Ultrasound-guided robotic surgical procedures: a systematic review.

INTRODUCTION: Ultrasound has been nicknamed "the surgeon's stethoscope". The advantages of laparoscopic ultrasound beyond a substitute for the sense of touch are considerable, especially for robotic surgery. Being able to see through parenchyma and into vascular structures enables to avoid unnecessary dissection by providing a thorough assessment at every stage without the need for contrast media or ionising radiation. The limitations of restricted angulation and access within the abdominal cavity during laparoscopy can be overcome by robotic handling of miniaturised ultrasound probes and the use of various and specific frequencies will meet tissue- and organ-specific characteristics. The aim of this systematic review was to assess the reported applications of intraoperative ultrasound-guided robotic surgery and to outline future perspectives. METHODS: The study adhered to the PRISMA guidelines. PubMed, Google Scholar, ScienceDirect and ClinicalTrials.gov were searched up to October 2023. Manuscripts reporting data on ultrasound-guided robotic procedures were included in the qualitative analysis. RESULTS: 20 studies met the inclusion criteria. The majority (53%) were related to the field of general surgery during liver, pancreas, spleen, gallbladder/bile duct, vascular and rectal surgery. This was followed by other fields of oncological surgery (42%) including urology, lung surgery, and retroperitoneal lymphadenectomy for metastases. Among the studies, ten (53%) focused on locating tumoral lesions and defining resection margins, four (15%) were designed to test the feasibility of robotic ultrasound-guided surgery, while two (10.5%) aimed to compare robotic and laparoscopic ultrasound probes. Additionally two studies (10.5%) evaluated the robotic drop-in probe one (5%) assessed the hepatic tissue consistency and another one (5%) aimed to visualize the blood flow in the splenic artery. CONCLUSION: The advantages of robotic instrumentation, including ergonomics, dexterity, and precision of movements, are of relevance for robotic intraoperative ultrasound (RIOUS). The present systematic review demonstrates the virtue of RIOUS to support surgeons and potentially reduce minimally invasive procedure times.

External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups.

Importance: Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy. Objective: To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy. Design, Setting, and Participants: Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022. Exposures: Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy. Main Outcomes and Measures: Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information. Results: Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%). Conclusions and Relevance: The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.

Sonographic, Demographic, and Clinical Characteristics of Pre- and Postmenopausal Women with Endometrial Cancer; Results from a Post Hoc Analysis of the IETA4 (International Endometrial Tumor Analysis) Multicenter Cohort.

In this study, we conducted a comparative analysis of demographic, histopathological, and sonographic characteristics between pre- and postmenopausal women diagnosed with endometrial cancer, while also examining sonographic and anthropometric features in 'low' and 'intermediate/high-risk' cases, stratified by menopausal status. Our analysis, based on data from the International Endometrial Tumor Analysis (IETA) 4 cohort comprising 1538 women (161 premenopausal, 1377 postmenopausal) with biopsy-confirmed endometrial cancer, revealed that premenopausal women, compared to their postmenopausal counterparts, exhibited lower parity (median 1, IQR 0-2 vs. 1, IQR 1-2, p = 0.001), a higher family history of colon cancer (16% vs. 7%, p = 0.001), and smaller waist circumferences (median 92 cm, IQR 82-108 cm vs. 98 cm, IQR 87-112 cm, p = 0.002). Premenopausal women more often had a regular endometrial-myometrial border (39% vs. 23%, p < 0.001), a visible endometrial midline (23% vs. 11%, p < 0.001), and undefined tumor (73% vs. 84%, p = 0.001). Notably, despite experiencing a longer duration of abnormal uterine bleeding (median 5 months, IQR 3-12 vs. 3 months, 2-6, p < 0.001), premenopausal women more often had 'low' risk disease (78% vs. 46%, p < 0.001). Among sonographic and anthropometric features, only an irregular endometrial-myometrial border was associated with 'intermediate/high' risk in premenopausal women. Conversely, in postmenopausal women, multiple features correlated with 'intermediate/high' risk disease. Our findings emphasize the importance of considering menopausal status when evaluating sonographic features in women with endometrial cancer.

Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study.

OBJECTIVE: To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. DESIGN: Multicentre cohort study. SETTING: 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre. PARTICIPANTS: Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up. MAIN OUTCOME MEASURES: Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain. RESULTS: The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125. CONCLUSIONS: Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively. TRIAL REGISTRATION: ClinicalTrials.gov NCT01698632.

Role of ultrasound in advanced peritoneal malignancies.

INTRODUCTION: Ovarian cancer is the seventh most common cancer among women in the developed world, and most women with ovarian cancer are diagnosed at an advanced stage of disease, when large intraperitoneal dissemination has already occurred. An accurate preoperative assessment of the tumor dissemination is pivotal for adequate counseling among risks and benefits of an aggressive surgical procedure, often required to achieve a complete cytoreduction. When performed by an experienced sonographer, ultrasound has an invaluable role in the primary diagnosis of gynecological cancer, in the assessment of tumor extent in the pelvis and abdominal cavity; however, there is a paucity of data on its use in the evaluation of the extent of disease of such patients. EVIDENCE ACQUISITION: The search retrieved 208 articles in the best matching results list. Selection by abstract and full-text, yielded 15 publications that contained information on the role of ultrasound examination in the assessment of diffused peritoneal malignancies. EVIDENCE SYNTHESIS: Sonographic appearance of metastatic nodules in peritoneum and omentum were firstly analyzed in preliminar descriptive studies, together with a systematic method to scan the abdomen and pelvis in in the staging of diffused gynecological malignancies. To date, three prospective studies mainly focused on the specific role of ultrasound (without comparison with other imaging modalities) in the evaluation of intra-abdominal tumor extension in ovarian cancer patients. In these studies, authors were in agreement to conclude that ultrasound has a very reliable role in the staging of ovarian cancer. In particular, ultrasound examination showed a high sensitivity (range 81.4-91%) and specificity (range 88-96%) in the diagnosis of peritoneal carcinomatosis, as well as in omental involvement (sense 67-94%, specificity 90%). In a recent prospective study ultrasound shows similar accuracy of CT scan in the staging of ovarian cancer patients (71% vs. 75%) when compared with surgical results. CONCLUSIONS: Even if ultrasound is a largely diffuse and practice imaging technique, there is a paucity of data in literature on its use in the evaluation of the extent of disease in ovarian cancer patiens. Nevertheless, this review has demonstrated that ultrasound has a high accuracy in staging advanced ovarian cancer patients. In certain settings, ultrasound has already replaced CT scan in the pre-operative evaluation of pelvic and abdominal disease. Finally, ultrasound allows to perform a biopsy in patients with peritoneal carcinomatosis obtaining an adequate specimen for histologic diagnosis.

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

OBJECTIVES: To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. METHODS: Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. RESULTS: Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. CONCLUSIONS: The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan.

Age-related differences in the sonographic characteristics of endometriomas.

