Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging

Jianan Zhou; Jianan Zhou; Jianan Zhou; Zujun Hou; Chuanshuai Tian; Chuanshuai Tian; Chuanshuai Tian; Zhengyang Zhu; Zhengyang Zhu; Meiping Ye; Meiping Ye; Sixuan Chen; Sixuan Chen; Huiquan Yang; Huiquan Yang; Xin Zhang; Xin Zhang; Xin Zhang; Bing Zhang; Bing Zhang; Bing Zhang

doi:10.3389/fonc.2024.1380793

Frontiers in Oncology (Jun 2024)

Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging

Jianan Zhou,
Jianan Zhou,
Jianan Zhou,
Zujun Hou,
Chuanshuai Tian,
Chuanshuai Tian,
Chuanshuai Tian,
Zhengyang Zhu,
Zhengyang Zhu,
Meiping Ye,
Meiping Ye,
Sixuan Chen,
Sixuan Chen,
Huiquan Yang,
Huiquan Yang,
Xin Zhang,
Xin Zhang,
Xin Zhang,
Bing Zhang,
Bing Zhang,
Bing Zhang

Affiliations

Jianan Zhou: Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
Jianan Zhou: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Jianan Zhou: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Zujun Hou: The Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
Chuanshuai Tian: Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
Chuanshuai Tian: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Chuanshuai Tian: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Zhengyang Zhu: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Zhengyang Zhu: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Meiping Ye: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Meiping Ye: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Sixuan Chen: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Sixuan Chen: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Huiquan Yang: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Huiquan Yang: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Xin Zhang: Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
Xin Zhang: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Xin Zhang: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
Bing Zhang: Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
Bing Zhang: Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
Bing Zhang: Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

DOI: https://doi.org/10.3389/fonc.2024.1380793
Journal volume & issue: Vol. 14

Abstract

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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.

Published in Frontiers in Oncology

ISSN: 2234-943X (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://www.frontiersin.org/journals/oncology/

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