| 1. |
- Van Den Bosch, T., et al.
(författare)
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Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding
- 2021
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Ingår i: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 57:1, s. 164-172
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To describe the ultrasound features of different endometrial and other intracavitary pathologies inpre- and postmenopausal women presenting with abnormal uterine bleeding, using the International Endometrial Tumor Analysis (IETA) terminology. Methods: This was a prospective observational multicenter study of consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler and fluid-instillation sonography were performed. Endometrial sampling was performed according to each center's local protocol. The histological endpoints were cancer, atypical endometrial hyperplasia/endometrioid intraepithelial neoplasia (EIN), endometrial atrophy, proliferative or secretory endometrium, endometrial hyperplasia without atypia, endometrial polyp, intracavitary leiomyoma and other. For fluid-instillation sonography, the histological endpoints were endometrial polyp, intracavitary leiomyoma and cancer. For each histological endpoint, we report typical ultrasound features using the IETA terminology. Results: The database consisted of 2856 consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler was performed in all cases and fluid-instillation sonography in 1857. In 2216 women, endometrial histology was available, and these comprised the study population. Median age was 49 years (range, 19–92 years), median parity was 2 (range, 0–10) and median body mass index was 24.9 kg/m2 (range, 16.0–72.1 kg/m2). Of the study population, 843 (38.0%) women were postmenopausal. Endometrial polyps were diagnosed in 751 (33.9%) women, intracavitary leiomyomas in 223 (10.1%) and endometrial cancer in 137 (6.2%). None (0% (95% CI, 0.0–5.5%)) of the 66 women with endometrial thickness < 3 mm had endometrial cancer or atypical hyperplasia/EIN. Endometrial cancer or atypical hyperplasia/EIN was found in three of 283 (1.1% (95% CI, 0.4–3.1%)) endometria with a three-layer pattern, in three of 459 (0.7% (95% CI, 0.2–1.9%)) endometria with a linear endometrial midline and in five of 337 (1.5% (95% CI, 0.6–3.4%)) cases with a single vessel without branching on unenhanced ultrasound. Conclusions: The typical ultrasound features of endometrial cancer, polyps, hyperplasia and atrophy and intracavitary leiomyomas, are described using the IETA terminology. The detection of some easy-to-assess IETA features (i.e. endometrial thickness < 3 mm, three-layer pattern, linear midline and single vessel without branching) makes endometrial cancer unlikely.
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| 2. |
- Testa, A. C., et al.
(författare)
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Intravenous contrast ultrasound examination using contrast-tuned imaging (CnTI (TM)) and the contrast medium SonoVue (R) for discrimination between benign and malignant adnexal masses with solid components
- 2009
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 34:6, s. 699-710
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Tidskriftsartikel (refereegranskat)abstract
- Objective To determine whether intravenous contrast ultrasound examination is superior to gray-scale or power Doppler ultrasound for discrimination between benign and malignant adnexal masses with complex ultrasound morphology. Methods In an international multicenter study, 134 patients with an ovarian mass with solid components or a multilocular cyst with more than 10 cyst locules, underwent a standardized transvaginal ultrasound examination followed by contrast examination using the contrast-tuned imaging technique and intravenous injection of the contrast medium SonoVue (R). Time intensity curves were constructed, and peak intensity, area under the intensity curve, time to peak, sharpness and half wash-out time were calculated. The sensitivity and specificity with regard to malignancy were calculated and receiver-operating characteristics (ROC) curves were drawn for gray-scale, power Doppler and contrast variables and for pattern recognition (subjective assignment of a certainly benign, probably benign, uncertain or malignant diagnosis, using gray-scale and power Doppler ultrasound findings). The gold standard was the histological diagnosis of the surgically removed tumors. Results After exclusions (surgical removal of the mass > 3 months after the ultrasound examination, technical problems), 72 adnexal masses with solid components were used in our statistical analyses. The values for peak contrast signal intensity and area under the contrast signal intensity curve in malignant tumors were significantly higher than those in borderline tumors and benign tumors, while those for the benign and borderline tumors were similar. The area under the ROC curve of the best contrast variable with regard to diagnosing borderline or invasive malignancy (0.84) was larger than that of the best gray-scale (0.75) and power Doppler ultrasound variable (0.79) but smaller than that of pattern recognition (0.93). Conclusion Findings on ultrasound contrast examination differed between benign and malignant tumors but there was a substantial overlap in contrast findings between benign and borderline tumors. It appears that ultrasound contrast examination is not superior to conventional ultrasound techniques, which also have difficulty in distinguishing between benign and borderline tumors, but can easily differentiate invasive malignancies from other tumors. Copyright (C) 2009 ISUOG. Published by John Wiley & Sons, Ltd.
