Magnetic resonance imaging in the differential diagnosis of ovarian masses: Capabilities of quantitative multiparametric evaluation

Solopova A.E., Makatsaria A.D., Sdvizhkov A.M., Ternovoy S.K.

1Department of Radiation Diagnosis and Radiation Therapy, Faculty of General Medicine, Sechenov First Moscow State Medical University, Ministry of Health of Russia, Moscow 119991, Bolshaya Pirogovskaya str. 2, bld. 4, Russia 2Department of Obstetrics and Gynecology, Faculty of Medical Prevention, Sechenov First Moscow State Medical University, Ministry of Health of Russia, Moscow 119991, Bolshaya Pirogovskaya str. 2, bld. 4, Russia 3Clinical Oncology Dispensary One, Moscow Healthcare Department, Moscow 105425, Baumana str. 17/1, Russia

Objective. To estimate the capabilities of comprehensive magnetic resonance imaging (MRI) in the differential diagnosis of ovarian tumors.
Subjects and methods. In 2011 to 2015, a total of 256 patients with 289 ovarian masses underwent small pelvic and abdominal MRI (if necessary) to clarify the pattern and extent of the tumor process. MRI was performed on a 1.5 Tl scanner. The MRI protocol was to obtain T2-weighted images (WI) in three projections, STIR, Т1–WI, DWI with b-factors 0, 1000 м/мм2, to calculate the values of the diffusion coefficient, and to make the diffusion maps Dynamic 3D FatSat. Postprocessing involved an analysis of signal intensity-time curves in a given area of interest (8–45 pixels). MRI findings were compared with intraoperative tumor histological structural data or verified during a follow-up for at least 6 months.
Results. The pattern of detected abnormalities was as follows: true ovarian tumors (71%), endometriomas (16%), cysts (11%), and tubo-ovarian abscesses (2%). Among the true tumors, there were serous epithelial tumors (51%), mucinous epithelial tumors (26%), endometrioid cysts (2%), dermoid cysts (6%), clear-cell carcinomas (2%), granulosa cell tumors (6%), fibromas (4%), Brenner tumors (1%), and metastatic tumors (3%). The degree distribution of the tumors identified was the following: benign tumors (49%), borderline tumors (12%) (occurring only in a group of epithelial tumors), and malignant tumors (39%). FIGO staging of the borderline ovarian tumors classified as Stages IA (66%) and IC (34%). That of the malignant tumors classified as Stages IA (7.3%), IIA (17%), IIB (12.2%), IIC (17%), IIIB (21.9%), IIIC (14.6%), and IV (9.7%). Quantitative estimation of the parameters of perfusion images showed that the amplitude of contrast agent accumulation was significantly higher in malignant tumors (167% (115.2–212.5%)) than in benign tumors (61.2% (41.2–99.0%)) (P < 0.001) and borderline ones (85.7% (58.3–138.2%)), (P < 0.01); the signal intensity semi-elevation period was significantly longer in benign tumors (35.1 sec (30.8–42.5 sec)) than in borderline tumors (27.9 sec (23.5–29.8 sec) (P < 0.05), and malignant ones (23.1 sec (20.5–30.9 sec)) (P = 0.01). The largest curvature (inflection) of the curve (%/sec) amounted to 1.78 (1.0–2.6); 2.86 (2.01–3.95), and 6.1 (4.19–9.46) for benign, borderline, and malignant tumors, respectively, and it was significantly higher in invasive carcinomas (P < 0.01). Malignant tumors have significantly lower mean apparent diffusion coefficients (ADC) than benign tumors (1.012±0.18 and 1.54±0.25 mm2/sec x 10-3, respectively); the value intervals did not intersect. The threshold ADC value of malignant ovarian tumors was lower than 1.139 mm2/sec x 10-3. The information values of advanced MRI techniques were an accuracy of 92.1%, a sensitivity of 93.6%, and a specificity of 91.2%.
Conclusion. The incorporation of MRI with quantitative evaluation of perfusion parameters and diffusion-weighted images in a comprehensive examination algorithm allows differentiation of the degree of malignancy of ovarian tumors with a high degree of accuracy, by determining the opportunities for optimizing management tactics for patients.

Keywords

Supplementary Materials

1. Fig. 1. Magnetic resonance imaging with multiparametric evaluation. Patient H., 54 years old. The combination of ovarian adenofibroma and cystadenocarcinoma in one patient.
2. Fig. 2. Magnetic resonance imaging. a) T2-W.I.– coronal plane, b) T2-W.I.– sagittal plane), c) T2-W.I.– axial plane, g,d) T1-FatSat, before and after the contrast injection, clearly visualized complex structure of the tumor originating from the right ovary with a pronounced soft-tissue component extending into the right parameters, on the posterior uterine wall, into paravesical space

References

About the Authors

Solopova Alina Evgen’evna, Candidate of Medicine, assistant professor, Department of radiology and radiotherapy, Faculty of Medicine, Sechenov First Moscow State
Medical University, Ministry of Health of Russia. 119991, Russia, Moscow, Bolshaya Pirogovskaya str. 2, bld. 4. E-mail: dr.solopova@mail.ru
Makatsariya Aleksandr Davidovich, Doctor of Medicine, Professor, Head of Department of Obstetrics and Gynecology, Faculty of Preventive Medicine, I.M. Sechenov
First Moscow State Medical University, Ministry of Health of Russia. 119991, Russia, Moscow, Bolshaya Pirogovskaya str. 2, bld. 4
Sdzvizhkov Aleksandr M., chief physician of clinical GBUZ Cancer Clinic № 1 of Moscow Health Department.
105425, Russia, Moscow, Baumana str. 17/1. Tel.: +74992613042
Ternovoy Sergey Konstantinovich, Doctor of Medicine, Professor, Head of Department of radiology and radiotherapy, Faculty of Medicine, I.M. Sechenov
First Moscow State Medical University, Ministry of Health of Russia. 119991, Russia, Moscow, Bolshaya Pirogovskaya str. 2, bld. 4

For citations: Solopova A.E., Makatsaria A.D., Sdvizhkov A.M., Ternovoy S.K. Magnetic resonance imaging in the differential diagnosis of ovarian masses: Capabilities of quantitative multiparametric evaluation. Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2017; (2): 80-5. (in Russian)
http://dx.doi.org/10.18565/aig.2017.2.80-5

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