Color and power Doppler combined with Fetal Intelligent Navigation Echocardiography (FINE) to evaluate the fetal heart

Advances in the Application of Artificial Intelligence in Fetal Echocardiography

Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning can significantly improve fetal survival rates. Echocardiography is one of the most accessible and widely used diagnostic tools in the diagnosis of fetal congenital heart disease. However, traditional fetal echocardiography has limitations due to fetal, maternal, and ultrasound equipment factors and is highly dependent on the skill level of the operator. Artificial intelligence (AI) technology, with its rapid development utilizing advanced computer algorithms, has great potential to empower sonographers in time-saving and accurate diagnosis and to bridge the skill gap in different regions. In recent years, AI-assisted fetal echocardiography has been successfully applied to a wide range of ultrasound diagnoses. This review systematically reviews the applications of AI in the field of fetal echocardiography over the years in terms of image processing, biometrics, and disease diagnosis and provides an outlook for future research.

Semi-Automatic Measurement of Fetal Cardiac Axis in Fetuses with Congenital Heart Disease (CHD) with Fetal Intelligent Navigation Echocardiography (FINE)

Congenital heart disease (CHD) is one of the most common organ-specific birth defects and a major cause of infant morbidity and mortality. Despite ultrasound screening guidelines, the detection rate of CHD is limited. Fetal intelligent navigation echocardiography (FINE) has been introduced to extract reference planes and cardiac axis from cardiac spatiotemporal image correlation (STIC) volume datasets. This study analyses the cardiac axis in fetuses affected by CHD/thoracic masses (n = 545) compared to healthy fetuses (n = 1543) generated by FINE. After marking seven anatomical structures, the FINE software generated semi-automatically nine echocardiography standard planes and calculated the cardiac axis. Our study reveals that depending on the type of CHD, the cardiac axis varies. In approximately 86% (471 of 542 volumes) of our pathological cases, an abnormal cardiac axis (normal median = 40-45°) was detectable. Significant differences between the fetal axis of the normal heart versus CHD were detected in HLHS, pulmonary atresia, TOF (p-value < 0.0001), RAA, situs ambiguus (p-value = 0.0001-0.001) and absent pulmonary valve syndrome, DORV, thoracic masses (p-value = 0.001-0.01). This analysis confirms that in fetuses with CHD, the cardiac axis can significantly deviate from the normal range. FINE appears to be a valuable tool to identify cardiac defects.

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.

Application of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) in Twin Pregnancies: Half the Work or Twice the Effort?

OBJECTIVE

To assess the performance of fetal intelligent navigation echocardiography (FINE, 5D Heart™) for automated volumetric investigation of the fetal heart in twin pregnancies.

METHODS

Three hundred twenty-eight twin fetuses underwent fetal echocardiography in the second and third trimesters. Spatiotemporal image correlation (STIC) volumes were obtained for a volumetric investigation. The volumes were analyzed using the FINE software, and the data were investigated regarding image quality and many properly reconstructed planes.

RESULTS

Three hundred and eight volumes underwent final analysis. 55.8% of the included pregnancies were dichorionic twin pregnancies, and 44.2% were monochorionic twin pregnancies. The mean gestational age (GA) was 22.1 weeks, and the mean maternal BMI was 27.3 kg/m². The STIC-volume acquisition was successful in 100.0% and 95.5% of cases. The overall depiction rates of FINE were 96.5% (twin 1) and 94.7% (twin 2), respectively (p = 0.0849, not significant). In 95.9% (twin 1) and 93.9% (twin 2), at least 7 planes were reconstructed properly (p = 0.6056, not significant).

CONCLUSION

Our results indicate that the FINE technique used in twin pregnancies is reliable. No significant difference between the depiction rates of twin 1 and twin 2 could be detected. In addition, the depiction rates are as high as those derived from singleton pregnancies. Due to the challenges of fetal echocardiography in twin pregnancies (i.e., greater rates of cardiac anomaly and more difficult scans), the FINE technique might be a valuable tool to improve the quality of medical care in those pregnancies.