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| 3. |
- Eriksson, L. S.E., et al.
(författare)
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Ultrasound-based risk model for preoperative prediction of lymph-node metastases in women with endometrial cancer : model-development study
- 2020
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Ingår i: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 56:3, s. 443-452
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To develop a preoperative risk model, using endometrial biopsy results and clinical and ultrasound variables, to predict the individual risk of lymph-node metastases in women with endometrial cancer. Methods: A mixed-effects logistic regression model for prediction of lymph-node metastases was developed in 1501 prospectively included women with endometrial cancer undergoing transvaginal ultrasound examination before surgery, from 16 European centers. Missing data, including missing lymph-node status, were imputed. Discrimination, calibration and clinical utility of the model were evaluated using leave-center-out cross validation. The predictive performance of the model was compared with that of risk classification from endometrial biopsy alone (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). Results: Lymphadenectomy was performed in 691 women, of whom 127 had lymph-node metastases. The model for prediction of lymph-node metastases included the predictors age, duration of abnormal bleeding, endometrial biopsy result, tumor extension and tumor size according to ultrasound and undefined tumor with an unmeasurable endometrium. The model's area under the curve was 0.73 (95% CI, 0.68–0.78), the calibration slope was 1.06 (95% CI, 0.79–1.34) and the calibration intercept was 0.06 (95% CI, –0.15 to 0.27). Using a risk threshold for lymph-node metastases of 5% compared with 20%, the model had, respectively, a sensitivity of 98% vs 48% and specificity of 11% vs 80%. The model had higher sensitivity and specificity than did classification as high-risk, according to endometrial biopsy alone (50% vs 35% and 80% vs 77%, respectively) or combined endometrial biopsy and ultrasound (80% vs 75% and 53% vs 52%, respectively). The model's clinical utility was higher than that of endometrial biopsy alone or combined endometrial biopsy and ultrasound at any given risk threshold. Conclusions: Based on endometrial biopsy results and clinical and ultrasound characteristics, the individual risk of lymph-node metastases in women with endometrial cancer can be estimated reliably before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound.
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| 4. |
- Landolfo, C., et al.
(författare)
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Benign descriptors and ADNEX in two-step strategy to estimate risk of malignancy in ovarian tumors : retrospective validation on IOTA 5 multicenter cohort
- 2023
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Ingår i: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 61:2, s. 231-242
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Previous work suggested that the ultrasound-based benign Simple Descriptors can reliably exclude malignancy in a large proportion of women presenting with an adnexal mass. We aim to validate a modified version of the Benign Simple Descriptors (BD), and we introduce a two-step strategy to estimate the risk of malignancy: if the BDs do not apply, the ADNEX model is used to estimate the risk of malignancy. Methods: This is a retrospective analysis using the data from the 2-year interim analysis of the IOTA5 study, in which consecutive patients with at least one adnexal mass were recruited irrespective of subsequent management (conservative or surgery). The main outcome was classification of tumors as benign or malignant, based on histology or on clinical and ultrasound information during one year of follow-up. Multiple imputation was used when outcome based on follow-up was uncertain according to predefined criteria. Results: 8519 patients were recruited at 36 centers between 2012 and 2015. We included all masses that were not already in follow-up at recruitment from 17 centers with good quality surgical and follow-up data, leaving 4905 patients for statistical analysis. 3441 (70%) tumors were benign, 978 (20%) malignant, and 486 (10%) uncertain. The BDs were applicable in 1798/4905 (37%) tumors, and 1786 (99.3%) of these were benign. The two-step strategy based on ADNEX without CA125 had an area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI, 0.91-0.95). The risk of malignancy was slightly underestimated, but calibration varied between centers. A sensitivity analysis in which we expanded the definition of uncertain outcome resulted in 1419 (29%) tumors with uncertain outcome and an AUC of the two-step strategy without CA125 of 0.93 (95% CI, 0.91-0.95). Conclusion: A large proportion of adnexal masses can be classified as benign by the BDs. For the remaining masses the ADNEX model can be used to estimate the risk of malignancy. This two-step strategy is convenient for clinical use.
