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http://dx.doi.org/10.13104/imri.2021.25.2.118

Benign versus Malignant Soft-Tissue Tumors: Differentiation with 3T Magnetic Resonance Image Textural Analysis Including Diffusion-Weighted Imaging  

Lee, Youngjun (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Jee, Won-Hee (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Whang, Yoon Sub (Department of Radiology, Myongji St. Mary's Hospital)
Jung, Chan Kwon (Department of Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Chung, Yang-Guk (Department of Orthopedic Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Lee, So-Yeon (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Publication Information
Investigative Magnetic Resonance Imaging / v.25, no.2, 2021 , pp. 118-128 More about this Journal
Abstract
Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm2), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.
Keywords
Magnetic resonance imaging; Diffusion; Texture analysis; Sarcoma; Neoplasm;
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