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Objective: To describe the sonographic features of endometrial cancer in relation to tumor stage, grade and histological type, using the International Endometrial Tumor Analysis (IETA) terminology. Methods: This was a prospective multicenter study of 1714 women with biopsy-confirmed endometrial cancer undergoing standardized transvaginal grayscale and Doppler ultrasound examination according to the IETA study protocol, by experienced ultrasound examiners using high-end ultrasound equipment. Clinical and sonographic data were entered into a web-based database. We assessed how strongly sonographic characteristics, according to IETA, were associated with outcome at hysterectomy, i.e. tumor stage, grade and histological type, using univariable logistic regression and the c-statistic. Results: In total, 1538 women were included in the final analysis. Median age was 65 (range, 27–98) years, median body mass index was 28.4 (range 16–67) kg/m2, 1377 (89.5%) women were postmenopausal and 1296 (84.3%) reported abnormal vaginal bleeding. Grayscale and color Doppler features varied according to grade and stage of tumor. High-risk tumors, compared with low-risk tumors, were less likely to have regular endometrial–myometrial junction (difference of −23%; 95% CI, −27 to −18%), were larger (mean endometrial thickness; difference of +9%; 95% CI, +8 to +11%), and were more likely to have non-uniform echogenicity (difference of +7%; 95% CI, +1 to +13%), a multiple, multifocal vessel pattern (difference of +21%; 95% CI, +16 to +26%) and a moderate or high color score (difference of +22%; 95% CI, +18 to +27%). Conclusion: Grayscale and color Doppler sonographic features are associated with grade and stage of tumor, and differ between high- and low-risk endometrial cancer. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Objectives: To identify ultrasound features of papillations or of the cyst wall that can discriminate between benign and malignant unilocular-solid cysts with papillations but no other solid components. Methods: From the International Ovarian Tumor Analysis (IOTA) database derived from seven ultrasound centers, we identified patients with an adnexal lesion described at ultrasonography as unilocular-solid with papillations but no other solid components. All patients had undergone transvaginal ultrasound between 1999 and 2007 or 2009 and 2012, by an experienced examiner following the IOTA research protocol. Information on four ultrasound features of papillations had been collected prospectively. Information on a further seven ultrasound features was collected retrospectively from electronic or paper ultrasound images of good quality. The histological diagnosis of the surgically removed adnexal lesion was considered the gold standard. Results: Of 204 masses included, 131 (64.2%) were benign, 42 (20.6%) were borderline tumors, 30 (14.7%) were primary invasive tumors and one (0.5%) was a metastasis. Multivariate logistic regression analysis showed the following ultrasound features to be associated independently with malignancy: height of the largest papillation, presence of blood flow in papillations, papillation confluence or dissemination, and shadows behind papillations. Shadows decreased the odds of malignancy, while the other features increased them. Conclusion: We have identified ultrasound features that can help to discriminate between benign and malignant unilocular-solid cysts with papillations but no other solid components. Our results need to be confirmed in prospective studies. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Background: The intratracheal instillation of bleomycin in mice induces early damage to alveolar epithelial cells and development of inflammatio

Purpose: To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)]. Experimental Design: A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2, 763 patients (2, 403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals. Results: The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar. Conclusions: All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care.

PURPOSE: To prospectively test the mathematical models for calculation of the risk of malignancy in adnexal masses that were developed on the International Ovarian Tumor Analysis (IOTA) phase 1 data set on a new data set and to compare their performance with that of pattern recognition, our standard method. Methods: Three IOTA centers included 507 new patients who all underwent a transvaginal ultrasound using the standardized IOTA protocol. The outcome measure was the histologic classification of excised tissue. The diagnostic performance of 11 mathematical models that had been developed on the phase 1 data set and of pattern recognition was expressed as area under the receiver operating characteristic curve (AUC) and as sensitivity and specificity when using the cutoffs recommended in the studies where the models had been created. For pattern recognition, an AUC was made based on level of diagnostic confidence. RESULTS: All IOTA models performed very well and quite similarly, with sensitivity and specificity ranging between 92% and 96% and 74% and 84%, respectively, and AUCs between 0.945 and 0.950. A least squares support vector machine with linear kernel and a logistic regression model had the largest AUCs. For pattern recognition, the AUC was 0.963, sensitivity was 90.2%, and specificity was 92.9%. CONCLUSION: This internal validation of mathematical models to estimate the malignancy risk in adnexal tumors shows that the IOTA models had a diagnostic performance similar to that in the original data set. Pattern recognition used by an expert sonologist remains the best method, although the difference in performance between the best mathematical model is not large.

