The examiner's ultrasound experience has a significant impact on the detection rate of congenital heart defects at the second-trimester fetal examination

High Heterogeneity in Prenatal Detection of Severe Congenital Heart Defects Among Physicians, Hospitals and Regions in Quebec

BACKGROUND

Prenatal detection rates (PDRs) of severe congenital heart defects (SCHDs) are often presented as regional and national aggregates, which might hide significant heterogeneity in PDRs among physicians, hospitals, and regions. The objective was to quantify the variability in the sensitivity of second-trimester ultrasound examination (U/S) to detect SCHDs, and to identify at which level this variability was the greatest.

METHODS

This was a retrospective observational cohort of all pregnancy-child dyads with SCHDs in Quebec between 2007 and 2015. We matched the clinical data from the hospitals with the administrative data from the health care system. The variability at each level was estimated using multilevel models by calculating intraclass correlation coefficients.

RESULTS

Of 1274 SCHD, 697 were diagnosed prenatally following a referral for a suspected cardiac anomaly on U/S, yielding a sensitivity of 54.7% (95% confidence interval [CI], 52.0%-57.4%). Significant heterogeneity was observed among physicians, hospitals, and regions with the greatest heterogeneity among physicians. The U/S sensitivities in the lowest quartile for physicians, hospitals, and regions were 27.4%, 29.0%, and 39.8%, and those in the highest quartile were 87.3%, 70.1%, and 62.9%, respectively. The mean difference of sensitivity between the lowest and highest quartiles was 59.9% (95% CI, 51.7-68.1) for physicians, and 41.1% (95% CI, 30.3-51.9) for hospitals. The intraclass correlation coefficients at the physician level indicated the greatest heterogeneity among physicians (intrahospital).

CONCLUSIONS

There was considerable heterogeneity in PDRs between physicians and hospitals. The driver of the heterogeneity seemed to be at the physician level, with higher interphysician variability. Any measures of improvement should be directed to the physician level.

Artificial Intelligence-Assisted Echocardiographic Image-Analysis for the Diagnosis of Fetal Congenital Heart Disease: A Systematic Review and Meta-Analysis

Background

To assess the precision of artificial intelligence (AI) in aiding the diagnostic process of congenital heart disease (CHD).

Methods

PubMed, Embase, Cochrane, and Web of Science databases were searched for clinical studies published in English up to March 2024. Studies using AI-assisted ultrasound for diagnosing CHD were included. To evaluate the quality of the studies included in the analysis, the Quality Assessment Tool for Diagnostic Accuracy Studies-2 scale was employed. The overall accuracy of AI-assisted imaging in the diagnosis of CHD was determined using Stata15.0 software. Subgroup analyses were conducted based on region and model architecture.

Results

The analysis encompassed a total of 7 studies, yielding 19 datasets. The combined sensitivity was 0.93 (95% confidence interval (CI): 0.88-0.96), and the specificity was 0.93 (95% CI: 0.88-0.96). The positive likelihood ratio was calculated as 13.0 (95% CI: 7.7-21.9), and the negative likelihood ratio was 0.08 (95% CI: 0.04-0.13). The diagnostic odds ratio was 171 (95% CI: 62-472). The summary receiver operating characteristic (SROC) curve analysis revealed an area under the curve of 0.98 (95% CI: 0.96-0.99). Subgroup analysis found that the ResNet and DenNet architecture models had better diagnostic performance than other models.

Conclusions

AI demonstrates considerable value in aiding the diagnostic process of CHD. However, further prospective studies are required to establish its utility in real-world clinical practice.

The PROSPERO registration

CRD42024540525, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=540525.

Comparison of the Size Measurement of Gallbladder Polyps by Three Different Radiologists in Abdominal Ultrasonography

BACKGROUND

There is little information regarding the size measurement differences in gallbladder (GB) polyps performed by different radiologists on abdominal ultrasonography (US).

AIM

To reveal the differences in GB polyp size measurements performed by different radiologists on abdominal US.

METHODS

From June to September 2022, the maximum diameter of 228 GB polyps was measured twice on abdominal US by one of three radiologists (a third-year radiology resident [reader A], a radiologist with 7 years of experience in abdominal US [reader B], and an abdominal radiologist with 8 years of experience in abdominal US [reader C]). Intra-reader agreements for polyp size measurements were assessed by intraclass correlation coefficient (ICC). A Bland-Altman plot was used to visualize the differences between the first and second size measurements in each reader.

RESULTS

Reader A, reader B, and reader C evaluated 65, 77, and 86 polyps, respectively. The mean size of measured 228 GB polyps was 5.0 ± 1.9 mm. Except for the case where reader A showed moderate intra-reader agreement (0.726) for polyps with size ≤ 5 mm, all readers showed an overall high intra-reader reliability (reader A, ICC = 0.859; reader B, ICC = 0.947, reader C, ICC = 0.948), indicative of good and excellent intra-reader agreements. The 95% limit of agreement of reader A, B, and C was 1.9 mm of the mean in all three readers.

CONCLUSIONS

GB polyp size measurement on abdominal US showed good or excellent intra-reader agreements. However, size changes of approximately less than 1.9 mm should be interpreted carefully because these may be within the measurement error.

Role of artificial-intelligence-assisted automated cardiac biometrics in prenatal screening for coarctation of aorta

OBJECTIVE

Although remarkable strides have been made in fetal medicine and the prenatal diagnosis of congenital heart disease, around 60% of newborns with isolated coarctation of the aorta (CoA) are not identified prior to birth. The prenatal detection of CoA has been shown to have a notable impact on survival rates of affected infants. To this end, implementation of artificial intelligence (AI) in fetal ultrasound may represent a groundbreaking advance. We aimed to investigate whether the use of automated cardiac biometric measurements with AI during the 18-22-week anomaly scan would enhance the identification of fetuses that are at risk of developing CoA.

METHODS

We developed an AI model capable of identifying standard cardiac planes and conducting automated cardiac biometric measurements. Our data consisted of pregnancy ultrasound image and outcome data spanning from 2008 to 2018 and collected from four distinct regions in Denmark. Cases with a postnatal diagnosis of CoA were paired with healthy controls in a ratio of 1:100 and matched for gestational age within 2 days. Cardiac biometrics obtained from the four-chamber and three-vessel views were included in a logistic regression-based prediction model. To assess its predictive capabilities, we assessed sensitivity and specificity on receiver-operating-characteristics (ROC) curves.

RESULTS

At the 18-22-week scan, the right ventricle (RV) area and length, left ventricle (LV) diameter and the ratios of RV/LV areas and main pulmonary artery/ascending aorta diameters showed significant differences, with Z-scores above 0.7, when comparing subjects with a postnatal diagnosis of CoA (n = 73) and healthy controls (n = 7300). Using logistic regression and backward feature selection, our prediction model had an area under the ROC curve of 0.96 and a specificity of 88.9% at a sensitivity of 90.4%.

CONCLUSIONS

The integration of AI technology with automated cardiac biometric measurements obtained during the 18-22-week anomaly scan has the potential to enhance substantially the performance of screening for fetal CoA and subsequently the detection rate of CoA. Future research should clarify how AI technology can be used to aid in the screening and detection of congenital heart anomalies to improve neonatal outcomes. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

How automated techniques ease functional assessment of the fetal heart: Applicability of two-dimensional speckle-tracking echocardiography for comprehensive analysis of global and segmental cardiac deformation using fetalHQ®

BACKGROUND

Prenatal echocardiographic assessment of fetal cardiac function has become increasingly important. Fetal two-dimensional speckle-tracking echocardiography (2D-STE) allows the determination of global and segmental functional cardiac parameters. Prenatal diagnostics is relying increasingly on artificial intelligence, whose algorithms transform the way clinicians use ultrasound in their daily workflow. The purpose of this study was to demonstrate the feasibility of whether less experienced operators can handle and might benefit from an automated tool of 2D-STE in the clinical routine.

METHODS

A total of 136 unselected, normal, singleton, second- and third-trimester fetuses with normofrequent heart rates were examined by targeted ultrasound. 2D-STE was performed separately by beginner and expert semiautomatically using a GE Voluson E10 (FetalHQ®, GE Healthcare, Chicago, IL). Several fetal cardiac parameters were calculated (end-diastolic diameter [ED], sphericity index [SI], global longitudinal strain [EndoGLS], fractional shortening [FS]) and assigned to gestational age (GA). Bland-Altman plots were used to test agreement between both operators.

RESULTS

The mean maternal age was 33 years, and the mean maternal body mass index prior to pregnancy was 24.78 kg/m2. The GA ranged from 16.4 to 32.0 weeks (average 22.9 weeks). Averaged endoGLS value of the beginner was -18.57% ± 6.59 percentage points (pp) for the right and -19.58% ± 5.63 pp for the left ventricle, that of the expert -14.33% ± 4.88 pp and -16.37% ± 5.42 pp. With increasing GA, right ventricular endoGLS decreased slightly while the left ventricular was almost constant. The statistical analysis for endoGLS showed a Bland-Altman-Bias of -4.24 pp ± 8.06 pp for the right and -3.21 pp ± 7.11 pp for the left ventricle. The Bland-Altman-Bias of the ED in both ventricles in all analyzed segments ranged from -.49 mm ± 1.54 mm to -.10 mm ± 1.28 mm, that for FS from -.33 pp ± 11.82 pp to 3.91 pp ± 15.56 pp and that for SI from -.38 ± .68 to -.15 ± .45.

CONCLUSIONS

Between both operators, our data indicated that 2D-STE analysis showed excellent agreement for cardiac morphometry parameters (ED and SI), and good agreement for cardiac function parameters (EndoGLS and FS). Due to its complexity, the application of fetal 2D-STE remains the domain of scientific-academic perinatal ultrasound and should be placed preferably in the hands of skilled operators. At present, from our perspective, an implementation into clinical practice "on-the-fly" cannot be recommended.

Cost-utility analysis of prenatal diagnosis of congenital cardiac diseases using deep learning

BACKGROUND

Deep learning (DL) is a new technology that can assist prenatal ultrasound (US) in the detection of congenital heart disease (CHD) at the prenatal stage. Hence, an economic-epidemiologic evaluation (aka Cost-Utility Analysis) is required to assist policymakers in deciding whether to adopt the new technology.

