A Prospective Study of the Use of Fetal Intelligent Navigation Echocardiography (FINE) to Obtain Standard Fetal Echocardiography Views

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.

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.

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.

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.

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.

Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV)

The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (RVOT) view, and 3-vessels and trachea (3VT) view in fetuses with double-outlet right ventricle (DORV). In this prospective study, thirty fetuses diagnosed with DORV by fetal echocardiography in the second and third trimesters were enrolled. One or more STIC volume data-sets were collected from the 4-chamber view as initial view for each fetus, one optimal volume per fetus was selected for on-line analysis using FINE, and the diagnosis plane image was optimized using the Virtual Intelligent Sonographer Assistance (VIS-assistance).The visualization rates of 3 specific abnormal fetal echocardiography views of DORV and key diagnostic elements were calculated. One or more STIC volumes (n = 30 total) were obtained in 25 patients. A single STIC volume per patient was analyzed using the FINE method. FINE was able to successfully generate and display 3 specific abnormal fetal echocardiography views. The display rates of the 3 specific abnormal fetal echocardiography views (3VT, LVOT, RVOT) were 84.0%, 76.0% and 84.0%, respectively. By applying intelligent navigation technology to STIC volume data-sets, the FINE method can successfully generate three specific abnormal cardiac fetal echocardiography diagnostic views in fetuses with DORV, the FINE method can be used for screening and remote consultation of fetal DORV.

Electronic versus conventional spatiotemporal image correlation (STIC) fetal echocardiography: a direct comparison

Objectives: Recent advances in Spatial Temporal Image Correlation (STIC) 4 D fetal echocardiography include the application of eSTIC based on electronic probe image acquisition. We aimed to directly compare the performance of conventional STIC versus eSTIC technique (B-Mode and color Doppler imaging) during off-line reconstruction of STIC/eSTIC fetal heart volume pairs.Methods: Pairs of B-Mode and Color Doppler STIC volumes were acquired sequentially by firstly conventional (STIC) followed by electronic (eSTIC) probes during 33 consecutive obstetric scans at median 23 (range 13-31) gestational weeks. The resulting 66 fetal heart volume pairs were assessed blindly off-line by a fetal cardiologist who documented feasibility of reconstruction, presence of motion artifacts, subjective image quality on a 4-level scale: 1-best to 4-non-diagnostic and morphological diagnosis, to enable a paired comparison of STIC and eSTIC in the same fetus under similar scanning conditions.Results: eSTIC volumes had higher temporal resolution (37 vs. 24 frames per second, p < .001), less motion during acquisition (12 vs. 20 cases, O.R. 7.0, p = .002) and better average image quality (1.9 vs. 2.2, p = .006) compared to STIC volumes. More diagnostic reconstructions were achieved by eSTIC (n = 55, 86%) than STIC (n = 52, 78.8%), p = .001), in a comparable analysis time (mean 4.96 vs. 4.94 min). During a comparison of image quality of the original acquisition (A) and reconstructed planes (B and C planes) e STIC was superior in 22 (33%), 39 (59%) and 21 (38%) volumes, respectively, with the remaining cases being of similar quality (<10% in each plane in favor of STIC). Imaging mode and gestational age had a similar impact on both eSTIC and STIC performance: diagnostically acceptable studies in 49 (75.8%) vs. 48 (72.2%) by B-Mode, 60 (90.9%) vs. 56 (84.8%) by Color Doppler Mode, 8 (62.5%) vs. 10 (50%) in early scans, 38 (95%) vs. 38 (95%) in mid-gestation scans, and 7 (70%) vs. 6 (60%) in third trimester scans. Eight obstetric scans identified a fetus with a cardiac variant or structural abnormality. Diagnostic concordance of the two STIC approaches was comparable (40/48 concordant interpretations, kappa 0.657) all confirmed by fetal and/or postnatal echocardiography.Conclusions: eSTIC was associated with more effective 4 D fetal heart reconstruction due to reduced motion artifacts and superior image quality in all planes, when compared to STIC. Early gestation reconstructions were not generally successful using either technology. Further study is needed to define the cost-effectiveness and diagnostic impact of eSTIC over conventional STIC and their role over, or in addition to, screening 2 D fetal echocardiography by appropriately trained sonographers.

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.

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.

Assessment of the quality of fetal heart standard views using the FAST, STAR, and FINE four-dimensional ultrasound techniques in the screening of congenital heart diseases

OBJECTIVE

To compare the quality of standard fetal echocardiographic views obtained by four-dimensional ultrasound with those obtained by the simple targeted arterial rendering (STAR) technique, four-chamber view swing technique (FAST), and fetal intelligent navigation echocardiography (FINE/5D Heart^® ) technique.

METHODS

This was a cross-sectional prospective study that included pregnant women between 22 and 34 weeks of gestation, with normal fetuses. Fetal heart volumes were acquired using spatio-temporal image correlation (STIC) with the fetal spine between 2 and 9 o'clock. The FAST/STAR techniques consist of the manipulation of STIC volumes by drawing OmniView^™ lines to obtain echocardiographic views. The FINE/5D Heart® technique uses intelligent navigation to automatically generate echocardiographic views. The quality of the images was classified as excellent, good, acceptable, and unacceptable. The analysis was performed using the Bonferroni multiple comparisons test.

