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 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 35  |  Issue : 3  |  Page : 401-406

Diffusion-weighted magnetic resonance imaging for the characterization of ovarian tumors in the reproductive age group


1 Department of Diagnostic Radiology, Meet Ghamer Oncology Center, Mansoura, Egypt
2 Department of Diagnostic Radiology, Benha University, Benha, Egypt

Date of Submission22-Jul-2018
Date of Acceptance18-Sep-2018
Date of Web Publication07-Jan-2019

Correspondence Address:
Samar El-Ghazaly Taalab
Department of Diagnostic Radiology, Meet Ghamer Oncology Center, Meet Ghamer, Mansoura
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/bmfj.bmfj_160_18

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  Abstract 


Aim/objective This study aims at emphasizing the role of Diffusion-weighted MR imaging in characterization of ovarian tumors at reproductive age group.
Background Ovarian tumors are relatively common and represent approximately 6% of female malignancies. Although the final diagnosis of an ovarian tumor is based on the histological examination, the accurate characterization of ovarian masses as benign or malignant could avoid unnecessary surgery and allow young females (in reproductive age group) to go for conservative treatment. Diffusion Weighted Imaging (DWI) depends on Brownian motion phenomenon which describe the random motion of molecules of water and how it is affected by tissue cellularity and microstructures. As a result, malignant ovarian tumors due to its hyper cellular nature show diffusion restriction, unlike most benign tumors.
Patients and Methods MRI Unit, Radio diagnosis department, Meet Ghamer oncology center and Banha University hospital. A cross sectional study, included 30 women who presented with suspicious adnexal masses on previous ultrasound examination and referred for further assessment by DW-MRI. Post-menopausal females and females with contraindications to MRI (e.g. cardiac prosthesis, metallic implants and sever claustrophobia) are excluded.
Results The study included 30 women ranging in age between 19 and 49 years with mean age 33.03 ± 9.9. Out of 30 cases, 11 had malignant ovarian tumors while 19 had benign tumors.
Conclusion Adding DWI to conventional MRI increases the specificity and accuracy of MRI study.

Keywords: diffusion weighted, ovarian tumors, reproductive age group


How to cite this article:
Taalab SE, Reffat MM, Elshazly IM. Diffusion-weighted magnetic resonance imaging for the characterization of ovarian tumors in the reproductive age group. Benha Med J 2018;35:401-6

How to cite this URL:
Taalab SE, Reffat MM, Elshazly IM. Diffusion-weighted magnetic resonance imaging for the characterization of ovarian tumors in the reproductive age group. Benha Med J [serial online] 2018 [cited 2019 Dec 15];35:401-6. Available from: http://www.bmfj.eg.net/text.asp?2018/35/3/401/249416




  Introduction Top


In fact when imaging findings cannot be categorized into benign or malignant lesions, ovarian masses present a special diagnostic challenge [1].

As biopsy is not commonly applicable, preoperative imaging-based diagnosis of ovarian tumors is important [2].

Ultrasonography, computed tomography, and MRI are currently used for the evaluation of ovarian tumors.

Diffusion-weighted imaging (DWI) is a noninvasive modality that increases the contrast between lesions and the surrounding tissues; it helps in the discrimination between benign and malignant lesions and improves the detection and delineation of peritoneal implants at both initial staging and follow-up. Moreover, DWI provides quantitative information about the cellular structure of the tissue that helps to distinguish treatment-related changes from viable tumors [3].

DWI demonstrates high intensity not only at the primary tumor site but also in disseminated peritoneal implants in patients with malignant ovarian tumors, when added to the findings of conventional MRI [4].

Our study aims at reviewing and emphasizing the role of diffusion-weighted MRI as a noninvasive and cost-effective technique in the characterization of ovarian tumors at the reproductive age group.


  Patients and methods Top


A cross-sectional study was performed on 30 patients referred to us from the surgical and gynecological departments as ovarian masses based on abdominal and transvaginal ultrasound study. Pelvic MRI with DWI and histopathological correlation was done.

The study was conducted at the Meet Ghamer Oncology Center and Benha University in the period from April 2016 to April 2018.

The patient’s age ranged from 19 to 49 years; 12 patients presented with vague pelvic pain, three were complaining of abdominal swelling, 12 patients were presented with vaginal bleeding, and three patients presented with primary infertility.