METHODS

The incremental cost-utility ratios (CUR), of adding DL assisted ultrasound (DL-US) to the current provision of US plus pulse oximetry (POX), was calculated by building a spreadsheet model that integrated demographic, economic epidemiological, health service utilization, screening performance, survival and lifetime quality of life data based on the standard formula: CUR = Increase in Intervention Costs - Decrease in Treatment costs Averted QALY losses of adding DL to US & POX US screening data were based on real-world operational routine reports (as opposed to research studies). The DL screening cost of 145 USD was based on Israeli US costs plus 20.54 USD for reading and recording screens.

RESULTS

The addition of DL assisted US, which is associated with increased sensitivity (95% vs 58.1%), resulted in far fewer undiagnosed infants (16 vs 102 [or 2.9% vs 15.4%] of the 560 and 659 births, respectively). Adoption of DL-US will add 1,204 QALYs. with increased screening costs 22.5 million USD largely offset by decreased treatment costs (20.4 million USD). Therefore, the new DL-US technology is considered "very cost-effective", costing only 1,720 USD per QALY. For most performance combinations (sensitivity > 80%, specificity > 90%), the adoption of DL-US is either cost effective or very cost effective. For specificities greater than 98% (with sensitivities above 94%), DL-US (& POX) is said to "dominate" US (& POX) by providing more QALYs at a lower cost.

CONCLUSION

Our exploratory CUA calculations indicate the feasibility of DL-US as being at least cost-effective.

Diagnostic accuracy of ultrasound screening for fetal structural abnormalities during the first and second trimester of pregnancy in low-risk and unselected populations

BACKGROUND

Prenatal ultrasound is widely used to screen for structural anomalies before birth. While this is traditionally done in the second trimester, there is an increasing use of first-trimester ultrasound for early detection of lethal and certain severe structural anomalies.

OBJECTIVES

To evaluate the diagnostic accuracy of ultrasound in detecting fetal structural anomalies before 14 and 24 weeks' gestation in low-risk and unselected pregnant women and to compare the current two main prenatal screening approaches: a single second-trimester scan (single-stage screening) and a first- and second-trimester scan combined (two-stage screening) in terms of anomaly detection before 24 weeks' gestation.

SEARCH METHODS

We searched MEDLINE, EMBASE, Science Citation Index Expanded (Web of Science), Social Sciences Citation Index (Web of Science), Arts & Humanities Citation Index and Emerging Sources Citation Index (Web of Science) from 1 January 1997 to 22 July 2022. We limited our search to studies published after 1997 and excluded animal studies, reviews and case reports. No further restrictions were applied. We also screened reference lists and citing articles of each of the included studies.

SELECTION CRITERIA

Studies were eligible if they included low-risk or unselected pregnant women undergoing a first- and/or second-trimester fetal anomaly scan, conducted at 11 to 14 or 18 to 24 weeks' gestation, respectively. The reference standard was detection of anomalies at birth or postmortem.

DATA COLLECTION AND ANALYSIS

Two review authors independently undertook study selection, quality assessment (QUADAS-2), data extraction and evaluation of the certainty of evidence (GRADE approach). We used univariate random-effects logistic regression models for the meta-analysis of sensitivity and specificity.

MAIN RESULTS

Eighty-seven studies covering 7,057,859 fetuses (including 25,202 with structural anomalies) were included. No study was deemed low risk across all QUADAS-2 domains. Main methodological concerns included risk of bias in the reference standard domain and risk of partial verification. Applicability concerns were common in studies evaluating first-trimester scans and two-stage screening in terms of patient selection due to frequent recruitment from single tertiary centres without exclusion of referrals. We reported ultrasound accuracy for fetal structural anomalies overall, by severity, affected organ system and for 46 specific anomalies. Detection rates varied widely across categories, with the highest estimates of sensitivity for thoracic and abdominal wall anomalies and the lowest for gastrointestinal anomalies across all tests. The summary sensitivity of a first-trimester scan was 37.5% for detection of structural anomalies overall (95% confidence interval (CI) 31.1 to 44.3; low-certainty evidence) and 91.3% for lethal anomalies (95% CI 83.9 to 95.5; moderate-certainty evidence), with an overall specificity of 99.9% (95% CI 99.9 to 100; low-certainty evidence). Two-stage screening had a combined sensitivity of 83.8% (95% CI 74.7 to 90.1; low-certainty evidence), while single-stage screening had a sensitivity of 50.5% (95% CI 38.5 to 62.4; very low-certainty evidence). The specificity of two-stage screening was 99.9% (95% CI 99.7 to 100; low-certainty evidence) and for single-stage screening, it was 99.8% (95% CI 99.2 to 100; moderate-certainty evidence). Indirect comparisons suggested superiority of two-stage screening across all analyses regarding sensitivity, with no significant difference in specificity. However, the certainty of the evidence is very low due to the absence of direct comparisons.

AUTHORS' CONCLUSIONS

A first-trimester scan has the potential to detect lethal and certain severe anomalies with high accuracy before 14 weeks' gestation, despite its limited overall sensitivity. Conversely, two-stage screening shows high accuracy in detecting most fetal structural anomalies before 24 weeks' gestation with high sensitivity and specificity. In a hypothetical cohort of 100,000 fetuses, the first-trimester scan is expected to correctly identify 113 out of 124 fetuses with lethal anomalies (91.3%) and 665 out of 1776 fetuses with any anomaly (37.5%). However, 79 false-positive diagnoses are anticipated among 98,224 fetuses (0.08%). Two-stage screening is expected to correctly identify 1448 out of 1776 cases of structural anomalies overall (83.8%), with 118 false positives (0.1%). In contrast, single-stage screening is expected to correctly identify 896 out of 1776 cases before 24 weeks' gestation (50.5%), with 205 false-positive diagnoses (0.2%). This represents a difference of 592 fewer correct identifications and 88 more false positives compared to two-stage screening. However, it is crucial to acknowledge the uncertainty surrounding the additional benefits of two-stage versus single-stage screening, as there are no studies directly comparing them. Moreover, the evidence supporting the accuracy of first-trimester ultrasound and two-stage screening approaches primarily originates from studies conducted in single tertiary care facilities, which restricts the generalisability of the results of this meta-analysis to the broader population.

Dual-modal Photoacoustic and Ultrasound Imaging: from preclinical to clinical applications

Photoacoustic imaging is a novel biomedical imaging modality that has emerged over the recent decades. Due to the conversion of optical energy into the acoustic wave, photoacoustic imaging offers high-resolution imaging in depth beyond the optical diffusion limit. Photoacoustic imaging is frequently used in conjunction with ultrasound as a hybrid modality. The combination enables the acquisition of both optical and acoustic contrasts of tissue, providing functional, structural, molecular, and vascular information within the same field of view. In this review, we first described the principles of various photoacoustic and ultrasound imaging techniques and then classified the dual-modal imaging systems based on their preclinical and clinical imaging applications. The advantages of dual-modal imaging were thoroughly analyzed. Finally, the review ends with a critical discussion of existing developments and a look toward the future.

Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection

INTRODUCTION

Congenital anomalies are the most encountered cause of fetal death, infant mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly. Early detection of congenital anomalies facilitates life-saving treatments and stops the progression of disabilities. Congenital anomalies can be diagnosed prenatally through morphology scans. A correct interpretation of the morphology scan allows a detailed discussion with the parents regarding the prognosis. The central feature of this project is the development of a specialised intelligent system that uses two-dimensional ultrasound movies obtained during the standard second trimester morphology scan to identify congenital anomalies in fetuses.

METHODS AND ANALYSIS

The project focuses on three pillars: committee of deep learning and statistical learning algorithms, statistical analysis, and operational research through learning curves. The cross-sectional study is divided into a training phase where the system learns to detect congenital anomalies using fetal morphology ultrasound scan, and then it is tested on previously unseen scans. In the training phase, the intelligent system will learn to answer the following specific objectives: (a) the system will learn to guide the sonographer's probe for better acquisition; (b) the fetal planes will be automatically detected, measured and stored and (c) unusual findings will be signalled. During the testing phase, the system will automatically perform the above tasks on previously unseen videos.Pregnant patients in their second trimester admitted for their routine scan will be consecutively included in a 32-month study (4 May 2022-31 December 2024). The number of patients is 4000, enrolled by 10 doctors/sonographers. We will develop an intelligent system that uses multiple artificial intelligence algorithms that interact between themselves, in bulk or individual. For each anatomical part, there will be an algorithm in charge of detecting it, followed by another algorithm that will detect whether anomalies are present or not. The sonographers will validate the findings at each intermediate step.

ETHICS AND DISSEMINATION

All protocols and the informed consent form comply with the Health Ministry and professional society ethics guidelines. The University of Craiova Ethics Committee has approved this study protocol as well as the Romanian Ministry of Research Innovation and Digitization that funded this research. The study will be implemented and reported in line with the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement.

TRIAL REGISTRATION NUMBER

The study is registered under the name 'Pattern recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical Learning', project number 101PCE/2022, project code PN-III-P4-PCE-2021-0057.

TRIAL REGISTRATION

ClinicalTrials.gov, unique identifying number NCT05738954, date of registration: 2 November 2023.

Prevalence of anomalies on the routine mid-trimester ultrasound: 3172 consecutive cases by a single maternal-fetal medicine specialist

Introduction/Purpose

The routine mid-trimester fetal anatomy ultrasound (FAS) is offered to every pregnant woman and remains critical in the detection of structural fetal anomalies. Our study aimed to determine the prevalence of abnormalities on routine FAS performed by a single operator, who is an experienced sub-specialist in maternal-fetal medicine.

Methods

A retrospective analysis of all routine FAS performed a tertiary private obstetric ultrasound practice in metropolitan Sydney over a 7-year period, August 2015-July 2022. An advanced ultrasound protocol including detailed cardiac views was used in every case. Second opinion scans for suspected abnormalities were excluded. Fetal anomalies were classified into major and minor, based on the likely need for neonatal intervention.

Results

Among 14,908 obstetric ultrasound examinations, routine FAS were performed on 3172 fetuses by a single operator. More than 99% of women had screened low-risk for fetal aneuploidy. Structural anomalies were identified in 5% (157/3172) of fetuses; the prevalence of major anomalies was 1% (30/3172). Almost 60% of total anomalies were either cardiac or renal. No differences were identified in anomaly rates for singletons compared with twins (5.0% vs. 4.2%; P = 0.75). The prevalence of placenta previa and vasa previa was 10% and 0.1%, respectively.

Discussion

The prevalence of fetal anomalies on routine FAS by a single operator using a standardised protocol was higher in our practice (5%) than in previously published studies. Although most anomalies were minor, the rate of major abnormality was 1%.