STUDY QUESTION: Do sonographic characteristics of ovarian endometriomas vary with age in premenopausal women? SUMMARY ANSWER: With increasing age, multilocular cysts and cysts with papillations and other solid components become more common whereas ground glass echogenicity of cyst fluid becomes less common. WHAT IS KNOWN ALREADY: Expectant or medical management of women with endometriomas is now accepted. Therefore, the accuracy of non-invasive diagnosis of these cysts is pivotal. A clinically relevant question is whether the sonographic characteristics of ovarian endometriomas are the same irrespective of the age of the woman. STUDY DESIGN, SIZE, DURATION: This is a secondary analysis of cross-sectional data in the International Ovarian Tumor Analysis (IOTA) database. The database contains clinical and ultrasound information collected pre-operatively between 1999 and 2012 from 5914 patients with adnexal masses in 24 ultrasound centres in 10 countries. PARTICIPANTS/MATERIALS, SETTING, METHODS: There were 1005 histologically confirmed endometriomas in adult premenopausal patients found in the database and these were used in our analysis. The following ultrasound variables (defined using IOTA terminology) were used to describe the ultrasound appearance of the endometriomas: tender mass at ultrasound, largest diameter of lesion, tumour type (unilocular, unilocular-solid, multilocular, multilocular-solid, solid), echogenicity of cyst content, presence of papillations, number of papillations, height (mm) of largest papillation, presence and proportion of solid tissue and number of cyst locules, as well as vascularity in papillations and colour content of the tumour scan (colour score) on colour or power Doppler ultrasounds. Results are reported as median difference or odds ratio (OR) per 10 years increase in age. MAIN RESULTS AND THE ROLE OF CHANCE: Maximal lesion diameter did not vary substantially with age (+1.3 mm difference per 10 years increase in age, 95% confidence interval (CI) -1.4 to 4.0). Tender mass at scan was less common in the older the woman (OR 0.75, 95% CI 0.63-0.89), as were unilocular cysts relative to multilocular cysts (OR 0.70, 95% CI 0.57-0.85) and to lesions with solid components (OR 0.61, 95% CI 0.48-0.77), and ground glass echogenicity relative to homogeneous low-level echogenicity (OR 0.74, 95% CI 0.58-0.94) and other types of echogenicity of cyst contents (OR 0.64, 95% CI 0.50-0.81). Papillations were more common the older the woman (OR 1.65, 95% CI 1.24-2.21), but their height and vascularization showed no clear relation to age. LIMITATIONS, REASONS FOR CAUTION: It is a limitation that we have little clinical information on the women included, e.g. previous surgery or medical treatment for endometriosis. It is important to emphasize that we do not know the age of the endometrioma itself and that our study is not longitudinal and so does not describe changes in endometriomas over time. The differences in the ultrasound appearance of endometriomas between women of different ages might be explained by previous surgery or medical treatment and might not be an effect of age per se. WIDER IMPLICATIONS OF THE FINDINGS: Awareness of physicians that the ultrasound appearance of endometriomas differs between women of different ages may facilitate a correct diagnosis of endometrioma. STUDY FUNDING/COMPETING INTERESTS: This study was supported in part by the Regione Autonoma della Sardegna (project code CPR-24750). B.V.C., A.C. and D.T. are supported by the Fund for Scientific Research Flanders, Belgium (FWO). The authors declare that there is no conflict of interest.

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.

OBJECTIVES: To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. DESIGN: Observational diagnostic study using prospectively collected clinical and ultrasound data. SETTING: 24 ultrasound centres in 10 countries. PARTICIPANTS: Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. MAIN OUTCOME MEASURES: Histological classification and surgical staging of the mass. RESULTS: The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. CONCLUSIONS: The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.

External validation of diagnostic models to estimate the risk of malignancy in adnexal masses.

PURPOSE: To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses. EXPERIMENTAL DESIGN: We externally validated the diagnostic performance of 11 models developed by the International Ovarian Tumor Analysis (IOTA) group and 12 other (non-IOTA) models on 997 prospectively collected patients. The non-IOTA models included the original risk of malignancy index (RMI), three modified versions of the RMI, six logistic regression models, and two artificial neural networks. The ability of the models to discriminate between benign and malignant adnexal masses was expressed as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and likelihood ratios (LR(+), LR(-)). RESULTS: Seven hundred and forty-two (74%) benign and 255 (26%) malignant masses were included. The IOTA models did better than the non-IOTA models (AUCs between 0.941 and 0.956 vs. 0.839 and 0.928). The difference in AUC between the best IOTA and the best non-IOTA model was 0.028 [95% confidence interval (CI), 0.011-0.044]. The AUC of the RMI was 0.911 (difference with the best IOTA model, 0.044; 95% CI, 0.024-0.064). The superior performance of the IOTA models was most pronounced in premenopausal patients but was also observed in postmenopausal patients. IOTA models were better able to detect stage I ovarian cancer. CONCLUSION: External validation shows that the IOTA models outperform other models, including the current reference test RMI, for discriminating between benign and malignant adnexal masses.

Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models.

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.

Ultrasound experience substantially impacts on diagnostic performance and confidence when adnexal masses are classified using pattern recognition.

AIM: To determine how accurately and confidently examiners with different levels of ultrasound experience can classify adnexal masses as benign or malignant and suggest a specific histological diagnosis when evaluating ultrasound images using pattern recognition. METHODS: Ultrasound images of selected adnexal masses were evaluated by 3 expert sonologists, 2 senior and 4 junior trainees. They were instructed to classify the masses using pattern recognition as benign or malignant, to state the level of confidence with which this classification was made and to suggest a specific histological diagnosis. Sensitivity, specificity, accuracy and positive and negative likelihood ratios (LR+ and LR-) with regard to malignancy were calculated. The area under the receiver operating characteristic curve (AUC) of pattern recognition was calculated by using six levels of diagnostic confidence. RESULTS: 166 masses were examined, of which 42% were malignant. Sensitivity with regard to malignancy ranged from 80 to 86% for the experts, was 70 and 84% for the 2 senior trainees and ranged from 70 to 86% for the junior trainees. The specificity of the experts ranged from 79 to 91%, was 77 and 89% for the senior trainees and ranged from 59 to 83% for the junior trainees. The experts were uncertain about their diagnosis in 4-13% of the cases, the senior trainees in 15-20% and the junior trainees in 67-100% of the cases. The AUCs ranged from 0.861 to 0.922 for the experts, were 0.842 and 0.855 for the senior trainees, and ranged from 0.726 to 0.795 for the junior trainees. The experts suggested a correct specific histological diagnosis in 69-77% of the cases. All 6 trainees did so significantly less often (22-42% of the cases). CONCLUSION: Expert sonologists can accurately classify adnexal masses as benign or malignant and can successfully predict the specific histological diagnosis in many cases. Whilst less experienced operators perform reasonably well when predicting the benign or malignant nature of the mass, they do so with a very low level of diagnostic confidence and are unable to state the likely histology of a mass in most cases.

Characterising pelvic masses using ultrasound.

The evaluation of a pelvic mass, detected at routine ultrasound or in the context of having acute symptoms, requires certain methodical steps. It is necessary to diagnose the primary site or origin of the lesion; understand whether the lesion is an intra- or an extra-peritoneal lesion; distinguish whether the structure of interest is 'functional' and transitory or if we are dealing with a persistent mass; attempt to discriminate between the benign or malignant nature of the lesion; formulate a specific diagnosis; and furthermore, in the case of a possible malignant mass, define the stage of the disease process. Transvaginal ultrasonography is a dynamic and interactive examination and besides an analysis of the echostructure, and 'elasticity' of a pelvic mass, it also permits an assessment of site-specific pain in different pelvic areas, and an evaluation of the movement of the mass in relation to adjacent structures. All these 'dynamic' features, together with morphological and vascular parameters, are essential for making a correct diagnosis. The features of acute ovarian pathology including torsion are not discussed in detail here. This article will concentrate on the characterisation of pelvic masses that may be encountered by any examiner in the course of an assessment of the female pelvis.

Prospective internal validation of mathematical models to predict malignancy in adnexal masses: results from the international ovarian tumor analysis study.

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.

How often are endometrial polyps malignant in asymptomatic postmenopausal women? A multicenter study.

