Hoang Lien N, Zachara Susanna, Soma Anita, Köbel Martin, Lee Cheng-Han, McAlpine Jessica N, Huntsman David, Thomson Thomas, van Niekerk Dirk, Singh Naveena, Gilks C Blake
Department of Pathology and Laboratory Medicine, Vancouver General Hospital and University of British Columbia, Vancouver, Canada (L.N.H., S.Z., D.H., C.B.G.) Department of Histopathology, King Edward Memorial Hospital, Perth, Western Australia, Australia (A.S.) Department of Pathology and Laboratory Medicine, Calgary Laboratory Services and University of Calgary, Calgary, Canada (M.K.) Department of Laboratory Medicine and Pathology, Royal Alexandra Hospital and University of Alberta, Edmonton, Canada (C.H.L.) Department of Gynecology and Obstetrics, University of British Columbia, Vancouver, BC, Canada (J.N.M., D.H.) Department of Pathology, British Columbia Cancer Agency, Vancouver, BC, Canada (D.H., T.T., D.V.N.) Department of Cellular Pathology, Barts and the London NHS Trust, London, United Kingdom (N.S.).
Int J Gynecol Pathol. 2015 Nov;34(6):517-27. doi: 10.1097/PGP.0000000000000199.
Growing insights into the biological features and molecular underpinnings of ovarian cancer has prompted a shift toward histotype-specific treatments and clinical trials. As a result, the preoperative diagnosis of ovarian carcinomas based on small tissue sampling is rapidly gaining importance. The data on the accuracy of ovarian carcinoma histotype-specific diagnosis based on small tissue samples, however, remains very limited in the literature. Herein, we describe a prospective series of 30 ovarian tumors diagnosed using cytology, frozen section, core needle biopsy, and immunohistochemistry (p53, p16, WT1, HNF-1β, ARID1A, TFF3, vimentin, and PR). The accuracy of histotype diagnosis using each of these modalities was 52%, 81%, 85%, and 84% respectively, using the final pathology report as the reference standard. The accuracy of histotype diagnosis using the Calculator for Ovarian Subtype Prediction (COSP), which evaluates immunohistochemical stains independent of histopathologic features, was 85%. Diagnostic accuracy varied across histotype and was lowest for endometrioid carcinoma across all diagnostic modalities (54%). High-grade serous carcinomas were the most overdiagnosed on core needle biopsy (accounting for 45% of misdiagnoses) and clear cell carcinomas the most overdiagnosed on frozen section (accounting for 36% of misdiagnoses). On core needle biopsy, 2/30 (7%) cases had a higher grade lesion missed due to sampling limitations. In this study, we identify several challenges in the diagnosis of ovarian tumors based on limited tissue sampling. Recognition of these scenarios can help improve diagnostic accuracy as we move forward with histotype-specific therapeutic strategies.
对卵巢癌生物学特征和分子基础的深入了解促使治疗方法和临床试验向组织学类型特异性方向转变。因此，基于小组织样本的卵巢癌术前诊断正迅速变得重要起来。然而，关于基于小组织样本的卵巢癌组织学类型特异性诊断准确性的数据在文献中仍然非常有限。在此，我们描述了一个前瞻性系列研究，对30例卵巢肿瘤进行了细胞学、冰冻切片、粗针活检及免疫组织化学检查（检测p53、p16、WT1、HNF-1β、ARID1A、TFF3、波形蛋白和PR）。以最终病理报告作为参考标准，使用上述每种方法进行组织学类型诊断的准确性分别为52%、81%、85%和84%。使用卵巢亚型预测计算器（COSP）进行组织学类型诊断的准确性为85%，该计算器独立于组织病理学特征评估免疫组织化学染色结果。诊断准确性因组织学类型而异，在所有诊断方法中，子宫内膜样癌的诊断准确性最低（54%）。高级别浆液性癌在粗针活检时被过度诊断的情况最多（占误诊的45%），透明细胞癌在冰冻切片时被过度诊断的情况最多（占误诊的36%）。在粗针活检中，2/30（7%）的病例因取样限制而漏诊了更高分级的病变。在本研究中，我们确定了基于有限组织样本诊断卵巢肿瘤时存在的几个挑战。认识到这些情况有助于在我们推进组织学类型特异性治疗策略时提高诊断准确性。