Conclusion

The routine mid-trimester FAS remains an integral component of prenatal ultrasound screening.

Postnatal diagnosis of congenital anomalies despite active systematic prenatal screening policies: a population-based registry study

BACKGROUND

Prenatal screening for congenital anomalies is an important component of maternity care, with continual advances in screening technology. However, few recent studies have investigated the overall effectiveness of a systematic policy of prenatal screening for congenital anomalies, such as in France where an ultrasound per trimester is recommended for all pregnant individuals.

OBJECTIVE

This study aimed to assess the proportion and the type of congenital anomalies that are not detected during pregnancy.

STUDY DESIGN

The study population included all singleton fetuses and newborns with congenital anomalies from the Paris Registry of Congenital Malformations (remaPAR) from 2001 to 2021. The registry includes all live births and stillbirths at ≥22 weeks of gestation and terminations of pregnancy for fetal anomaly at any gestational age with congenital anomalies diagnosed from the prenatal period until discharge home from hospital after birth. The prevalence of postnatally detected congenital anomalies was estimated overall and for 5-year intervals within the study period. We also reported the proportion of postnatal detection by subgroups of congenital anomalies according to the EUROCAT classification.

RESULTS

Of the 16,602 malformed singleton fetuses and newborns, 32.7% were detected postnatally. Of those with severe anomalies, 11.9% were detected postnatally. The postnatal detection rate decreased from 34.3% from 2001 to 2005, to 27.8% from 2016 to 2021 (P<.001). Anomalies most frequently detected postnatally were genital anomalies (n=969; 87.0%), followed by ear, neck, and face anomalies (n=71; 78.0%), eye anomalies (n=154; 74.0%), and limb anomalies (n=1802; 68.4%). Anomalies of the kidneys and the urinary tract (n=219; 7.1%) and the abdominal wall (n=37; 8.7%) were least likely to be detected after birth. Among the anomalies classified as severe, postnatal detection rates were highest for limb reduction defects (n=142; 40.6%), complete transposition of the great arteries (n=31; 17.6%), and diaphragmatic hernia (n=26; 17.2%).

CONCLUSION

Despite improvement of prenatal screening over a 20-year period, our results show that there is still a margin for improvement in prenatal diagnosis of congenital anomalies.

Entrustable professional activities of graduate accredited General Medical Sonographers in Australia - Industry perceptions

INTRODUCTION

Linking individual competencies to entrustable professional tasks provides a holistic view of Sonography graduate work readiness. The Australian Sonographers Accreditation Registry (ASAR) publishes a set of entrustable professional activities (EPAs) as part of its Standards for Accreditation of Sonography Courses. EPAs are distinct ultrasound examinations grouped within six critical practice units. This study reports on industry perspectives of current EPAs and their classification for graduates completing general sonography courses in Australia. The article also examines the value of EPAs and links their function to the assessment of graduate competency.

METHODS

An online survey tool elicited stakeholder feedback on graduate EPAs across six critical practice units and the potential for including a new Paediatric unit. From an original sample size of 655, 309 responded to questions about general sonography courses.

RESULTS

A majority (55.3%) recommended no changes to the existing EPA list, and 44.7% recommended amending the list. From respondents that recommended changes (138/309), all current EPAs received >80% agreement to be retained; in addition, nine new examinations received >70% agreement for inclusion at the graduate level. Whilst 42.7% (132/309) supported the current ASAR model requiring competency in five out of six critical practice units, 45.6% (141/309) recommended increasing it to all six. There was limited support, 11.7% (36/309), to reduce this number. Responding to the potential to add a new Paediatric specific critical practice unit, 61.8% (181/293) recommended its inclusion.

CONCLUSIONS

The findings demonstrate that the current list of EPAs aligns with industry expectations. In contrast, there are divergent views on the modelling and grouping of critical practice units. The article's critical analysis of the results and implications provides stakeholders with a practical approach to clinical teaching and EPA assessment, and helps to inform any review of accreditation standards.

The Left Outflow Tract in Fetal Cardiac Screening Examination: Introduction of Quality Criteria Is Not Always Associated With an Improvement of Practice When Supervised by Humans

OBJECTIVES

Since 2016, the French CNEOF included the left ventricular outflow tract (LVOT) in the second and third trimester of pregnancy in addition to the four-chamber view and the parasagittal view of the right outflow tract. The objective of this study was to define quality criteria for fetal LVOT assessment and to perform a human audit of past and current practices, before and after the implementation of those quality criteria at a large scale.

METHODS

Seven quality criteria were investigated and rated from 0 to 1 during three periods of interest. Files were randomly selected from three centers, and average total and specific scores were calculated.

RESULTS

LVOT pictures were present in more than 94.3% of reports. The average quality score was 5.49/7 (95% confidence interval [CI]: 5.36-5.62), 5.91/7 (95% CI: 5.80-6.03), and 5.70/7 (95% CI: 5.58-5.82) for the three centers in the three periods of interest. There was no significant difference following the introduction of the quality criteria, 2017 versus 2020, P = .054.

CONCLUSION

Fetal LVOT images were present in most of ultrasound reports but the introduction of the proposed quality criteria under human supervision seems not associated with a significant change in practice.

Four-section approach of fetal congenital heart disease at 11-13+6 weeks

Objective

The objective of the study is to explore the value of the four-section approach in detecting fetal heart defects in the first trimester (11-13+6 weeks), analyze the reasons for the inconsistency between the results of ultrasound examination in the first trimester and subsequent verification, and describe the most common abnormal flow patterns of four sections.

Materials and methods

Between June 2019 and June 2021, a prenatal four-section approach (upper abdominal transverse section, four-chamber section, three vessel-trachea section, and bilateral subclavian artery section) with verification results in early pregnancy was analyzed.

Results

In total, 9,533 fetuses were included. Finally, 176 fetuses with congenital heart disease (CHD), containing 34 types, were identified. The total detection rate of cardiac abnormalities was 1.85%. 102 cases were accurately diagnosed by ultrasonography during early pregnancy. A total of 74 fetuses who had inconsistent results between fetal cardiac ultrasound and verification in early pregnancy were reported, of which the cases of 22 fetuses were inconsistent due to disease evolution and progression and the cases of 52 fetuses were inconsistent due to missed diagnosis and misdiagnosis. The sensitivity, specificity, positive predictive value, and negative predictive value of the four-section approach were 67.05%, 99.96%, 96.58%, and 99.33%, respectively. In this study, a total of 30 abnormal ultrasonic imaging patterns in four sections were summarized.

Conclusion

We confirmed that the four-section approach in early pregnancy has a good diagnostic efficacy for fetal CHD. Intrauterine evolution of the fetal heart, missed diagnosis, and misdiagnosis are the reasons for the inconsistency between the results of early pregnancy ultrasound and subsequent verification. This study also presents the abnormal imaging patterns of four scan sections of CHD in early pregnancy, which are instructive for the rapid identification and diagnosis of CHD in the first trimester.

Evaluation fetal heart in the first and second trimester: Results and limitations

Background

Cardiac heart defects affect nearly 6-12 per 1000 live births in the general population and are more frequent than common trisomies.

Aim

To assess the efficacy and technical limitations of first-trimester fetal heart evaluation in the 11-14^th-weeks' scan and comparison with the second-trimester anatomical exam by ultrasound.

Material and Method

Between April 2015 and July 2020, medical records and ultrasound data of 3295 pregnancies who underwent first-trimester fetal anatomy exams by ultrasound were reviewed retrospectively. All ultrasound exams were performed by the same two operators (TUKD, OP) with transabdominal transducers. Fetal situs, four-chamber view, outflow tracts, and three-vessel trachea view are the cornerstones of first-trimester fetal heart examination. Conventional grayscale mode and high-definition power Doppler mode were utilized. The same operators re-examined all cases between the 18 and 23 weeks of gestation by ISUOG guidelines.

Results

We performed a combined transvaginal and transabdominal approach for only 101 cases (3.06%). The mean maternal age was 31.28 ± 4.43, the median gestational age at the first-trimester ultrasound exam was 12.4 weeks, and the median CRL was 61.87 mm (range was 45.1-84 mm). Even combined approach situs, cardiac axis, and four-chamber view could not be visualized optimally in 28 cases (0.7%). Outflow tracts were visualized separately in 80% (2636 in 3295) cases. Three vessel-trachea views were obtained in 85.4% (2814 in 3295) cases by high-definition Doppler mode. There were 47 fetuses with cardiac defects in 3295 pregnancies with the known pregnancy outcome. Ten cases had abnormal karyotype results. Thirty-two fetuses with cardiac anomalies (9.7 in 1000 pregnancies) were detected in the first-trimester examination, and the remaining 15 (4.55 in 1000 pregnancies) cases were diagnosed in the second-trimester examination. The prevalence of congenital cardiac anomalies was 14.25 in 1000 pregnancies. Fifteen cases were missed in the first-trimester exam. Also, ten fetuses which had abnormal cardiac findings in the first-trimester exam were not confirmed in the second-trimester exam. Sensitivity, specificity, positive, and negative predictive values were calculated as 65.3%, 99.7%, 66.8%, and 99.67%, respectively.

Conclusion

Late first-trimester examination of the fetus is feasible and allows earlier detection of many structural abnormalities of the fetus, including congenital heart defects. Suspicious and isolated cardiac abnormal findings should be re-examined and confirmed in the second-trimester exam. Previous abdominal surgery, high BMI, and subtle cardiac defects can cause missed cardiac abnormalities.

Deep Learning and Gaussian Mixture Modelling clustering mix. A new approach for fetal morphology view plane differentiation

The last three years have been a game changer in the way medicine is practiced. The COVID-19 pandemic changed the obstetrics and gynecology scenery. Pregnancy complications, and even death, are preventable due to maternal-fetal monitoring. A fast and accurate diagnosis can be established by a doctor + Artificial Intelligence combo. The aim of this paper is to propose a framework designed as a merger between Deep learning algorithms and Gaussian Mixture Modelling clustering applied in differentiating between the view planes of a second trimester fetal morphology scan. The deep learning methods chosen for this approach were ResNet50, DenseNet121, InceptionV3, EfficientNetV2S, MobileNetV3Large, and Xception. The framework establishes a hierarchy of the component networks using a statistical fitness function and the Gaussian Mixture Modelling clustering method, followed by a synergetic weighted vote of the algorithms that gives the final decision. We have tested the framework on two second trimester morphology scan datasets. A thorough statistical benchmarking process has been provided to validate our results. The experimental results showed that the synergetic vote of the framework outperforms the vote of each stand-alone deep learning network, hard voting, soft voting, and bagging strategy.