Our patients had been subjected to the following: complete history taking: patient age, menstrual history, previous history of gynecological complications or operations, and checking for contraindication to MRI imaging (e.g. pacemakers, metallic implants, and severe claustrophobia).


  Magnetic resonance imaging Top


MRI was performed on a 1.5-T MRI unit in the supine position using a pelvic phased-array torso coil. The patients were prepared by fasting for 6 h before postcontrast MRI. To diminish bowel peristalsis, intravenous 10 mg of visceralgine (an antispasmodic drug) was given immediately before MRI. UB should be at least half full.

Magnetic resonance imaging protocol

  1. Axial T1-weighted image, axial T2-weighted image, and postcontrast fat-suppressed image :(slice thickness, 6 mm; gap, 1 mm. Field of view (FOV), 32–42 cm; matrix 256×256.
  2. Coronal and sagittal T2-weighted image (slice thickness, 8–10 mm; gap, 1 mm; FOV, 40–50 cm; matrix, 256×256).
  3. DW-MRI DWI was acquired in the axial plane by using a single-shot echo-planar imaging sequence, prior to the administration of a contrast medium, with b values of 0, 500, 1000 for each section (matrix, 128×128;FOV, 40 cm; section thickness, 4–6 mm; gap 1 mm). Apparent diffusion coefficient (ADC) maps are then constructed for all DWI.


Interpretation of magnetic resonance imaging

Images of MRI were analyzed for the following: laterality, morphology, size, signal intensity and enhancement of the lesion wall thickness and regularity; presence of solid vegetation, septation, and solid component; and also for the presence of infiltrated pelvic or para-aortic lymph nodes, peritoneal, omental deposits, and ascites.

Interpretation of diffusion-weighted imaging

Qualitative analysis

As regards signal intensity, if the lesion shows low signal intensity on diffusion images with high signal in the corresponding ADC maps it is considered to be facilitated for benign masses yet if it shows high-signal intensity on diffusion images with lowering of the signal in the corresponding ADC maps it is considered to be restricted for malignant masses.

Quantitative analysis

ADC maps were generated and then ROI were manually selected on the solid and the cystic component of the tumors, which was then automatically calculated on the work station to get the ADC values.

Data were statistically described in terms of mean±SD and range, or frequencies (number of cases) and percentages when appropriate. Comparisons of numerical variables between the studied groups were established using Student’s t test for independent samples. Accuracy was represented using the terms sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy. In addition, comparison between groups was established using the unpaired t test, Mann–Whitney test and Kruskal–Wallis test. A P value less than 0.05 was considered statistically significant. All statistical calculations were done using computer programs statistical package for the social sciences (version 15; SPSS Inc., Chicago, Illinois, USA) for Microsoft Windows image evaluation ([Figure 1] and [Figure 2]).
Figure 1 A 22 year-old female patient complaining of abdominal pain. Conventional MRI (a–c) showed well-defined right ovarian mixed signal intensity lesion displaying mixed high signal fatty and low signal cystic element with fat fluid intensity and suppression of signal in fat suppression denoting fat content and slight wall enhancement in postcontrast images. DWI (d and e), the lesion showing an area of restricted diffusion that showed high signal on DWI with low signal on the corresponding ADC map. ADC value of the tumor (0.92×10−3 mm2/s) for the cystic component and (1.1×10−3 mm2/s) for the solid component (conventional and DWI-MRI): benign looking right adnexal cystic lesion likely dermoid. Pathology showed mature cystic teratoma (benign germ cell tumor). Mature cystic teratoma showed restricted diffusion may be attributed to keratinoid substance and Rokitansky protuberance. DWI, diffusion-weighted imaging.

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Figure 2 A 49-year-old female patient, known case of cancer stomach complaining of vaginal bleeding. (a–c) Conventional MRI showed bilateral mainly solid adnexal masses eliciting low T1 signal, high T2 and STIR signal with moderate heterogeneous postcontrast enhancement, no fatty elements or calcification. DWI, the lesions show high signal on DWI (d), low signal on ADC (e), and an ADC value of 0.899×10−3 mm2/s. Conventional and DWI-MRI: bilateral metastatic lesions. Pathology showed bilateral Krukenberg tumor. DWI, diffusion-weighted imaging.

