Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Gynecological Masses

Eman Mosad Fawzy Elsafty

Department of Radiodiagnosis, Faculty of Medicine, Tanta University, Tanta, Egypt.

Amr Mohamed Tawfek EL-Badry

Department of Radiodiagnosis, Faculty of Medicine, Tanta University, Tanta, Egypt.

Ayman Abd El Aziz El Dorf

Department of Obestetrics and Gynecology, Faculty of Medicine, Tanta University, Tanta, Egypt.

Alaa Mohamed Reda

Department of Radiodiagnosis, Faculty of Medicine, Tanta University, Tanta, Egypt.

*Author to whom correspondence should be addressed.


Abstract

Background: Diffusion-weighted MRI has potential for tissue differentiation, including cancer. It can also determine cancer histologic type. The ADC value reflects tumor cellular density, allowing tumor grading evaluation. This study aims to assess the role of DW-MRI in gynecological masses.

Methods: This prospective cross-sectional research was conducted on 30 female patients between the ages of 20 and 75 who were sent from the gynaecological department to the Radio diagnostic and Medical Imaging department at Tanta University hospitals. All patients gave their informed permission in writing. We included patients with clinically or sonographically suspected uterine and cervical lesions. Patients having indeterminate ultrasonography criteria for adnexal lesions.

Results: Resistance Index (RI) showed significant predictive value of the malignant masses (p=0.13), with an area under curve (AUC) of 0.84. An RI cutoff value of ≥0.365 could predict malignant masses with a sensitivity of 81.8% and specificity of 87.5%. T ROC curve analysis to assess the validity of ADC to discriminate malignant masses is illustrated. ADC values showed significant predictive value of the malignant masses (p<0.001*), with an area under curve (AUC) of 0.89. An ADC cutoff value of ≤1 could predict malignant masses with a sensitivity of 85.7% and specificity of 89.5%.

Conclusions: Combined ultrasound and MRI examination produced radiologic findings with 98 percent sensitivity, 92.9 percent specificity, 95 percent positive predictive value, and 97 percent negative predictive value when compared to the final pathologic diagnosis. The research indicated that DWI and ADC mapping are excellent imaging methods for discriminating benign from malignant tumours with a high degree of sensitivity and specificity. However, their effectiveness and benefits depend on a precise diagnosis of the lesions' essential features, such as their origin, size, and composition, as assessed by ultrasound and standard MRI tests.

Keywords: Diffusion weighted magnetic resonance imaging, gynecological, masses


How to Cite

Elsafty , Eman Mosad Fawzy, Amr Mohamed Tawfek EL-Badry, Ayman Abd El Aziz El Dorf, and Alaa Mohamed Reda. 2023. “Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Gynecological Masses”. Journal of Advances in Medicine and Medical Research 35 (21):80-96. https://doi.org/10.9734/jammr/2023/v35i215214.

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References

Lupean RA, Ștefan PA, Csutak C, Lebovici A, Măluțan AM, Buiga R, et al. Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis. Medicina (Kaunas). 2020;56:78-92.

Nougaret S, Nikolovski I, Paroder V, Vargas HA, Sala E, Carrere S, et al. MRI of Tumors and Tumor Mimics in the Female Pelvis: Anatomic Pelvic Space-based Approach. Radiographics. 2019;39:1205-29.

Duarte AL, Dias JL, Cunha TM. Pitfalls of diffusion-weighted imaging of the female pelvis. Radiol Bras. 2018;51:37-44.

Addley H, Moyle P, Freeman S. Diffusion-weighted imaging in gynaecological malignancy. Clin Radiol. 2017;72:981-90.

Yajima R, Kido A, Kurata Y, Fujimoto K, Nakao KK, Kuwahara R, et al. Diffusion-weighted imaging of uterine adenomyosis: Correlation with clinical backgrounds and comparison with malignant uterine tumors. J Obstet Gynaecol Res. 2021;47:949-60.