How Automated Techniques Ease Functional Assessment of the Fetal Heart: Applicability of MPI+™ for Direct Quantification of the Modified Myocardial Performance Index

(1) Objectives: In utero functional cardiac assessments using echocardiography have become increasingly important. The myocardial performance index (MPI, Tei index) is currently used to evaluate fetal cardiac anatomy, hemodynamics and function. An ultrasound examination is highly examiner-dependent, and training is of enormous significance in terms of proper application and subsequent interpretation. Future experts will progressively be guided by applications of artificial intelligence, on whose algorithms prenatal diagnostics will rely on increasingly. The objective of this study was to demonstrate the feasibility of whether less experienced operators might benefit from an automated tool of MPI quantification in the clinical routine. (2) Methods: In this study, a total of 85 unselected, normal, singleton, second- and third-trimester fetuses with normofrequent heart rates were examined by a targeted ultrasound. The modified right ventricular MPI (RV-Mod-MPI) was measured, both by a beginner and an expert. A calculation was performed semiautomatically using a Samsung Hera W10 ultrasound system (MPI+™, Samsung Healthcare, Gangwon-do, South Korea) by taking separate recordings of the right ventricle's in- and outflow using a conventional pulsed-wave Doppler. The measured RV-Mod-MPI values were assigned to gestational age. The data were compared between the beginner and the expert using a Bland-Altman plot to test the agreement between both operators, and the intraclass correlation was calculated. (3) Results: The mean maternal age was 32 years (19 to 42 years), and the mean maternal pre-pregnancy body mass index was 24.85 kg/m2 (ranging from 17.11 to 44.08 kg/m2). The mean gestational age was 24.44 weeks (ranging from 19.29 to 36.43 weeks). The averaged RV-Mod-MPI value of the beginner was 0.513 ± 0.09, and that of the expert was 0.501 ± 0.08. Between the beginner and the expert, the measured RV-Mod-MPI values indicated a similar distribution. The statistical analysis showed a Bland-Altman bias of 0.01136 (95% limits of agreement from -0.1674 to 0.1902). The intraclass correlation coefficient was 0.624 (95% confidence interval from 0.423 to 0.755). (4) Conclusions: For experts as well as for beginners, the RV-Mod-MPI is an excellent diagnostic tool for the assessment of fetal cardiac function. It is a time-saving procedure, offers an intuitive user interface and is easy to learn. There is no additional effort required to measure the RV-Mod-MPI. In times of reduced resources, such assisted systems of fast value acquisition represent clear added value. The establishment of the automated measurement of the RV-Mod-MPI in clinical routine should be the next level in cardiac function assessment.

Application and Progress of Artificial Intelligence in Fetal Ultrasound

Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However, problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter-observer variability limit the development of traditional ultrasound in clinical applications. The combination of artificial intelligence (AI) and obstetric ultrasound may help optimize fetal ultrasound examination by shortening the examination time, reducing the physician's workload, and improving diagnostic accuracy. AI has been successfully applied to automatic fetal ultrasound standard plane detection, biometric parameter measurement, and disease diagnosis to facilitate conventional imaging approaches. In this review, we attempt to thoroughly review the applications and advantages of AI in prenatal fetal ultrasound and discuss the challenges and promises of this new field.

Multi-path decoder U-Net: A weakly trained real-time segmentation network for object detection and localization in ultrasound scans

Detecting and localizing an anatomical structure of interest within the field of view of an ultrasound scan is an essential step in many diagnostic and therapeutic procedures. However, ultrasound scans suffer from high levels of variabilities across sonographers and patients, making it challenging for sonographers to accurately identify and locate these structures without extensive experience. Segmentation-based convolutional neural networks (CNNs) have been proposed as a solution to assist sonographers in this task. Despite their accuracy, these networks require pixel-wise annotations for training; an expensive and labor-intensive operation that requires the expertise of an experienced practitioner to identify the precise outline of the structures of interest. This complicates, delays, and increases the cost of network training and deployment. To address this problem, we propose a multi-path decoder U-Net architecture that is trained on bounding box segmentation maps; not requiring pixel-wise annotations. We show that the network can be trained on small training sets, which is the case in medical imaging datasets; reducing the cost and time needed for deployment and use in clinical settings. The multi-path decoder design allows for better training of deeper layers and earlier attention to the target anatomical structures of interest. This architecture offers up to a 7% relative improvement compared to the U-Net architecture in localization and detection performance, with an increase of only 0.75% in the number of parameters. Its performance is on par with, or slightly better than, the more computationally expensive U-Net++, which has 20% more parameters; making the proposed architecture a more computationally efficient alternative for real-time object detection and localization in ultrasound scans.

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) - a study protocol for developing an automated intelligent decision support system for early fetal echocardiography

BACKGROUND

Congenital Heart Disease represents the most frequent fetal malformation. The lack of prenatal identification of congenital heart defects can have adverse consequences for the neonate, while a correct prenatal diagnosis of specific cardiac anomalies improves neonatal care neurologic and surgery outcomes. Sonographers perform prenatal diagnosis manually during the first or second-trimester scan, but the reported detection rates are low. This project's primary objective is to develop an Intelligent Decision Support System that uses two-dimensional video files of cardiac sweeps obtained during the standard first-trimester fetal echocardiography (FE) to signal the presence/absence of previously learned key features.

METHODS

The cross-sectional study will be divided into a training part of the machine learning approaches and the testing phase on previously unseen frames and eventually on actual video scans. Pregnant women in their 12-13 + 6 weeks of gestation admitted for routine first-trimester anomaly scan will be consecutively included in a two-year study, depending on the availability of the experienced sonographers in early fetal cardiac imaging involved in this research. The Data Science / IT department (DSIT) will process the key planes identified by the sonographers in the two- dimensional heart cine loop sweeps: four-chamber view, left and right ventricular outflow tracts, three vessels, and trachea view. The frames will be grouped into the classes representing the plane views, and then different state-of-the- art deep-learning (DL) pre-trained algorithms will be tested on the data set. The sonographers will validate all the intermediary findings at the frame level and the meaningfulness of the video labeling.

DISCUSSION

FE is feasible and efficient during the first trimester. Still, the continuous training process is impaired by the lack of specialists or their limited availability. Therefore, in our study design, the sonographer benefits from a second opinion provided by the developed software, which may be very helpful, especially if a more experienced colleague is unavailable. In addition, the software may be implemented on the ultrasound device so that the process could take place during the live examination.

TRIAL REGISTRATION

The study is registered under the name "Learning deep architectures for the Interpretation of Fetal Echocardiography (LIFE)", project number 408PED/2020, project code PN-III-P2-2.1-PED-2019.

TRIAL REGISTRATION

ClinicalTrials.gov , unique identifying number NCT05090306, date of registration 30.10.2020.

Improvement of diagnostic efficiency in fetal congenital heart disease using fetal intelligent navigation echocardiography by less-experienced operators

OBJECTIVE

This study investigated the feasibility and accuracy of fetal intelligent navigation echocardiography (FINE) for the prenatal diagnosis of congenital heart disease (CHD) by inexperienced and experienced operators.

METHOD

In this prospective study, all volume data sets from 120 fetuses with a broad spectrum of CHD were acquired using spatiotemporal image correlation technology. The prenatal diagnostic procedures were performed by two operators with different experience (beginner: 1 year and expert: 15 years) using FINE and traditional fetal echocardiography. Data were analyzed on the time of examination and acquisition of results.

RESULTS

Diagnoses made by FINE and traditional echocardiography were completely consistent with the final diagnosis of CHD in 98 (81.66%) versus 20 (16.66%) (P < 0.001) beginners and 87.50% (n = 105) versus 101 (84.16%) experts, respectively. On the contrary, there was significant difference using traditional echocardiography (16.66% versus 84.16%, P < 0.001) by two examiners. Furthermore, the examination time decreased when using FINE compared with using traditional echocardiography (beginner operators: 4.54 ± 1.03 min versus 20.58 ± 3.36 min, P < 0.001; expert operators: 3.89 ± 0.96 min versus 12.73 ± 1.62 min, P < 0.001).

CONCLUSION

Based on our results, a prenatal diagnosis of CHD can be made with high feasibility and accuracy using FINE compared with traditional fetal echocardiography for beginner operators.

Fetal intelligent navigation echocardiography (FINE) has superior performance compared to manual navigation of the fetal heart by non-expert sonologists

OBJECTIVES

Manual and intelligent navigation (i.e. fetal intelligent navigation echocardiography or FINE) by the operator are two methods to obtain standard fetal cardiac views from spatiotemporal image correlation (STIC) volumes. The objective was to compare the performance between manual and intelligent navigation (FINE) of the fetal heart by non-expert sonologists.

METHODS

In this prospective observational study, ten sonologists underwent formal training on both navigational methods. Subsequently, they were tested on their ability to obtain nine cardiac views from five STIC volumes of normal fetal hearts (19-28 gestational weeks) using such methods. The following parameters were determined for both methods: (1) success rate of obtaining nine cardiac views; (2) mean time to obtain nine cardiac views per sonologist; and (3) maximum number of cardiac views successfully obtained for each STIC volume.

RESULTS

All fetal cardiac images obtained from 100 STIC volumes (50 for each navigational method) were reviewed by an expert in fetal echocardiography. Compared to manual navigation, FINE was associated with a significantly: (1) higher success rate of obtaining eight (excluding the abdomen view) appropriate cardiac views (92-100% vs. 56-88%; all p<0.05); (2) shorter mean time (minute:seconds) to obtain nine cardiac views (2:11 ± 0:37 vs. 15:49 ± 7:44; p<0.0001); and (3) higher success rate of obtaining all nine cardiac views for a given STIC volume (86 vs. 14%; p<0.001).

CONCLUSIONS

When performed by non-expert sonologists, intelligent navigation (FINE) had a superior performance compared to manual navigation of the normal fetal heart. Specifically, FINE obtained appropriate fetal cardiac views in 92-100% of cases.

Coarctation of the aorta: Prenatal assessment, postnatal management and neonatal outcomes

Coarctation of the aorta (Coa) is a potentially life threatening diagnosis. It occurs in 0.3 per 1000 live births and accounts for 6-8% of all infants with congenital heart defects. Neonates with severe Coa may be completely asymptomatic at birth, as the ductus arteriosus can provide flow to the lower body. Those who are not diagnosed prenatally may be diagnosed only after constriction of the ductus arteriosus, when they present in cardiogenic shock. This group has a higher risk for mortality and morbidity relative to those diagnosed prenatally. Despite the increasing practice of universal pulse oximetry screening, many cases with significant coarctation of the aorta still go undiagnosed in the newborn period. In this article, we present the pathophysiology, diagnosis, presentation, treatment and outcomes of Coa.

