IntroductionIntroductionBorderline ovarian tumors (BOTs) are described as histologically by a degree of cellular proliferation and nuclear atypia in the absence of infiltrative destructive growth or obvious stromal invasion (1). They are relatively uncommon with an incidence of 1.5–2.5 per 100,000 people per year (2). Borderline ovarian tumors comprise about 15 % of all epithelial tumors of the ovary. Histologically BOTs are serous, mucinous, endometrioid, clear cell and brenner types (3,4).

Surgical treatment has always been a crucial component of borderline ovarian tumor therapy. In case of women willing to retain their reproductive capacity, the decision to proceed with gonad-sparing treatment should be based on precise data. Because surgical decision-making is established intra-operatively, frozen section diagnosis must be sufficiently accurate to support conservative surgery.

We evaluated the diagnostic accuracy of frozen section analysis in BOT patients and identified the clinical features and treatment methods of the borderline ovary tumor cases.

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THE ACCURACY OF FROZEN SECTION DIAGNOSIS OF OVARIAN MASSES AND THE CLINICAL PROPERTIES OF THE BORDERLINE

OVARIAN TUMORS (BOTs) Guzin Kadir ¹, Bozdag Halenur ¹, Usta Akın ¹, Kabaca Sedef ¹, Yılmaz Burcu¹, Goynumer Gokhan¹, Gocmen Ahmet ², Akdeniz Duran Esra ³

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Patients & MethodsPatients & MethodsA total of 40 patients with histologically (frozen or permanent) BOTs, between January, 2000 and December, 2013 were included in the study.

The result of pathology as frozen or permanent paraffin section, surgical treatment methods, histological type of BOTs, preoperative CA 125 levels were reviewed and evaluated. Definite diagnosis was made according to paraffin section result. Correct diagnosis was described as the result of either pathologic section was same. Under diagnosis was used for a benign frozen result and over diagnosis was used for a malignant frozen section result or a borderline frozen result while permanent paraffin section was made borderline and benign respectively. The effect of all the variables (histological type, morphologic index, tumor size) on each diagnosis type were investigated.

Morphology indexing (MI) was performed according to a modification of the classification reported by De Priest and colleagues (5). Scoring system was based on Fig 1, where cut off points were based on the literature available (6).

The data were analyzed using the SPSS (SPSS Inc, Chicago, IL) version 17.0 statistical package and PROCEDURE MİXED İN SAS R (System 9.1, SAS Institute Inc., Cary, NC, USA).

ResultsResultsThe average age of the patients in the study was 49.3 ± 18.7 (range: 20-84) and 42.5% of the cases were found to be under 40 years. Histological distribution of permanent paraffin section was as follows: 1 (2.5%) adenofibroma, 4 (10%) Serous epithelial ovarian carcinoma, 35 (87.5%) BOTs. Histological distribution of borderline ovarian tumors was 1 (3%) brenner BOT, 1(3%) endometrioid BOT, 10 (30%) mucinous BOT, 23 (66 %) serous BOT respectively. The mean of tumors size was 11.7 cm (range: 3-30 cm) ( 8 cm for serous BOTs and 3.5 cm for mucinous BOTs). The above cut off value of CA 125 level was only detected in ten cases (9 cases in BOTs and 1 case in malign ovarian carcinoma). The mean value was 115 U/ml (41-442 U/ml ).

The mean morphology index score of BOTs and malignant ovarian tumors were 5±2 and 7.5±2.3, respectively. There was no statistically significant difference between the groups.

Among the 36 patients with frozen section confirmed as BOT, 28 patients (78 %) were correctly diagnosed by frozen section analysis. Under-diagnosis and over-diagnosis occurred in 6 of 36 (17%) and 2 of 36 patients (5%), respectively. Sensitivity, and positive predictive values of the frozen section diagnosis of BOT were 93.3% and 82.3% respectively. Positive likelihood ratio is 0.93 (95% CI: 0.85 to 1.03).

According to outcomes univariate analysis, it is found that histological type has a very significant effect on accuracy of diagnosis (p=0.001) while morphological classification (p=0.67) and tumor size (p=0.39) have no significant effects (Table 1). In the multiple exact logistic regression analysis (Table 2), none of the variables have significant effect on diagnosis type.

The distribution of applied surgical methods were outlined in Table 3.

ConclusionConclusionFrozen section is the first pathological evaluation for suspicious adnexial masses and has greatly impact on the surgical approach over gynaecologic oncology patients (7). Accuracy of frozen section in this period is important to designate the extent of surgery. This decision is important especially in woman who demands to preserve her fertility or is pregnant at the time of diagnosis (8). On the basis of these results, we conclude that the accuracy of the frozen section analysis is quite high for distinguishing malignant and benign cases. However, the highest rate of false diagnosis with frozen section analysis for BOTs should be kept in mind. If fertility sparing surgery was performed, patients should be informed in terms of recurrence and be followed (9).

ReferencesReferences1)Seidman JD, Russell P, Kurman RJ. Surface epithelial tumors of the ovary. In: Blaustein's pathology of the female genital tract, 5th, Kurman RJ (Ed), Springer Verlag, New York 2002. p.791.2)Gershenson DM. Clinical management potential tumours of low malignancy. Best Pract Res Clin Obstet Gynaecol 2002; 16:513–527.3)Acs G. Serous and mucinous borderline (low malignant potential) tumors of the ovary. Am J Clin Pathol 2005; 123[suppl]:S13–S57.4). Jones MB. Borderline ovarian tumors: current concepts for prognostic factors and clinical management. Clin Obstet Gynecol 2006; 49:517–525.5) DePriest PD, Shenson D, Fried A, Hunter JE, Andrews SJ, Gallion HH, et al. A morphology index based on sonographic findings in ovarian cancer. Gynecol Oncol 1993;51:7–11.6) Ueland FR, DePriest PD, Pavlik EJ, Kryscio RJ, van Nagell JR Jr. Preoperative differentiation of malignant from benign ovarian tumors: The efficacy of morphology indexing and Doppler flow sonography. Gynecol Oncol 2003; 91: 46-50.7) Baker P, Oliva E. A practical approach to intraoperative consultation in gynecological pathology. Int J Gynecol Pathol 2008; 27: 353-65.8) Rao GG, Skinner EN, Gehrig PA, Duska LR, Miller DS, Schorge JO. Fertility-sparing surgery for ovarian low malignant potential tumors. Gynecol Oncol. 2005 Aug; 98(2): 263- 6.9) Romeo M, Pons F. Incomplete staging surgery as a major predictorn of relapse of borderline ovarian tumor . World J Surg Oncol. 2013 Jan 23;11:13.

Table 1. Patient characteristics and diagnostic performance of frozen section evaluation in BOTs

BOZDAG, HALENUR MDBOZDAG, HALENUR MDDepartment of Obstetrics and Gynecology, İstanbul Medeniyet University Göztepe Teaching and Research Hospital, Istanbul, Turkey

halenurbozdag@hotmail.com , +905355909472

Table 2. Multiple Exact Logistic Regression Analysis Results

Table 3. The distribution of cases according to the surgical methods and mean age

Fig 1. Pictorial representation of morphology index for ovarian tumors

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