CLINICORADIOLOGICAL CORRELATION OF ADNEXAL MASSES USING ULTRASOUND AND MRI IN A TERTIARY CARE HOSPITAL: A RETROSPECTIVE STUDY
Main Article Content
Keywords
Adnexal masses; ultrasound; MRI; O-RADS; ovarian malignancy; clinicoradiological; Bihar; Muzaffarpur; RDJMMCH; DWI
Abstract
Background:Adnexal masses represent a diagnostically challenging and clinically significant group of gynaecological conditions encountered across all reproductive age groups. In Bihar, the combination of delayed healthcare presentation, limited access to specialist gynaecological oncology services, and a high prevalence of pelvic inflammatory disease, endometriosis, and tubo-ovarian abscess creates a distinctive regional adnexal mass spectrum that differs from published urban tertiary care series. Accurate pre-operative characterisation of adnexal masses as benign, borderline, or malignant has major implications for surgical planning — determining whether laparoscopic versus open surgery, conservative versus radical resection, and specialist oncological input are required. Ultrasound (USG) remains the first-line imaging modality, while MRI provides superior soft-tissue contrast, multiplanar capability, and functional sequences (diffusion-weighted imaging, dynamic contrast enhancement) that significantly improve characterisation of sonographically indeterminate masses. Despite MRI's established superiority for complex mass assessment, its systematic comparative evaluation against USG with histopathological correlation in a North Bihar tertiary care setting has not been formally conducted at RDJMMCH, Muzaffarpur.
Objectives:To evaluate the clinicoradiological correlation of adnexal masses using ultrasound and MRI at RDJMMCH, Muzaffarpur, July 2024–February 2025; to determine and compare the diagnostic performance (sensitivity, specificity, PPV, NPV, accuracy, AUC) of USG and MRI against histopathological gold standard; and to identify independent imaging and clinical predictors of malignancy.
Methodology:Retrospective observational study of 186 consecutive adult female patients with confirmed adnexal masses who underwent both USG (transabdominal + transvaginal) and MRI pelvis (1.5T, multiparametric protocol: T1, T2, DWI, DCE) at RDJMMCH, Muzaffarpur, during July 2024–February 2025, with subsequent histopathological confirmation. Masses classified per O-RADS (ACR 2020) for USG and O-RADS MRI (Thomassin-Naggara 2020) for MRI. Statistical analysis: IBM SPSS v26 — chi-square, ANOVA, multivariate logistic regression, ROC analysis, Cohen's weighted kappa.
Results:186 patients; mean age 42.2±13.8 years. Histopathology: benign 74.2% (n=138), borderline 8.6% (n=16), malignant 17.2% (n=32). Most common diagnoses: serous cystadenoma 23.7%, dermoid/teratoma 19.4%, endometrioma 15.1%. USG: sensitivity 87.5%, specificity 83.3%, accuracy 84.9%, AUC 0.88. MRI: sensitivity 96.9%, specificity 92.8%, accuracy 93.5%, AUC 0.93. Combined USG+MRI: sensitivity 96.9%, specificity 95.7%, accuracy 95.7%, AUC 0.96. MRI significantly outperformed USG for peritoneal seedling detection (82.4% vs 28.5%), solid component characterisation (91.4% vs 72.0%), and ascites characterisation. Independent MRI predictors of malignancy: solid component (OR 12.36), peritoneal seedlings (OR 18.62), DWI restriction ADC<1.0×10⁻³ mm²/s (OR 11.48). USG–MRI O-RADS concordance: 79.0%; weighted κ=0.78 (p<0.001).
Conclusion:MRI demonstrates substantially superior diagnostic performance over USG alone for characterising adnexal masses at RDJMMCH, Muzaffarpur, and should be systematically used as the second-line modality for all USG-indeterminate masses, particularly for pre-operative malignancy risk stratification and surgical pathway determination. O-RADS system implementation in routine radiology reporting is recommended to standardise risk communication between radiologists and gynaecologists at RDJMMCH.
References
2. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229-263. doi: 10.3322/caac.21834. PMID: 38572751.
3. Timmerman D, Valentin L, Bourne TH, Collins WP, Verrelst H, Vergote I. Terms, definitions and measurements to describe the sonographic features of adnexal tumors: a consensus opinion from the International Ovarian Tumor Analysis (IOTA) Group. Ultrasound Obstet Gynecol. 2000;16(5):500-505. doi: 10.1046/j.1469-0705.2000.00287.x. PMID: 11106488.
4. Andreotti RF, Timmerman D, Strachowski LM, Froyman W, Benacerraf BR, Bennett GL, et al. O-RADS US risk stratification and management system: a consensus guideline from the ACR Ovarian-Adnexal Reporting and Data System Committee. Radiology. 2020;294(1):168-185. doi: 10.1148/radiol.2019191150. PMID: 31714182.
5. Thomassin-Naggara I, Poncelet E, Jalaguier-Coudray A, Guerra A, Fournier LS, Stojanovic S, et al. Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of sonographically indeterminate adnexal masses. JAMA Netw Open. 2020;3(1):e1919896. doi: 10.1001/jamanetworkopen.2019.19896. PMID: 31990347.
6. Rizzo S, Cozzi A, Dolciami M, Del Grande F, Scarano AL, Papadia A, et al. O-RADS MRI: a systematic review and meta-analysis of diagnostic performance and category-wise malignancy rates. Radiology. 2023;307(1):e220795. doi: 10.1148/radiol.220795. PMID: 36594815.
7. Zhang Q, Dai X, Li W. Systematic review and meta-analysis of O-RADS ultrasound and O-RADS MRI for risk assessment of ovarian and adnexal lesions. AJR Am J Roentgenol. 2023;221(1):21-33. doi: 10.2214/AJR.22.28396. PMID: 36722758.