OBJECTIVE: The objective of the study was to evaluate the prevalence of cancer and premalignant lesions in polyps on atrophic endometrium in asymptomatic postmenopausal women to compare these findings with a similar cohort of patients with abnormal uterine bleeding. STUDY DESIGN: One thousand one hundred fifty-two asymptomatic and 770 consecutive postmenopausal women with abnormal uterine bleeding were included in a retrospective multicenter study. Recruited patients underwent hysteroscopic polypectomy based on a sonohysterographic or hysteroscopic diagnosis. The pathologic report was the main outcome measure. RESULTS: One single case of stage 1 grade 1 endometrial carcinoma on a polyp with a mean diameter of 40 mm (0.1%) was observed in asymptomatic women. This prevalence was 10 times lower than in symptomatic patients (P < .0001). The prevalence of atypical hyperplastic polyps was 1.2% in asymptomatic women (2.2% in symptomatic patients; P < .005). At multivariate analysis, polyps' diameter was the only variable significantly associated to an abnormal histology (cancer, polypoid cancer, and atypical hyperplasia) in asymptomatic women (odds ratio for polyps with mean diameter > 18 mm, 6.9; confidence interval, 2.2-21.4). CONCLUSION: Follow-up and/or treatment of endometrial polyps incidentally diagnosed in asymptomatic postmenopausal patients could be safely restricted to few selected cases based on polyp diameter.

Inclusion of CA-125 does not improve mathematical models developed to distinguish between benign and malignant adnexal tumors.

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.

External validation of mathematical models to distinguish between benign and malignant adnexal tumors: a multicenter study by the International Ovarian Tumor Analysis Group.

PURPOSE: Several scoring systems have been developed to distinguish between benign and malignant adnexal tumors. However, few of them have been externally validated in new populations. Our aim was to compare their performance on a prospectively collected large multicenter data set. EXPERIMENTAL DESIGN: In phase I of the International Ovarian Tumor Analysis multicenter study, patients with a persistent adnexal mass were examined with transvaginal ultrasound and color Doppler imaging. More than 50 end point variables were prospectively recorded for analysis. The outcome measure was the histologic classification of excised tissue as malignant or benign. We used the International Ovarian Tumor Analysis data to test the accuracy of previously published scoring systems. Receiver operating characteristic curves were constructed to compare the performance of the models. RESULTS: Data from 1,066 patients were included; 800 patients (75%) had benign tumors and 266 patients (25%) had malignant tumors. The morphologic scoring system used by Lerner gave an area under the receiver operating characteristic curve (AUC) of 0.68, whereas the multimodal risk of malignancy index used by Jacobs gave an AUC of 0.88. The corresponding values for logistic regression and artificial neural network models varied between 0.76 and 0.91 and between 0.87 and 0.90, respectively. Advanced kernel-based classifiers gave an AUC of up to 0.92. CONCLUSION: The performance of the risk of malignancy index was similar to that of most logistic regression and artificial neural network models. The best result was obtained with a relevance vector machine with radial basis function kernel. Because the models were tested on a large multicenter data set, results are likely to be generally applicable.

Logistic regression model to distinguish between the benign and malignant adnexal mass before surgery: a multicenter study by the International Ovarian Tumor Analysis Group.

PURPOSE: To collect data for the development of a more universally useful logistic regression model to distinguish between a malignant and benign adnexal tumor before surgery. PATIENTS AND METHODS: Patients had at least one persistent mass. More than 50 clinical and sonographic end points were defined and recorded for analysis. The outcome measure was the histologic classification of excised tissues as malignant or benign. RESULTS: Data from 1,066 patients recruited from nine European centers were included in the analysis; 800 patients (75%) had benign tumors and 266 (25%) had malignant tumors. The most useful independent prognostic variables for the logistic regression model were as follows: (1) personal history of ovarian cancer, (2) hormonal therapy, (3) age, (4) maximum diameter of lesion, (5) pain, (6) ascites, (7) blood flow within a solid papillary projection, (8) presence of an entirely solid tumor, (9) maximal diameter of solid component, (10) irregular internal cyst walls, (11) acoustic shadows, and (12) a color score of intratumoral blood flow. The model containing all 12 variables (M1) gave an area under the receiver operating characteristic curve of 0.95 for the development data set (n = 754 patients). The corresponding value for the test data set (n = 312 patients) was 0.94; and a probability cutoff value of .10 gave a sensitivity of 93% and a specificity of 76%. CONCLUSION: Because the model was constructed from multicenter data, it is more likely to be generally applicable. The effectiveness of the model will be tested prospectively at different centers.

The role of sonographic examination in the follow-up of gynecological neoplasms.