Prenatal Diagnosis and Fetopsy Validation of Complete Atrioventricular Septal Defects Using the Fetal Intelligent Navigation Echocardiography Method

(1) Background: Artificial Intelligence (AI) is a modern tool with numerous applications in the medical field. The case series reported here aimed to investigate the diagnostic performance of the fetal intelligent navigation echocardiography (FINE) method applied for the first time in the prenatal identification of atrioventricular septal defects (AVSD). This congenital heart disease (CHD) is associated with extracardiac anomalies and chromosomal abnormalities. Therefore, an early diagnosis is essential to advise parents and make adequate treatment decisions. (2) Methods: Four fetuses diagnosed with AVSD via two-dimensional (2D) ultrasound examination in the second trimester were enrolled. In all cases, the parents chose to terminate the pregnancy. Since the diagnosis of AVSD with 2D ultrasound may be missed, one or more four-dimensional (4D) spatiotemporal image correlation (STIC) volume datasets were obtained from a four-chamber view. The manual navigation enabled by the software is time-consuming and highly operator-dependent. (3) Results: FINE was applied to these volumes and nine standard fetal echocardiographic views were generated and optimized automatically, using the assistance of the virtual intelligent sonographer (VIS). Here, 100% of the four-chamber views, and after the VISA System application the five-chamber views, of the diagnostic plane showed the atrioventricular septal defect and a common AV valve. The autopsies of the fetuses confirmed the ultrasound results. (4) Conclusions: By applying intelligent navigation technology to the STIC volume datasets, 100% of the AVSD diagnoses were detected.

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.

Maximal Reduction of STIC Acquisition Time for Volumetric Assessment of the Fetal Heart—Benefits and Limitations of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) Static Mode

(1) Objective: To scrutinize the reliability and the clinical value of routinely used fetal intelligent navigation echocardiography (FINE) static mode (5DHeartStatic™) for accelerated semiautomatic volumetric assessment of the normal fetal heart. (2) Methods: In this study, a total of 296 second and third trimester fetuses were examined by targeted ultrasound. Spatiotemporal image correlation (STIC) volumes of the fetal heart were acquired for further volumetric assessment. In addition, all fetal hearts were scanned by a fast acquisition time volume (1 s). The volumes were analyzed using the FINE software. The data were investigated regarding the number of properly reconstructed planes and cardiac axis. (3) Results: A total of 257 volumes were included for final analysis. The mean gestational age (GA) was 23.9 weeks (14.3 to 37.7 weeks). In 96.9 (standard acquisition time, FINE standard mode) and 94.2% (fast acquisition time, FINE static mode) at least seven planes were reconstructed properly (p = 0.0961, not significant). Regarding the overall depiction rate, the standard mode was able to reconstruct 96.9% of the planes properly, whereas the static mode showed 95.2% of the planes (p = 0.0098). Moreover, there was no significant difference between the automatic measurement of the cardiac axis (37.95 + 9.14 vs. 38.00 + 8.92 degrees, p = 0.8827, not significant). (4) Conclusions: Based on our results, the FINE static mode technique is a reliable method. It provides similar information of the cardiac anatomy compared to conventional STIC volumes assessed by the FINE method. The FINE static mode has the potential to minimize the influence of motion artifacts during volume acquisition and might therefore be helpful concerning volumetric cardiac assessment in daily routine.

