کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5726010 1609725 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Research articleValue of diffusion tensor imaging in differentiating malignant from benign parotid gland tumors
ترجمه فارسی عنوان
مقاله پژوهشی ارزش تصویر برداری از تهاجم منتشر در تشخیص بدخیمی از تومورهای خوشخیم غده پروستات
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی رادیولوژی و تصویربرداری
چکیده انگلیسی


- Diffusion tensor imaging provides ADC and fractional anisotropy (FA).
- Malignant parotid tumors had significantly higher FA than benign parotid tumors.
- No significant difference was observed in ADC for Warthin and malignant tumors.
- Diffusion tensor imaging might help differentiate malignant from benign parotid tumors.

PurposeTo evaluate whether diffusion tensor imaging (DTI) can be used to differentiate malignant parotid gland tumors from the benign ones.Materials and methodsThe study population comprised 59 parotid gland tumors (24 Warthin's tumors, 19 pleomorphic adenomas, seven other benign tumors, and nine malignant tumors). Single-shot echo-planar DTI was performed with motion-probing gradients along 30 noncollinear directions (b = 1000 s/mm2) at 3.0 T. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values for benign and malignant tumors were compared using the Mann-Whitney U test. Receiver-operating characteristic (ROC) curve analysis was performed to assess the ability of the ADC and FA values to differentiate malignant tumors from the benign ones.ResultsADC values showed no significant difference between malignant (0.93 ± 0.21 × 10−3 mm2/s) and benign tumors (1.19 ± 0.50 × 10−3 mm2/s) (p = 0.225). FA values of malignant tumors were significantly higher than those of benign tumors (0.26 ± 0.06 vs. 0.17 ± 0.05, p < 0.001). The area under the ROC curve of FA was significantly greater than that under the curve of ADC (0.884 vs. 0.628, p = 0.010).ConclusionsDTI, particularly FA, can help differentiate malignant parotid gland tumors from the benign ones.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Radiology - Volume 95, October 2017, Pages 249-256
نویسندگان
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