OBJECTIVES: To describe the clinical and ultrasound features of fibroma and fibrothecoma of the ovary. METHODS: Sixty-eight women with a histological diagnosis of fibroma or fibrothecoma of the ovary who had undergone a preoperative ultrasound examination between 1999 and 2007 were identified from the databases of four ultrasound centers. The tumors were characterized on the basis of ultrasound images, ultrasound reports and research protocols (when applicable) using the terms and definitions of the International Ovarian Tumor Analysis (IOTA) group. In 51 patients, ultrasound information had been collected prospectively; in the remaining 17 cases it was retrieved retrospectively from ultrasound reports and images. In 44 cases, electronic ultrasound images of good quality were available. These were reviewed by two observers, who described them using pattern recognition. RESULTS: Of the 68 patients identified, 53 had fibroma and 15 had fibrothecoma. The mean patient age was 54 (range, 17-80) years. Sixty-three percent (41/65) were postmenopausal and 60% (39/65) had no symptoms. Most (75%; 51/68) fibromas/fibrothecomas were solid tumors and most (75%; 51/68) manifested minimal or moderate blood flow on color Doppler examination. Using pattern recognition, all solid fibromas/fibrothecomas were described as round, oval or slightly lobulated tumors. Most (66%; 29/44) were solid tumors, with regular or slightly irregular internal echogenicity with stripy shadows, and some contained cystic spaces. Others (23%, 10/44) were solid tumors with regular or slightly irregular internal echogenicity without stripy shadows and with or without cystic spaces. Two were solid tumors that were so dense it was difficult to assess their internal echogenicity, two were multilocular solid tumors with large cystic spaces and one was described as being mainly cystic. Half of the women with fibroma/fibrothecoma had fluid in the pouch of Douglas and 16% (11/68) had ascites; CA 125 titers > or =35

OBJECTIVES: To determine the effect of an ultrasound training course on the performance of pattern recognition when used by less experienced examiners and to compare the performance of pattern recognition, a logistic regression model and a scoring system to estimate the risk of malignancy between examiners with different levels of experience. METHODS: Using ultrasound images of selected adnexal masses, two trainees classified the masses as benign or malignant by using pattern recognition both before and after they had attended a theoretical gynecological ultrasound course. They also classified the masses by using a logistic regression model and a scoring system, but only after they had attended the course. The performance of these three methods when they were used by the trainees was then compared with that when they were used by experts. RESULTS: One hundred and sixty-five adnexal masses were included, of which 42% were malignant (21% invasive tumors and 21% borderline tumors). The area under the receiver-operating characteristics curve of pattern recognition when used by the trainees was similar before and after they had attended the course. Training decreased sensitivity (84% vs. 70% for Trainee 1, P = 0.004; 70% vs. 61% for Trainee 2, P = 0.058) and increased specificity (77% vs. 92% for Trainee 1, P = 0.001; 89% vs. 95% for Trainee 2, P = 0.058). The performance of pattern recognition was poorer in the hands of the trainees than in the hands of the experts. The sensitivities of the logistic regression model were 70% and 54% for the trainees vs. 83% for an expert (P = 0.020 and < 0.001, respectively) and the specificities were 84% and 94% vs. 89% (P = 0.25 and 0.59, respectively). The sensitivities of the scoring system were 59% and 54% for the trainees vs. 75% for the expert (P = 0.002 and < 0.001, respectively), and the specificities were 90% and 93% vs. 85% (P = 0.103 and 0.008, respectively). CONCLUSION: Theoretical ultrasound teaching did not seem to improv

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OBJECTIVES: To determine the sensitivity and specificity of subjective evaluation of gray-scale and Doppler ultrasound findings (here called pattern recognition) when used by experienced ultrasound examiners with regard to making a specific diagnosis of adnexal masses. METHODS: Within the framework of a European multicenter study, the International Ovarian Tumor Analysis study, comprising nine ultrasound centers, women with at least one adnexal mass were examined with gray-scale and color Doppler ultrasonography by experienced ultrasound examiners. A standardized examination technique, and standardized terms and definitions were used. Using pattern recognition the examiners classified each mass as benign or malignant and suggested a specific diagnosis (e.g. dermoid cyst or endometrioma). The reference standard was the histology of the surgically removed adnexal tumors. RESULTS: A total of 1066 women were included, of whom 800 had a benign mass and 266 a malignant mass. A specific diagnosis based on ultrasound findings was suggested in 899 (84%) tumors. The specificity was high for all diagnoses (range, 94-100%). The sensitivity was highest for benign teratoma/dermoid cysts (86%, 100/116), hydrosalpinges (86%, 18/21), peritoneal pseudocysts (80%, 4/5) and endometriomas (77%, 153/199), and lowest for functional cysts (17%, 4/24), paraovarian/parasalpingeal cysts (14%, 3/21), benign rare tumors (11%, 1/9), adenofibromas (8%, 3/39), simple cysts (6%, 1/18) and struma ovarii (0%, 0/5). The positive and negative likelihood ratios of pattern recognition with regard to dermoid cysts, hydrosalpinges and endometriomas were 68.2 and 0.14, 38.9 and 0.15, and 33.3 and 0.24, respectively. Dermoid cysts, hydrosalpinges, functional cysts, paraovarian cysts, peritoneal pseudocysts, fibromas/fibrothecomas and simple cysts were never misdiagnosed as malignancies by the ultrasound examiner, whereas more than 10% of inflammatory processes, adenofibromas and rare benign tumors including

