Benign ve malign jinekolojik kitlelerde görünen difüzyon katsayısı ölçümlerinin ve manyetik rezonans görüntüleme bulgularının değerlendirilmesi

Öz

Amaç: Bu çalışma, benign ve malign jinekolojik kitleler arasında manyetik rezonans görüntüleme (MRG) bulguları ve çeşitli görünen difüzyon katsayısı (ADC) ölçümleri açısından farkları araştırmayı amaçlamaktadır. Yöntemler: Haziran 2016 ile Kasım 2018 tarihleri arasında incelenen, pelvik kitleye sahip 102 hastanın MRG görüntüleri retrospektif olarak değerlendirildi. Hastalar histopatolojik olarak benign (n=82) veya malign (n=20) şeklinde, lezyon kompozisyonuna (kistik, solid, mikst) ve anatomik lokalizasyona (over, uterus, tüp, serviks) göre sınıflandırıldı. Üç ADC ölçüm yöntemi uygulandı: tüm lezyonu kapsayan geniş ROI'lerden elde edilen diffüz ADC (dADC), her kesitteki en koyu bölgelere yerleştirilen küçük ROI'lerden elde edilen fokal ADC (fADC) ve en düşük üç fADC değerinin ortalaması olarak hesaplanan spesifik ADC (sADC). Bulgular: Lezyon kompozisyonuna göre solid lezyonlar, mikst lezyonlardan daha düşük ADC değerleri gösterdi, ancak her bir lezyon kompozisyonunda benign ve malign kategoriler arasında farklılık gözlenmedi. Over ve uterin kitlelerde, ADC değerleri benign ve malign gruplar arasında anlamlı fark göstermedi. Servikal kitlelerde benign lezyonların ortalama ADC değerleri malign gruba kıyasla daha yüksekti (dADC için 2,4±0,2 ve 1,1±0,3, p=0,002; fADC için 2,3±0,2 ve 0,7±0,1, p=0,001; sADC için 2,2±0,2 ve 0,6±0,02, p=0,001). Sonuç: Farklı ADC ölçüm yöntemleri arasında, özellikle servikal lezyonlarda, fokal ve spesifik ADC değerleri benign ve malign jinekolojik kitleler arasındaki difüzyon farklılıklarını daha açık şekilde yansıtmıştır. ADC değerleri lezyon kompozisyonundan etkilense de her kompozisyon alt grubunda iyi huylu ve kötü huylu lezyonlar benzer değerler gösterdi.

Anahtar Kelimeler

• Jinekolojik kitleler
• difüzyon ağırlıklı görüntüleme
• görünen difüzyon katsayısı
• malign
• servikal kanser

Evaluation of apparent diffusion coefficient measurements and magnetic resonance imaging findings in benign and malignant gynecologic masses

Öz

Aim: This study aimed to investigate the differences in magnetic resonance imaging (MRI) findings and various apparent diffusion coefficient (ADC) measurements between benign and malignant gynecologic masses. Methods: MRI images of 102 patients with pelvic masses, examined between June 2016 and November 2018, were retrospectively reviewed. Patients were categorized histopathologically as benign or malignant, by lesion composition (cystic, solid, mixed), and according to anatomical location (ovary, uterus, tube, cervix). Three ADC measurement methods were applied: diffuse ADC (dADC) from large ROIs covering the entire lesion, focal ADC (fADC) from small ROIs placed on the darkest regions of each slice, and specific ADC (sADC) calculated as the mean of the three lowest fADC values. Results: According to lesion composition, solid lesions demonstrated lower ADC values than mixed lesions, yet no differences were observed between benign and malignant categories within each lesion composition. In ovarian and uterine masses, the value of ADCs showed no significant differences between benign and malignant groups. For cervical masses, the mean ADCs were higher in benign masses compared to malignant masses (dADC: 2.4±0.2 vs. 1.1±0.3, p=0.002; fADC : 2.3±0.2 vs. 0.7±0.1, p=0.001; sADC: 2.2±0.2 vs. 0.6±0.02, p=0.001). Conclusion: Among various ADC measurement strategies, focal and specific ADC values more clearly reflected diffusion differences between benign and malignant gynecologic masses, particularly in cervical lesions. ADC values were affected by lesion composition, yet within each composition subgroup, benign and malignant lesions exhibited comparable values.