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| 5. |
- Timmerman, D., et al.
(författare)
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Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group
- 2010
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 36:2, s. 226-234
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Tidskriftsartikel (refereegranskat)abstract
- Objectives The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner ('subjective assessment'). Methods Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each mass as benign or malignant on the basis of subjective evaluation of ultrasound findings. The gold standard was the histology of the mass with local clinicians deciding whether to operate on the basis of ultrasound results and the clinical picture. The models' ability to discriminate between malignant and benign masses was assessed, together with the accuracy of the risk estimates. Results Of the 1938 patients included in the study, 1396 had benign, 373 had primary invasive, 111 had borderline malignant and 58 had metastatic tumors. On external validation (997 patients from 12 centers), the area under the receiver operating characteristics curve (AUC) for a model containing 12 predictors (LR1) was 0.956, for a reduced model with six predictors (LR2) was 0.949 and for subjective assessment was 0.949. Subjective assessment gave a positive likelihood ratio of 11.0 and a negative likelihood ratio of 0.14. The corresponding likelihood ratios for a previously derived probability threshold (0.1) were 6.84 and 0.09 for LR1, and 6.36 and 0.10 for LR2. On temporal validation (941 patients from seven centers), the AUCs were 0.945 (LR1), 0.918 (LR2) and 0.959 (subjective assessment). Conclusions Both models provide excellent discrimination between benign and malignant masses. Because the models provide an objective and reasonably accurate risk estimation, they may improve the management of women with suspected ovarian pathology. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd.
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| 6. |
- Timmerman, D., et al.
(författare)
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Simple ultrasound-based rules for the diagnosis of ovarian cancer
- 2008
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 31:6, s. 681-690
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Tidskriftsartikel (refereegranskat)abstract
- Objective To derive simple and clinically useful ultrasound-based rules for discriminating between benign and malignant adnexal masses. Methods In a multicenter study involving nine centers consecutive patients with persistent adnexal tumors underwent transvaginal gray-scale and Doppler ultrasound examination using a standardized examination technique and standardized terms and definitions. Information on 42 gray-scale ultrasound variables and six Doppler variables was collected and entered into a research protocol. When developing simple ultrasound-based rules to predict malignancy (M-rules) we chose the ultrasound variable or the combination of ultrasound variables that bad the highest positive predictive value (PPV) with regard to malignancy; when developing simple rules to predict a benign tumor (B-rules) we chose the ultrasound variable or the combination of ultrasound variables that had the lowest PPV with regard to malignancy. We selected ten rules that were in agreement with our clinical experience and were applicable to at least 30 tumors and then tested them prospectively on 507 tumors examined in three of the nine centers. Results 1066 patients with 1233 adnexal tumors were included. There were 903 benign tumors (73%) and 330 malignant tumors (27%). In 167 patients the tumors were bilateral. We selected five simple rules to predict malignancy (M-rules): (1) irregular solid tumor; (2) ascites; (3) at least four papillary structures; (4) irregular multilocular-solid tumor with a largest diameter of at least 100 mm; and (5) very high color content on color Doppler examination. We chose five simple rules to suggest a benign tumor (B-rules): (1) unilocular cyst; (2) presence of solid components where the largest solid component is < 7 mm in largest diameter; (3) acoustic shadows; (4) smooth multilocular tumor less than 100 mm in largest diameter; and (S) no detectable blood flow on Doppler examination. These ten rules were applicable to 76% of all tumors, where they resulted in a sensitivity of 93%, specificity of 90%, positive likelihood ratio (LR+) of 9.45 and negative likelihood ratio (LR-) of 0.08. When prospectively tested the rules were applicable in 76% (386/507) of the tumors, where they had a sensitivity of 95% (106/112), a specificity of 91% (249/274), LR+ of 10.37, and LR- of 0.06. Conclusion Most adnexal tumors in an ordinary tumor population can be correctly classified as benign or malignant using simple ultrasound-based rules. For tumors that cannot be classified using simple rules, ultrasound examination by an expert examiner might be useful. Copyright (C) 2008 ISUOG. Published by John Wiley & Sons, Ltd.
