Literature DB >> 17444554

Accuracy of ultrasound subjective 'pattern recognition' for the diagnosis of borderline ovarian tumors.

J Yazbek1, K S Raju, J Ben-Nagi, T Holland, K Hillaby, D Jurkovic.   

Abstract

OBJECTIVES: To assess the value of pattern recognition for the preoperative ultrasound diagnosis of borderline ovarian tumors (BOTs).
METHODS: This was a prospective study of women who were referred to our regional cancer center with the diagnosis of an adnexal mass on a Level II (routine) gynecological ultrasound scan. Women with lesions of uncertain nature were referred for a Level III (expert) ultrasound scan in our tertiary center. The tumor pattern recognition method was used to differentiate between various types of ovarian tumors. Morphological features suggestive of BOTs were: unilocular cyst with a positive ovarian crescent sign and extensive papillary projections arising from the inner wall, or a cyst with a well defined multilocular nodule. The ultrasound findings were compared with the final histological diagnosis.
RESULTS: A total of 224 women with an adnexal mass of uncertain nature were referred for an expert scan, 166 (74.1%) of whom underwent surgery. In this group of women the final histological diagnoses were: 99 (60%) benign lesions, 32 (19%) invasive ovarian cancer and 35 (21%) BOTs. Using pattern recognition combining the different morphological features, a correct preoperative diagnosis of BOT was made in 24/35 (68.6%) women: area under the receiver-operating characteristics curve 0.812 (standard error 0.049; 95% CI, 0.716-0.908), sensitivity 0.69 (95% CI, 0.52-0.81), specificity 0.94 (95% CI, 0.88-0.97), positive likelihood ratio 11.3 (95% CI, 5.53-22.8) and negative likelihood ratio 0.34 (95% CI, 0.21-0.55).
CONCLUSIONS: Ultrasound diagnosis of BOTs is highly specific. However, typical features are absent in one-third of cases, which are typically misdiagnosed as benign lesions. Copyright (c) 2007 ISUOG.

Entities:  

Mesh:

Year:  2007        PMID: 17444554     DOI: 10.1002/uog.4002

Source DB:  PubMed          Journal:  Ultrasound Obstet Gynecol        ISSN: 0960-7692            Impact factor:   7.299


  8 in total

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