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ObjectiveUltrasound is considered a safe imaging modality and is routinely applied during early pregnancy. However, reservations are expressed concerning the application of Doppler ultrasound in early pregnancy due to energy emission of the ultrasound probe and its conversion to heat. The objective of this study was to evaluate the thermal effects of emitted Doppler ultrasound of different ultrasound machines and probes by means of temperature increase of in-vitro test-media.MethodsWe investigated the energy-output of 5 vaginal and abdominal probes of 3 ultrasound machines (GE Healthcare, Siemens, Aloka). Two in-vitro test objects were developed at the Center for Medical Physics and Biomedical Engineering, Medical University Vienna (water bath and hydrogel bath). Temperature increase during Doppler ultrasound emission was measured via thermal sensors, which were placed inside the test objects or on the probes’ surface. Each probe was emitting for 5 minutes into the absorbing test object with 3 different TI/MI settings in Spectral Doppler mode.ResultsDuring water bath test, temperature increase varied between 0.1 and 1.0°C, depending on probe, setting and focus, and was found highest for spectral Doppler mode alone. Maximum temperature increase was found during the surface heating test, where values up to 2.4°C could be measured within 5 minutes of emission.ConclusionsActivation of Doppler ultrasound in the waterbath model causes a significant increase of temperature within one minute. Thermally induced effects on the embryo cannot be excluded when using Doppler ultrasound in early pregnancy.

ObjectiveTo develop a tool for individualized risk estimation of presence of cancer in women with adnexal masses, and to assess the added value of plasma fibrinogen.Study designWe performed a retrospective analysis of a prospectively maintained database of 906 patients with adnexal masses who underwent cystectomy or oophorectomy. Uni- and multivariate logistic regression analyses including pre-operative plasma fibrinogen levels and established predictors were performed. A nomogram was generated to predict the probability of ovarian cancer. Internal validation with split-sample analysis was performed. Decision curve analysis (DCA) was then used to evaluate the clinical net benefit of the prediction model.ResultsOvarian cancer including borderline tumours was found in 241 (26.6%) patients. In multivariate analysis, elevated plasma fibrinogen, elevated CA-125, suspicion for malignancy on ultrasound, and postmenopausal status were associated with ovarian cancer and formed the basis for the nomogram. The overall predictive accuracy of the model, as measured by AUC, was 0.91 (95% CI 0.87–0.94). DCA revealed a net benefit for using this model for predicting ovarian cancer presence compared to a strategy of treat all or treat none.ConclusionWe confirmed the value of plasma fibrinogen as a strong predictor for ovarian cancer in a large cohort of patients with adnexal masses. We developed a highly accurate multivariable model to help in the clinical decision-making regarding the presence of ovarian cancer. This model provided net benefit for a wide range of threshold probabilities. External validation is needed before a recommendation for its use in routine practice can be given.