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MR imaging as a precise technique to evaluate skull-base tumor volume: Comparison of CT,MR imaging and FDG PET from murine and clinical data
Institution:1. Department of Neurosurgery, First Medical Center, Chinese PLA General Hospital, Beijing, China;2. Department of Nuclear Medicine, First Medical Center, Chinese PLA General Hospital, Beijing, China;3. Department of Neurosurgery, Pingjin Hospital, Characteristic Medical Center of Chinese People''s Armed Police Force, Tianjin, China;4. Pingjin Hospital, Characteristic Medical Center of Chinese People''s Armed Police Force, Tianjin, China;5. Department of Neurosurgery, The 988th hospital of PLA, Zhengzhou, Henan, China;6. The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China
Abstract:In spite of the many imaging modalities used in clinics, the one that best reflects the true delineation of skull-base (infratemporal fossa, ITF) malignancies is still unknown. In order to compare the tumor recognition capabilities of different imaging modalities, established murine models and patients with skull-base tumors were evaluated by computer tomography (CT), magnetic resonance (MR) imaging, and fluorine-18 fluorodeoxyglucose (18FDG) positron emission tomography (PET) for delineation of gross tumor volume (GTV).PET, MR imaging, and CT enhanced by iodine staining were all sensitive to, and able to recognize, the skull-base tumor in the murine model. No significant difference (p > 0.9999) was observed between average GTV according to MR imaging (176.67 ± 19.6 mm3) and the histological measurement result (170.23 ± 22.24 mm3) for the murine model. In contrast, the GTVs according to CT (88.77 ± 13.03 mm3, p < 0.0001) and 18FDG PET (35.67 ± 6.56 mm3, p < 0.0001) were much smaller.In nine patients for whom the three modalities were available, tumor volume comparisons tended to be consistent with the murine model data. According to both the established murine model and clinical patient data, MR imaging possessed the optimal ability to recognize tumor contours.
Keywords:Skull-base tumor  Multimodal imaging  Animal model  MR imaging
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