The Discrepancy between Preoperative Tumor Markers and Imaging Outcomes in Predicting Ovarian Malignancy

Simple Summary Preoperative tumor markers and imaging often differ in predicting whether an ovarian tumor is malignant. We evaluated the correlation between the predictive values of imaging and tumor markers for diagnosing ovarian tumors, especially when there were discrepancies between the two. We found that, to prevent misidentification, it is necessary to understand the underlying disease that can increase tumor marker levels or benign tumors, which are difficult to distinguish from malignant tumors in imaging tests and several rare histopathologies with low risk of ovarian malignancy algorithm values. The malignant prediction of tumor markers and imaging was different in many patients with ovarian tumors, and this study will help to reduce the misidentification of tumors. Abstract Preoperative tumor markers and imaging often differ in predicting whether an ovarian tumor is malignant. Therefore, we evaluated the correlation between the predictive values of imaging and tumor markers for diagnosing ovarian tumors, especially when there were discrepancies between the two. We enrolled 1047 patients with ovarian tumors. The predictive values and concordance rates between the preoperative risk of ovarian malignancy algorithm (ROMA) and imaging, including CT and MRI, were evaluated. Diagnoses of 561 CT (77.9%) and 322 MRI group (69.2%) participants were consistent with the ROMA. Among them, 96.4% of the CT (541/561) and 92.5% of the MRI (298/322) group predicted an accurate diagnosis. In contrast, 67.3% (101/150) of CT and 75.2% (100/133) of MRI cases accurately predicted the diagnosis in cases with discrepancies between ROMA and CT or MRI; a total of 32% (48/150) of the CT and 25.5% (34/133) of the MRI group showed an accurate ROMA diagnosis in cases with discrepancies between ROMA and imaging. In the event of a discrepancy between ROMA and imaging when ovarian tumor malignancy prediction, the question is which method should take precedence. This study demonstrates that MRI has the greatest diagnostic accuracy, followed by CT and ROMA. It is also important to understand underlying diseases and benign conditions and rare histopathologies of malignant tumors.

[1]  S. Tirumani,et al.  Past, Present, and Future of Serum Tumor Markers in Management of Ovarian Cancer: A Guide for the Radiologist. , 2021, Radiographics : a review publication of the Radiological Society of North America, Inc.

[2]  G. Levin,et al.  Management of adnexal mass: A comparison of five national guidelines. , 2021, European journal of obstetrics, gynecology, and reproductive biology.

[3]  T. Cunha,et al.  Low-grade serous epithelial ovarian cancer: a comprehensive review and update for radiologists , 2021, Insights into Imaging.

[4]  Kun Peng,et al.  Quantitative analysis of the MRI features in the differentiation of benign, borderline, and malignant epithelial ovarian tumors , 2021, Journal of Ovarian Research.

[5]  Zhiqun Li,et al.  Systematic review and meta-analysis of imaging differential diagnosis of benign and malignant ovarian tumors. , 2021, Gland surgery.

[6]  C. Menias,et al.  Borderline epithelial ovarian tumors: what the radiologist should know , 2020, Abdominal Radiology.

[7]  A. Perrone,et al.  The generally low sensitivity of CA 125 for FIGO stage I ovarian cancer diagnosis increases for endometrioid histotype. , 2020, Minerva medica.

[8]  E. Oral,et al.  Endometriomas with low-risk malignancy potential in ultrasonography with high human epididymis protein 4 and risk of ovarian malignancy algorithm: a cases series , 2020, Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology.

[9]  I. Jacobs,et al.  Serum HE4 and diagnosis of ovarian cancer in postmenopausal women with adnexal masses , 2020, American journal of obstetrics and gynecology.

[10]  S. Faria,et al.  Low-grade epithelial ovarian cancer: what a radiologist should know. , 2019, The British journal of radiology.

[11]  Yan Li,et al.  Human Epididymis Protein 4 as a Potential Biomarker of Chronic Kidney Disease in Female Patients With Normal Ovarian Function , 2017, Laboratory medicine.

[12]  Catharine M. Sturgeon,et al.  Clinical Use of Cancer Biomarkers in Epithelial Ovarian Cancer , 2015, International Journal of Gynecologic Cancer.

[13]  B. Borghese,et al.  Management of presumed benign ovarian tumors: updated French guidelines. , 2014, European journal of obstetrics, gynecology, and reproductive biology.

[14]  P. Pandharipande,et al.  ACR Appropriateness Criteria® Staging and Follow-Up of Ovarian Cancer. , 2013, Journal of the American College of Radiology : JACR.

[15]  Y. Jeon,et al.  CA19-9 elevation in ovarian mature cystic teratoma: Discrimination from ovarian cancer – CA19-9 level in teratoma , 2013, Medical science monitor : international medical journal of experimental and clinical research.

[16]  C. Borgfeldt,et al.  High preoperative blood levels of HE4 predicts poor prognosis in patients with ovarian cancer , 2012, Journal of Ovarian Research.

[17]  Mollamahmutoglu Leyla,et al.  Tumor markers in mature cystic teratomas of the ovary , 2009, Archives of Gynecology and Obstetrics.

[18]  H. Frierson,et al.  Comprehensive analysis of HE4 expression in normal and malignant human tissues , 2006, Modern Pathology.

[19]  Christopher P Crum,et al.  Human epididymis protein 4 (HE4) is a secreted glycoprotein that is overexpressed by serous and endometrioid ovarian carcinomas. , 2005, Cancer research.

[20]  A. Prakash,et al.  The management of ovarian cysts in premenopausal women , 2004 .

[21]  K. Togashi.  Ovarian cancer: the clinical role of US, CT, and MRI , 2003, European Radiology.

[22]  M. Yeoh.  Investigation and management of an ovarian mass. , 2015, Australian family physician.

[23]  A. Guirguis,et al.  Evaluation and Management of Adnexal Masses , 2016 .

[24]  Steven J Skates,et al.  A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. , 2009, Gynecologic oncology.