New and advanced features of fetal intelligent navigation echocardiography (FINE) or 5D heart

Congenital heart disease (CHD) is the leading organ-specific birth defect, as well as the leading cause of infant morbidity and mortality from congenital malformations. Therefore, a comprehensive screening examination of the fetal heart should be performed in all women to maximize the detection of CHD. Four-dimensional sonography with spatiotemporal image correlation (STIC) technology displays a cine loop of a complete single cardiac cycle in motion. A novel method known as Fetal Intelligent Navigation Echocardiography (or FINE) was previously developed to interrogate STIC volume datasets using "intelligent navigation" technology. Such method allows the automatic display of nine standard fetal echocardiography views required to diagnose most cardiac defects. FINE considerably simplifies fetal cardiac examinations and reduces operator dependency. It has both high sensitivity and specificity for the detection of CHD. Indeed, FINE has been integrated into several commercially available ultrasound platforms.Recently, eight novel and advanced features have been developed for the FINE method and they will be described herein. Such features can be categorized based upon their broad goals. The first goal is to simplify FINE further, and consists of the following features: (1) Auto fetal positioning (or FINE align); (2) Skip points; (3) Predictive cursor; (4) Static mode volume; and (5) Breech sweep. The second goal is to allow quantitative measurements to be performed on the cardiac views generated by FINE: (6) Automatic cardiac axis; and (7) Cardiac biometry. Finally, the last goal is to improve the success of obtaining fetal echocardiography view(s); and consists of (8) Maestro planar navigation.

Artificial Intelligence in Prenatal Ultrasound Diagnosis

The application of artificial intelligence (AI) technology to medical imaging has resulted in great breakthroughs. Given the unique position of ultrasound (US) in prenatal screening, the research on AI in prenatal US has practical significance with its application to prenatal US diagnosis improving work efficiency, providing quantitative assessments, standardizing measurements, improving diagnostic accuracy, and automating image quality control. This review provides an overview of recent studies that have applied AI technology to prenatal US diagnosis and explains the challenges encountered in these applications.

Diagnostic quality of 3Tesla postmortem magnetic resonance imaging in fetuses with and without congenital heart disease

BACKGROUND

Postmortem confirmation of prenatally diagnosed congenital heart disease after termination of pregnancy and evaluation of potential cardiac defects after spontaneous fetal or neonatal death are essential. Conventional autopsy rates are decreasing, and 1.5Tesla magnetic resonance imaging has demonstrated limited diagnostic accuracy for postmortem cardiovascular assessment.

OBJECTIVE

This study aimed to evaluate the feasibility and image quality of cardiac 3Tesla postmortem magnetic resonance imaging and to assess its diagnostic accuracy in detecting fetal heart defects compared with conventional autopsy. Secondarily, the study aimed to explore whether clinical factors affect the quality of 3Tesla postmortem magnetic resonance imaging.

STUDY DESIGN

A total of 222 consecutive fetuses between 12 and 41 weeks' gestation, who underwent 3Tesla postmortem magnetic resonance imaging and conventional autopsy after spontaneous death or termination of pregnancy for fetal malformations, were included. First, 3Tesla postmortem magnetic resonance imaging of each fetus was rated as diagnostic or nondiagnostic for fetal cardiac assessment by 2 independent raters. The image quality of individual cardiac structures was then further evaluated by visual grading analysis. Finally, the presence or absence of a congenital heart defect was assessed by 2 radiologists and compared with autopsy results.

RESULTS

Overall, 87.8% of 3Tesla postmortem magnetic resonance imaging examinations were rated as diagnostic for the fetal heart. Diagnostic imaging rates of individual cardiac structures at 3Tesla postmortem magnetic resonance imaging ranged from 85.1% (atrioventricular valves) to 94.6% (pericardium), with an interrater agreement of 0.82 (0.78-0.86). Diagnostic imaging of the fetal aortic arch and the systemic veins at 3Tesla postmortem magnetic resonance imaging was possible from 12+5 weeks' gestation onward in 90.1% and 92.3% of cases, respectively. A total of 55 fetuses (24.8%) had at least 1 cardiac anomaly according to autopsy, 164 (73.9%) had a normal heart, and in 3 fetuses (1.4%), autopsy was nondiagnostic for the heart. Considering all examinations rated as diagnostic, 3Tesla postmortem magnetic resonance imaging provided high diagnostic accuracy for the detection of fetal congenital heart defects with a sensitivity of 87.8%, a specificity of 97.9%, and concordance with autopsy of 95.3%. 3Tesla postmortem magnetic resonance imaging was less accurate in young fetuses (<20 weeks compared with ≥20 weeks; P<.001), in fetuses with low birthweight (≤100 g compared with >100 g; P<.001), in cases after spontaneous fetal death (compared with other modes of death; P=.012), in cases with increasing latency between death and 3Tesla postmortem magnetic resonance imaging (P<.001), and in cases in which there was a high degree of maceration (maceration score of 3 compared with a score from 0 to 2; P=.004).

