Defining Models to Classify between Benign and Malignant Adnexal Masses Using Routine Laboratory Parameters.
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ABSTRACT:
SUBMITTER: Reiser E
PROVIDER: S-EPMC9264825 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveOvarian cancer is the most deadly deadliest gynecological tumor in the female reproductive system. Therefore, the present study sought to determine the diagnostic performance of International Ovarian Tumor Analysis Simple Rules (IOTA SR), the Ovarian-Adnexal Reporting and Data System (O-RADS), and Cancer Antigen 125 (CA125) in discriminating benign and malignant ovarian tumors. The study also assessed whether a combination of the two ultrasound categories systems and CA125 can improve the diagnostic performance.MethodsA total of 453 patients diagnosed with ovarian tumors were retrospectively enrolled from Fujian Cancer Hospital between January 2017 and September 2020. The data collected from patients included age, maximum lesion diameter, location, histopathology, levels of CA125, and detailed ultrasound reports. Additionally, all ultrasound images were independently assessed by two ultrasound physicians with more than 5 years of experience in the field, according to the IOTA simple rules and O-RADS guidelines. Furthermore, the area under the curve (AUC), sensitivity, and specificity of the above mentioned predictors were calculated using the receiver operating characteristic curve.ResultsOut of the 453 patients, 184 had benign lesions, while 269 had malignant ovarian tumors. In addition, the AUCs of IOTA SR, O-RADS, and CA125 in the overall population were 0.831, 0.804, and 0.812, respectively, and the sensitivities of IOTA SR, O-RADS, and CA125 were 94.42, 94.42, and 80.30%, respectively. On the other hand, the AUCs of IOTA SR combined with CA125, O-RADS combined with CA125, and IOTA SR plus O-RADS combined with CA125 were 0.900, 0.891, and 0.909, respectively. The findings also showed that the AUCs of a combination of the three approaches were significantly higher than those of individual strategies (p<0.05) but not significantly higher than the AUC of a combination of two methods (p>0.05).ConclusionThe findings showed that a combination of IOTA SR or O-RADS in combination with CA125 may improve the ability to distinguish benign from malignant ovarian tumors.
| S-EPMC8785584 | biostudies-literature
Project description:Adnexal masses detected during pregnancy require a prompt and accurate diagnosis to ensure fetal safety and good oncological outcomes. Computed tomography is the most common and useful diagnostic imaging modality for diagnosing adnexal masses; however, it is contraindicated in pregnant women because of the teratogenic effect of radiation on the fetus. Therefore, ultrasonography (US) is commonly used as the main alternative for the differential diagnosis of adnexal masses during pregnancy. Additionally, magnetic resonance imaging (MRI) can assist in the diagnosis when US findings are inconclusive. As each disease has characteristic US and MRI findings, understanding these features is important for the initial diagnosis and subsequent treatment. Thus, we thoroughly reviewed the literature and summarized the key findings of US and MRI to apply these in real-world clinical practice for various adnexal masses detected during pregnancy.
| S-EPMC10191762 | biostudies-literature
Project description:BackgroundThe composition of pelvic masses during pregnancy is complex, and over >70% of masses are physiology. Determining the source and nature of tumor tissue is incredibly important in clinical practice, as the proportion of metastatic and low-grade tumors in adnexal masses increase during pregnancy. This study sought to analyze the pathological features of persistent adnexal masses in pregnancy.MethodsA retrospective case analysis method was adopted to summarize the pathologic features of persistent adnexal masses in pregnancy in 228 patients at the Beijing Chao-Yang Hospital, Capital Medical University.ResultsMature teratoma was the most common histopathological type of persistent adnexal masses in pregnancy (66/228, 28.95%), followed by the corpus luteum of pregnancy (38/228, 16.67%). Borderline/malignant tumors accounted for 5.70% (13/228) of tumors. Malignant adnexal tumor tissues were derived from multiple types of tissues. a single-factor analysis showed that borderline/malignant tumors had a significant relationship with the morphological features of mass in the ultrasound (P=0.000), and had a significant relationship with initial mass size (P=0.018). A multivariate binary logistic regression analysis indicated no certain independent risk factor. A significant difference in tumor pathology distribution was noted between those who underwent emergency surgery during pregnancy, elective surgery during pregnancy, and simultaneous tumor removal during cesarean section (χ2=24.22, P=0.000).ConclusionsA special particularity exists in the pathology distribution of persistent adnexal masses in pregnancy. Additionally, extensive histological sources and the need to rule out borderline/malignancy for solid cystic tumors were noted.
