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Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) Score for Risk Stratification of Sonographically Indeterminate Adnexal Masses.

ABSTRACT: Importance:Approximately one-quarter of adnexal masses detected at ultrasonography are indeterminate for benignity or malignancy, posing a substantial clinical dilemma. Objective:To validate the accuracy of a 5-point Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of adnexal masses. Design, Setting, and Participants:This multicenter cohort study was conducted between March 1, 2013, and March 31, 2016. Among patients undergoing expectant management, 2-year follow-up data were completed by March 31, 2018. A routine pelvic MRI was performed among consecutive patients referred to characterize a sonographically indeterminate adnexal mass according to routine diagnostic practice at 15 referral centers. The MRI score was prospectively applied by 2 onsite readers and by 1 reader masked to clinical and ultrasonographic data. Data analysis was conducted between April and November 2018. Main Outcomes and Measures:The primary end point was the joint analysis of true-negative and false-negative rates according to the MRI score compared with the reference standard (ie, histology or 2-year follow-up). Results:A total of 1340 women (mean [range] age, 49 [18-96] years) were enrolled. Of 1194 evaluable women, 1130 (94.6%) had a pelvic mass on MRI with a reference standard (surgery, 768 [67.9%]; 2-year follow-up, 362 [32.1%]). A total of 203 patients (18.0%) had at least 1 malignant adnexal or nonadnexal pelvic mass. No invasive cancer was assigned a score of 2. Positive likelihood ratios were 0.01 for score 2, 0.27 for score 3, 4.42 for score 4, and 38.81 for score 5. Area under the receiver operating characteristic curve was 0.961 (95% CI, 0.948-0.971) among experienced readers, with a sensitivity of 0.93 (95% CI, 0.89-0.96; 189 of 203 patients) and a specificity of 0.91 (95% CI, 0.89-0.93; 848 of 927 patients). There was good interrater agreement among both experienced and junior readers (??=?0.784; 95% CI, 0.743-0824). Of 580 of 1130 women (51.3%) with a mass on MRI and no specific gynecological symptoms, 362 (62.4%) underwent surgery. Of them, 244 (67.4%) had benign lesions and a score of 3 or less. The MRI score correctly reclassified the mass origin as nonadnexal with a sensitivity of 0.99 (95% CI, 0.98-0.99; 1360 of 1372 patients) and a specificity of 0.78 (95% CI, 0.71-0.85; 102 of 130 patients). Conclusions and Relevance:In this study, the O-RADS MRI score was accurate when stratifying the risk of malignancy in adnexal masses.

SUBMITTER: Thomassin-Naggara I

PROVIDER: S-EPMC6991280 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo determine the accuracy of interpretation of a non-contrast MRI protocol in characterizing adnexal masses.Methods and materialsTwo hundred ninety-one patients (350 adnexal masses) who underwent gynecological MRI at our institution between the 1st of January 2008 and the 31st of December 2018 were reviewed. A random subset (102 patients with 121 masses) was chosen to evaluate the reproducibility and repeatability of readers' assessments. Readers evaluated non-contrast MRI scans retrospectively, assigned a 5-point score for the risk of malignancy and gave a specific diagnosis. The reference standard for the diagnosis was histopathology or at least one-year imaging follow-up. Diagnostic accuracy of the non-contrast MRI score was calculated. Inter- and intra-reader agreement was analyzed with Cohen's kappa statistics.ResultsThere were 53/350 (15.1%) malignant lesions in the whole cohort and 20/121 (16.5%) malignant lesions in the random subset. Good agreement between readers was found for the non-contrast MRI score (к = 0.73, 95% confidence interval [CI] 0.58-0.86) whilst the intra-reader agreement was excellent (к = 0.81, 95% CI 0.70-0.88). The non-contrast MRI score value of ≥ 4 was associated with malignancy with a sensitivity of 84.9%, a specificity of 95.9%, an accuracy of 94.2% and a positive likelihood ratio of 21 (area under the receiver operating curve 0.93, 95% CI 0.90-0.96).ConclusionAdnexal mass characterization on MRI without the administration of contrast medium has a high accuracy and excellent inter- and intra-reader agreement. Our results suggest that non-contrast studies may offer a reasonable diagnostic alternative when the administration of intravenous contrast medium is not possible.Key points• A non-contrast pelvic MRI protocol may allow the characterization of adnexal masses with high accuracy. • The non-contrast MRI score may be used in clinical practice for differentiating benign from malignant adnexal lesions when the lack of intravenous contrast medium precludes analysis with the O-RADS MRI score.

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.

