Zhou Jianan, Hou Zujun, Tian Chuanshuai, Zhu Zhengyang, Ye Meiping, Chen Sixuan, Yang Huiquan, Zhang Xin, Zhang Bing
Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China.
Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China.
Front Oncol. 2024 Jun 14;14:1380793. doi: 10.3389/fonc.2024.1380793. eCollection 2024.
Glioma is the most common type of primary malignant tumor of the central nervous system (CNS), and is characterized by high malignancy, high recurrence rate and poor survival. Conventional imaging techniques only provide information regarding the anatomical location, morphological characteristics, and enhancement patterns. In contrast, advanced imaging techniques such as dynamic contrast-enhanced (DCE) MRI or DCE CT can reflect tissue microcirculation, including tumor vascular hyperplasia and vessel permeability. Although several studies have used DCE imaging to evaluate gliomas, the results of data analysis using conventional tracer kinetic models (TKMs) such as Tofts or extended-Tofts model (ETM) have been ambiguous. More advanced models such as Brix's conventional two-compartment model (Brix), tissue homogeneity model (TH) and distributed parameter (DP) model have been developed, but their application in clinical trials has been limited. This review attempts to appraise issues on glioma studies using conventional TKMs, such as Tofts or ETM model, highlight advancement of DCE imaging techniques and provides insights on the clinical value of glioma management using more advanced TKMs.
胶质瘤是中枢神经系统(CNS)最常见的原发性恶性肿瘤类型,其特点是恶性程度高、复发率高且生存率低。传统成像技术仅提供有关解剖位置、形态特征和强化模式的信息。相比之下,动态对比增强(DCE)MRI或DCE CT等先进成像技术可以反映组织微循环,包括肿瘤血管增生和血管通透性。尽管有几项研究使用DCE成像来评估胶质瘤,但使用Tofts或扩展Tofts模型(ETM)等传统示踪剂动力学模型(TKMs)进行数据分析的结果并不明确。已经开发了更先进的模型,如Brix的传统双室模型(Brix)、组织均匀性模型(TH)和分布参数(DP)模型,但它们在临床试验中的应用有限。本综述试图评估使用Tofts或ETM模型等传统TKMs进行胶质瘤研究的问题,强调DCE成像技术的进展,并提供关于使用更先进的TKMs进行胶质瘤管理的临床价值的见解。