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| 7. |
- Van Calster, Ben, et al.
(författare)
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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.
- 2014
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Ingår i: BMJ: British Medical Journal. - : BMJ. - 1756-1833. ; 349, s. 5920-5920
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Tidskriftsartikel (refereegranskat)abstract
- To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours.
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| 8. |
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| 9. |
- Van Calster, B., et al.
(författare)
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Preoperative diagnosis of ovarian tumors using Bayesian kernel-based methods
- 2007
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 29:5, s. 496-504
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To develop flexible classifiers that predict malignancy in adnexal masses using a large database from nine centers. Methods The database consisted of 1066 patients with at least one persistent adnexal mass for which a large amount of clinical and ultrasound data were recorded. The outcome of interest was the histological classification of the adnexal mass as benign or malignant. The outcome was predicted using Bayesian least squares support vector machines in comparison with relevance vector machines. The models were developed on a training set (n = 754) and tested on a test set (n = 312). Results Twenty-five percent of the patients (n = 266) bad a malignant tumor. Variable selection resulted in a set of 12 variables for the models: age, maximal diameter of the ovary, maximal diameter of the solid component, personal history of ovarian cancer, hormonal therapy, very strong intratumoral blood flow (i.e. color score 4), ascites, presumed ovarian origin of tumor, multilocular-solid tumor, blood flow within papillary projections, irregular internal cyst wall and acoustic shadows. Test set area under the receiver-operating characteristics curve (AUC) for all models exceeded 0.940, with a sensitivity above 90% and a specificity above 80% for all models. The least squares support vector machine model with linear kernel performed very well, with an AUC of 0.946, 91% sensitivity and 84% specificity. The models performed well in the test sets of all the centers. Conclusions Bayesian kernel-based methods can accurately separate malignant from benign masses. The robustness of the models will be investigated in future studies. Copyright (c) 2007 ISUOG. Published by John Wiley & Sons, Ltd.
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| 10. |
- Van Holsbeke, C., et al.
(författare)
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Acoustic streaming cannot discriminate reliably between endometriomas and other types of adnexal lesion: a multicenter study of 633 adnexal masses
- 2010
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 35:3, s. 349-353
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Tidskriftsartikel (refereegranskat)abstract
- Objective To determine the ability of acoustic streaming to discriminate between endometriomas and other adnexal masses. Methods We used data from 1938 patients with an adnexal mass included in Phase 2 of the International Ovarian Tumor Analysis (IOTA) study. All patients had been examined by transvaginal gray-scale and Doppler ultrasound following a standardized research protocol. Assessment of acoustic streaming was voluntary and was carried out only in lesions containing echogenic cyst fluid. Acoustic streaming was defined as movement of particles inside the cyst fluid during gray-scale and/or color Doppler examination provided that the probe had been held still for two seconds to ensure that the movement of the particles was not caused by movement of the probe or the patient. Only centers where acoustic streaming had been evaluated in > 90% of cases were included. Sensitivity, specificity, positive and negative likelihood ratios (LR+, LR-), and positive and negative predictive values (PPV and NPV) of acoustic streaming with regard to endometrioma were calculated. Results 460 (24%) masses were excluded because they were examined in centers where <= 90% of the masses with echogenic cyst fluid had been evaluated for the presence of acoustic streaming. Acoustic streaming was evaluated in 633 of 646 lesions containing echogenic cyst fluid. It was present in 19 (9%) of 209 endometriomas and in 55 (13%) of 424 other lesions. This corresponds to a sensitivity of absent acoustic streaming with regard to endometrioma of 91% (190/209), a specificity of 13% (55/424), LR+ of 1.04, LR- of 0.69, PPV of 34% (190/559) and NPV of 74% (55/74). Conclusions Acoustic streaming cannot discriminate reliably between endometrioinas and other adnexal lesions, and the presence of acoustic streaming does not exclude an endometrioma. Copyright (C) 2009 ISUOG. Published by John Wiley & Sons, Ltd.
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| 11. |
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| 12. |
- Ameye, L., et al.
