Diagnostic accuracy of intraoperative consultation (frozen section) in borderline ovarian tumours and factors associated with misdiagnosis

Abstract

The objective of our study was to evaluate the accuracy of frozen section (FS) in borderline ovarian tumours (BOT) and to define the factors associated with misdiagnosis during FS evaluation. We performed a retrospective review of patients who underwent exploratory laparotomy for an adnexal mass, from January 2007 to July 2012, at a tertiary oncology centre in Turkey. Patients with a diagnosis of BOT either in FS or in permanent pathology were identified. Agreement between FS diagnosis and permanent histology was observed in 37/59 patients (62.7%), which gave a sensitivity and a positive predictive value of 71.2% and 84.1%, respectively. In patients with a diagnosis of BOT by frozen section only (n = 44), the diagnosis was consistent with permanent histopathology in 37/44 patients (84.1%). Frozen section interpreted a malignant tumour as BOT (under-diagnosis) in 6/44 (13.6%) of cases and interpreted a benign lesion as BOT (over-diagnosis) in 1/44 (2.3%) of cases. Slide review of discrepant cases revealed that major pathological causes of under-diagnosis were misinterpretation and sampling errors. Univariate analysis showed that presence of bilateral tumour and positive peritoneal cytology were associated with under-diagnosis. We concluded that, despite significant risk of under-diagnosis, FS analysis is an accurate method for intraoperative diagnosis of BOTs.

Factors associated with misdiagnosis of frozen section of mucinous borderline ovarian tumor

“…Our study demonstrated that the presence of bilateral mBOTs diagnosed by FS had a high probability of being malignant by permanent pathology. This finding is supported by another similar study by Basaran et al., 24 who evaluated patients with a diagnosis of BOT either by FS or permanent pathology and reported that the presence of bilateral tumors was associated with underdiagnosis. Notably, the patients included in the latter study were different from those in our study.…”

Frozen section diagnosis of borderline ovarian tumors with suspicious features of invasive cancer is a devil’s dilemma for the surgeon: A systematic review and meta‐analysis

“…Of these, 126 evaluated the use of frozen section technique in ovarian neoplasms (Figure 1). Twenty‐one studies discussed the use of qualifying terms in the case of frozen section results that could not rule out invasive carcinoma 6,11‐30 . Eleven of these actually reported on numbers of women with such frozen section diagnoses, using “at least borderline” 11,12,14,16,22,23,25‐28,30 .…”

“…Twenty-one studies discussed the use of qualifying terms in the case of frozen section results that could not rule out invasive carcinoma. 6,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] Eleven of these actually reported on numbers of women with such frozen section diagnoses, using "at least borderline". 11,12,14,16,22,23,[25][26][27][28]30 The study by Robinson et al was excluded from quantitative analysis because it was unclear whether the qualifying terms used in 11 women indicated a suspicion of a borderline ovarian tumor or invasive carcinoma (eg "suggestive of").…”

“…6,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] Eleven of these actually reported on numbers of women with such frozen section diagnoses, using "at least borderline". 11,12,14,16,22,23,[25][26][27][28]30 The study by Robinson et al was excluded from quantitative analysis because it was unclear whether the qualifying terms used in 11 women indicated a suspicion of a borderline ovarian tumor or invasive carcinoma (eg "suggestive of"). 11 The studies by Nili et al 26 and Yoshida et al 30 were also excluded from quantitative analysis because only the number of women with an "at least borderline" frozen section diagnosis prior to a permanent diagnosis of invasive carcinoma were reported.…”

Intraoperative Diagnosis Support Tool for Serous Ovarian Tumors Based on Microarray Data Using Multicategory Machine Learning

“…In the literature, accuracy of frozen sections in differentiating SBOTs ranges between 48% and 79%. 37 Several studies have investigated the reason for low accuracy in frozen-section diagnosis of SBOTs and found several clinicopathologic features for prediction of misdiagnosis. 5,38 They reported several factors including histologic type, spread outside the ovary, bilateral disease, and tumor sizes that were significantly associated with misdiagnosis.…”