OBJECTIVES: To determine whether CA 125 measurement is superior to ultrasound imaging performed by an experienced examiner for discriminating between benign and malignant adnexal lesions, and to determine whether adding CA 125 to ultrasound examination improves diagnostic performance. METHODS: This is a prospective multicenter study (International Ovarian Tumor Analysis (IOTA) study) conducted in nine European ultrasound centers in university hospitals. Of 1149 patients with an adnexal mass examined in the IOTA study, 83 were excluded. Of the remaining 1066 patients, 809 had CA 125 results available and were included. The patients underwent preoperative serum CA 125 measurements and transvaginal ultrasound examination by an experienced ultrasound examiner blinded to CA 125 values. The examiner classified each mass as certainly or probably benign, difficult to classify, or probably or certainly malignant. The outcome measure was the sensitivity and specificity with regard to malignancy of CA 125, ultrasound imaging and their combined use, the 'gold standard' being the histological diagnosis of the adnexal mass removed surgically within 120 days after the ultrasound examination. RESULTS: There were 242 (30%) malignancies. For 534 tumors judged to be certainly benign or certainly malignant by the ultrasound examiner the sensitivity and specificity of ultrasound examination and CA 125 (> or =35 U/mL indicating malignancy) were 97% vs. 86% (95% CI of difference, 4.7-17.2) and 99% vs. 79% (95% CI of difference, 15.7-24.2); for 209 tumors judged probably benign or probably malignant, sensitivity and specificity were 81% vs. 57% (95% CI of difference, 12.3-36.0) and 91% vs. 74% (95% CI of difference, 8.5-25.7); for 66 tumors that were difficult to classify, sensitivity and specificity were 57% vs. 39% (95% CI of difference, -9.7 to 41.1) and 74% vs. 67% (95% CI of difference, -14.6 to 27.7). Diagnostic performance deteriorated when CA 125 was used as a second-stage test aft

Background Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. Objective We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. Study Design This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Results Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates sho

Background Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. Objective We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. Study Design This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Results Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates sho

Background: Pseudomonas aeruginosa (Pa) infection is an important contributor to the progression of cystic fibrosis (CF) lung disease. The cornerstone treatment for Pa infection is the use of inhaled antibiotics. However, there is substantial lung disease heterogeneity within and between patients that likely impacts deposition patterns of inhaled antibiotics. Therefore, this may result in airways below the minimal inhibitory concentration of the inhaled agent. Very little is known about antibiotic concentrations in small airways, in particular the effect of structural lung abnormalities. We therefore aimed to develop a patient-specific airway model to predict concentrations of inhaled antibiotics and to study the impact of structural lung changes and breathing profile on local concentrations in airways of patients with CF. Methods: In- and expiratory CT-scans of children with CF (5-17 years) were scored (CF-CT score), segmented and reconstructed into 3D airway models. Computational fluid dynamic (CFD) simulations were performed on 40 airway models to predict local Aztreonam lysine for inhalation (AZLI) concentrations. Patient-specific lobar flow distribution and nebulization of 75 mg AZLI through a digital Pari eFlow model with mass median aerodynamic diameter range were used at the inlet of the airway model. AZLI concentrations for central and small airways were computed for different breathing patterns and airway surface liquid thicknesses. Results In most simulated conditions, concentrations in both central and small airways were well above the minimal inhibitory concentration. However, small airways in more diseased lobes were likely to receive suboptimal AZLI. Structural lung disease and increased tidal volumes, respiratory rates and larger particle sizes greatly reduced small airway concentrations. Conclusions: CFD modeling showed that concentrations of inhaled antibiotic delivered to the small airways are highly patient specific and vary throughout the bronch