(författare)
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A scoring system to differentiate malignant from benign masses in specific ultrasound-based subgroups of adnexal tumors
- 2009
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 33:1, s. 92-101
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Tidskriftsartikel (refereegranskat)abstract
- Objective To investigate if the prediction of malignant adnexal masses can be improved by considering different ultrasound-based subgroups of tumors and constructing a scoring system for each subgroup instead of using a risk estimation model applicable to all tumors. Methods We used a multicenter database of 1573 patients with at least one persistent adnexal mass. The masses were categorized into four subgroups based on their ultrasound appearance: ( 1) unilocular cyst; ( 2) multilocular cyst; ( 3) presence of a solid component but no papillation; and ( 4) presence of papillation. For each of the four subgroups a scoring system to predict malignancy was developed in a development set consisting of 754 patients in total ( respective numbers of patients: ( 1) 228; ( 2) 143; ( 3) 183; and ( 4) 200). The subgroup scoring system was then tested in 312 patients and prospectively validated in 507 patients. The sensitivity and specificity, with regard to the prediction of malignancy, of the scoring system were compared with that of the subjective evaluation of ultrasound images by an experienced examiner ( pattern recognition) and with that of a published logistic regression (LR) model for the calculation of risk of malignancy in adnexal masses. The gold standard was the pathological classification of the mass as benign or malignant ( borderline, primary invasive, or metastatic). Results In the prospective validation set, the sensitivity of pattern recognition, the LR model and the subgroup scoring system was 90% (129/143), 95% (136/143) and 88% (126/143), respectively, and the specificity was 93% (338/364), 74% (270/364) and 90% (329/364), respectively. Conclusions In the hands of experienced ultrasound examiners, the subgroup scoring system for diagnosing malignancy has a performance that is similar to that of pattern recognition, the latter method being the best diagnostic method currently available. The scoring system is less sensitive but more specific than the LR model. Copyright (C) 2008 ISUOG. Published by John Wiley & Sons, Ltd.
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| 13. |
- Ameye, L., et al.
(författare)
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Clinically oriented three-step strategy for assessment of adnexal pathology
- 2012
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 40:5, s. 582-591
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Tidskriftsartikel (refereegranskat)abstract
- Objective To determine the diagnostic performance of ultrasound-based simple rules, risk of malignancy index (RMI), two logistic regression models (LR1 and LR2) and real-time subjective assessment by experienced ultrasound examiners following the exclusion of masses likely to be judged as easy and 'instant' to diagnose by an ultrasound examiner, and to develop a new strategy for the assessment of adnexal pathology based on this. Methods 3511 patients with at least one persistent adnexal mass preoperatively underwent transvaginal ultrasonography to assess tumor morphology and vascularity. They were included in two consecutive prospective studies by the International Ovarian Tumor Analysis (IOTA) group: Phase 1 (1999-2005), development of the simple rules and logistic regression models LR1 and LR2, and Phase 2, a validation study (2005-2007). Results Almost half of the cases (43%) were identified as 'instant' to diagnose on the basis of descriptors applied to the database. To assess diagnostic performance in the more difficult 'non-instant' masses, we used only Phase 2 data (n = 1036). The sensitivity of LR2 was 88%, of RMI it was 41% and of subjective assessment it was 87%. The specificity of LR2 was 67%, of RMI it was 90% and of subjective assessment it was 86%. The simple rules yielded a conclusive result in almost 2/3 of the masses, where they resulted in sensitivity and specificity similar to those of real-time subjective assessment by experienced ultrasound examiners: sensitivity 89 vs 89% (P = 0.76), specificity 91 vs 91% (P = 0.65). When a three-step strategy was appliedwith easy 'instant' diagnoses as Step 1, simple rules where conclusive as Step 2 and subjective assessment by an experienced ultrasound examiner in the remaining masses as Step 3, we obtained a sensitivity of 92% and specificity of 92% compared with sensitivity 90% (P = 0.03) and specificity 93% (P = 0.44) when using real-time subjective assessment by experts in all tumors. Conclusion A diagnostic strategy using simple descriptors and ultrasound rules when applied to the variables contained in the IOTA database obtains results that are at least as good as those obtained by subjective assessment of a mass by an expert. Copyright. (C) 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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| 14. |
- Di Legge, A., et al.
