Diagnostic Value of Volumetric Histogram- Based Diffusion Analysis in the Differentiation between Benign &Malignant Gynecologic  Lesions

Sieza Samir Abd Allah; El said Mohamed Abd El Hady; Ghada Mohamed Gab Allah; Asmaa Hafez Mahmoud; Ahmed Mohamed Tawfik

doi:10.53730/ijhs.v6nS9.12825

Authors

Sieza Samir Abd Allah Professor of Diagnostic Radiology, Diagnostic radiology department, Mansoura University, Egypt
El said Mohamed Abd El Hady Professor of Gynecology and Obstetrics, Obstetrics & Gynecology department, Mansoura University, Egypt
Ghada Mohamed Gab Allah Professor of Diagnostic Radiology, Diagnostic radiology department, Mansoura University, Egypt
Asmaa Hafez Mahmoud
asmaahafez@mans.edu.eg
Assistant Lecturer of Diagnostic Radiology, Diagnostic radiology department, Mansoura University, Egypt
Ahmed Mohamed Tawfik Professor of Diagnostic Radiology, Diagnostic radiology department, Mansoura University, Egypt

Keywords:

Histogram diffusion metrics, magnetic resonance imaging

Abstract

Purpose: To evaluate the diagnostic value of volumetric histogram based diffusion analysis in the differentiation between benign and malignant gynecologic lesions & to compare it with the conventional partial slice mean apparent diffusion coefficient (ADC). Patients & methods: This is a prospective study included 80 patients with different gynecologic lesions. Fifty one patients had benign lesions & twenty nine patients had pathologically proved malignant lesions. All patients underwent Diffusion Weighted Imaging (DWI) of the pelvis. The images were evaluated qualitatively by visual assessment, then quantitatively using two different methods. The first method was the volumetric histogram based diffusion analysis (including minimum ADC, maximum ADC, mean ADC, kurtosis & skewness) & the second method was via evaluation of ADC by the conventional single slice method.

Results: There was statistically significant difference between benign and malignant lesions on qualitative DWI assessment (P<0.001). All malignant lesions displayed restricted diffusion. While most of benign lesions exhibited non restricted diffusion (n=35).

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References

Silvana C, Tara S l, Aparna B, et al, 2015. Imaging in endometrial carcinoma. Indian J Radiol Imaging. 25 (2): 137–147.

Tara D., Alexandra T, Andrea R.,2013. Functional Imaging to Predict Tumor Response in Locally Advanced Cervical Cancer. Curr Oncol Rep. 15 (6):549-558.

Koh W-J, Greer BE, Abu-Rustum NR, et al, 2013. Cervical cancer. J Natl Compr Canc Ne. 11(3):320–343

Mohaghegh P, Rockall AG, 2012. Imaging strategy for early ovarian cancer: characterization of adnexal masses with conventional and advanced imaging techniques. Radiographics.( 32): 1751-1773.

Spencer JA, Ghattamaneni S,2010. MR imaging of the sonographically indeterminate adnexal mass. Radiology. 256 (3):677–694.

Rajaram S, Maheshwari A, Srivastava A, 2015. Staging for vaginal cancer. Best Pract Res Clin Obstet Gynaecol .(29):822–832

Sala E, Rockall AG, Freeman SJ, et al, 2013. The added role of MR imaging in treatment stratification of patients with gynecologic malignancies: what the radiologist needs to know. Radiology. 266 (3):717–740.

Kuang F, Ren J, Huan Y, et al, 2012. Apparent diffusion coefficients of normal uterus in premenopausal women with 3.0-T magnetic resonance imaging. J Comput Assist Tomogr . (36): 54-59

Spencer JA, Weston MJ, Wilkinson N, 2014. Integration of imaging and pathology in the multidisciplinary process. In: Wilkinson N, ed. Pathology of the ovary, fallopian tube and peritoneum. London: Springer. P 109–131.

Nougaret S, Tirumani SH, Addley H, et al, 2013. Pearls and pitfalls in MRI of gynecologic malignancy with diffusion-weighted technique. AJR Am J Roentgenol. 200 (2):261–276.

Jie M, Lijing Z, Li Z, et al, 2017. Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT. Oncotarget. 8 (54): 92442-92453.

Otero-García M M, Mesa-Álvarez A, Nikolic O, Blanco-Lobato P, Basta-Nikolic M, de Llano-Ortega R M, et al. 2019. Role of MRI in staging and follow-up of endometrial and cervical cancer: pitfalls and mimickers. Insights into imaging; 10: (1), 19-19.

Duc NM and Huy HO, 2018. Effect of magnetic resonance imaging characteristics on uterine fibroid treatment. Reports in Medical Imaging ; 11 1–8.

Mansour S,Soha Hamed S, Sayed S and Hosny S, 2019. Role of diffusion MR imaging (DWI) and three-dimensional ultrasound (3D US)in the assessment of placental insufficiency in the gestational hypertension.Journal of radiology and Nuclear Medicine 50:50.

Addley H, Moyle P , Freeman S , 2017. Diffusion-weighted imaging in gynaecological malignancy, Clinical Radiology xxx. 1e10.

Lee Y • Kim K A • Song M J • Park Y S • Lee J • Choi J W • Lee C H, 2020. Multiparametric magnetic resonance imaging of endometrial polypoid lesions. Springer Science+Business Media, LLC, part of Springer Nature.

Gupta A, Gupta P, and Manaktala U, 2018. Varied Clinical Presentations, the Role of Magnetic Resonance Imaging in the Diagnosis, and Successful Management of Cervical Leiomyomas: A Case-Series and Review of Literature, Cureus 10(5): e2653.

DeMulder D , Ascher S M, 2018. Uterine Leiomyosarcoma: Can MRI Differentiate Leiomyosarcoma From Benign Leiomyoma Before Treatment? AJR Am J Roentgenol; 211(6):1405-1415

Nasr M O and Mohamed A F M, 2021. The value of the added diffusion-weighted images to multiparametric MRI in the early diagnosis of uterine cervix cancers and nodal assessment. Osman and Mourad Egyptian Journal of Radiology and Nuclear Medicine. 52:43.

Agostinho L, Horta M, Salvador J C, and Cunha T M, 2019. Benign ovarian lesions with restricted diffusion. Radiol Bras. 52 (2): 106–111.

Yuan X, Guo L, Du W, Mo F, Liu M, 2017. Diagnostic accuracy of DWI in patients with ovarian cancer. the journal. Medicine. 96:19(e6659).

Kierans AS, Bennett GL, Haghighi M, et al. 2014. Utility of conventional and diffusion-weighted MRI features in distinguishing benign from malignant endometrial lesions. Eur J Radiol; 83:726–732.

Kierans A S, Doshi A M, Dunst D, Popiolek D, Blank S V and Rosenkrantz A B, 2016. Retrospective Assessment of Histogram-Based Diffusion Metrics for Differentiating Benign and Malignant Endometrial Lesions. J Comput Assist Tomogr ;00: 00–00.

Ozturk M, Polat A V, Selcuk M B, 2021. Whole-lesion ADC histogram analysis versus single-slice ADC measurement for the differentiation of benign and malignant soft tissue tumors. European Journal of Radiology. Volume 143, October 2021, 109934.