Reference ranges of fetal heart function using a Modified Myocardial Performance Index: a prospective multicentre, cross-sectional study

An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study

BACKGROUND

The motion relationship and time intervals of the pulsed-wave Doppler (PWD) spectrum are essential for diagnosing fetal arrhythmia. However, few technologies currently are available to automatically calculate fetal cardiac time intervals (CTIs).

OBJECTIVE

The purpose of this study was to develop a fetal heart rhythm intelligent quantification system (HR-IQS) for the automatic extraction of CTIs and establish the normal reference range for fetal CTIs.

METHODS

A total of 6498 PWD spectrums of 2630 fetuses over the junction between the left ventricular inflow and outflow tracts were recorded across 14 centers. E, A, and V waves were manually labeled by 3 experienced fetal cardiologists, with 17 CTIs extracted. Five-fold cross-validation was performed for training and testing of the deep learning model. Agreement between the manual and HR-IQS-based values was evaluated using the intraclass correlation coefficient and Spearman's rank correlation coefficient. The Jarque-Bera test was applied to evaluate the normality of CTIs' distributions, and the normal reference range of 17 CTIs was established with quantile regression. Arrhythmia subset was compared with the non-arrhythmia subset using the Mann-Whitney U test.

RESULTS

Significant positive correlation (P <.001) and moderate-to-excellent consistency (P <.001) between the manual and HR-IQS automated measurements of CTIs was found. The distribution of CTIs was non-normal (P <.001). The normal range (2.5th to 97.5th percentiles) was successfully established for the 17 CTIs.

CONCLUSIONS

Using our HR-IQS is feasible for the automated calculation of CTIs in practice and thus could provide a promising tool for the assessment of fetal rhythm and function.

Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology

Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and hindered by the need for specialized training. To overcome these limitations, AI models have been proposed for automated plane acquisition, anatomical measurements, and pathology detection. This study aims to overview recent literature on AI applications in OB/GYN US imaging, highlighting their benefits and limitations. For the methodology, a systematic literature search was performed in the PubMed and Cochrane Library databases. Matching abstracts were screened based on the PICOS (Participants, Intervention or Exposure, Comparison, Outcome, Study type) scheme. Articles with full text copies were distributed to the sections of OB/GYN and their research topics. As a result, this review includes 189 articles published from 1994 to 2023. Among these, 148 focus on obstetrics and 41 on gynecology. AI-assisted US applications span fetal biometry, echocardiography, or neurosonography, as well as the identification of adnexal and breast masses, and assessment of the endometrium and pelvic floor. To conclude, the applications for AI-assisted US in OB/GYN are abundant, especially in the subspecialty of obstetrics. However, while most studies focus on common application fields such as fetal biometry, this review outlines emerging and still experimental fields to promote further research.

The Relationship Between Fetal Central Nervous System Malformations and Modified Myocardial Performance Index

INTRODUCTION

Fetal ventriculomegaly, the most commonly identified abnormality of the fetal central nervous system (CNS), has been associated with elevated levels of the modified myocardial performance index (mMPI). However, the impact of other CNS pathologies on mMPI has not yet been evaluated. This study aimed to investigate whether there were changes in the myocardial performance index of fetuses with CNS pathologies without congenital heart diseases.

METHODS

A total of 126 singleton pregnant women were included in this study. Sixty-three fetuses had fetal CNS abnormalities of acrania, anencephaly, encephalocele, Dandy-Walker malformation, hydrocephalus, and meningocele. The control group consisted of 63 healthy and gestational age-matched fetuses. All ultrasonographic examinations were done in the second trimester of gestation. The data related to the characteristics of pregnant women were evaluated, and fetal left ventricular mMPI was obtained by ultrasound scan.

RESULTS

The study and the control group participants were not significantly different by means of pregnancy characteristics. The mean mMPI was higher in the fetal CNS malformation group compared to the control groups (0.39±0.02 vs. 0.45±0.04, P<0.001). The mean mMPI value was similar for fetuses with both closed and open calvarium defects of fetal CNS malformation.

