmean]、达峰时间[TTP]和斜率）。通过 Kaplan-Meier 估计评估其在无进展生存期（PFS）和总生存期（OS）方面的预后价值。
20 名患者 IDH1 为野生型，17 名患者 IDH1 为突变型。肿瘤内质心#1 和质心#3 的百分比越高，与 IDH1 突变状态呈正相关（P=0.016）和负相关（P=0.01）。此外，TBRmax、TBRmean、TTP 和斜率在有无 IDH1 突变的肿瘤之间有显著差异（P 值范围为 0.01 至 0.04）。22 名患者（59%）出现进展，中位时间为 13.1 个月（7.6-37.6 个月），13 名患者（35%）死于肿瘤进展。与质心#1 百分比<90%的患者相比，质心#1 百分比>90%的患者的生存时间更长（PFS 为 P=0.003，OS 为 P=0.028）。在分层 IDH1 突变状态后，这仍然具有显著性（PFS 为 P=0.029，OS 为 P=0.034）。与其他常规 18F-FET PET 参数相比，TTP 和斜率与 PFS 和 OS 相关（P 值范围为 0.009 至 0.04）。
基于动态 18F-FET PET 采集，我们开发了一种全自动 TAC 聚类方法，该方法似乎是一种有价值的胶质瘤患者非侵入性诊断和预后标志物。
