OBJECTIVES: The new magnetic resonance whole body diffusion-weighted imaging with background body signal suppression (DWIBS) uses short tau inversion recovery-echo planar imaging sequence under normal respiration. DWIBS is different from 2-[fluorine-18]-fluoro-2-deoxy-D: -glucose positron emission tomography ((18)F-FDG PET) imaging in technology, but their images are similar. We compared the two modalities regarding the detection and characterization of malignant tumors. METHODS: DWIBS and (18)F-FDG PET/computed tomography (CT) were performed on 16 cancer patients on the same day. The diagnoses were the following: lung cancer (n = 12), colon cancer (n = 2), breast cancer (n = 1), and pulmonary metastasis (n = 1). A total of 27 malignant tumors (15 lung cancer, 5 pulmonary metastases of parathyroid cancer, 3 pulmonary metastases of lung cancer, 3 colon cancer, 1 breast cancer) and seven reference organs around malignant lesions (two liver regions, four normal lymph nodes, one muscle region) were evaluated visually and quantitatively using the apparent diffusion coefficient (ADC) (x10(-3) mm(2)/s) and standardized uptake value (SUV). RESULTS: Twenty-five (92.6%) of the 27 malignant lesions were detected visually with DWIBS imaging in contrast to 22 malignant tumors (81.5%) with (18)F-FDG PET/CT imaging. The quantitative evaluation showed that there was a significant difference between the mean SUVs of the reference organs (n = 7, 1.48 +/- 0.62) and the malignant (n = 22, 5.36 +/- 2.80) lesions (P < 0.01). However, there was no significant difference between the mean ADCs of the reference organs (n = 7, 1.54 +/- 0.24) and the malignant (n = 25, 1.18 +/- 0.70) lesions. CONCLUSIONS: DWIBS can be used for the detection of malignant tumors or benign tumors; however, it may be difficult to differentiate between benign and malignant lesions by ADC.
OBJECTIVES: The new magnetic resonance whole body diffusion-weighted imaging with background body signal suppression (DWIBS) uses short tau inversion recovery-echo planar imaging sequence under normal respiration. DWIBS is different from 2-[fluorine-18]-fluoro-2-deoxy-D: -glucose positron emission tomography ((18)F-FDG PET) imaging in technology, but their images are similar. We compared the two modalities regarding the detection and characterization of malignant tumors. METHODS:DWIBS and (18)F-FDG PET/computed tomography (CT) were performed on 16 cancerpatients on the same day. The diagnoses were the following: lung cancer (n = 12), colon cancer (n = 2), breast cancer (n = 1), and pulmonary metastasis (n = 1). A total of 27 malignant tumors (15 lung cancer, 5 pulmonary metastases of parathyroid cancer, 3 pulmonary metastases of lung cancer, 3 colon cancer, 1 breast cancer) and seven reference organs around malignant lesions (two liver regions, four normal lymph nodes, one muscle region) were evaluated visually and quantitatively using the apparent diffusion coefficient (ADC) (x10(-3) mm(2)/s) and standardized uptake value (SUV). RESULTS: Twenty-five (92.6%) of the 27 malignant lesions were detected visually with DWIBS imaging in contrast to 22 malignant tumors (81.5%) with (18)F-FDG PET/CT imaging. The quantitative evaluation showed that there was a significant difference between the mean SUVs of the reference organs (n = 7, 1.48 +/- 0.62) and the malignant (n = 22, 5.36 +/- 2.80) lesions (P < 0.01). However, there was no significant difference between the mean ADCs of the reference organs (n = 7, 1.54 +/- 0.24) and the malignant (n = 25, 1.18 +/- 0.70) lesions. CONCLUSIONS:DWIBS can be used for the detection of malignant tumors or benign tumors; however, it may be difficult to differentiate between benign and malignant lesions by ADC.
Authors: Ananth J Madhuranthakam; Karen S Lee; Aya Yassin; Jean H Brittain; Ivan Pedrosa; Neil M Rofsky; David C Alsop Journal: MAGMA Date: 2013-09-20 Impact factor: 2.310
Authors: D Cafagna; G Rubini; F Iuele; N Maggialetti; A Notaristefano; D Pinto; A Niccoli-Asabella; G Palmiotti; M Lasciarrea; A Maggialetti Journal: Radiol Med Date: 2011-07-09 Impact factor: 3.469
Authors: Andreas Gutzeit; Aleksis Doert; Johannes M Froehlich; Boris P Eckhardt; Andreas Meili; Patrick Scherr; Daniel T Schmid; Nicole Graf; Constantin A von Weymarn; Edwin M M Willemse; Christoph A Binkert Journal: Skeletal Radiol Date: 2010-04 Impact factor: 2.199