Literature DB >> 35284306

Systematic review and meta-analysis of imaging differential diagnosis of benign and malignant ovarian tumors.

Wen-Huan Wang1, Chang-Bao Zheng2, Jin-Niao Gao3, Shang-Shang Ren4, Guo-Yan Nie1, Zhi-Qun Li5.   

Abstract

Background: With the increasing incidence of gynecological ovarian tumors, the differential diagnosis of benign and malignant ovarian tumors is of great significance for subsequent treatment. Currently, ovarian examinations commonly use computed tomography (CT) or magnetic resonance imaging (MRI). This study sought to compare the value of CT and MRI in differentiating between benign and malignant ovarian tumors.
Methods: The PubMed, Cochrane Central Register of Controlled Trials, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang, and Weipu databases were searched for published articles using the following terms "CT" or "Computed Tomography" or "MRI" or "Magnetic Resonance imaging" and "ovarian cancer" or "ovarian tumor" or "ovarian neoplasm" or "adnexal mass" or "adnexal lesion". The articles were screened and the data were extracted based on the inclusion and exclusion criteria. The Quality Assessment of Diagnostic Accuracy Studies-2 recommended by the Cochrane Collaboration was used to assess the methodological quality of the included studies, and the network meta-analysis was performed by Stata 15.0.
Results: The results showed that the overall sensitivity and specificity of CT were 0.79 [95% confidence intervals (CI): 0.70-0.87] and 0.87 (95% CI: 0.80-0.92), respectively. The overall sensitivity and specificity of MRI were 0.94 (95% CI: 0.91-0.95) and 0.91 (95% CI: 0.90-0.93), respectively. The area under the curve of the CT and MRI summary receiver operating characteristics were 0.9016 and 0.9764, respectively. The positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CT were 5.26 (95% CI: 2.78-9.93), 0.26 (95% CI: 0.13-0.50), and 22.19 (95% CI: 7.54-65.30), respectively. The positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of MRI were 8.69 (95% CI: 5.06-14.92), 0.07 (95% CI: 0.04-0.13), and 146.19 (95% CI: 68.88-310.24), respectively. Conclusions: Compared to CT, MRI has a stronger ability to differentiate between benign and malignant ovarian tumors. It's a promising non-radiological imaging technique and a more favorable choice for patients with ovarian tumors. However, in the future, large-sample, multi-center prospective studies need to be conducted to compare the performance of MRI and CT in distinguishing between benign and malignant ovarian tumors. 2022 Gland Surgery. All rights reserved.

Entities:  

Keywords:  Ovarian tumor; computed tomography (CT); differential diagnosis; magnetic resonance imaging (MRI)

Year:  2022        PMID: 35284306      PMCID: PMC8899432          DOI: 10.21037/gs-21-889

Source DB:  PubMed          Journal:  Gland Surg        ISSN: 2227-684X


  24 in total

1.  Magnetic resonance imaging radiomics in categorizing ovarian masses and predicting clinical outcome: a preliminary study.

Authors:  He Zhang; Yunfei Mao; Xiaojun Chen; Guoqing Wu; Xuefen Liu; Peng Zhang; Yu Bai; Pengcong Lu; Weigen Yao; Yuanyuan Wang; Jinhua Yu; Guofu Zhang
Journal:  Eur Radiol       Date:  2019-04-08       Impact factor: 5.315

2.  Comparative evaluation of multidetector CT and MR imaging in the differentiation of adnexal masses.

Authors:  A C Tsili; C Tsampoulas; M Argyropoulou; I Navrozoglou; Y Alamanos; E Paraskevaidis; S C Efremidis
Journal:  Eur Radiol       Date:  2008-01-10       Impact factor: 5.315

Review 3.  The Dualistic Model of Ovarian Carcinogenesis: Revisited, Revised, and Expanded.

Authors:  Robert J Kurman; Ie-Ming Shih
Journal:  Am J Pathol       Date:  2016-04       Impact factor: 4.307

4.  Cancer risk estimates for family members of a population-based family registry for breast and ovarian cancer.

Authors:  A Ziogas; M Gildea; P Cohen; D Bringman; T H Taylor; D Seminara; D Barker; G Casey; R Haile; S Y Liao; D Thomas; B Noble; T Kurosaki; H Anton-Culver
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2000-01       Impact factor: 4.254

Review 5.  The genesis and evolution of high-grade serous ovarian cancer.

Authors:  David D L Bowtell
Journal:  Nat Rev Cancer       Date:  2010-10-14       Impact factor: 60.716

6.  A Prospective Evaluation of Early Detection Biomarkers for Ovarian Cancer in the European EPIC Cohort.

Authors:  Kathryn L Terry; Helena Schock; Renée T Fortner; Anika Hüsing; Raina N Fichorova; Hidemi S Yamamoto; Allison F Vitonis; Theron Johnson; Kim Overvad; Anne Tjønneland; Marie-Christine Boutron-Ruault; Sylvie Mesrine; Gianluca Severi; Laure Dossus; Sabina Rinaldi; Heiner Boeing; Vassiliki Benetou; Pagona Lagiou; Antonia Trichopoulou; Vittorio Krogh; Elisabetta Kuhn; Salvatore Panico; H Bas Bueno-de-Mesquita; N Charlotte Onland-Moret; Petra H Peeters; Inger Torhild Gram; Elisabete Weiderpass; Eric J Duell; Maria-Jose Sanchez; Eva Ardanaz; Nerea Etxezarreta; Carmen Navarro; Annika Idahl; Eva Lundin; Karin Jirström; Jonas Manjer; Nicholas J Wareham; Kay-Tee Khaw; Karl Smith Byrne; Ruth C Travis; Marc J Gunter; Melissa A Merritt; Elio Riboli; Daniel W Cramer; Rudolf Kaaks
Journal:  Clin Cancer Res       Date:  2016-04-08       Impact factor: 12.531

Review 7.  Radiological staging of ovarian cancer: imaging findings and contribution of CT and MRI.

Authors:  Rosemarie Forstner
Journal:  Eur Radiol       Date:  2007-08-14       Impact factor: 5.315

8.  Characterization of tubo-ovarian abscess mimicking adnexal masses: Comparison between contrast-enhanced CT, 18F-FDG PET/CT and MRI.

Authors:  Hua Fan; Ting-Ting Wang; Gang Ren; Hong-Liang Fu; Xiang-Ru Wu; Cai-Ting Chu; Wen-Hua Li
Journal:  Taiwan J Obstet Gynecol       Date:  2018-02       Impact factor: 1.705

9.  Risk factors for epithelial ovarian cancer by histologic subtype.

Authors:  Margaret A Gates; Bernard A Rosner; Jonathan L Hecht; Shelley S Tworoger
Journal:  Am J Epidemiol       Date:  2009-11-12       Impact factor: 4.897

Review 10.  Imaging before cytoreductive surgery in advanced ovarian cancer patients.

Authors:  Stefania Rizzo; Maria Del Grande; Lucia Manganaro; Andrea Papadia; Filippo Del Grande
Journal:  Int J Gynecol Cancer       Date:  2019-11-21       Impact factor: 3.437

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.