| S-EPMC8267286 | biostudies-literature
Project description:BackgroundMachine learning algorithms used to classify cystic renal masses (CRMs) nave not been applied to unenhanced CT images, and their diagnostic accuracy had not been compared against radiologists.MethodThis retrospective study aimed to develop radiomics models that discriminate between benign and malignant CRMs in a triple phase computed tomography (CT) protocol and compare the diagnostic accuracy of the radiomics approach with experienced radiologists. Predictive models were established using a training set and validation set of unenhanced and enhanced (arterial phase [AP] and venous phase [VP]) CT images of benign and malignant CRMs. The diagnostic capabilities of the models and experienced radiologists were compared using Receiver Operating Characteristic (ROC) curves.ResultsOn unenhanced, AP and VP CT images in the validation set, the AUC, specificity, sensitivity and accuracy for discriminating between benign and malignant CRMs were 90.0 (95%CI: 81-98%), 90.0%, 90.5% and 90.2%; 93.0% (95%CI: 86-99%), 86.7%, 95.2% and 88.3%; and 95.0% (95%CI: 90%-100%), 93.3%, 90.5% and 92.1%, respectively, for the radiomics models. Diagnostic accuracy of the radiomics models differed significantly on unenhanced images in the training set vs. each radiologist (p = 0.001 and 0.003) but not in the validation set (p = 0.230 and 0.590); differed significantly on AP images in the validation set vs. each radiologist (p = 0.007 and 0.007) but not in the training set (p = 0.663 and 0.663); and there were no differences on VP images in the training or validation sets vs. each radiologist (training set: p = 0.453 and 0.051, validation set: p = 0.236 and 0.786).ConclusionsRadiomics models may have clinical utility for discriminating between benign and malignant CRMs on unenhanced and enhanced CT images. The performance of the radiomics model on unenhanced CT images was similar to experienced radiologists, implying it has potential as a screening and diagnostic tool for CRMs.
| S-EPMC10538730 | biostudies-literature
Project description:ObjectivesTo perform a meta-analysis assessing the ability of shear wave elastography (SWE) to identify malignant breast masses.MethodsPubMed, the Cochrane Library, and the ISI Web of Knowledge were searched for studies evaluating the accuracy of SWE for identifying malignant breast masses. The diagnostic accuracy of SWE was evaluated according to sensitivity, specificity, and hierarchical summary receiver operating characteristic (HSROC) curves. An analysis was also performed according to the SWE mode used: supersonic shear imaging (SSI) and the acoustic radiation force impulse (ARFI) technique. The clinical utility of SWE for identifying malignant breast masses was evaluated using analysis of Fagan plot.ResultsA total of 9 studies, including 1888 women and 2000 breast masses, were analyzed. Summary sensitivities and specificities were 0.91 (95% confidence interval [CI], 0.88-0.94) and 0.82 (95% CI, 0.75-0.87) by SSI and 0.89 (95% CI, 0.81-0.94) and 0.91 (95% CI, 0.84-0.95) by ARFI, respectively. The HSROCs for SSI and ARFI were 0.92 (95% CI, 0.90-0.94) and 0.96 (95% CI, 0.93-0.97), respectively. SSI and ARFI were both very informative, with probabilities of 83% and 91%, respectively, for correctly differentiating between benign and malignant breast masses following a "positive" measurement (over the threshold value) and probabilities of disease as low as 10% and 11%, respectively, following a "negative" measurement (below the threshold value) when the pre-test probability was 50%.ConclusionsSWE could be used as a good identification tool for the classification of breast masses.
| S-EPMC3799848 | biostudies-literature
Project description:ObjectivesThe use of magnetic resonance (MR) imaging in differentiation between benign and malignant adnexal masses in children and adolescents might be of great value in the diagnostic workup of sonographically indeterminate masses, since preserving fertility is of particular importance in this population. This systematic review evaluates the diagnostic value of MR imaging in children with an ovarian mass.MethodsThe review was made according to the PRISMA Statement. PubMed and EMBASE were systematically searched for studies on the use of MR imaging in differential diagnosis of ovarian masses in both adult women and children from 2008 to 2018.ResultsSixteen paediatric and 18 adult studies were included. In the included studies, MR imaging has shown good diagnostic performance in differentiating between benign and malignant ovarian masses. MR imaging techniques including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to further improve the diagnostic performance.ConclusionThe addition of DWI with apparent diffusion coefficient (ADC) values measured in enhancing components of solid lesions and DCE imaging may further increase the good diagnostic performance of MR imaging in the pre-operative differentiation between benign and malignant ovarian masses by increasing specificity. Prospective age-specific studies are needed to confirm the high diagnostic performance of MR imaging in children and adolescents with a sonographically indeterminate ovarian mass.Key points• MR imaging, based on several morphological features, is of good diagnostic performance in differentiating between benign and malignant ovarian masses. Sensitivity and specificity varied between 84.8 to 100% and 20.0 to 98.4%, respectively. • MR imaging techniques like diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to improve the diagnostic performance. • Specific studies in children and adolescents with ovarian masses are required to confirm the suggested increased diagnostic performance of DWI and DCE in this population.