Anahtar Kelimeler

• Gynecologic masses
• diffusion-weighted imaging
• apparent diffusion coefficient
• malignant
• cervical cancer

Etik Beyan

The study was performed in accordance with the Declaration of Helsinki, and was approved by the Cumhuriyet University Non-Interventional Clinical Research Ethics Committee (Date: 20.02.2019, Approval No: 2019-02/26).

Kaynakça

1. Kim HJ, Lee SY, Shin YR, Park CS, and Kim K. The Value of Diffusion-Weighted Imaging in the Differential Diagnosis of Ovarian Lesions: A Meta-Analysis. PLoS One. 2016;11(2):e0149465. DOI: 10.1371/journal.pone.0149465.
2. Chandramohan A, Bhat TA, John R, and Simon B. Multimodality imaging review of complex pelvic lesions in female pelvis. Br J Radiol. 2020;93(1116):20200489. DOI: 10.1259/bjr.20200489.
3. Vargas HA, Barrett T, and Sala E. MRI of ovarian masses. J Magn Reson Imaging. 2013;37(2):265-81. DOI: 10.1002/jmri.23721.
4. Lin R, Hung YY, Cheng J, and Suh-Burgmann E. Accuracy of Magnetic Resonance Imaging for Identifying Ovarian Cancer in a Community-Based Setting. Womens Health Rep (New Rochelle). 2022;3(1):43-48. DOI: 10.1089/whr.2021.0106.
5. Salman S, Shireen N, Riyaz R, Khan SA, Singh JP, and Uttam A. Magnetic resonance imaging evaluation of gynecological mass lesions: A comprehensive analysis with histopathological correlation. Medicine (Baltimore). 2024;103(32):e39312. DOI: 10.1097/MD.0000000000039312.
6. Manoharan D, Das CJ, Aggarwal A, and Gupta AK. Diffusion weighted imaging in gynecological malignancies - present and future. World J Radiol. 2016;8(3):288-97. DOI: 10.4329/wjr.v8.i3.288.
7. Dhanda S, Thakur M, Kerkar R, and Jagmohan P. Diffusion-weighted imaging of gynecologic tumors: diagnostic pearls and potential pitfalls. Radiographics. 2014;34(5):1393-416. DOI: 10.1148/rg.345130131.
8. Mukuda N, Fujii S, Inoue C, et al. Apparent diffusion coefficient (ADC) measurement in ovarian tumor: Effect of region-of-interest methods on ADC values and diagnostic ability. J Magn Reson Imaging. 2016;43(3):720-5. DOI: 10.1002/jmri.25011.