Noninvasive Dual-Modality Photoacoustic-Ultrasonic Imaging to Detect Mammalian Embryo Abnormalities after Prenatal Exposure to Methylmercury Chloride (MMC): A Mouse Study

BACKGROUND

Severe environmental pollution and contaminants left in the environment due to the abuse of chemicals, such as methylmercury, are associated with an increasing number of embryonic disorders. Ultrasound imaging has been widely used to investigate embryonic development malformation and dysorganoplasia in both research and clinics. However, this technique is limited by its low contrast and lacking functional parameters such as the ability to measure blood oxygen saturation (SaO 2 ) and hemoglobin content (HbT) in tissues, measures that could be early vital indicators for embryonic development abnormality. Herein, we proposed combining two highly complementary techniques into a photoacoustic-ultrasound (PA-US) dual-modality imaging approach to noninvasively detect early mouse embryo abnormalities caused by methylmercury chloride (MMC) in real time.

OBJECTIVES

This study aimed to assess the use of PA-US dual-modality imaging for noninvasive detection of embryonic toxicity at different stages of growth following prenatal MMC exposure. Additionally, we compared the PA-US imagining results to traditional histological methods to determine whether this noninvasive method could detect early developmental defects in utero.

METHODS

Different dosages of MMC were administrated to pregnant mice by gavage to establish models of different levels of embryonic malformation. Ultrasound, photoacoustic signal intensity (PSI), blood oxygen saturation (SaO 2 ), and hemoglobin content (HbT) were quantified in all experimental groups. Furthermore, the embryos were sectioned and examined for pathological changes.

RESULTS

Using PA-US imaging, we detected differences in PSI, SaO 2 , HbT, and heart volume at embryonic day (E)14.5 and E11.5 for low and high dosages of MMC, respectively. More important, our results showed that differences between control and treated embryos identified by in utero PA-US imaging were consistent with those identified in ex vivo embryos using histological methods.

CONCLUSION

Our results suggest that noninvasive dual-modality PA-US is a promising strategy for detecting developmental toxicology in the uterus. Overall, this study presents a new approach for detecting embryonic toxicities, which could be crucial in clinics when diagnosing aberrant embryonic development. https://doi.org/10.1289/EHP8907.

The electrical heart axis of the fetus between 18 and 24 weeks of gestation: A cohort study

Introduction

A fetal anomaly scan in mid-pregnancy is performed, to check for the presence of congenital anomalies, including congenital heart disease (CHD). Unfortunately, 40% of CHD is still missed. The combined use of ultrasound and electrocardiography might boost detection rates. The electrical heart axis is one of the characteristics which can be deduced from an electrocardiogram (ECG). The aim of this study was to determine reference values for the electrical heart axis in healthy fetuses around 20 weeks of gestation.

Material and methods

Non-invasive fetal electrocardiography was performed subsequent to the fetal anomaly scan in pregnant women carrying a healthy singleton fetus between 18 and 24 weeks of gestation. Eight adhesive electrodes were applied on the maternal abdomen including one ground and one reference electrode, yielding six channels of bipolar electrophysiological measurements. After removal of interferences, a fetal vectorcardiogram was calculated and then corrected for fetal orientation. The orientation of the electrical heart axis was determined from this normalized fetal vectorcardiogram. Descriptive statistics were used on normalized cartesian coordinates to determine the average electrical heart axis in the frontal plane. Furthermore, 90% prediction intervals (PI) for abnormality were calculated.

Results

Of the 328 fetal ECGs performed, 281 were included in the analysis. The average electrical heart axis in the frontal plane was determined at 122.7° (90% PI: -25.6°; 270.9°).

Discussion

The average electrical heart axis of healthy fetuses around mid-gestation is oriented to the right, which is, due to the unique fetal circulation, in line with muscle distribution in the fetal heart.

The diagnostic value of the early extended fetal heart examination at 13 to 14 weeks gestational age in a high-risk population

BACKGROUND

Congenital heart disease (CHD) is the most common congenital malformation that affects high-risk populations. A more definite heart diagnosis in the first trimester should be provided to guide clinical treatment. The study aim was to evaluate the diagnostic precision of the early extended fetal heart examination (EFHE) that includes abdominal situs view, four-chamber view (4CV), left ventricular outflow tract view (LVOT), right ventricular outflow tract view (RVOT), 3-vessel and tracheal view (3VT), ductal arch view, and the aortic arch view in the detection of CHD at the gestational age (GA) 13 to 14 weeks in a population with high risks.

METHODS

This study was a diagnostic test study. EFHE was performed by transabdominal sonography in women at GA 13 to 14 weeks with singleton pregnancies who were at high risk for CHD. The risk of CHD was determined by family history of CHD, rubella infection, metabolic disorders, exposure to teratogens, conception by in-vitro fertilization (IVF), increased nuchal translucency (NT) thickness, abnormal obstetric ultrasound, etc. The operator had more than 5 years of experience in first-trimester scans and fetal echocardiography. Early scans were compared with a fetal echocardiography in the second trimester (16-24 weeks).

RESULTS

EFHE was performed, and the pregnancy outcomes were obtained in 234 single pregnancies with a high risk of CHD. The average crown-rump length (CRL) was (76.17±7.09) mm. CHD was diagnosed in 43 cases by EFHE; 10 of these cases were misdiagnosed, and 2 cases were missed. Four cases were inconsistent in the main diagnosis of CHD. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa coefficient (Ko) value of EFHE in diagnosing CHD by type and severity was 84.6% [95% confidence interval (CI), 69.5-94.1%], 96.9% (95% CI, 93.4-98.9%), 84.6% (95% CI, 69.5-94.1%), 96.9% (95% CI, 93.4-98.9%), and 0.82 (P<0.001), respectively.

CONCLUSIONS

EFHE can work as a diagnose examination for most major CHD cases at GA 13 to 14 weeks by an experienced operator; Therefore, this diagnostic system for fetal CHD may be applied in the first trimester. The study has been registered in the Chinese Clinical Trial Registry (www.chictr.org.cn). The registration number is ChiCTR2000038451.

A CNN Segmentation-Based Approach to Object Detection and Tracking in Ultrasound Scans with Application to the Vagus Nerve Detection

Ultrasound scanning is essential in several medical diagnostic and therapeutic applications. It is used to visualize and analyze anatomical features and structures that influence treatment plans. However, it is both labor intensive, and its effectiveness is operator dependent. Real-time accurate and robust automatic detection and tracking of anatomical structures while scanning would significantly impact diagnostic and therapeutic procedures to be consistent and efficient. In this paper, we propose a deep learning framework to automatically detect and track a specific anatomical target structure in ultrasound scans. Our framework is designed to be accurate and robust across subjects and imaging devices, to operate in real-time, and to not require a large training set. It maintains a localization precision and recall higher than 90% when trained on training sets that are as small as 20% in size of the original training set. The framework backbone is a weakly trained segmentation neural network based on U-Net. We tested the framework on two different ultrasound datasets with the aim to detect and track the Vagus nerve, where it outperformed current state-of-the-art real-time object detection networks.Clinical Relevance-The proposed approach provides an accurate method to detect and localize target anatomical structures in real-time, assisting sonographers during ultrasound scanning sessions by reducing diagnostic and detection errors, and expediting the duration of scanning sessions.

Super-Resolution Cine Image Enhancement for Fetal Cardiac Magnetic Resonance Imaging

BACKGROUND

Fetal cardiac magnetic resonance imaging (MRI) improves the diagnosis of congenital heart defects, but is sensitive to fetal motion due to long image acquisition time. This may be overcome with faster image acquisition with low resolution, followed by image enhancement to provide clinically useful images.

PURPOSE

To combine phase-encoding undersampling with super-resolution neural networks to achieve high-resolution fetal cine cardiac MR images with short acquisition time.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-eight fetuses (gestational week 36 [interquartile range 33-38 weeks]).

FIELD STRENGTH/SEQUENCE

1.5 T, balanced steady-state free precession (bSSFP) cine sequence.

ASSESSMENT

Images were acquired using fully sampled Doppler ultrasound-gated clinical bSSFP cine as reference, with equivalent cine sequences with decreased phase-encoding resolution (25%, 33%, and 50% of clinical standard). Two super-resolution methods based on convolutional neural networks were proposed and evaluated (phasrGAN and phasrresnet). Data were partitioned into training (36 cine slices), validation (3 cine slices), and test sets (67 cine slices) without overlap. Conventional reconstruction methods using bicubic interpolation and k-space zeropadding were used for comparison. Three blinded observers scored image quality between 1 and 10.

STATISTICAL TESTS

Image scores are reported as median [interquartile range] and were compared using Mann-Whitney's nonparametric test with P < 0.05 showing statistically significant differences.

RESULTS

Both proposed methods showed no significant difference in image quality compared to clinical images (8 [7-8.5]) down to 33% (phasrGAN 8 [6.5-8]; phasrresnet 8 [7-8], all P ≥ 0.19) phase-encoding resolution, i.e., up to three times faster image acquisition, whereas bicubic interpolation and k-space zeropadding showed significantly lower quality for 33% phase-encoding resolution (both 7 [6-8]).

DATA CONCLUSION

Super-resolution enhancement can be used for fetal cine cardiac MRI to reduce image acquisition time while maintaining image quality. This may lead to an improved success rate for fetal cine MR imaging, as the impact of fetal motion is lessened by shortened acquisitions.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Postmortem Assessment of Isolated Congenital Heart Defects Remains Essential Following Termination of Pregnancy

OBJECTIVES

To investigate the correlation between prenatal ultrasound (US) and autopsy findings in pregnancies terminated due to isolated congenital heart defects (CHDs), including CHDs associated with heterotaxy syndrome.

MATERIALS AND METHODS

The material consists of 67 fetuses with prenatally detected isolated CHDs or CHDs associated with heterotaxy syndrome at a tertiary center in Norway between 1985 and 2014. The main CHDs were categorized into subdiagnoses of CHDs in accordance with ICD-10. The US and autopsy findings were categorized according to degree of concordance.

