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[Doppler ultrasonography in the diagnosis of ovarian cysts: indications, pertinence and diagnostic criteria].

Authors: H, Marret;

[Doppler ultrasonography in the diagnosis of ovarian cysts: indications, pertinence and diagnostic criteria].

Abstract

To discriminate ovarian lesions is of particular importance in gynecological practice. Two main problems need answers: discrimination of benign and malignant adnexal masses and choice of the appropriate surgical treatment if necessary. Nearly 2% of the adnexal masses are ovarian carcinomas or border line tumors. It is now well established that ultrasonography is the gold standard for ovarian cyst diagnosis. The purpose of this work was to review the literature and to establish, with the evidence based medicine model, which parameters and existing diagnostic models using ultrasound and Doppler performs best in the evaluation of adnexal masses. Transvaginal sonography has demonstrated considerable advantage over conventional transabdominal sonography. However, transparietal sonography is still useful in large tumors. It is no longer reasonable to subject all patients undergoing pelvic sonography to bladder distension. Functional ovarian cyst characterization seems easy using sonography and Doppler. In case of complication, discrimination of such functional cyst may be difficult but spontaneous regression confirms usually the expectative management. Dermoid cysts and endometriomas seem to be easier to discriminate from other adnexal masses. Papillary formations on the inside of the cyst wall and masses with a non hyperechoic solid component are the most statistically significant predictors of a malignant ovarian mass. Ultrasound and morphologic parameters have a sensitivity of 80% and a specificity of 93%, that make this exam the gold standard for ovarian masses diagnosis. Another parameter is important: experienced hands with subjective evaluation seems to be one of the best ultrasound method for adnexal masses discrimination. Scoring system help differentiate benign from malignant masses (sensitivity 90%, VPP 50%). Doppler flow measurement and assessment of tumor vascularity by doppler energy increase the confidence with which a correct diagnosis is made. Moreover, combined US techniques and a diagnostic algorithm perform significantly better than morphologic assessment, color doppler or CA125 measurement alone. Logistic regression and neural network models are good methods and may be useful for malignancy prediction but the improvement is small and the concordance with histology far from 100%. In front of a benign and maybe functional cyst, spontaneous resolution may be controlled by sonographic exam at 3 and 6 months. Three-dimensional ultrasound and power doppler, contrast enhanced sonography, and sonography during the laparoscopic procedure are not still validated. Every suspicious ovarian mass needs sonography by an expert which can first use all the techniques and the different parameters to discriminate benign and malignant tumors. Secondly, after control if necessary, he can propose the patient for appropriate surgical treatment.

Keywords

Diagnosis, Differential, Ovarian Neoplasms, Ovarian Cysts, Vagina, Humans, Female, Ultrasonography, Doppler

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
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