Qian Jing, Pafundi Deanna H, Breen William G, Brown Paul D, Hunt Christopher H, Jacobson Mark S, Johnson Derek R, Kaufmann Timothy J, Kemp Bradley J, Kizilbash Sani H, Lowe Val J, Ruff Michael W, Sarkaria Jann N, Uhm Joon H, Zakhary Mark J, Seaberg Maasa H, Wan Chan Tseung Hok Seum, Yan Elizabeth S, Zhang Yan, Laack Nadia N, Brinkmann Debra H
Department of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL, United States.
Front Oncol. 2025 Aug 13;15:1623313. doi: 10.3389/fonc.2025.1623313. eCollection 2025.
BACKGROUND/OBJECTIVES: F-DOPA is an amino acid radiotracer with high uptake in glioblastoma and low uptake in normal brain. Patients underwent pre-radiation and post-radiation F-DOPA PET scans on a prospective clinical trial. This analysis investigates quantitative image features correlated with prognosis and treatment response to identify patients who benefit the most from dose-escalated therapy. METHODS: Quantitative image features from F-DOPA PET scans of 58 glioblastoma patients were extracted from the high uptake region (TBR>2.0) in both pre-RT and early post-RT follow-up PET images, which were then refined using Pearson pair correlation. To explore the possibility to identify patients who benefit the most from dose-escalated therapy, pre-irradiation features were identified with univariate Cox regression analysis. Classifications with simple threshold or with Decision Tree models were carried out to categorize patients into distinct survival groups. Additionally, the features with notable changes before and after RT were identified and the temporal patterns of these changes between the survival groups were compared. Multivariates cox analysis was performed to assess the prognostic value of delta features in survival analysis. RESULTS: The pre-irradiation features demonstrated predictive capability in distinguishing survival groups, yielding an accuracy of 0.78 on the reserved test dataset. We also pinpointed eight quantitative features that exhibited a significant difference before and after radiotherapy in patients with MGMT-unmethylated glioblastoma. The change of the features presented different patterns between the survival groups separated by median overall survival and the inclusion of delta features can enhance the accuracy of survival analysis. Conversely, for patients with methylated MGMT, no feature displayed such significant changes between preRT and early postRT. CONCLUSIONS: Our study showcased the potential of employing quantitative features derived from F-DOPA images to refine the stratification of patients with unmethylated MGMT for dose escalated therapy. Moreover, the change of these features can serve as valuable tools for monitoring treatment responses following radiotherapy.
背景/目的：F-DOPA是一种氨基酸放射性示踪剂，在胶质母细胞瘤中摄取率高，在正常脑组织中摄取率低。患者在一项前瞻性临床试验中接受了放疗前和放疗后的F-DOPA PET扫描。本分析研究与预后和治疗反应相关的定量图像特征，以识别从剂量递增治疗中获益最大的患者。 方法：从58例胶质母细胞瘤患者的F-DOPA PET扫描中，在放疗前和放疗后早期随访PET图像的高摄取区域（TBR>2.0）提取定量图像特征，然后使用Pearson配对相关性进行细化。为了探索识别从剂量递增治疗中获益最大的患者的可能性，通过单变量Cox回归分析确定放疗前特征。采用简单阈值或决策树模型进行分类，将患者分为不同的生存组。此外，识别放疗前后有显著变化的特征，并比较生存组之间这些变化的时间模式。进行多变量Cox分析以评估δ特征在生存分析中的预后价值。 结果：放疗前特征在区分生存组方面具有预测能力，在保留的测试数据集上准确率为0.78。我们还确定了8个定量特征，这些特征在MGMT未甲基化的胶质母细胞瘤患者放疗前后表现出显著差异。特征变化在按中位总生存期分隔的生存组之间呈现不同模式，纳入δ特征可提高生存分析的准确性。相反，对于MGMT甲基化的患者，没有特征在放疗前和放疗后早期显示出如此显著的变化。 结论：我们的研究展示了利用F-DOPA图像衍生的定量特征来优化未甲基化MGMT患者进行剂量递增治疗分层的潜力。此外，这些特征的变化可作为监测放疗后治疗反应的有价值工具。
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