ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences


Application potential of susceptibility-weighted imaging (SWI), diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) in the diagnosis of soft tissue tumors

Objective: The prime aim of the present study was to analyse the application value of 3.0 T Susceptibility Weighted Imaging (SWI), Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI) sequence in the diagnosis of benign as well as malignant soft tissue tumors.

Methods: 30 cases of benign soft tissue tumor and 30 cases of malignant soft tissue tumor (diagnosed pathologically) were selected as study subjects. Routine MRI scanning sequences viz. SWI, DWI and DTI sequences were utilized for the examination.

Results: The DWI Apparent Diffusion Coefficient (ADC values) under different b values (400 s/mm2, 800 s/mm2) in malignant group were significantly less in comparison to benign group (P<0.05). Further, ADC values of cystic change and necrotic zone in malignant group were also significantly less than the benign group (P<0.05). On the other hand, the occurrence rate of hemorrhage, calcification, cystic change, necrosis, and fiber separation determined by SWI in malignant group was significantly higher when compared with benign group (P<0.05). The mean FA value and RA values of malignant tumor determined by DTI sequence examination were significantly higher than those of benign tumor. Also, VR values of malignant tumors were lower than that of benign tumors (P<0.05). The anisotropy of benign tumor parenchyma was lower than that of malignant tumor. Three-dimensional fiber tracking imaging showed that there was a difference in the influence of benign tumor and malignant tumor on adjacent muscle fiber bundle.

Conclusion: SWI, DWI and DTI sequence could be utilized for the identification of the benign/malignant soft tissue tumor, tumor anatomical boundary as well as respectability of malignant tumors.

Author(s): Xiaoguang You, Yikai Xu
Abstract | Full-Text | PDF

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