RESULTS

Gestational age at termination was 12 + 0-22 + 6 weeks. Hypoplastic left heart syndrome was the most common main diagnosis among the 67 fetuses (32.8%). There was full agreement between US and autopsy findings in 97.4% (222/228) of all subdiagnoses. The discrepant findings in three fetuses had no influence on the decision to terminate the pregnancy.

CONCLUSIONS

The correlation was high between prenatal US and postmortem findings in fetuses with isolated CHDs. Meticulous assessment of cardiac anatomy is particularly necessary when the decision to terminate relies on isolated CHDs. The trend of earlier termination challenges verification of diagnoses at autopsy. Consequently, the fetus should be examined at a tertiary center with fetal medicine specialists, pediatric cardiologists and perinatal pathologists.

Prenatal diagnosis of congenital heart defects: echocardiography

Congenital heart defects (CHD) are the most common congenital anomaly, and the majority can be diagnosed during prenatal life. Prenatal detection rates remain highly variable, as most CHD occur in low risk pregnancies and therefore depend on the maternal obstetric provider to recognize fetal cardiac abnormality on obstetric screening anatomic ultrasound. Fetuses with abnormal findings on obstetric screening anatomic ultrasound and/or risk factors for cardiac disease should be referred for evaluation with fetal echocardiography. Fetal echocardiography should be performed by specialized sonographers and interpreted by physicians with knowledge of evolving fetal cardiac anatomy and physiology throughout gestation. A fetal echocardiography examination, which can be done from the late first trimester onward, utilizes a standardized and systemic approach to diagnose fetuses with CHD or other forms of primary or secondary cardiac disease. The field of fetal cardiology has advanced past the accurate prenatal diagnosis of simple and complex CHD, as fetal echocardiography enables understanding of dynamic fetal cardiac physiology and consideration of potential fetal/neonatal treatment. The greatest impact of fetal echocardiography remains identification of critical CHD before birth to allow immediate cardiac management after delivery to decrease neonatal morbidity and mortality. Analyzing the severity of abnormal cardiac physiology in various forms of CHD before birth allows the fetal cardiologist to prognosticate effects on the developing fetus, predict risk of postnatal hemodynamic instability, guide delivery planning through multidisciplinary collaboration, and anticipate how the disease will impact the neonate after delivery.

Reliability of Sonography-based Volume Computer Aided Diagnosis in the Normal Fetal Heart

OBJECTIVES

To explore the inter- and intra-observer reliability of Sonography-based Volume Computer Aided Diagnosis (SonoVCAD) in the display of 8 diagnostic planes of fetal echocardiography and to evaluate its efficiency.

METHODS

Three-dimensional volume data sets of the 56 normal singleton fetuses were acquired from a 4-chamber view by using a volume probe. After processing the data sets by using SonoVCAD, 8 cardiac diagnostic planes were displayed automatically. Three doctors with different experiences of performing fetal echocardiography evaluated each diagnostic plane and the success rates of 8 diagnostic planes were calculated. Inter-observer and intra-observer reliabilities were estimated by Cohen's kappa statistics.

RESULTS

A total of 276 volume data sets acquired from the 56 normal fetuses were used for SonoVCAD analysis and display. The success rate of each diagnostic section was more than 90%, ranging from 90.6% to 99.6%. Among 276 volumes, 81.5% (225/276) of volumes were able to generate all 8 diagnostic views successfully. Moderate to substantial agreement (kappa, 0.509-0.794) was found between 2 less experienced operators. Moderate to near-perfect agreement (kappa, 0.439-0.933) was found between an expert and 2 less experienced sonographers. Intra-observer reliability was substantial to near-perfect (kappa, 0.602-0.903). The efficiency of SonoVCAD was assessed. The expert spent less time than 2 less experienced examiners (P < 0.001) but no significant difference was found between 2 less experienced examiners (P = 0.176). Besides, SonoVCAD consumed significantly less time than 2-dimensional ultrasound (P < 0.001).

CONCLUSIONS

SonoVCAD can significantly improve the success rates of 8 diagnostic planes in fetal echocardiography with low operator dependency, good reproducibility and high efficiency.

A preliminary study on the prenatal diagnosis of fetal conotruncal defects using intelligent navigation echocardiography

OBJECTIVE

To compare the accuracy, efficiency, and consistency between experienced and less-experienced professionals using intelligent navigation echocardiography.

METHODS

In this prospective study, we enrolled 93 second- and third-trimester fetuses with conotruncal defects (CTD) from July 2017 to February 2018. One or more spatiotemporal image correlation volume data sets were collected per case. The fetuses with CTD were diagnosed by the following two groups of professionals (n = 20 in each) with different experience levels using intelligent navigation echocardiography and two-dimensional ultrasound: group A with 15 years of experience and group B with 1 year of experience. The diagnostic consistency and accuracy of the technologies between the two groups were analyzed.

RESULTS

Satisfactory consistency was noted in the two groups (group A, τ = 0.855, P < 0.05, and group B, τ = 0.821, P < 0.05), and no significant difference in accuracy (χ²  = 3.218, P > 0.05) in using intelligent navigation echocardiography was reported between the two groups. However, there a significant difference in accuracy (χ²  = 0.021, P < 0.05) when using two-dimensional ultrasound was observed between the two groups.

CONCLUSION

Intelligent navigation echocardiography was found to be efficient and accurate for the diagnosis of CTD and good consistency existed in the experienced and less-experienced professionals.

The relationship between isolated pes equinovarus and aneuploidies and perinatal outcomes: Results of a tertiary center

Objective

Congenital pes equinovarus (PEV) is the most common congenital deformity of the foot, characterized by plantar flexion with a frequency of 0.2-0.3%. It can be diagnosed from the 12^th week of pregnancy. Non-isolated cases tend to be syndromic and complex. We aimed to evaluate the results of perinatally diagnosed isolated PEV.

Materials and Methods

This was a retrospective cohort study conducted between March 2015-March 2020. Women who presented for fetal anomaly screening or were referred due to any suspected fetal anomaly were subjected to detailed fetal anomaly scans and checked for the presence of PEV. Karyotype analysis was discussed for patients with PEV. Pregnancy termination was recommended for those with chromosomal/life-threatening anomalies. The diagnosis was confirmed by postnatal examination/autopsy. Postnatal diagnosis was accepted as false-positive in those with no PEV.

Results

One-hundred thirty-eight patients were found to have PEV, 41 (29.7%) of which were isolated. In the isolated group, the false-positive rate in the first trimester was significantly higher compared with the second trimester, 50%/15.3%, respectively (p<0.05). Chromosomal anomalies were detected in 2 (4.8%) patients in the isolated group. Termination was performed to 1 (2.4%) patients due to trisomy 21. In the non-isolated group, chromosomal anomalies were detected in 13 (13.4%) patients, and termination was recommended. Termination was also recommended to 18 (18.5%) patients due to anomalies incompatible with life. In the postnatal evaluation, the surgical treatment rate in the isolated/non-isolated groups was 6%/39.7% (p<0.05).

Conclusion

When PEV is diagnosed, detailed fetal anomaly screening must be performed, patients should be informed about the chromosomal anomaly risk. High false-positive rates in the first trimester should be kept in mind for diagnosis. Karyotype analysis should be recommended also to isolated cases. It should be remembered that some neuromuscular/skeletal system anomalies may occur for the first time in the postnatal period in isolated cases.

Achieving universal access to obstetric ultrasound in resource constrained settings: A narrative review

OBJECTIVES

The potential benefits and challenges of achieving universal access to obstetric ultrasound services in resource constrained settings were reviewed, with a view to making some recommendations to address the huge burden of avoidable maternal and child morbidity and mortality.

KEY FINDINGS

In most resource-poor settings of the world, antenatal ultrasound is available only to a privileged few in urban centres, while the majority of the population living in rural areas have little or no access to diagnostic imaging services. There is also the extreme shortage of sonographers and doctors with specialist training in sonography. A comprehensive regulation must be put in place to achieve maximum benefits and to ensure quality assurance; appropriate use and application of ethics and training must be comprehensive.

CONCLUSION

Ultrasound service provision, in resource-scarce settings, has the potential to improve access and quality of health care services in areas like the point of care ultrasound service provision and in the fields of obstetrics and gynaecology. A comprehensive regulation must be put in place to achieve maximum benefits and to ensure quality assurance.

IMPLICATIONS FOR PRACTICE

Making ultrasound technology available and affordable in resource scare settings has the potential to improve access to diagnostic imaging services and reduce avoidable maternal and child death in resource constrained settings.

Impact of maternal obesity on fetal cardiac screening: which follow-up strategy is cost-effective?

OBJECTIVE

To perform a cost-effectiveness analysis of different follow-up strategies for non-obese and obese women who had incomplete fetal cardiac screening for major congenital heart disease (CHD).

METHODS

Three decision-analytic models, one each for non-obese, obese and Class-III-obese women, were developed to compare five follow-up strategies for initial suboptimal fetal cardiac screening. The five strategies were: (1) no follow-up ultrasound (US) examination but direct referral to fetal echocardiography (FE); (2) one follow-up US, then FE if fetal cardiac views were still suboptimal; (3) up to two follow-up US, then FE if fetal cardiac views were still suboptimal; (4) one follow-up US and no FE; and (5) up to two follow-up US and no FE. The models were designed to identify fetuses with major CHD in a theoretical cohort of 4 000 000 births in the USA. Outcomes related to neonatal mortality and neurodevelopmental disability were evaluated. A cost-effectiveness willingness-to-pay threshold was set at US$100 000 per quality-adjusted life year (QALY). Base-case and sensitivity analysis and Monte-Carlo simulation were performed.

RESULTS

In our base-case models for all body mass index (BMI) groups, no follow-up US, but direct referral to FE led to the best outcomes, detecting 7%, 25% and 82% more fetuses with CHD in non-obese, obese and Class-III-obese women, respectively, compared with the baseline strategy of one follow-up US and no FE. However, no follow-up US, but direct referral to FE was above the US$100 000/QALY threshold and therefore not cost-effective. The cost-effective strategy for all BMI groups was one follow-up US and no FE. Both up to two follow-up US with no FE and up to two follow-up US with FE were dominated (being more costly and less effective), while one follow-up US with FE was over the cost-effectiveness threshold. One follow-up US and no FE was the optimal strategy in 97%, 93% and 86% of trials in Monte-Carlo simulation for non-obese, obese and Class-III-obese models, respectively.