CONCLUSION

Fetal CNS anomalies may be associated with prenatal cardiac dysfunction. Moreover, this relationship might be independent of the type of fetal CNS malformation, whether a closed or open calvarium defect.

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.

Prenatal Diagnosis of Fetal Heart Failure

Fetal heart failure (FHF) is a condition of inability of the fetal heart to deliver adequate blood flow for tissue perfusion in various organs, especially the brain, heart, liver and kidneys. FHF is associated with inadequate cardiac output, which is commonly encountered as the final outcome of several disorders and may lead to intrauterine fetal death or severe morbidity. Fetal echocardiography plays an important role in diagnosis of FHF as well as of the underlying causes. The main findings supporting the diagnosis of FHF include various signs of cardiac dysfunction, such as cardiomegaly, poor contractility, low cardiac output, increased central venous pressures, hydropic signs, and the findings of specific underlying disorders. This review will present a summary of the pathophysiology of fetal cardiac failure and practical points in fetal echocardiography for diagnosis of FHF, focusing on essential diagnostic techniques used in daily practice for evaluation of fetal cardiac function, such as myocardial performance index, arterial and systemic venous Doppler waveforms, shortening fraction, and cardiovascular profile score (CVPs), a combination of five echocardiographic markers indicative of fetal cardiovascular health. The common causes of FHF are reviewed and updated in detail, including fetal dysrhythmia, fetal anemia (e.g., alpha-thalassemia, parvovirus B19 infection, and twin anemia-polycythemia sequence), non-anemic volume load (e.g., twin-to-twin transfusion, arteriovenous malformations, and sacrococcygeal teratoma, etc.), increased afterload (intrauterine growth restriction and outflow tract obstruction, such as critical aortic stenosis), intrinsic myocardial disease (cardiomyopathies), congenital heart defects (Ebstein anomaly, hypoplastic heart, pulmonary stenosis with intact interventricular septum, etc.) and external cardiac compression. Understanding the pathophysiology and clinical courses of various etiologies of FHF can help physicians make prenatal diagnoses and serve as a guide for counseling, surveillance and management.

Modified Myocardial Performance Index in Fetal Growth Disturbances as Diagnostic and Prognostic Adjunct

BACKGROUND

Fetal growth disturbance can be associated with cardiac dysfunction. This study aimed to assess the modified myocardial performance index in growth-restricted and appropriate for gestational age fetuses and evaluate both its prognostic value in perinatal period and also its association with adverse perinatal outcomes.

METHODS

Totally 131 pregnant women were included in this prospective study. Of these, 56 cases were in study group with a diagnosis of small fetus and 75 cases were in control group with a diagnosis appropriately grown fetus. Fetal echocardiography was performed in all pregnant women to measure modified myocardial performance index. Umbilical, middle cerebral and uterine artery Doppler ultrasound parameters were measured in the study group. Small fetuses were categorized into 2 subgroups of late-onset fetal growth restriction and small for gestational age.

RESULTS

Modified myocardial performance index was significantly higher in small fetuses compared to controls (0.45 vs. 0.37, P <.001). Newborn intensive care unit admission rates were significantly higher in small fetuses than in controls (chi-square test, P <.001). The highest mean modified myocardial performance index was recorded in the late-onset fetal growth restriction subgroup (0.45 vs. 0.41 vs. 0.37). The sensitivity and specificity of modified myocardial performance index in predicting adverse outcomes at a cut-off value of 0.41 were 63% and 75%, respectively. There was a significant negative correlation between modified myocardial performance index values and birth weights.

CONCLUSIONS

We found higher left fetal heart modified myocardial performance index values in small fetuses indicating the presence of prenatal cardiac dysfunction. Fetal myocardial performance deteriorates in concordance with severity of growth restriction. Modified myocardial performance index can also be used to predict adverse perinatal outcomes among growth-restricted fetuses.