CONCLUSION

Diagnostic 3Tesla postmortem magnetic resonance imaging assessment of the fetal heart is feasible in most fetuses from 12 weeks' gestation onward. In diagnostic images, sensitivity and, particularly, specificity in the detection of congenital heart disease are high compared with conventional autopsy. Owing to its high diagnostic accuracy, we suggest that 3Tesla postmortem magnetic resonance imaging may serve as a suitable imaging modality with which to direct a targeted conventional autopsy when pathology resources are limited or to provide a virtual autopsy when full autopsy is declined by the parents.

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 "holistic" sonographic view on congenital heart disease: How automatic reconstruction using fetal intelligent navigation echocardiography eases unveiling of abnormal cardiac anatomy part II-Left heart anomalies

Volume ultrasound has been shown to provide valid complementary information on fetal anatomy. Four-dimensional assessment (4D) of the fetal cardiovascular system using spatial-temporal image correlation (STIC) allows for detailed examination of a highly complex organ from the early second trimester onward. There is compelling evidence that this technique harbors quite a number of diagnostic opportunities, but manual navigation through STIC volume datasets is highly operator dependent. In fact, STIC is not incorporated yet into daily practice. Application of the novel fetal intelligent navigation echocardiography (FINE) considerably simplifies fetal cardiac volumetric examinations. This automatic technique applied on cardiac volume datasets reportedly has both high sensitivity and specificity for the detection of congenital heart defects (CHDs). Part I reviewed current data regarding detection rates of CHDs and illustrated the additional value of an automatic approach in delineating cardiac anatomy exemplified by congenital lesions of the right heart. In part II of this pictorial essay, we focused on left heart anomalies and aimed to tabulate recent findings on the quantification of normal and abnormal cardiac anatomy.

Feasibility of Semiautomatic Fetal Intelligent Navigation Echocardiography for Different Fetal Spine Positions: A Matter of "Time"?

OBJECTIVES

We investigated the feasibility of a semiautomatic approach for assessments of the fetal heart (fetal intelligent navigation echocardiography [FINE]) in cases of optimal and unfavorable fetal spine positions.

METHODS

In this study, a total of 1693 spatiotemporal image correlation volumes of first-, second-, and third-trimester fetuses were evaluated by experts using the FINE approach. The data were analyzed regarding proper reconstruction of the diagnostic cardiac planes depending on the fetal spine position.

RESULTS

A total of 1531 volumes were included. The volumes were divided into 4 groups depending on the fetal spine position: 5-7 o'clock, 4 + 8 o'clock, 3 + 9 o'clock, and 2 + 10 o'clock. In total, 93.2% of the diagnostic planes were displayed properly. Between 5 and 7 o'clock, 94.9% of the diagnostic planes were displayed properly. The correct depiction rates in the other groups were 92.4% (4 + 8 o'clock; n = 538; P = 0.0027), 88.3% (3 + 9 o'clock; n = 156; P < .0001), and 87.3% (2 + 10 o'clock; n = 41; P = .0139). In total, the highest dropout rates were found in the sagittal planes: ductal arch, 13.9%; aortic arch, 10.5%; and venae cavae, 12.0%.