(författare)
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Lesion size affects diagnostic performance of IOTA logistic regression models, IOTA simple rules and risk of malignancy index in discriminating between benign and malignant adnexal masses
- 2012
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 40:3, s. 345-354
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To estimate the ability to discriminate between benign and malignant adnexal masses of different size using: subjective assessment, two International Ovarian Tumor Analysis (IOTA) logistic regression models (LR1 and LR2), the IOTA simple rules and the risk of malignancy index (RMI). Methods We used a multicenter IOTA database of 2445 patients with at least one adnexal mass, i.e. the database previously used to prospectively validate the diagnostic performance of LR1 and LR2. The masses were categorized into three subgroups according to their largest diameter: small tumors (diameter < 4 cm; n = 396), medium-sized tumors (diameter, 49.9 cm; n = 1457) and large tumors (diameter = 10 cm, n = 592). Subjective assessment, LR1 and LR2, IOTA simple rules and the RMI were applied to each of the three groups. Sensitivity, specificity, positive and negative likelihood ratio (LR+, LR-), diagnostic odds ratio (DOR) and area under the receiveroperating characteristics curve (AUC) were used to describe diagnostic performance. A moving window technique was applied to estimate the effect of tumor size as a continuous variable on the AUC. The reference standard was the histological diagnosis of the surgically removed adnexal mass. Results The frequency of invasive malignancy was 10% in small tumors, 19% in medium-sized tumors and 40% in large tumors; 11% of the large tumors were borderline tumors vs 3% and 4%, respectively, of the small and medium-sized tumors. The type of benign histology also differed among the three subgroups. For all methods, sensitivity with regard to malignancy was lowest in small tumors (5684% vs 6793% in medium-sized tumors and 7495% in large tumors) while specificity was lowest in large tumors (6087%vs 8395% in medium-sized tumors and 8396% in small tumors ). The DOR and the AUC value were highest in medium-sized tumors and the AUC was largest in tumors with a largest diameter of 711 cm. Conclusion Tumor size affects the performance of subjective assessment, LR1 and LR2, the IOTA simple rules and the RMI in discriminating correctly between benign and malignant adnexal masses. The likely explanation, at least in part, is the difference in histology among tumors of different size. Copyright (C) 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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| 15. |
- Epstein, E, et al.
(författare)
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Erratum
- 2018
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Ingår i: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology. - : Wiley. - 1469-0705. ; 52:5, s. 684-684
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Tidskriftsartikel (refereegranskat)
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| 16. |
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| 17. |
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| 18. |
- Kaijser, J., et al.
(författare)
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Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies
- 2013
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 41:1, s. 9-20
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Forskningsöversikt (refereegranskat)abstract
- In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two-step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence-based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2 or IOTA simple rules and subjective assessment by an experienced examiner. Copyright (c) 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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| 19. |
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| 20. |
- Timmerman, Dirk, et al.
(författare)
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Inclusion of CA-125 does not improve mathematical models developed to distinguish between benign and malignant adnexal tumors
- 2007
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Ingår i: Journal of Clinical Oncology. - 1527-7755. ; 25:27, s. 4194-4200
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Tidskriftsartikel (refereegranskat)abstract
- Purpose To test the value of serum CA-125 measurements alone or as part of a multimodal strategy to distinguish between malignant and benign ovarian tumors before surgery based on a large prospective multicenter study (International Ovarian Tumor Analysis). Patients and Methods Patients with at least one persistent ovarian mass preoperatively underwent transvaginal ultrasonography using gray scale imaging to assess tumor morphology and color Doppler imaging to obtain indices of blood flow. Results Data from 809 patients recruited from nine centers were included in the analysis; 567 patients (70%) had benign tumors and 242 (30%) had malignant tumors - of these 152 were primary invasive (62.8%), 52 were borderline malignant (21.5%), and 38 were metastatic (15.7%). A logistic regression model including CA-125 (M2) resulted in an area under the receiver operating characteristic curve (AUC) of 0.934 and did not outperform a published (M1) without serum CA-125 information (AUC, 0.936). Specifically designed new models including CA-125 for premenopausal women (M3) and for postmenopausal women (M4) did not perform significantly better than the model without CA-125 ( M1; AUC, 0.891 v AUC, 0.911 and AUC, 0.975 v AUC, 0.949, respectively). In postmenopausal patients, serum CA-125 alone (AUC, 0.920) and the risk of malignancy index (AUC, 0.924) performed very well. Results were very similar when the models were prospectively tested on a group of 345 new patients with adnexal masses of whom 126 had malignant tumors (37%). Conclusion Adding information on CA-125 to clinical information and ultrasound information does not improve discrimination of mathematical models between benign and malignant adnexal masses.
