Diagnosing ovarian masses by using nuclear magnetic resonance
Abstract
In the research, nuclear magnetic resonance (NMR) was used to study and diagnose ovarian tumour. A total of 80 ovarian tumour patients who were admitted to the hospital from February 2014 to May 2016 were selected and randomly divided into 2 groups, 40 in the case group and 40 in the control group. The case group used NMR whereas the control group utilized B-mode ultrasound to compare the characteristics of tumor masses, accuracy, sensitivity, and specificity of the clinical diagnosis afterwards. The accuracy, sensitivity, specificity, and characteristics of tumour masses by NMR were 95.84%, 94.75%, 90.92%, and 100%, respectively, which were apparently higher than those of the B-mode ultrasound scanning (64.28%, 77.78%, 75.08%, and 70.83%, respectively). Difference of each index among the four between the two methods was statistically significant (p < 0.05). Therefore, NMR is superior to ultrasound in diagnosing ovarian tumour.
References
Shen Y, Zhou Y, Hou W, Zhu HC, Wang F, et al. Diffusion-weighted imaging IVIM model and dynamic enhanced MRI appli-cations in benign and malignant ovarian tumors. Chin J Clin Radiol 2016; 35(3): 410–414.
Liang YZ, Zhang HW, Cui Q. NMR diagnosis of ovarian cancer. J Chin Pharm Sci 2014; 4(21): 114–116.
Wa n ZH. Magnetic resonance spectroscopy applications in brain tumor diagnosis. J Vasc Card Cereb 2013; 11: 83–84.
Wang X, Chen Z. Combined use of magnetic resonance imaging and ultrasonography in the diagnosis of ovarian cancer. Hebei Med 2015;21(3): 487–489.
Xiong K, Yu DF. Diagnostic value and significance of PET/CT and MRI for gynecologic malignant tumors. Chin J Woman Child Health Res 2014; 5: 885–887.
Gao C, Pu J, Sui C. Characteristics and clinical application of NMR imaging ovarian tumors. Chin Matern Child Health 2016; 3: 628–631.
Mao F. Nuclear magnetic resonance imaging in diagnosing ovarian cancer. Med Forum 2011; 15(31): 1040–1041.
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