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  Results Top


In our study 30 patients who are in the reproductive age (12–49 years) are included. The patients age ranged from 19 to 49 years (mean age±SD, 33.03±9.9). We divide the patients as regards age into two groups, group less than 35 years 53.3 and group more than or equal to 35 years 46.7%. The tumors pathologically were classified into: 11 malignant and 19 benign tumors ([Table 1] and [Table 2]).
Table 1 Pathology of tumors of study cases

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Table 2 Histopathology of tumors of study cases

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According to MRI ([Table 3]) 11 cases showed typical criteria of malignant lesions, as size more than 6 cm, wall thickness and septa more than 3 mm, and solid vegetation more than 1 cm, while two cases (false positive) were suspected to be malignant as regards the size, thick septa, and solid nodule, yet proved to be benign by pathology (one mature cystic teratoma and one serous cystic adenoma).
Table 3 Validity of MRI in the diagnosis of malignant lesions

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According to DWI ([Table 4] and [Table 5]) 11 cases showed restricted diffusion (high signal in diffusion images, low signal on the corresponding ADC map and low ADC values range from 0.69 to 0.96 with an average of 0.828×10−3 mm2/s; all these cases proved to be malignant pathologically while 18 cases showed facilitated diffusion (low signal in diffusion images, high signal on the corresponding ADC map and high ADC values range from 1.3 to 2.5 with an average of 1.7×10−3 mm2/s; all these cases proved to be benign pathologically, one case of mature teratoma (false positive) showed slight high signal in diffusion images, slight low signal on the corresponding ADC map and low ADC values (0.924×10−3 mm2/s) for cystic component and (1.16×10−3 mm2/s) for solid component due to mixed cellularity of the cystic component.
Table 4 ADC mean value of cystic and solid lesions in studied cases according to age groups and tumor type

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Table 5 Validity of diffusion-weighted imaging-MRI in the diagnosis of malignant lesions

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There are highly significant differences between the mean of solid lesions in each age group and the nature of tumor.


  Discussion Top


Ovarian carcinomas are considered the fifth to sixth most common cancer among women, causing more deaths every year than any other gynecological malignancies in women worldwide [5]. One of the promising new functional imaging techniques for the evaluation of ovarian tumors is DWI. Combining interpretation of DWI with conventional MRIs and with realizing of the possible pitfalls, it has shown to be effective in the differentiation of benign from malignant ovarian masses [6]. Our study includes 30 patients at the reproductive age group. We noticed that the mean age±SD of patients of benign tumors was 30.52±7.62 and that of malignant tumors was 40.57±9.5. Percentage of malignant tumors in the group (<35 years old was 25% and in the group ≥35 years old was 50%). The National Cancer Institute reports that the percentage of new cases of ovarian cancer found among women more than or equal to 35 years old is higher than among women less than 35 years old. In our study according to DWI: the sensitivity of MRI and DWI was the same (100%). The specificity was higher for DWI (94.7%) compared with the conventional MRI sequences (89.5%), as well as the accuracy which was 93.3% for MRI while that of DWI was 96.7%, so addition of DWI to the MRI is expected to increase the specificity and the accuracy of examination ([Figure 3]).The best cutoff of ADC mean value of solid lesions in the diagnosis of presence of benign tumor is more than or equal to 0.929 with a sensitivity of 100%, specificity of 91.9%, and accuracy of 96.7% with a P value less than 0.001 denoting high statistical significance. Endometriomas showed high signal on both DWI and the corresponding ADC map and ADC values 1.3 to 1.4×10−3 mm2/s, which can be explained as T2 shine through. A study was carried out by Fujii and colleagues in 2008 [8] on 123 ovarian tumors including 81 benign and 42 malignant lesions, most benign tumors did not show abnormal high signal intensity on DWI while most malignant ovarian tumors as well as some of the mature cystic teratomas showed high signal intensity on DWI. This agrees with our results that all malignant lesions (11 cases) and one case of mature cystic teratoma showed high signal on DWI. A similar study was carried out by Metwally and colleagues in 2017 [7] which included 30 women who presented with suspicious adnexal masses (12 benign and 18 malignant). The mean ADC value in cases of benign tumors (1.22±0.20×10−3) and that of malignant tumors (0.82±0.07×10−3) with a P value less than 0.001 denoting high statistical significance, while in our study the mean ADC value in cases of benign tumors was 1.71±0.4×10−3 and that of malignant tumors was 0.83±0.08×10−3. The best cutoff value of ADC was 0.91 with a sensitivity of 94.4%, specificity of 91.7%, and diagnostic accuracy of 93.3% on the ROC curve which is similar to the best cutoff value of our study, 0.929 with a sensitivity of 100%, specificity of 91.9%, and diagnostic accuracy of 96.7%. A study was carried out by Takeuchi and colleagues in 2010 on [2] 47 women (10 benign, six borderline, and 33 malignant tumors). The mean±SD ADC value in malignant tumors was 1.03×10−3 (0.19) mm2/s which was significantly lower than that in the 10 benign tumors (1.38×10−3 (0.30) mm2/s). In our study the mean ADC value in malignant tumors (0.83×10−3 mm2/s) was also significantly lower than that in benign tumors (1.71×10−3 mm2/s). Using a cutoff ADC value of 1.15, malignant lesions had a sensitivity of 74%, specificity of 80%, positive predicative value (PPV) of 94%, and negative predicative value (NPV) of 44% compared with our study cutoff value of 0.929, benign lesion had a sensitivity of 100%, specificity of 91.9%, PPV of 95%, and an NPV of 100%. Another study was carried out by Li and colleagues in 2011 [9] on 127 patients with pelvic masses (85 malignant and 46 benign). The aim of this study was to evaluate the differences in ADC values for the solid component of benign and malignant ovarian surface epithelial tumors. In their study, the sensitivity, specificity, PPV, NPV, and accuracy of conventional MRI all have increased from 91.8, 78.3, 88.6, 83.7, and 87.0%, respectively, to 96.5, 89.1, 94.3, 93.2, and 93.1% after adding DWI to the conventional MRI. This was comparable to our study as addition of DWI to conventional MRI raises the specificity, PPV, and accuracy from 89.5, 84.6, and 93.3 to 94.7, 91.7, and 96.7%, respectively.
Figure 3 Combined bar chart showing tumor types according to histopathology, MRI, and DWI. DWI, diffusion-weighted imaging.