RESULTS

The study included 101 pregnant women aged between 16 and 44 years. There was no mean difference in image quality between the techniques regarding fetal spine position in all echocardiographic views (P > .05). However, in the five-chamber, left ventricular outflow tract, right ventricular outflow tract, ductal arch, superior vena cava/inferior vena cava, and abdomen/stomach views, there was a statistically significant mean difference quality between the techniques, regardless of the spine position (P < .05). The best mean image quality was obtained by the FINE technique (P ≤ .016 for all fetal echocardiographic views).

CONCLUSION

The quality of the echocardiographic views obtained using the FINE technique was superior to that of those generated by the FAST/STAR techniques in normal fetuses.

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.

4D fetal echocardiography-An update

With the introduction of the electronic 4-dimensional and spatial-temporal image Correlation (e-STIC), it is now possible to obtain large volume datasets of the fetal heart that are virtually free of artifact. This allows the examiner to use a number of imaging modalities when recording the volumes that include two-dimensional real time, power and color Doppler, and B-flow images. Once the volumes are obtained, manipulation of the volume dataset allows the examiner to recreate views of the fetal heart that enable examination of cardiac anatomy. The value of this technology is that a volume of the fetal heart can be obtained, irrespective of the position of the fetus in utero, and manipulated to render images for interpretation and diagnosis. This article presents a summary of the various imaging techniques and provides clinical examples of its application used for prenatal diagnosis of congenital heart defects and abnormal cardiac function.

The effect of the introduction of the three-vessel view on the detection rate of transposition of the great arteries and tetralogy of Fallot

OBJECTIVES

The aim of this study was to analyze the annual detection rate (DR) of transposition of the great arteries (TGA) and tetrology of Fallot (ToF), after the introduction of the three-vessel view as a mandatory plane in 2012.

METHODS

All registered TGA and ToF cases were retrospectively extracted from our registry between 2007 and 2016. We compared the DR in a 10-year period, before 2011, with the DR of TGA and ToF after 2012.

RESULTS

In the period before 2012, 23 of the 52 TGA cases were prenatally detected (44.2%), compared with 42 of the 51 cases (82.4%) after 2012. For ToF, the DRs increased from 28 of 64 cases (43.8%) to 42 of 62 cases (67.7%) in the aforementioned periods. The increase in DRs for both defects was statistically significant (P ≤ 0.001 and P ≤ 0.05).

CONCLUSIONS

In this nationally organized prenatal screening program with a quality monitoring system and a uniform protocol, DRs of 82.4% for TGA and 67.7% for ToF were reached after the introduction of the three-vessel view as a mandatory item. The three-vessel view significantly contributes to the detection of these conotruncal anomalies.

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.

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

OBJECTIVE

To evaluate the performance of color and bidirectional power Doppler ultrasound combined with Fetal Intelligent Navigation Echocardiography (FINE) in examining the fetal heart.

METHODS

A prospective cohort study was conducted of fetuses in the second and third trimesters with a normal heart or with congenital heart disease (CHD). One or more spatiotemporal image correlation (STIC) volume datasets, combined with color or bidirectional power Doppler (S-flow) imaging, were acquired in the apical four-chamber view. Each successfully obtained STIC volume was evaluated by STICLoop™ to determine its appropriateness before applying the FINE method. Visualization rates for standard fetal echocardiography views using diagnostic planes and/or Virtual Intelligent Sonographer Assistance (VIS-Assistance®) were calculated for grayscale (removal of Doppler signal), color Doppler and S-flow Doppler. In four cases with CHD (one case each of tetralogy of Fallot, hypoplastic left heart and coarctation of the aorta, interrupted inferior vena cava with azygos vein continuation and asplenia, and coarctation of the aorta with tricuspid regurgitation and hydrops), the diagnostic potential of this new technology was presented.

RESULTS

A total of 169 STIC volume datasets of the normal fetal heart (color Doppler, n = 78; S-flow Doppler, n = 91) were obtained from 37 patients. Only a single STIC volume of color Doppler and/or a single volume of S-flow Doppler per patient were analyzed using FINE. Therefore, 60 STIC volumes (color Doppler, n = 27; S-flow Doppler, n = 33) comprised the final study group. Median gestational age at sonographic examination was 23 (interquartile range, 21-27.5) weeks. Color Doppler FINE generated nine fetal echocardiography views (grayscale) using (1) diagnostic planes in 73-100% of cases, (2) VIS-Assistance in 100% of cases, and (3) a combination of diagnostic planes and/or VIS-Assistance in 100% of cases. The rate of generating successfully eight fetal echocardiography views with appropriate color and S-flow Doppler information was 89-100% and 91-100% of cases, respectively, using a combination of diagnostic planes and/or VIS-Assistance. However, the success rate for the ninth echocardiography view (i.e. superior and inferior venae cavae) was 33% and 30% for color and S-flow Doppler, respectively. In all four cases of CHD, color Doppler FINE demonstrated evidence of abnormal fetal cardiac anatomy and/or hemodynamic flow.

CONCLUSIONS

The FINE method applied to STIC volumes of normal fetal hearts acquired with color or bidirectional power Doppler information can generate successfully eight to nine standard fetal echocardiography views (via grayscale, color Doppler or power Doppler) in the second and third trimesters. In cases of CHD, color Doppler FINE demonstrates successfully abnormal anatomy and/or Doppler flow characteristics. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

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.