Stolyarova IV, Yakovleva EK, Sharakova VV. [Evaluation of diagnostic effectiveness of the method of diffusion-weighted MR-images in diagnosis of pathology of the uterine body]. Vopr Onkol. 2015;61:986-93.

Abd El Hafeez MN, Ahmed EA, Mohammad EM, El Sayed HA, Abdel-Tawab M. Role of diffusion-weighted magnetic resonance imaging in the characterization of uterine neoplasms. Curr Med Res Pract. 2020;5:33-7.

Keriakos NN, Darwish E. Diffusion weighted imaging in suspicious uterine tumors; how efficient is it? Egypt J Radiol Nucl Med. 2018;49:838-45.

El-Sayed E-SM, Abdullah MS, Ali HG. The role of diffusion-weighted MRI on the differentiation of complex adnexal masses. Menoufia Medical Journal. 2019;32:881.

Ali RF, Nassef HH, Ibrahim AM, Chalabi NAM, Mohamed AM. The Role of Diffusion Weighted Imaging in suspected cases of ovarian cancer. Egyptian Journal of Radiology and Nuclear Medicine. 2020;51:1-11.

Türkoğlu S, Kayan M. Differentiation between benign and malignant ovarian masses using multiparametric MRI. Diagn Interv Imaging. 2020;101:147-55.

Abd Elsamie HA, El-Rasheedy MI, Mohammed MA. Evaluating the role of MRI with diffusion-weighted images in diagnosis of uterine focal lesions. Al-Azhar Assiut Medical Journal. 2019;17:103.

Osman NM, Mourad MA-f. The value of the added diffusion-weighted images to multiparametric MRI in the early diagnosis of uterine cervix cancers and nodal assessment. Egypt J Radiol Nucl Med. 2021;52:1-8.

Elsammak A, Shehata S, Abulezz M, Gouhar G. Efficiency of diffusion weighted magnetic resonance in differentiation between benign and malignant endometrial lesions. Egypt J Radiol Nucl Med. 2017;48:751-9.

Dimova J, Zlatareva D, Bakalova R, Aoki I, Hadjidekov G. Adnexal masses characterized on 3 tesla magnetic resonance imaging - added value of diffusion techniques. Radiol Oncol. 2020;54:419-28.

Agostinho L, Horta M, Salvador JC, Cunha TM. Benign ovarian lesions with restricted diffusion. Radiol Bras. 2019;52:106-11.

Dhanda S, Thakur M, Kerkar R, Jagmohan P. Diffusion-weighted imaging of gynecologic tumors: diagnostic pearls and potential pitfalls. Radiographics. 2014;34:1393-416.

El-Sayed E-SM, Abdullah MS, Ali HG. The role of diffusion-weighted MRI on the differentiation of complex adnexal masses. Menoufia Med J. 2019;32:881.

Sharma H, Kumar M, Pandey A, Kumar L, Nishi N. Gynaecological Pelvic Masses: A Clinical Challenge – Radiological Evaluation using Ultrasound and CT with Pathological Correlation. Int J Contemp Med. 2019;4:148-87.

Abd-Elmageed MK, Mohamed RA, Elaziz Maaly MA. Role of MRI Diffusion Weighted Imaging in Evaluation of Gynecological Pelvic Masses. Egypt J Hosp Med. 2021;85:3857-64.

Rai R, Bhutia PC, Tshomo U. Clinicopathological profile of adnexal masses presenting to a tertiary-care hospital in Bhutan. South Asian J Cancer. 2019;8:168-72.

Cass GK, Newton C. The pelvic mass: assessment and evaluation. Obstet Gynaecol Reprod Med. 2020;30:139-45.

Guo W, Zou X, Xu H, Zhang T, Zhao Y, Gao L, et al. The diagnostic performance of the Gynecologic Imaging Reporting and Data System (GI-RADS) in adnexal masses. Ann Transl Med. 2021;9:39-58.