9. Gladwish A, Milosevic M, Fyles A, et al. Association of Apparent Diffusion Coefficient with Disease Recurrence in Patients with Locally Advanced Cervical Cancer Treated with Radical Chemotherapy and Radiation Therapy. Radiology. 2016;279(1):158-66. DOI: 10.1148/radiol.2015150400.
10. Marconi DG, Fregnani JH, Rossini RR, et al. Pre-treatment MRI minimum apparent diffusion coefficient value is a potential prognostic imaging biomarker in cervical cancer patients treated with definitive chemoradiation. BMC Cancer. 2016;16:556. DOI: 10.1186/s12885-016-2619-0.
11. Onal C, Guler OC, and Yildirim BA. Prognostic Use of Pretreatment Hematologic Parameters in Patients Receiving Definitive Chemoradiotherapy for Cervical Cancer. Int J Gynecol Cancer. 2016;26(6):1169-75. DOI: 10.1097/IGC.0000000000000741.
12. Ali MN, Habib D, Hassanien AI, and Abbas AM. Comparison of the four malignancy risk indices in the discrimination of malignant ovarian masses: A cross-sectional study. J Gynecol Obstet Hum Reprod. 2021;50(5):101986. DOI: 10.1016/j.jogoh.2020.101986.
13. Gala FB, Gala KB, and Gala BM. Magnetic Resonance Imaging of Uterine Cervix: A Pictorial Essay. Indian J Radiol Imaging. 2021;31(2):454-67. DOI: 10.1055/s-0041-1734377.
14. Oh H, Park SB, Park HJ, et al. Ultrasonographic features of uterine cervical lesions. Br J Radiol. 2021;94(1121):20201242. DOI: 10.1259/bjr.20201242.
15. Duarte AL, Dias JL, and Cunha TM. Pitfalls of diffusion-weighted imaging of the female pelvis. Radiol Bras. 2018;51(1):37-44. DOI: 10.1590/0100-3984.2016.0208.
16. Liu R, Li R, Fang J, et al. Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors. Front Oncol. 2022;12:904323. DOI: 10.3389/fonc.2022.904323.
17. Roussel A, Thomassin-Naggara I, Darai E, Marsault C, and Bazot M. [Value of diffusion-weighted imaging in the evaluation of adnexal tumors]. J Radiol. 2009;90(5 Pt 1):589-96. DOI: 10.1016/s0221-0363(09)74025-9.
18. Fujii S, Kakite S, Nishihara K, et al. Diagnostic accuracy of diffusion-weighted imaging in differentiating benign from malignant ovarian lesions. J Magn Reson Imaging. 2008;28(5):1149-56. DOI: 10.1002/jmri.21575.
19. Kim H, Rha SE, Shin YR, et al. Differentiating Uterine Sarcoma From Atypical Leiomyoma on Preoperative Magnetic Resonance Imaging Using Logistic Regression Classifier: Added Value of Diffusion-Weighted Imaging-Based Quantitative Parameters. Korean J Radiol. 2024;25(1):43-54. DOI: 10.3348/kjr.2023.0760.
20. Tamai K, Koyama T, Saga T, et al. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol. 2008;18(4):723-30. DOI: 10.1007/s00330-007-0787-7.
21. Rizescu RA, Salcianu IA, Ionescu A, et al. The Added Role of Diffusion-Weighted Magnetic Resonance Imaging in Staging Uterine Cervical Cancer. Cureus. 2024;16(12):e75707. DOI: 10.7759/cureus.75707.
22. Chen J, Zhang Y, Liang B, and Yang Z. The utility of diffusion-weighted MR imaging in cervical cancer. Eur J Radiol. 2010;74(3):e101-6. DOI: 10.1016/j.ejrad.2009.04.025.
23. Naganawa S, Sato C, Kumada H, Ishigaki T, Miura S, and Takizawa O. Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix. Eur Radiol. 2005;15(1):71-8. DOI: 10.1007/s00330-004-2529-4.
24. McVeigh PZ, Syed AM, Milosevic M, Fyles A, and Haider MA. Diffusion-weighted MRI in cervical cancer. Eur Radiol. 2008;18(5):1058-64. DOI: 10.1007/s00330-007-0843-3.
25. Hou B, Xiang SF, Yao GD, et al. Diagnostic significance of diffusion-weighted MRI in patients with cervical cancer: a meta-analysis. Tumour Biol. 2014;35(12):11761-9. DOI: 10.1007/s13277-014-2290-5.
26. Liu Y, Ye Z, Sun H, and Bai R. Clinical Application of Diffusion-Weighted Magnetic Resonance Imaging in Uterine Cervical Cancer. Int J Gynecol Cancer. 2015;25(6):1073-8. DOI: 10.1097/IGC.0000000000000472.
27. Wang X, Song J, Zhou S, et al. A comparative study of methods for determining Intravoxel incoherent motion parameters in cervix cancer. Cancer Imaging. 2021;21(1):12. DOI: 10.1186/s40644-020-00377-0.
28. Ghardon SSL, Hemida R, Borg MA, Sallam HF, and Ahmed HM. Correlative study between apparent diffusion coefficient value and grading of cervical cancer. Egyptian Journal of Radiology and Nuclear Medicine. 2022;53(1):170.
29. Yang W, Qiang JW, Tian HP, Chen B, Wang AJ, and Zhao JG. Minimum apparent diffusion coefficient for predicting lymphovascular invasion in invasive cervical cancer. J Magn Reson Imaging. 2017;45(6):1771-79. DOI: 10.1002/jmri.25542.
30. Lura N, Wagner-Larsen KS, Ryste S, et al. Tumor ADC value predicts outcome and yields refined prognostication in uterine cervical cancer. Cancer Imaging. 2025;25(1):23.