8. Cui L, Xu H, Zhang Y. Diagnostic accuracies of the ultrasound and magnetic resonance imaging ADNEX scoring systems for ovarian adnexal mass: systematic review and meta-analysis. Acad Radiol. 2022;29(6):897-908. doi: 10.1016/j.acra.2021.05.029. PMID: 34217614.
9. Vara J, Manzour N, Chacón E, López-Picazo A, Linares M, Pascual MA, et al. Ovarian adnexal reporting data system (O-RADS) for classifying adnexal masses: a systematic review and meta-analysis. Cancers (Basel). 2022;14(13):3151. doi: 10.3390/cancers14133151. PMC9264796.
10. Sayasneh A, Ekechi C, Ferrara L, Kaijser J, Stalder C, Sur S, et al. The characteristic ultrasound features of specific types of ovarian pathology: a pictorial essay. Int J Clin Exp Med. 2015;8(4):4674-4683. PMID: 26101514.
11. Patel MD, Ascher SM, Horrow MM, Marcelino A, Francis B, Brown DL, et al. Management of incidental adnexal findings on CT and MRI: a white paper of the ACR Incidental Findings Committee. J Am Coll Radiol. 2020;17(2):248-254. doi: 10.1016/j.jacr.2019.11.018. PMID: 31924279.
12. Brown DL, Andreotti RF, Lee SI, Dejesus Allison SO, Bennett GL, Dubinsky T, et al. ACR Appropriateness Criteria ovarian cancer screening. Ultrasound Q. 2010;26(4):219-223. doi: 10.1097/RUQ.0b013e3181fbe820. PMID: 21073521.
13. Epstein E, Testa A, Gaurilcikas A, Di Legge A, Ameye L, Atstupenaite V, et al. Early-stage cervical cancer: tumor delineation by magnetic resonance imaging and ultrasound. Gynecol Oncol. 2010;117(3):439-444. doi: 10.1016/j.ygyno.2010.02.042. PMID: 20299099.
14. Srirambhatla A, Hosamani RD, Nandury EC. The role of diffusion-weighted imaging in the evaluation of adnexal lesions. Pol J Radiol. 2022 Aug 20;87:e469-e477. doi: 10.5114/pjr.2022.119064. PMID: 36091651. PMC9453242.
15. Timmerman D, Ameye L, Fischerova D, Epstein E, Melis GB, Guerriero S, et al. Simple ultrasound rules to distinguish between benign and malignant adnexal masses before surgery: prospective validation by IOTA group. BMJ. 2010;341:c6839. doi: 10.1136/bmj.c6839. PMID: 21156740.
16. Kaijser J, Vandecaveye V, Deroose CM, Lahaye M, Rockall A, Bourne T, et al. Imaging techniques for the preoperative classification of epithelial ovarian tumours. Best Pract Res Clin Obstet Gynaecol. 2014;28(5):724-735. doi: 10.1016/j.bpobgyn.2014.04.004. PMID: 24818636.
17. Valentin L, Ameye L, Testa A, Lecuru F, Bernard JP, Paladini D, et al. Ultrasound characteristics of different types of adnexal malignancies. Gynecol Oncol. 2006;102(1):41-48. doi: 10.1016/j.ygyno.2005.11.032. PMID: 16434086.
18. Iyer VR, Lee SI. MRI, CT, and PET/CT for ovarian cancer detection and adnexal lesion characterization. AJR Am J Roentgenol. 2010;194(2):311-321. doi: 10.2214/AJR.09.3522. PMID: 20093589.
19. Fujii S, Kakite S, Nishihara K, Kanasaki Y, Harada T, Kigawa J, et al. Diagnostic accuracy of diffusion-weighted imaging in differentiating benign from malignant ovarian lesions. J Magn Reson Imaging. 2008;28(5):1149-1156. doi: 10.1002/jmri.21508. PMID: 18972356.
20. Bharwani N, Reznek RH, Rockall AG. Ovarian cancer management: the role of imaging and diagnostic challenges. Eur J Radiol. 2011;78(1):41-51. doi: 10.1016/j.ejrad.2010.12.009. PMID: 21239123.
21. Trimbos JB, Parmar M, Vergote I, Guthrie D, Bolis G, Colombo N, et al. International Collaborative Ovarian Neoplasm trial 1 and adjuvant chemotherapy in ovarian neoplasm trial: two parallel randomized phase III trials of adjuvant chemotherapy in patients with early-stage ovarian carcinoma. J Natl Cancer Inst. 2003;95(2):105-112. doi: 10.1093/jnci/95.2.105. PMID: 12529344.
22. Kinkel K, Lu Y, Mehdizade A, Pelte MF, Hricak H. Indeterminate ovarian mass at US: incremental value of second imaging test for characterization: meta-analysis and Bayesian analysis. Radiology. 2005;236(1):85-94. doi: 10.1148/radiol.2361041037. PMID: 15987967.
23. World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191-4. doi: 10.1001/jama.2013.281053. PMID: 24141714.
24. Jayashree V, Jeena Rajesh P, Jayasree M. The role of ultrasonography and magnetic resonance imaging in evaluation of adnexal masses with histopathological correlation. Cureus. 2025;17(5):e83712. doi: 10.7759/cureus.83712. PMC12681448.
25. Rashmi N, Singh S, Begum J, Sable MN. Diagnostic performance of ultrasound-based International Ovarian Tumor Analysis simple rules and Assessment of Different NEoplasias in the adneXa model for predicting malignancy in women with ovarian tumors: a prospective cohort study. Womens Health Rep (New Rochelle). 2023;4(1):202-210. doi: 10.1089/whr.2022.0072. PMID: 37124668.

