O-RADS US risk stratification and management system: A consensus guideline from the ACR ovarian-adnexal reporting and data system committee.

The Ovarian-Adnexal Reporting and Data System (O-RADS) US risk stratification and management system is designed to provide consistent interpretations, to decrease or eliminate ambiguity in US reports resulting in a higher probability of accuracy in assigning risk of malignancy to ovarian and other adnexal masses, and to provide a management recommendation for each risk category. It was developed by an international multidisciplinary committee sponsored by the American College of Radiology and applies the standardized reporting tool for US based on the 2018 published lexicon of the O-RADS US working group. For risk stratification, the O-RADS US system recommends six categories (O-RADS 0-5), incorporating the range of normal to high risk of malignancy. This unique system represents a collaboration between the pattern-based approach commonly used in North America and the widely used, European-based, algorithmic-style International Ovarian Tumor Analysis (IOTA) Assessment of Different Neoplasias in the Adnexa model system, a risk prediction model that has undergone successful prospective and external validation. The pattern approach relies on a subgroup of the most predictive descriptors in the lexicon based on a retrospective review of evidence prospectively obtained in the IOTA phase 1-3 prospective studies and other supporting studies that assist in differentiating management schemes in a variety of almost certainly benign lesions. With O-RADS US working group consensus, guidelines for management in the different risk categories are proposed. Both systems have been stratified to reach the same risk categories and management strategies regardless of which is initially used. At this time, O-RADS US is the only lexicon and classification system that encompasses all risk categories with their associated management schemes

Analysis of factors influencing the ultrasonic fetal weight estimation

Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation

Clinical utility of chromosomal microarray analysis in invasive prenatal diagnosis

Novel methodologies for detection of chromosomal abnormalities have been made available in the recent years but their clinical utility in prenatal settings is still unknown. We have conducted a comparative study of currently available methodologies for detection of chromosomal abnormalities after invasive prenatal sampling. A multicentric collection of a 1-year series of fetal samples with indication for prenatal invasive sampling was simultaneously evaluated using three screening methodologies: (1) karyotype and quantitative fluorescent polymerase chain reaction (QF-PCR), (2) two panels of multiplex ligation-dependent probe amplification (MLPA), and (3) chromosomal microarray-based analysis (CMA) with a targeted BAC microarray. A total of 900 pregnant women provided informed consent to participate (94% acceptance rate). Technical performance was excellent for karyotype, QF-PCR, and CMA (~1% failure rate), but relatively poor for MLPA (10% failure). Mean turn-around time (TAT) was 7 days for CMA or MLPA, 25 for karyotype, and two for QF-PCR, with similar combined costs for the different approaches. A total of 57 clinically significant chromosomal aberrations were found (6.3%), with CMA yielding the highest detection rate (32% above other methods). The identification of variants of uncertain clinical significance by CMA (17, 1.9%) tripled that of karyotype and MLPA, but most alterations could be classified as likely benign after proving they all were inherited. High acceptability, significantly higher detection rate and lower TAT, could justify the higher cost of CMA and favor targeted CMA as the best method for detection of chromosomal abnormalities in at-risk pregnancies after invasive prenatal sampling

A systematic review and meta-analysis to determine the contribution of mr imaging to the diagnosis of foetal brain abnormalities In Utero.

OBJECTIVES: This systematic review was undertaken to define the diagnostic performance of in utero MR (iuMR) imaging when attempting to confirm, exclude or provide additional information compared with the information provided by prenatal ultrasound scans (USS) when there is a suspicion of foetal brain abnormality. METHODS: Electronic databases were searched as well as relevant journals and conference proceedings. Reference lists of applicable studies were also explored. Data extraction was conducted by two reviewers independently to identify relevant studies for inclusion in the review. Inclusion criteria were original research that reported the findings of prenatal USS and iuMR imaging and findings in terms of accuracy as judged by an outcome reference diagnosis for foetal brain abnormalities. RESULTS: 34 studies met the inclusion criteria which allowed diagnostic accuracy to be calculated in 959 cases, all of which had an outcome reference diagnosis determined by postnatal imaging, surgery or autopsy. iuMR imaging gave the correct diagnosis in 91 % which was an increase of 16 % above that achieved by USS alone. CONCLUSION: iuMR imaging makes a significant contribution to the diagnosis of foetal brain abnormalities, increasing the diagnostic accuracy achievable by USS alone. KEY POINTS: • Ultrasound is the primary modality for monitoring foetal brain development during pregnancy • iuMRI used together with ultrasound is more accurate for detecting foetal brain abnormalities • iuMR imaging is most helpful for detecting midline brain abnormalities • The moderate heterogeneity of reviewed studies may compromise findings