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Abstract #5116

Differential Diagnosis between Tumor Recurrence and Treatment Response using Advanced Tracer Kinetic Model in Glioblastoma

Jianan Zhou1, Zujun Hou2, Zhengyang Zhu1, Chuanshuai Tian1, Bing Zhang1, and Xin Zhang1
1Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China, 2Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China., Suzhou, China

Synopsis

Keywords: Tumors (Post-Treatment), Tumor, Glioblastoma, Tumor recurrent, Treatment-related response, Distributed parameter model, Dynamic contrast-enhanced

Motivation: It is challenging to differentiate recurrent tumor from treatment response in glioblastoma.

Goal(s): This study explored the issue using an advanced tracer kinetic model.

Approach: Glioblastoma patients were examined using dynamic contrast-enhanced MRI and stratified into recurrent and treatment-related group based on histopathological results. Imaging data were analyzed using distributed parameter model.

Results: Blood flow in lesion was significantly higher and permeability in peritumoral edema was significantly smaller in recurrent than in treatment-related group (p=0.002, 0.023). Combining two parameters together, diagnostic performance was attained at AUC (area under ROC curve) 0.93. AUC of extended-Tofts model was 0.89.

Impact: With separate account of blood flow and vessel-wall permeability, advanced tracer kinetic model allowed more precise modeling the feature of tissue microenvironment, which could shed light on the difference between recurrent tumor and treatment-related response in glioblastoma.

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