کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6039227 | 1188816 | 2009 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Use of fractional anisotropy for determination of the cut-off value in 11C-methionine positron emission tomography for glioma
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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چکیده انگلیسی
Multimodal imaging is one of the necessary steps in the treatment of malignant brain tumors, and use of magnetic resonance imaging (MRI) and positron emission tomography (PET) are the current gold standard technique for the morphological and biological assessment of malignant brain tumors. In addition, fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI) and 11C-methionine PET are useful to determine the tumor border at the tumor and white matter interface. Although there is no question of their value, a universally accepted cut-off value to discriminate normal and abnormal tissue has not been established. In this study we attempted to calculate and determine the cut-off values in FA and 11C-methionine PET that will allow delineation of the tumor border at the tumor and white matter interface by combining these two modalities. We were able to determine individual cut-off values for 11 patients, and then found an average cut-off value in the T/N ratio of 11C-methionine PET of 1.27 and in FA of 0.26, values similar to those previously confirmed by histological study. Moreover, reconstructing images delineating the tumor border was possible combining these two imaging modalities. We propose that the combined analysis of DTI and 11C-methionine PET has the potential to improve tumor border imaging in glioma patients, providing important information for establishing neurosurgical strategies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 45, Issue 2, 1 April 2009, Pages 312-318
Journal: NeuroImage - Volume 45, Issue 2, 1 April 2009, Pages 312-318
نویسندگان
Manabu Kinoshita, Naoya Hashimoto, Tetsu Goto, Takufumi Yanagisawa, Yoshiko Okita, Naoki Kagawa, Haruhiko Kishima, Hisashi Tanaka, Norihiko Fujita, Eku Shimosegawa, Jun Hatazawa, Toshiki Yoshimine,