CONCLUSIONS

Based on our results, the FINE technique is an effective method, but its feasibility depends on the fetal position. The use of this semiautomatic work flow-based approach supports evaluation of the fetal heart in a standardized manner. Semiautomatic evaluation of the fetal heart might be useful in facilitating the detection of fetal cardiac anomalies.

Obstetric ultrasound: where are we and where are we going?

Diagnostic ultrasound (DUS) is, arguably, the most common technique used in obstetrical practice. From A mode, first described by Ian Donald for gynecology in the late 1950s, to B mode in the 1970s, real-time and gray-scale in the early 1980s, Doppler a little later, sophisticated color Doppler in the 1990s and three dimensional/four-dimensional ultrasound in the 2000s, DUS has not ceased to be closely associated with the practice of obstetrics. The latest innovation is the use of artificial intelligence which will, undoubtedly, take an increasing role in all aspects of our lives, including medicine and, specifically, obstetric ultrasound. In addition, in the future, new visualization methods may be developed, training methods expanded, and workflow and ergonomics improved.

WITHDRAWN: Effect of maternal rubella virus infection on fetal cardiac function and neural development by color doppler ultrasound (cardiography) information technology

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Diagnostic analysis of abnormal increase of PASP in fetus in middle- and late-stage pregnancy by color Doppler echocardiography

OBJECTIVE

Our study was conducted with an attempt to investigate the diagnostic analysis of abnormal increase of fetal pulmonary artery systolic pressure (PASP) in middle and late pregnancy by color Doppler echocardiography.

METHODS

From August 2017 to January 2019, 52 fetuses with moderate or greater tricuspid high-speed regurgitation were retrospectively analyzed and selected as Group A. 88 fetuses with full-color blood flow of the two ventricles and symmetrical sizes of the cardiac cavities on both sides harboring tricuspid valve and mild regurgitation or a small amount of regurgitation were selected as Group B. The pulmonary artery blood flow acceleration time (AT) and right ventricular ejection time (ET) was measured, and the PASP was calculated.

RESULTS

The tricuspid regurgitation velocity, tricuspid regurgitation pressure difference and PASP in Group A were higher than those in Group B (p < 0.05), and the AT and AT/ET values in Group A were lower than those in Group B (p < 0.05). Gestational age, tricuspid regurgitation velocity and tricuspid regurgitation pressure difference were positively correlated with PASP. However, AT/ET and AT value were negatively correlated with PASP.

CONCLUSION

The abnormal increase of pulmonary artery can be assessed by color Doppler echocardiography of fetal tricuspid regurgitation, which is worth popularizing and applying in clinic.

ADVANCES IN KNOWLEDGE

It was suggested that the middle- and late-stage fetuses with moderate or greater tricuspid regurgitation and with >20 mmHg regurgitation pressure difference should be followed up in clinic. If PASP was ≥70 mmHg with symptoms of right heart failure, fetuses should be closely observed until 35-36 weeks old to ensure fetal safety and early delivery would be recommended.

Semiautomatic Fetal Intelligent Navigation Echocardiography Has the Potential to Aid Cardiac Evaluations Even in Less Experienced Hands

OBJECTIVES

To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standardized assessment of the fetal heart (fetal intelligent navigation echocardiography [FINE]).

METHODS

A total of 30 stored spatiotemporal image correlation volume data sets of second-trimester fetuses were evaluated by 3 physicians with different levels of expertise in fetal echocardiography by using the FINE approach. Data were analyzed regarding the examination time and proper reconstruction of the diagnostic cardiac planes. The completions and numbers of correct depictions of all diagnostic planes were evaluated by a blinded expert (time t0). To determine interobserver and intraobserver variability, the volumes were reassessed after a 4-week training interval (time t1).