OBJECTIVE: The role and type of procedures of follow-up in patients with gynecological tumors are still a debatable issue. We prospectively analyzed the role of routine transabdominal and transvaginal ultrasound examination (US) in the detection of recurrent disease in gynecologic cancer patients. METHODS: Among 552 patients who underwent surgery for gynecological cancer, 385 were available for the analysis. Follow-up examinations included clinical examination, serum tumor marker assay, transvaginal and transabdominal sonography and CT scan/MRI. RESULTS: Positive US examination was documented in 83/385 patients (21.5%). In the overall series, the positive predictive value (PPV) of US examination was 100%, while the negative predictive value (NPV) was 92.7% failing to identify 22 cases of recurrences. When considering the subgroup of patients with positive clinical examination or abnormal tumor marker, positive US analysis was able to identify 66/66 cases of recurrence (PPV=100%), but exhibited an NPV of 22.2%, with 21/27 (77.8%) false negative cases. Conversely, in cases without clinical/serological signs of disease, positive US recognized all cases of recurrences (17/17, PPV=100%), and exhibited a very high NPV, with only 1 false negative case out of 275 (0.4%). The US detected recurrences appeared as a solitary lesion in 38/75 (50.6%) patients and in 28/75 (37%) appeared located centrally in the pelvis. The sonographic pattern of the ovarian recurrences was a solid lesion in most (33/40, 82%) cases. In the other gynecological tumors, the lesions appeared as solid masses in 33/35 (94%) cases. CONCLUSIONS: We showed that routine US might play a role in the follow-up of gynecologic malignancies, especially in the group of asymptomatic patients, while CT/MRI imaging might be more properly applied to patients with clinical or serological signs of disease.

Celecoxib modulates the expression of cyclooxygenase-2, ki67, apoptosis-related marker, and microvessel density in human cervical cancer: a pilot study.

PURPOSE: We investigated whether a short treatment with the cyclooxygenase-2 (COX-2) inhibitor celecoxib could modulate Ki67 antigen and the caspase cleavage product of keratin 18, recognized as a marker of early apoptosis. The activity of celecoxib on microvessel density (MVD) and angio-power Doppler sonography-derived indices of tumor vascularization was also assessed. Serum levels of squamous cell carcinoma antigen and the proliferative potential and subsets of peripheral T cells before and after celecoxib treatment were also analyzed. EXPERIMENTAL DESIGN: Tumor biopsy specimens from 14 patients with cervical cancer were obtained at baseline and after 10 days of celecoxib treatment (400 mg twice daily). Tumor and stroma COX-2 expression, Ki67, apoptosis, and MVD were assessed by immunohistochemistry, whereas prostaglandin E(2) levels were measured by RIA. RESULTS: At baseline, COX-2 integrated density values in tumor compartment ranged from 10.7 to 60.1 (median, 26.5) and were significantly higher than tumor COX-2 integrated density values after celecoxib treatment (range, 0.6-42.3; median, 12.6; P = 0.0043). The percentages of Ki67-positive tumor cells in pre-celecoxib cases ranged from 39.3 to 87.4 (median, 50.8) and were significantly higher than the percentage in the corresponding posttreatment samples (range, 27.7-83.8; median, 43.1; P = 0.0092). MVD values in pre-celecoxib biopsies ranged from 28.0 to 55.0 (median, 38.5) and were significantly higher than the corresponding values in posttreatment samples (range, 16.0-49.5; median; 27.6; P = 0.012). Also, prostaglandin E(2) levels showed a trend to be reduced after celecoxib treatment (range: 4.7-386.6 pg/mg wet tissue in pretreated cases versus 4.8-91.9 pg/mg wet tissue in posttreated cases (P = 0.092). CONCLUSIONS: In cervical cancer, celecoxib treatment decreases tumor COX-2 expression and markers of proliferation and neoangiogenesis, while being uneffective on stroma COX-2 levels, thus suggesting that selective COX-2 inhibitors may be a promising strategy not only for chemopreventive approaches but also for therapeutic approaches in this neoplasia.