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| 21. |
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| 22. |
- Valentin, Lil, et al.
(författare)
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Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses.
- 2009
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Ingår i: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology. - : Wiley. - 1469-0705. ; 34, s. 345-354
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Tidskriftsartikel (refereegranskat)abstract
- 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 (>/=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 after ultrasound examination. CONCLUSIONS: Specialist ultrasound examination is superior to CA 125 for preoperative discrimination between benign and malignant adnexal masses, irrespective of the diagnostic confidence of the ultrasound examiner; adding CA 125 to ultrasound does not improve diagnostic performance. Our results indicate that greater investment in education and training in gynecological ultrasound imaging would be of value. Copyright (c) 2009 ISUOG. Published by John Wiley & Sons, Ltd.
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| 24. |
- Van Calster, B, et al.
(författare)
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Classifying ovarian tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A multi-center study
- 2006
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Ingår i: Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE. - 1557-170X. ; 1, s. 5342-5345
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Konferensbidrag (refereegranskat)abstract
- Ovarian masses are common and a good pre-surgical assessment of their nature is important for adequate treatment. Bayesian Multi-Layer Perceptrons (MLPs) using the evidence procedure were used to predict whether tumors are malignant or not. Automatic Relevance Determination (ARD) is used to select the most relevant of the 40+ available variables. Cross-validation is used to select an optimal combination of input set and number of hidden neurons. The data set consists of 1066 tumors collected at nine centers across Europe. Results indicate good performance of the models with AUC values of 0.93-0.94 on independent data. A comparison with a Bayesian perceptron model shows that the present problem is to a large extent linearly separable. The analyses further show that the number of hidden neurons specified in the ARD analyses for input selection may influence model performance.
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| 25. |
- Van Calster, Ben, et al.
(författare)
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Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
- 2010
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Hitherto, risk prediction models for preoperative ultrasound-based diagnosis of ovarian tumors were dichotomous (benign versus malignant). We develop and validate polytomous models (models that predict more than two events) to diagnose ovarian tumors as benign, borderline, primary invasive or metastatic invasive. The main focus is on how different types of models perform and compare. Methods: A multi-center dataset containing 1066 women was used for model development and internal validation, whilst another multi-center dataset of 1938 women was used for temporal and external validation. Models were based on standard logistic regression and on penalized kernel-based algorithms (least squares support vector machines and kernel logistic regression). We used true polytomous models as well as combinations of dichotomous models based on the 'pairwise coupling' technique to produce polytomous risk estimates. Careful variable selection was performed, based largely on cross-validated c-index estimates. Model performance was assessed with the dichotomous c-index (i.e. the area under the ROC curve) and a polytomous extension, and with calibration graphs. Results: For all models, between 9 and 11 predictors were selected. Internal validation was successful with polytomous c-indexes between 0.64 and 0.69. For the best model dichotomous c-indexes were between 0.73 (primary invasive vs metastatic) and 0.96 (borderline vs metastatic). On temporal and external validation, overall discrimination performance was good with polytomous c-indexes between 0.57 and 0.64. However, discrimination between primary and metastatic invasive tumors decreased to near random levels. Standard logistic regression performed well in comparison with advanced algorithms, and combining dichotomous models performed well in comparison with true polytomous models. The best model was a combination of dichotomous logistic regression models. This model is available online. Conclusions: We have developed models that successfully discriminate between benign, borderline, and invasive ovarian tumors. Methodologically, the combination of dichotomous models was an interesting approach to tackle the polytomous problem. Standard logistic regression models were not outperformed by regularized kernel-based alternatives, a finding to which the careful variable selection procedure will have contributed. The random discrimination between primary and metastatic invasive tumors on temporal/external validation demonstrated once more the necessity of validation studies.
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