CONCLUSION

For both non-obese and obese women with incomplete fetal cardiac screening, the optimal CHD follow-up screening strategy is no further US and immediate referral to FE; however, this strategy is not cost-effective. Considering costs, one follow-up US and no FE is the preferred strategy. For both obese and non-obese women, Monte-Carlo simulations showed clearly that one follow-up US and no FE was the optimal strategy. Both non-obese and obese women with initial incomplete cardiac screening examination should therefore be offered one follow-up US. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Detection of fetal cardiac anomalies: cost-effectiveness of increased number of cardiac views

OBJECTIVE

To compare the recommended three-view fetal heart screening method to detect major congenital heart disease (CHD) with more elaborate screening strategies to determine the cost-effective strategy in unselected (low-risk) pregnancies.

METHODS

A decision-analytic model was designed to compare four screening strategies to identify fetuses with major CHD in a theoretical cohort of 4 000 000 births in the USA. The four strategies were: (1) three views: four-chamber view (4CV) and views of the left (LVOT) and right (RVOT) ventricular outflow tracts; (2) five views: 4CV, LVOT, RVOT and longitudinal views of the ductal arch and aortic arch; (3) five axial views: 4CV, LVOT, RVOT, three-vessel (3V) view and three-vessels-and-trachea view; and (4) six views: 4CV, LVOT, RVOT and 3V views and longitudinal views of the ductal arch and aortic arch. Outcomes related to neonatal mortality and neurodevelopmental disability were evaluated. The analysis was performed from a healthcare-system perspective, with a cost-effectiveness willingness-to-pay threshold set at $100 000 per quality-adjusted life year (QALY). Baseline analysis, one-way sensitivity analysis and Monte-Carlo simulation were performed.

RESULTS

In our baseline model, screening with five axial views was the optimal strategy, detecting 3520 more CHDs, and resulting in 259 fewer children with neurodevelopmental disability, 40 fewer neonatal deaths and only slightly higher costs, compared with screening with the currently recommended three views. Screening with six views was more effective, but also cost considerably more, compared with screening with five axial views, and had an incremental cost of $490 023/QALY, which was over the willingness-to-pay threshold. The five-view strategy was dominated by the other three strategies, i.e. it was more costly and less effective in comparison. The data were robust when tested with Monte-Carlo and one-way sensitivity analysis.

CONCLUSION

Although current guidelines recommend a minimum of three views for detecting CHD during the mid-trimester anatomy scan, screening with five axial views is a cost-effective strategy that may lead to improved outcome compared with three-view screening. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.

Special statement: Proposed quality metrics to assess accuracy of prenatal detection of congenital heart defects

Congenital heart defects are a leading cause of neonatal morbidity and mortality. Accurate prenatal diagnosis of congenital heart defects can reduce morbidity and mortality by improving prenatal care, facilitating predelivery pediatric cardiology consultation, and directing delivery to facilities with resources to manage the complex medical and surgical needs of newborns with congenital heart defects. Unfortunately, less than one half of congenital heart defect cases are detected prenatally, resulting in lost opportunities for counseling, shared decision-making, and delivery at an appropriate facility. Quality improvement initiatives to improve prenatal congenital heart defects detection depend on the ability to measure the rate of detection at the level of providers, facilities, or populations, but no standard metric exists for measuring the detection of congenital heart defects at any level. The need for such a metric was recognized at a Cooperative Workshop held at the 2016 Annual Meeting of the Society for Maternal-Fetal Medicine, which recommended the development of a quality metric to assess the rate of prenatal detection of clinically significant congenital heart defects. In this paper, we propose potential quality metrics to measure prenatal detection of critical congenital heart defects, defined as defects with a high rate of morbidity or mortality or that require surgery or tertiary follow-up. One metric is based on a retrospective approach, assessing whether postnatally diagnosed congenital heart defects had been identified prenatally. Other metrics are based on a prospective approach, assessing the sensitivity and specificity of prenatal diagnosis of congenital heart defects by comparing prenatal ultrasound findings with newborn findings. Potential applications, limitations, challenges, barriers, and value for both approaches are discussed. We conclude that future development of these metrics will depend on an expansion of the International Classification of Diseases system to include specific codes that distinguish fetal congenital heart defects from newborn congenital heart defects and on the development of record systems that facilitate the linkage of fetal records (in the maternal chart) with newborn records.

Physician Barriers and Facilitators for Screening for Congenital Heart Disease With Routine Obstetric Ultrasound: A National United States Survey

OBJECTIVES

Prenatal detection of congenital heart disease with obstetric screening remains at less than 50% in most population studies, far from what is thought to be achievable. We sought to identify barriers/facilitators for screening from the perspective of interpreting physicians and to understand how these barriers/facilitators may be associated with interpretation of screening images.

METHODS

Our mixed-methods studies included 4 focus groups in centers across the United States with obstetric, maternal-fetal medicine, and radiology providers who interpreted obstetric ultrasound studies. Themes around barriers/facilitators for fetal heart screening were coded from transcripts. A national Web-based survey was then conducted, which quantitatively measured reported barriers/facilitators and measured physicians' ability to interpret fetal heart-screening images. Multivariable generalized linear random-effect models assessed the association between barriers/facilitators and the accuracy of image interpretation at the image level.

RESULTS

Three main themes were identified in the focus groups: intrinsic barriers (ie, comfort with screening), external barriers (ie, lack of feedback), and organizational barriers (ie, study volumes). Among 190 physician respondents, 104 interpreted ultrasound studies. Perceptions of barriers varied by practice setting, with nontertiary providers having lower self-efficacy and perceived usefulness of cardiac screening. Facilitators associated with the odds of accurate interpretation of screening images were knowledge (odds ratio, 2.54; P = .002) and the volume of scans per week (odds ratio, 1.01 for every additional scan; P = .04).

CONCLUSIONS

Some of the main barriers to cardiac screening identified and prioritized by physicians across the United States were knowledge of screening and minimal volumes of scans. Targeting these barriers will aid in improving prenatal detection of congenital heart disease.

Why are congenital heart defects being missed?

OBJECTIVE

Congenital heart defects (CHD) are still missed frequently in prenatal screening programs, which can result in severe morbidity or even death. The aim of this study was to evaluate the quality of fetal heart images, obtained during the second-trimester standard anomaly scan (SAS) in cases of CHD, to explore factors associated with a missed prenatal diagnosis.

METHODS

In this case-control study, all cases of a fetus born with isolated severe CHD in the Northwestern region of The Netherlands, between 2015 and 2016, were extracted from the PRECOR registry. Severe CHD was defined as need for surgical repair in the first year postpartum. Each cardiac view (four-chamber view (4CV), three-vessel (3V) view and left and right ventricular outflow tract (LVOT, RVOT) views) obtained during the SAS was scored for technical correctness on a scale of 0 to 5 by two fetal echocardiography experts, blinded to the diagnosis of CHD and whether it was detected prenatally. Quality parameters of the cardiac examination were compared between cases in which CHD was detected and those in which it was missed on the SAS. Regression analysis was used to assess the association of sonographer experience and of screening-center experience with the cardiac examination quality score.

RESULTS

A total of 114 cases of isolated severe CHD at birth were analyzed, of which 58 (50.9%) were missed and 56 (49.1%) were detected on the SAS. The defects comprised transposition of the great arteries (17%), aortic coarctation (16%), tetralogy of Fallot (10%), atrioventricular septal defect (6%), aortic valve stenosis (5%), ventricular septal defect (18%) and other defects (28%). No differences were found in fetal position, obstetric history, maternal age or body mass index (BMI) or gestational age at examination between missed and detected cases. Ninety-two cases had available cardiac images from the SAS. Compared with the detected group, the missed group had significantly lower cardiac examination quality scores (adequate score (≥ 12) in 32% vs 64%; P = 0.002), rate of proper use of magnification (58% vs 84%; P = 0.01) and quality scores for each individual cardiac plane (4CV (2.7 vs 3.9; P < 0.001), 3V view (3.0 vs 3.8; P = 0.02), LVOT view (1.9 vs 3.3; P < 0.001) and RVOT view (1.9 vs 3.3; P < 0.001)). In 49% of missed cases, the lack of detection was due to poor adaptational skills resulting in inadequate images in which the CHD was not clearly visible; in 31%, the images showed an abnormality (mainly septal defects and aortic arch anomalies) which had not been recognized at the time of the scan; and, in 20%, the cardiac planes had been obtained properly but showed normal anatomy. Multivariate regression analysis showed that the volume of SAS performed per year by each sonographer was associated significantly with quality score of the cardiac examination.

CONCLUSIONS

A lack of adaptational skills when performing the SAS, as opposed to circumstantial factors such as BMI or fetal position, appears to play an important role in failure to detect CHD prenatally. The quality of the cardiac views was inadequate significantly more often in undetected compared with detected cases. Despite adequate quality of the images, CHD was not recognized in 31% of cases. A high volume of SAS performed by each sonographer in a large ultrasound center contributes significantly to prenatal detection. In 20% of undetected cases, CHD was not visible even though the quality of the images was good. © 2019 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

The standardized 12-lead fetal electrocardiogram of the healthy fetus in mid-pregnancy: A cross-sectional study

Introduction

The examination of the fetal heart in mid-pregnancy is by ultrasound examination. The quality of the examination is highly dependent on the skill of the sonographer, fetal position and maternal body mass index. An additional tool that is less dependent on human experience and interpretation is desirable. The fetal electrocardiogram (ECG) could fulfill this purpose. We aimed to show the feasibility of recording a standardized fetal ECG in mid-pregnancy and explored its possibility to detect congenital heart disease (CHD).

Materials and methods

Women older than 18 years of age with an uneventful pregnancy, carrying a healthy singleton fetus with a gestational age between 18 and 24 weeks were included. A fetal ECG was performed via electrodes on the maternal abdomen. After removal of interferences, a vectorcardiogram was constructed. Based on the ultrasound assessment of the fetal orientation, the vectorcardiogram was rotated to standardize for fetal orientation and converted into a 12-lead ECG. Median ECG waveforms for each lead were calculated.

Results

328 fetal ECGs were recorded. 281 were available for analysis. The calculated median ECG waveform showed the electrical heart axis oriented to the right and inferiorly i.e. a negative QRS deflection in lead I and a positive deflection in lead aVF. The two CHD cases show ECG abnormalities when compared to the mean ECG of the healthy cohort.

Discussion

We have presented a method for estimating a standardized 12-lead fetal ECG. In mid-pregnancy, the median electrical heart axis is right inferiorly oriented in healthy fetuses. Future research should focus on fetuses with congenital heart disease.

