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Evaluation of primary adnexal masses by 3T MRI: categorization with conventional MR imaging and diffusion-weighted imaging
BACKGROUND: To investigate the 3.0-Tesla (3 T) magnetic resonance imaging (MRI) characteristics of primary adnexal lesions for discriminating benign from malignant lesions. METHODS: One hundred thirty-nine patients with pathologically proven primary adnexal masses referred for 3 T MRI assessment pre...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576319/ https://www.ncbi.nlm.nih.gov/pubmed/23148860 http://dx.doi.org/10.1186/1757-2215-5-33 |
Sumario: | BACKGROUND: To investigate the 3.0-Tesla (3 T) magnetic resonance imaging (MRI) characteristics of primary adnexal lesions for discriminating benign from malignant lesions. METHODS: One hundred thirty-nine patients with pathologically proven primary adnexal masses referred for 3 T MRI assessment preoperatively were included. Baseline characteristics, components, and conventional MRI and diffusion-weighted imaging (DWI-MRI) signals were recorded and compared. RESULTS: There were 22 ovarian cysts, 33 endometriomas, 43 benign tumors and 42 malignant tumors. When ovarian cyst and endometrioma were excluded, there were no significant differences in patients’ age between benign and malignant tumor (P = 0.235). There were no significant differences (P = 0.606) in the conventional MRI signals and significant difference (P = 0.008) in DWI-MRI signal between the non-malignant and malignant lesions. There was a significant difference (P = 0.000) in the apparent diffusion coefficient values (ADCs) between the non-malignant and malignant lesions. CONCLUSIONS: 3 T MRI categorized the characteristics of primary adnexal lesions. Conventional MRI signals were not useful for characterizing between benign and malignant lesions. DWI-MRI and ADCs were helpful for distinguishing malignant from benign ovarian lesions. |
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