<abstract xmlns="http://www.w3.org/1999/xhtml"><sec id="j_raon-2020-0061_s_006_w2aab3b7d120b1b6b1aab1c16b1Aa"><h3>Background</h3><p>To assess different types of adnexal masses as identified by 3T MRI and to discuss the added value of diffusion techniques compared with conventional sequences.</p></sec><sec id="j_raon-2020-0061_s_007_w2aab3b7d120b1b6b1aab1c16b2Aa"><h3>Patients and methods</h3><p>174 women age between 13 and 87 underwent an MRI examination of the pelvis for a period of three years. Patients were examined in two radiology departments – 135 of them on 3 Tesla MRI Siemens Verio and 39 on 3 Tesla MRI Philips Ingenia. At least one adnexal mass was diagnosed in 98 patients and they are subject to this study. Some of them were reviewed retrospectively. Data from patients’ history, physical examination and laboratory tests were reviewed as well.</p></sec><sec id="j_raon-2020-0061_s_008_w2aab3b7d120b1b6b1aab1c16b3Aa"><h3>Results</h3><p>124 ovarian masses in 98 females’ group of average age 47.2 years were detected. Following the MRI criteria, 59.2% of the cases were considered benign, 30.6% malignant and 10.2% borderline. Out of all masses 58.1% were classified as cystic, 12.9% as solid and 29% as mixed. Оf histologically proven tumors 74.4% were benign and 25.6% were malignant. All of the malignant tumors had restricted diffusion. 64 out of all patients underwent contrast enhancement. (34 there were a subject of contraindications). 39 (61%) of the masses showed contrast enhancement.</p></sec><sec id="j_raon-2020-0061_s_009_w2aab3b7d120b1b6b1aab1c16b4Aa"><h3>Conclusions</h3><p>Classifying adnexal masses is essential for the preoperative management of the patients. 3T MRI protocols, in particular diffusion techniques, increase significantly the accuracy of the diagnostic assessment.</p></sec></abstract>

BackgroundTo assess different types of adnexal masses as identified by 3T MRI and to discuss the added value of diffusion techniques compared with conventional sequences.Patients and methods174 women age between 13 and 87 underwent an MRI examination of the pelvis for a period of three years. Patients were examined in two radiology departments – 135 of them on 3 Tesla MRI Siemens Verio and 39 on 3 Tesla MRI Philips Ingenia. At least one adnexal mass was diagnosed in 98 patients and they are subject to this study. Some of them were reviewed retrospectively. Data from patients’ history, physical examination and laboratory tests were reviewed as well.Results124 ovarian masses in 98 females’ group of average age 47.2 years were detected. Following the MRI criteria, 59.2% of the cases were considered benign, 30.6% malignant and 10.2% borderline. Out of all masses 58.1% were classified as cystic, 12.9% as solid and 29% as mixed. Оf histologically proven tumors 74.4% were benign and 25.6% were malignant. All of the malignant tumors had restricted diffusion. 64 out of all patients underwent contrast enhancement. (34 there were a subject of contraindications). 39 (61%) of the masses showed contrast enhancement.ConclusionsClassifying adnexal masses is essential for the preoperative management of the patients. 3T MRI protocols, in particular diffusion techniques, increase significantly the accuracy of the diagnostic assessment.

Adnexal masses characterized on 3 tesla magnetic resonance imaging – added value of diffusion techniques

Radiology and Oncology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

BackgroundTo assess different types of adnexal masses as identified by 3T MRI and to discuss the added value of diffusion techniques compared with conventional...

Adnexal masses characterized on 3 tesla magnetic resonance imaging – added value of diffusion techniques

Article Category: Research Article

Online veröffentlicht: 21. Okt. 2020

Seitenbereich: 419 - 428

Eingereicht: 19. Juni 2020

Akzeptiert: 14. Sept. 2020

DOI: https://doi.org/10.2478/raon-2020-0061

© 2020 Julia Dimova, Dora Zlatareva, Rumiana Bakalova, Ichio Aoki, George Hadjidekov, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.