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  Conclusion Top


Our study which was conducted on 30 ovarian masses showed that addition of DWI to conventional MRI increases radiologist’s confidence in image interpretation, which will improve patient’s outcome and prognosis as it improves the specificity and accuracy of MRI study.

Acknowledgements

Sources of support in the form of equipment: Meet Ghamer Oncology Center.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Pierce N, Narayanan P, Sahdev A, Reznek R, Rockall A. Ovarian lesions pose diagnostic dilemmas. Diagnostic Imaging Eur 2008; 24:14–18.  Back to cited text no. 1
    
2.
Takeuchi M, Matsuzaki K, Nishitani H. Diffusion-weighted magnetic resonance imaging of ovarian tumors: differentiation of benign and malignant solid components of ovarian masses. J Comput Assist Tomogr 2010; 34:173–176.  Back to cited text no. 2
    
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Kyriazi S, Kaye SB, deSouza NM. Imaging ovarian cancer and peritoneal metastases, current and emerging techniques. Nat Rev Clin Oncol 2010; 7:381–393.  Back to cited text no. 3
    
4.
Namimoto T, Awai K, Nakaura T, Yanaga Y, Hirai T, Yamashita Y et al. Role of diffusion-weighted imaging in the diagnosis of gynecological diseases. Eur Soc Radiol 2008; 19:745–760. doi: 10.1007/s00330-008-1185-5.  Back to cited text no. 4
    
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Jemal A, Siegel R, Xu J, Ward E. Cancer statistics2010. Cancer J Clin 2010; 60:277–300.  Back to cited text no. 5
    
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Thomassin-Naggara I, Balvay D, Aubert E. Quantitative dynamic contrast-enhanced MR imaging analysis of complex adnexal masses: a preliminary study. Eur Radiol 2011; 22:738–745.  Back to cited text no. 6
    
7.
Metwally ES, Abdul Rahim SAA, Mazzohi HA. Role of diffusion weighted MRI in characterization of ovarian tumors. Egypt J Hosp Med 2017; 69:1778–1785.  Back to cited text no. 7
    
8.
Fujii S, Kakite S, Nishihara K. Diagnostic accuracy of diffusion weighted imaging in differentiating benign from malignant ovarian lesions. J Magn Reson Imaging 2008; 28:1149–1156.  Back to cited text no. 8
    
9.
Li W, Chu C, Cui Y. Diffusion-weighted MRI: a useful technique to discriminate benign versus malignant ovarian surface epithelial tumors with solid and cystic components. 29 October 2011. Available at: http://www. springerlink.com/content/g484143375287361/.  Back to cited text no. 9
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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