RESULTS

All operators were able to perform the investigation on all 30 volumes. At t0, the interobserver variability between the beginner and both the advanced (P = .0013) and expert (P < .0001) examiners was high. Focusing on intraobserver variability at t1, the beginner showed a marked improvement (P = .0087), whereas in advanced and expert hands, no further improvement regarding proper achievement of all diagnostic planes could be noticed (P > .999; P = .8383). The beginner also showed improvement in the mean investigation time (t0, 82.8 seconds; t1, 73.4 seconds; P = .0895); nevertheless, the advanced and expert examiners were faster in completing the examination (t1, advanced, 20.9 seconds; expert, 28.3 seconds; each P < .0001).

CONCLUSIONS

Based on our results, the FINE technique is a reliable and easily learned method. The use of this semiautomatic work flow-based approach supports evaluation of the fetal heart in a standardized and time-saving manner. A semiautomatic evaluation of the fetal heart might be useful in facilitating the detection of fetal cardiac anomalies.

First data from the new, unified database of the Hungarian case-control surveillance of congenital abnormalities

The Hungarian Case-Control Surveillance of Congenital Abnormalities (HCCSCA) is one of the largest case-control data sets of CA-surveillance in the world. We unified all data collected in the HCCSCA between 1980 and 2009 into a new, validated single database that is now open for examination. The details of this unified database are given in this paper. The total number of cases and control newborns is 32,345 and 57,231, respectively. The overall prevalence of CAs recorded in the HCCSCA was 10.7/1000 live-births. Data available for each pregnancy are: CA(s), gender, birth year/month/date, birth weight, gestational age, area of mother's living, maternal age, paternal age, birth order, mother's and father's qualification, employment status and type of employment, mother's marital status, outcome of previous pregnancies, maternal diseases during pregnancy (according to pregnancy months), drug intake during pregnancy (according to pregnancy months), folic acid and/or pregnancy vitamin supplement intake (according to pregnancy months), mother's smoking habits and alcohol consumption patterns. The most frequent anomalies detected were ventricular septal defect (2864), atrial septal defect (1895), polydactyly (1499), hypospadias (1083), and unilateral cleft lip ± palate (961). According to ICD-10, 701 diseases have been found to affect case mothers during pregnancy. Eight hundred and sixteen drugs were identified that had been taken by mothers during pregnancy. The authors are absolutely open for any scientific cooperation based on this database.

How to obtain diagnostic planes of the fetal central nervous system using three-dimensional ultrasound and a context-preserving rendering technology

The antenatal evaluation of the fetal central nervous system (CNS) is among the most difficult tasks of prenatal ultrasound (US), requiring technical skills in relation to ultrasound and image acquisition as well as knowledge of CNS anatomy and how this changes with gestation. According to the International Guidelines for fetal neurosonology, the basic assessment of fetal CNS is most frequently performed on the axial planes, whereas the coronal and sagittal planes are required for the multiplanar evaluation of the CNS within the context of fetal neurosonology. It can be even more technically challenging to obtain "nonaxial" views with 2-dimensional (2D) US. The modality of 3-dimensional (3D) US has been suggested as a panacea to overcome the technical difficulties of achieving nonaxial views. The lack of familiarity of most sonologists with the use of 3D US and its related processing techniques may preclude its use even where it could play an important role in complementing antenatal 2D US assessment. Furthermore, once a 3D volume has been acquired, proprietary software allows it to be processed in different ways, leading to multiple ways of displaying and analyzing the same anatomical imaging or plane. These are difficult to learn and time consuming in the absence of specific training. In this article, we describe the key steps for volume acquisition of a 3D US volume, manipulation, and processing with reference to images of the fetal CNS, using a newly developed context-preserving rendering technique.

Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease

OBJECTIVE

Fetal intelligent navigation echocardiography (FINE) is a novel method that automatically generates and displays 9 standard fetal echocardiographic views in normal hearts by applying intelligent navigation technology to spatiotemporal image correlation (STIC) volume data sets. The main objective was to determine the sensitivity and specificity of FINE in the prenatal detection of congenital heart disease (CHD).