Project description:BackgroundThe treatment and prognosis for muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) are different. We aimed to construct a nomogram based on the multiparametric MRI (mpMRI) radiomics signature and the Vesical Imaging-Reporting and Data System (VI-RADS) score for the preoperative differentiation of MIBC from NMIBC.MethodThe retrospective study involved 185 pathologically confirmed bladder cancer (BCa) patients (training set: 129 patients, validation set: 56 patients) who received mpMRI before surgery between August 2014 to April 2020. A total of 2,436 radiomics features were quantitatively extracted from the largest lesion located on the axial T2WI and from dynamic contrast-enhancement images. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature screening. The selected features were introduced to construct radiomics signatures using three classifiers, including least absolute shrinkage and selection operator (LASSO), support vector machines (SVM) and random forest (RF) in the training set. The differentiation performances of the three classifiers were evaluated using the area under the curve (AUC) and accuracy. Univariable and multivariable logistic regression were used to develop a nomogram based on the optimal radiomics signature and clinical characteristics. The performance of the radiomics signatures and the nomogram was assessed and validated in the validation set.ResultsCompared to the RF and SVM classifiers, the LASSO classifier had the best capacity for muscle invasive status differentiation in both the training (accuracy: 90.7%, AUC: 0.934) and validation sets (accuracy: 87.5%, AUC: 0.906). Incorporating the radiomics signature and VI-RADS score, the nomogram demonstrated better discrimination and calibration both in the training set (accuracy: 93.0%, AUC: 0.970) and validation set (accuracy: 89.3%, AUC: 0.943). Decision curve analysis showed the clinical usefulness of the nomogram.ConclusionsThe mpMRI radiomics signature may be useful for the preoperative differentiation of muscle-invasive status in BCa. The proposed nomogram integrating the radiomics signature with the VI-RADS score may further increase the differentiation power and improve clinical decision making.

Project description:Despite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated. Biopsy results were used as gold standard. PI-RADS 3 and PI-RADS 4 lesions were re-scored according to the PI-RADS v2.1 before and after DCE-MRI evaluation. Radiomic features were extracted from T2-weighted MRI (T2), Apparent diffusion Coefficient (ADC) map and DCE-MRI subtracted images using PyRadiomics. Feature selection was performed using Wilcoxon-ranksum test and Minimum Redundancy Maximum Relevance (mRMR). Predictive models were constructed for PCa detection in PI-RADS 3 and upPI-RADS 4 lesions using at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. 41 PI-RADS 3 and 32 upPI-RADS 4 lesions were analyzed. Among 293 radiomic features, the top selected features derived from T2 and ADC. For PI-RADS 3 stratification, second order model showed higher performances (Area Under the Receiver Operating Characteristic Curve-AUC- = 80%), while for upPI-RADS 4 stratification, first order model showed higher performances respect to superior order models (AUC = 89%). Our results support the significant role of T2 and ADC radiomic features for PCa detection in lesions scored as PI-RADS 3 and upPI-RADS 4. Radiomics models showed high diagnostic efficacy in classify PI-RADS 3 and upPI-RADS 4 lesions, outperforming PI-RADS v2.1 performance.

Project description:BACKGROUND:The METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) guidelines are designed to enable reproducible assessment in detecting and quantifying metastatic disease response using whole-body magnetic resonance imaging (WB-MRI) in patients with advanced prostate cancer (APC). The purpose of our study was to evaluate the inter-observer agreement of WB-MRI examination reports produced by readers of different expertise when using the MET-RADS-P guidelines. METHODS:Fifty consecutive paired WB-MRI examinations, performed from December 2016 to February 2018 on 31 patients, were retrospectively examined to compare reports by a Senior Radiologist (9?years of experience in WB-MRI) and Resident Radiologist (after a 6-months training) using MET-RADS-P guidelines, for detection and for primary/dominant and secondary response assessment categories (RAC) scores assigned to metastatic disease in 14 body regions. Inter-observer agreement regarding RAC score was evaluated for each region by using weighted-Cohen's Kappa statistics (K). RESULTS:The number of metastatic regions reported by the Senior Radiologist (249) and Resident Radiologist (251) was comparable. For the primary/dominant RAC pattern, the agreement between readers was excellent for the metastatic findings in cervical, dorsal, and lumbosacral spine, pelvis, limbs, lungs and other sites (K:0.81-1.0), substantial for thorax, retroperitoneal nodes, other nodes and liver (K:0.61-0.80), moderate for pelvic nodes (K:0.56), fair for primary soft tissue and not assessable for skull due to the absence of findings. For the secondary RAC pattern, agreement between readers was excellent for the metastatic findings in cervical spine (K:0.93) and retroperitoneal nodes (K:0.89), substantial for those in dorsal spine, pelvis, thorax, limbs and pelvic nodes (K:0.61-0.80), and moderate for lumbosacral spine (K:0.44). CONCLUSIONS:We found inter-observer agreement between two readers of different expertise levels to be excellent in bone, but mixed in other body regions. Considering the importance of bone metastases in patients with APC, our results favor the use of MET-RADS-P in response to the growing clinical need for monitoring of metastasis in these patients.

Dataset Information

Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) Score for Risk Stratification of Sonographically Indeterminate Adnexal Masses.

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