| S-EPMC6957553 | biostudies-literature
Project description:ObjectiveReliable results of wash-out CT in the diagnostic workup of adrenal incidentalomas are scarce. Thus, we evaluated the diagnostic accuracy of delayed wash-out CT and determined thresholds to accurately differentiate adrenal masses.DesignRetrospective, single-center cohort study including 216 patients with 252 adrenal lesions who underwent delayed wash-out CT. Definitive diagnoses based on histopathology (n = 92) or comprehensive follow-up.MethodsSize, average attenuation values of the adrenal lesions in all CT scan phases, and absolute and relative percentage wash-out (APW/RPW) were determined by an expert radiologist blinded for clinical data. Adrenal lesions with unenhanced attenuation values >10 Hounsfield units (HU) built a subgroup (n = 142). Diagnostic accuracy was calculated.ResultsThe study group consisted of 171 adenomas, 32 other benign tumors, 11 pheochromocytomas, 9 adrenocortical carcinomas, and 29 other malignant tumors. All (potentially) malignant and 46% of benign lesions showed unenhanced attenuation values >10 HU. In this most relevant subgroup, the established thresholds of 60% for APW and 40% for RPW misclassified 35.9 and 35.2% of the masses, respectively. When we applied optimized cutoffs (APW >83%; RPW >58%) and excluded pheochromocytomas, we missed only one malignant tumor by APW and none by RPW. However, only 11 and 15% of the benign tumors were correctly identified.ConclusionsWash-out CT with the established thresholds for APW and RPW is insufficient to reliably diagnose adrenal masses. Using the proposed cutoff of 58% for RPW, malignant tumors will be correctly identified, but the added value is limited, namely 15% of patients with benign tumors can be prevented from additional imaging or even unnecessary surgery.
| S-EPMC8679842 | biostudies-literature
Project description:BackgroundQuantitative contrast-enhanced ultrasonography parameters are affected by various factors. We evaluated corrected quantitative contrast enhanced ultrasonography in differentiating benign adnexal tumors from malignant tumors.MethodsPatients with adnexal masses who underwent conventional and contrast-enhanced ultrasonography were included. Contrast-enhanced ultrasonography parameters such as base intensity, arrival time, peak intensity, time to peak intensity, ascending slope, and descending slope were measured. Corrected (time to peak intensity - arrival time) mass/(time to peak intensity - arrival time) uterus and (peak intensity - base intensity) mass/(peak intensity - base intensity) uterus were calculated. Lesions were confirmed by pathologic examination of surgical specimens.ResultsThis study included 31 patients with 35 adnexal lesions including 20 (57.10%) benign and 15 (42.90%) malignant lesions. The corrected contrast-enhanced ultrasonography quantitative parameters in lesions were statistically different between malignant and benign groups (P<0.05). The optimal cut-off value for (time to peak intensity - arrival time) mass/(time to peak intensity - arrival time) uterus, ascending slope, and (peak intensity - base intensity) mass/(peak intensity - base intensity) uterus, and descending slope for differentiating malignant adnexal masses from benign tumors were 1.05 (area under curve: 0.93, P<0.05), 1.11 (area under curve: 0.83, P<0.05), 0.82 (area under curve: 0.73, P<0.05), and -0.27 (area under curve: 0.66, P=0.16), with sensitivity and specificity of 93.33% and 85.00%, 86.67% and 75.00%, 86.67% and 60.00%, and 54.55% and 66.67%, respectively.ConclusionsCorrected contrast-enhanced ultrasonography parameters provide practical differential diagnosis value of adnexal lesions with high reliability for sonologists.
| S-EPMC9632442 | biostudies-literature
Project description:BackgroundBased on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.MethodsIn a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).ResultsFour predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.ConclusionThe risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.
| S-EPMC10740199 | biostudies-literature
Project description:AimThis study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass.MethodsThis single-centre diagnostic accuracy study involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios.ResultsTo discriminate benign and malignant tumors, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92-0.96) with CA125 and 0.94 (95% CI: 0.91-0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83-0.90), 0.83 (95% CI: 0.80-0.86), and 0.82 (95% CI: 0.78-0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87-0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86-0.97) and a specificity of 0.86 (95% CI: 0.82-0.89) when inconclusive diagnoses (11.7%) were classified as malignant.ConclusionADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients.
| S-EPMC8204044 | biostudies-literature