METHODS

A case-control study was conducted in 50 fetuses with a broad spectrum of CHD (cases) and 100 fetuses with normal hearts (controls) in the second and third trimesters. Using 4-dimensional ultrasound with STIC technology, volume data sets were acquired. After all identifying information was removed, the data sets were randomly distributed to a different investigator for analysis using FINE. The sensitivity and specificity for the prenatal detection of CHD, as well as positive and negative likelihood ratios were determined.

RESULTS

The diagnostic performance of FINE for the prenatal detection of CHD was: sensitivity of 98% (49 of 50), specificity of 93% (93 of 100), positive likelihood ratio of 14, and negative likelihood ratio of 0.02. Among cases with confirmed CHD, the diagnosis with use of FINE completely matched the final diagnosis in 74% (37 of 50); minor discrepancies were seen in 12% (6 of 50), and major discrepancies were seen in 14% (7 of 50).

CONCLUSIONS

This is the first time the sensitivity and specificity of the FINE method in fetuses with normal hearts and CHD in the second and third trimesters has been reported. Because FINE identifies a broad spectrum of CHD with 98% sensitivity, this method could be used prenatally to screen for and diagnose CHD.

Prenatal diagnosis of tetralogy of Fallot with pulmonary atresia using: Fetal Intelligent Navigation Echocardiography (FINE)

Tetralogy of Fallot with pulmonary atresia, a severe form of tetralogy of Fallot, is characterized by the absence of flow from the right ventricle to the pulmonary arteries. This cardiac abnormality is challenging and complex due to its many different anatomic variants. The main source of variability is the pulmonary artery anatomy, ranging from well-formed, confluent pulmonary artery branches to completely absent native pulmonary arteries replaced by major aorto-pulmonary collateral arteries (MAPCAs) that provide all of the pulmonary blood flow. Since the four-chamber view is usually normal on prenatal sonography, the diagnosis may be missed unless additional cardiac views are studied. Fetal Intelligent Navigation Echocardiography (FINE) is a novel method developed recently that allows automatic generation of nine standard fetal echocardiography views in normal hearts by applying "intelligent navigation" technology to spatiotemporal image correlation volume datasets. We report herein for the first time, two different cases of tetralogy of Fallot with pulmonary atresia having variable sources of pulmonary blood flow in which the prenatal diagnosis was made successfully using the FINE method. Virtual Intelligent Sonographer Assistance (VIS-Assistance^®) and automatic labeling (both features of FINE) were very helpful in making such diagnosis.

Prenatal Diagnosis of Dextrocardia with Complex Congenital Heart Disease Using Fetal Intelligent Navigation Echocardiography (FINE) and a Literature Review

Fetal dextrocardia is a type of cardiac malposition where the major axis from base to apex points to the right side. This condition is usually associated with a wide spectrum of complex cardiac defects. As a result, dextrocardia is conceptually difficult to understand and diagnose on prenatal ultrasound. The advantage of four-dimensional sonography with spatiotemporal image correlation (STIC) is that this modality can facilitate fetal cardiac examination. A novel method known as fetal intelligent navigation echocardiography (FINE) allows automatic generation of nine standard fetal echocardiography views in normal hearts by applying intelligent navigation technology to STIC volume datasets. In fetuses with congenital heart disease, FINE is also able to demonstrate abnormal cardiac anatomy and relationships when there is normal cardiac axis and position. However, this technology has never been applied to cases of cardiac malposition. We report herein for the first time, a case of fetal dextrocardia and situs solitus with complex congenital heart disease in which the FINE method was invaluable in diagnosing multiple abnormalities and defining complex anatomic relationships. We also review the literature on prenatal sonographic diagnosis of dextrocardia (with an emphasis on situs solitus), as well as tricuspid atresia with its associated cardiac features.