Rai R, Bhutia PC, Tshomo U. Clinicopathological profile of adnexal masses presenting to a tertiary-care hospital in Bhutan. South Asian J Cancer. 2019;8:168-72.

Karimi-Zarchi M, Mojaver SP, Rouhi M, Hekmatimoghaddam SH, Moghaddam RN, Yazdian-Anari P, et al. Diagnostic Value of the Risk of Malignancy Index (RMI) for Detection of Pelvic Malignancies Compared with Pathology. Electron Physician. 2015;7:1505-10.

Terzic MM, Dotlic J, Likic I, Ladjevic N, Brndusic N, Arsenovic N, et al. Current diagnostic approach to patients with adnexal masses: which tools are relevant in routine praxis? Chin J Cancer Res. 2013;25:55-62.

Alamri F, Abdelfattah EH, Sait K, Anfinan NM, Sait H. Building a Predictive Model for Gynecologic Cancer Using Levels of Data Analytics. Academic Journal of Applied Mathematical Sciences. 2021;7:192-7.

Rauh-Hain JA, Melamed A, Buskwofie A, Schorge JO. Adnexal mass in the postmenopausal patient. Clin Obstet Gynecol. 2015;58:53-65.

Lovely K, Rajesh M, Kaushal L. Real Time Ultrasonographic Evaluation of Gynecological Pelvic Masses-a Prospective Study. J Evol Med Den Sci. 2013;2:47-83.

Neeyalavira V, Tongsong T, Wanapirak C. Doppler indices for prediction of benign and malignant ovarian tumor. Thai J Obstet Gynaecol. 2008;84:55-63.

Majeed H, Ramzan A, Imran F, Mahfooz ur R. Validity of resistive index for the diagnosis of malignant ovarian masses. J Pak Med Assoc. 2011;61:1104-7.

Abbas AM, Zahran KM, Nasr A, Kamel HS. A new scoring model for characterization of adnexal masses based on two-dimensional gray-scale and colour Doppler sonographic features. Facts Views Vis Obgyn. 2014;6:68-74.

Mansour TM, Tawfik MH, El-Barody MM, Sileem SA, Okasha A. Correlation between ultrasound and Magnetic Resonance Imaging in diagnosis of Ovarian Tumors. Al-Azhar Int Med Jo. 2020;1:214-23.

Hamed MK, Aborashed AA, Ria HFA, Tawfik MH. Ultrasound and diffusion MRI in evaluation of ovarian lesions. Scientific J Al-Azhar Med Faculty Girls. 2021;5:90-1.

Forstner R, Thomassin-Naggara I, Cunha TM, Kinkel K, Masselli G, Kubik-Huch R, et al. ESUR recommendations for MR imaging of the sonographically indeterminate adnexal mass: an update. Eur Radiol. 2017;27:2248-57.

Zhang H, Zhang GF, Wang TP, Zhang H. Value of 3.0 T diffusion-weighted imaging in discriminating thecoma and fibrothecoma from other adnexal solid masses. J Ovarian Res. 2013;6:58-9.

Inci E, Kilickesmez O, Hocaoglu E, Aydin S, Bayramoglu S, Cimilli T. Utility of diffusion-weighted imaging in the diagnosis of acute appendicitis. European radiology. 2011;21:768-75.

Ali RF, Nassef HH, Ibrahim AM, Chalabi NAM, Mohamed AM. The Role of Diffusion Weighted Imaging in suspected cases of ovarian cancer. Egypt J Radiol Nucl Med. 2020;51:1-11.

Crestani A, Theodore C, Levaillant JM, Thomassin-Naggara I, Skalli D, Miaihle G, et al. Magnetic Resonance and Ultrasound Fusion Imaging to Characterise Ovarian Masses: A Feasibility Study. Anticancer Res. 2020;40:4115-21.