Novel foetal echocardiographic image processing software (5D Heart) improves the display of key diagnostic elements in foetal echocardiography

Background

To evaluate the clinical value of foetal intelligent navigation echocardiography (5D Heart) for the display of key diagnostic elements in basic sections.

Methods

3D volume datasets of 182 normal singleton foetuses were acquired with a four chamber view by using a volume probe. After processing the datasets by using 5D Heart, eight cardiac diagnostic planes were demonstrated, and the image qualities of the key diagnostic elements were graded by 3 doctors with different experiences in performing foetal echocardiography.

Results

A total of 231 volume datasets acquired from the 182 normal foetuses were used for 5D Heart analysis and display. The success rate of 8 standard diagnostic views was 88.2%, and the success rate of each diagnostic view was 55.8–99.2% and 70.7–99.0% for the random four chamber view as the initial section and for the apical four chamber view as the initial section, respectively. The success rate of each diagnostic element in the 8 diagnostic sections obtained by 5D Heart was 58.9%~ 100%. Excellent agreement was found between experienced sonographers and less-experienced sonographers (kappa> 0.769). Inter- and intra-observer agreement were substantial to near-perfect, kappa values ranging from 0.612 to 1.000 (Cohen’s kappa).

Conclusions

5D Heart can significantly improve the image quality of key diagnostic elements in foetal echocardiography with low operator dependency and good reproducibility.

Is Fetal Intelligent Navigation Echocardiography Helpful in Screening for d-Transposition of the Great Arteries?

OBJECTIVES

To evaluate the performance of fetal intelligent navigation echocardiography (FINE) applied to spatiotemporal image correlation (STIC) volumes in generating 3 specific abnormal cardiac views (left ventricular outflow tract, right ventricular outflow tract, and 3-vessel and trachea) used to screen for d-transposition of the great arteries (d-TGA).

METHODS

In this prospective study, 1 or more STIC volumes were obtained from the 4-chamber view in 34 second- and third-trimester fetuses with d-TGA. Each appropriate STIC volume was evaluated by STICLoop (Samsung Medison, Seoul, Korea) before applying the FINE method. One optimal volume per fetus was selected by observers. The visualization rates of the 3 specific abnormal cardiac views of d-TGA and their diagnostic elements were calculated, and the reliability between 2 observers was verified by the intraclass correlation coefficient.

RESULTS

Fetal intelligent navigation echocardiography applied to STIC volume data sets of fetuses with d-TGA successfully generated the 3 specific abnormal cardiac views in the following manner for 2 observers: 75.0% (n = 21) for the left ventricular outflow tract, 89.2% (n = 25) for the right ventricular outflow tract, and 85.7% (n = 24) for the 3-vessel and trachea view. Twenty-four (85.7%) of the STIC volume data sets showed 2 or 3 of the abnormal cardiac views. The interobserver intraclass correlation coefficients between the 2 observers ranged from 0.842 to 1.000 (95% confidence interval), indicating almost perfect reliability for the 2 observers.

CONCLUSIONS

In cases of d-TGA, the FINE method has a high success rate in generating 3 specific abnormal cardiac views and therefore can be performed to screen for this congenital defect.

Intraobserver and interobserver reliability in sonographic size measurements of gallbladder polyps

OBJECTIVES

To evaluate the intraobserver and interobserver reliability of gallbladder polyp measurements using transabdominal US and the factors that affect reliability.

METHODS

From November 2017 to February 2018, two radiologists measured the maximum diameter of 91 gallbladder polyps using transabdominal US. Intraobserver and interobserver agreement were determined using 95% Bland-Altman limits of agreement and intraclass correlation coefficients (ICCs). The effects of image settings, polyp location, and polyp size were evaluated by comparing ICCs using z tests.

RESULTS

The intraobserver agreement rates were 0.960 (95% confidence interval [CI], 0.939-0.973) for observer 1 and 0.962 (95% CI, 0.943-0.975) for observer 2. The ICCs between the two observers were 0.963 (95% CI, 0.926-0.979) for the first measurement and 0.973 (95% CI, 0.950-0.984) for the second measurement. The 95% limits of agreement on repeated measurements were 22.3-25.2% of the mean, and those between the two observers were 25.5-34.2% of the mean. ICCs for large polyps (≥ 5 mm) were significantly higher than those for small polyps (< 5 mm). There were no significant differences in the ICCs between image settings and polyp location.

CONCLUSIONS

Polyp size measurements using transabdominal US are highly repeatable and reproducible. Polyp size significantly affects the reliability of measurement. Diameter changes of approximately less than 25% may fall within the measurement error; this should be considered while interpreting the change in size during follow-up US, especially for small polyps.

KEY POINTS

• Gallbladder polyp size measurement using transabdominal US is highly repeatable and reproducible. • Diameter changes of approximately less than 25% should be interpreted carefully, especially in small polyps.

Factors affecting perception of the normal pediatric appendix on sonography

Background

To determine if an inherent perception skill along with sonographer experience, knowledge base, scanning time play a role in the identification of the normal appendix in the pediatric population. This is a retrospective review of pediatric (< 18 years old) patients with a clinical suspicion of acute appendicitis presenting to the emergency department of two affiliated academic tertiary care hospitals over a 1-year time span. All patients had a sonogram performed by 1/15 sonographers or by 1/8 on-call radiology residents. Those with a normal or non-visualized appendix with subsequent discharge from ER were included in the study. Patient demographics, minutes spent scanning, and sonographer years of experience in general abdominal scanning and residents level of training were recorded.

Results

Of the 127 patients included in the study, 51 (40%) were male and 76 (60%) were female, with a mean age of 11.8 ± 4.2 years. Sonographers who failed to see a normal appendix had less experience (median 8 years) than those who did visualize the appendix (median 15 years), p ≤ 0.001. Longer time spent scanning was also associated with visualizing a normal appendix (20.4 versus 29.1 min, p = 0.001). In multivariable logistic regression, more time spent scanning (OR 1.04, 95% CI 1.01, 1.07, p = 0.012) and increased sonographer experience (OR 1.07, 95% CI 1.02, 1.13, p = 0.012) resulted in greater odds of perceiving the appendix. The top 4 were significantly more likely to visualize the appendix (88.0%) than all of the other combined (20.8%, p < 0.001), and they also had substantially more experience (median 15 years versus 8 years, p < 0.001). Overall, sonographers were more likely to see a normal appendix (61%) than the residents (14%), p < 0.001.

Conclusion

Sonography to rule out appendicitis in the pediatric patient is in general most successful when performed by experienced sonographers with adequate time to perform the scan. Triaging patients to those sonographers who have displayed optimal perceptual ability of the normal appendix may help optimize patient care and hospital resources. Having experienced sonographers available after hours would allow for optimal care in the setting of ‘query’ appendicitis.

Improving fetal congenital heart disease screening using a checklist-based approach

To determine if using a checklist of specific ultrasound image criteria to screen the fetal heart improves the cardiac exam completion rate, defined as the ability to classify the heart as normal or abnormal. This is a retrospective cohort study of patients with singleton pregnancies who underwent a fetal anatomy survey between 18 and 28 weeks' gestation. A checklist was used from 1 September 2015 to 31 March 2016 to categorize exams as complete-normal, complete-abnormal, or incomplete. Performance was compared with a 7-month period prior to checklist introduction (1 December 2014 to 30 June 2015). Checklist utilization improved the cardiac exam completion rate by 8.9%. With the checklist, 1083 of 1202 exams (90.1%) were completed compared to 987 of 1193 (82.7%) pre-checklist, P < .001. We did not detect a change in cases classified as abnormal and referred for echocardiography: 25 (2.1%) with the checklist and 16 (1.3%) pre-checklist, P = .16. We did not detect more congenital heart disease (CHD), 12 (1.0%) with checklist screening, 5 (0.4%) pre-checklist, P = .14. Critical CHD was not missed in either group. Using the checklist improved the cardiac exam completion rate. There was no change in congenital heart disease detection.

Live-Born Major Congenital Heart Disease in Denmark: Incidence, Detection Rate, and Termination of Pregnancy Rate From 1996 to 2013

Importance

The occurrence of major congenital heart disease (CHD) is affected by several variables. Determining the development of the true incidence is critical to the establishment of proper treatment of these patients.

Objective

To evaluate time trends in incidence, detection rate, and termination of pregnancy (TOP) rate of major CHD in fetuses in Denmark and assess the influence of the introduction of general prenatal screening in 2004.

Design, Setting, and Participants

Nationwide, population-based, retrospective observational study in Denmark from 1996 to 2013 that included a consecutive sample of 14 688 live-born children and terminated fetuses diagnosed as having CHD. Patient records on TOP and children with major CHD were reviewed to validate the diagnoses. Major CHD included univentricular heart, transposition of the great arteries, congenitally corrected transposition of the great arteries, truncus arteriosus, interrupted aortic arch, atrioventricular septal defects, double outlet right ventricle, coarctatio of the aorta, Ebstein anomaly, pulmonary atresia with ventricular septal defect, pulmonary atresia with intact ventricular septum, and tetralogy of Fallot. Data were analyzed between January 2017 and March 2018.

Main Outcomes and Measures

Temporal changes in incidence, detection rate, and TOP of major CHD.

Results

Of 14 688 children and fetuses diagnosed with CHD, 2695 (18.4%; 95% CI, 17.8-19.1) had major CHD. A total of 7131 boys (1304 with major CHD) and 6926 girls (920 with major CHD) were included, with a median age of 11 years (interquartile range, 6-15 years). During the study period, the live-birth incidence of CHD was constant at 1.22% (95% CI, 1.18-1.26), whereas it decreased for major CHD. When including TOP, the incidence of major CHD did not change over time. The detection rate of major CHD increased from 4.5% (95% CI, 1.2-7.8) to 71.0% (95% CI, 63.3-78.7) (P < .001). At the end of the study, all cases of double outlet right ventricle, Ebstein anomaly, congenitally corrected transposition of the great arteries, and pulmonary atresia with ventricular septal defect were detected prenatally, whereas coarctation of the aorta had the lowest detection rate (21.7%; 95% CI, 3.5-40.0). The TOP rate increased from 0.6% (95% CI, -0.6 to 1.9) to 39.1% (95% CI, 30.9-47.4) (P < .001) among all major CHD. For prenatally diagnosed major CHD, 57.8% of cases were terminated and the proportion did not change significantly throughout the study. Diagnoses leading to TOP included all major CHD diagnoses.

Conclusions and Relevance

Detection rates of major CHD improved during the study. This has led to increased TOP rates, with a subsequent 39% decrease in the live-birth incidence of major CHD.