Analysis of maturation features in fetal brain ultrasound via artificial intelligence for the estimation of gestational age

Background: Optimal prenatal care relies on accurate gestational age dating. After the first trimester, the accuracy of current gestational age estimation methods diminishes with increasing gestational age. Considering that, in many countries, access to first trimester crown rump length is still difficult owing to late booking, infrequent access to prenatal care, and unavailability of early ultrasound examination, the development of accurate methods for gestational age estimation in the second and third trimester of pregnancy remains an unsolved challenge in fetal medicine. Objective. This study aimed to evaluate the performance of an artificial intelligence method based on automated analysis of fetal brain morphology on standard cranial ultrasound sections to estimate the gestational age in second and third trimester fetuses compared with the current formulas using standard fetal biometry. Study Design: Standard transthalamic axial plane images from a total of 1394 patients undergoing routine fetal ultrasound were used to develop an artificial intelligence method to automatically estimate gestational age from the analysis of fetal brain information. We compared its performance—as stand alone or in combination with fetal biometric parameters—against 4 currently used fetal biometry formulas on a series of 3065 scans from 1992 patients undergoing second (n=1761) or third trimester (n=1298) routine ultrasound, with known gestational age estimated from crown rump length in the first trimester. Results: Overall, 95% confidence interval of the error in gestational age estimation was 14.2 days for the artificial intelligence method alone and 11.0 when used in combination with fetal biometric parameters, compared with 12.9 days of the best method using standard biometrics alone. In the third trimester, the lower 95% confidence interval errors were 14.3 days for artificial intelligence in combination with biometric parameters and 17 days for fetal biometrics, whereas in the second trimester, the 95% confidence interval error was 6.7 and 7, respectively. The performance differences were even larger in the small-for-gestational-age fetuses group (14.8 and 18.5, respectively). Conclusion: An automated artificial intelligence method using standard sonographic fetal planes yielded similar or lower error in gestational age estimation compared with fetal biometric parameters, especially in the third trimester. These results support further research to improve the performance of these methods in larger studies.The research leading to these results was partially funded by Transmural Biotech S.L. In addition, the research has received funding from “la Caixa” Foundation under grant agreements LCF/PR/GN14/10270005 and LCF/PR/GN18/10310003, the Instituto de Salud Carlos III (PI16/00861, PI17/00675) within the Plan Nacional de I+D+I and cofinanced by Instituto de Salud Carlos III— Subdirección General de Evaluación together with the Fondo Europeo de Desarrollo Regional (FEDER) “Una manera de hacer Europa,” Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, United Kingdom), Cellex Foundation, ASISA Foundation, and Agency for Management of University and Research Grants under grant 2017 SGR number 1531. In addition, E.E. has received funding from the Departament de Salut under grant number SLT008/18/00156.Peer ReviewedPostprint (published version

Comment on Yeste et al.: Polyphenols and IUGR Pregnancies: Intrauterine Growth Restriction and Hydroxytyrosol Affect the Development and Neurotransmitter Profile of the Hippocampus in a Pig Model

Intrauterine growth restriction (IUGR) affects 5-10% of newborns and increases the risks of intrauterine demise, neonatal morbidity, and death. In their recent publication, Yeste et al. found the benefits of hydroxytyrosol supplementation on brain remodeling from an IUGR pig model. Additionally, we found a significant decrease in phenolic alcohol (tyrosol and hydroxytyrosol) intake in IUGR pregnant women. Altogether, these findings support the notion that dietetic interventions, through supplementation but mostly via a balanced diet, can ameliorate IUGR complications. Furthermore, diet intervention combined with early biomarkers may allow clinicians to eventually anticipate IUGR diagnosis and help avoid one of the most frequent causes of newborn mortality and morbidity

Low birth weight as a potential risk factor for severe COVID-19 in adults

The identification of factors predisposing to severe COVID-19 in young adults remains partially characterized. Low birth weight (LBW) alters cardiovascular and lung development and predisposes to adult disease. We hypothesized that LBW is a risk factor for severe COVID-19 in non-elderly subjects. We analyzed a prospective cohort of 397 patients (18-70 years) with laboratory-confirmed SARS-CoV-2 infection attended in a tertiary hospital, where 15% required admission to Intensive Care Unit (ICU). Perinatal and current potentially predictive variables were obtained from all patients and LBW was defined as birth weight ≤ 2.500 g. Age (adjusted OR (aOR) 1.04 [1-1.07], P = 0.012), male sex (aOR 3.39 [1.72-6.67], P < 0.001), hypertension (aOR 3.37 [1.69-6.72], P = 0.001), and LBW (aOR 3.61 [1.55-8.43], P = 0.003) independently predicted admission to ICU. The area under the receiver-operating characteristics curve (AUC) of this model was 0.79 [95% CI, 0.74-0.85], with positive and negative predictive values of 29.1% and 97.6% respectively. Results were reproduced in an independent cohort, from a web-based survey in 1822 subjects who self-reported laboratory-positive SARS-CoV-2 infection, where 46 patients (2.5%) needed ICU admission (AUC 0.74 [95% CI 0.68-0.81]). LBW seems to be an independent risk factor for severe COVID-19 in non-elderly adults and might improve the performance of risk stratification algorithms

Reconstruction of the fetus face from three-dimensional ultrasound using a newborn face statistical shape model

BACKGROUND AND OBJECTIVE: The fetal face is an essential source of information in the assessment of congenital malformations and neurological anomalies. Disturbance in early stages of development can lead to a wide range of effects, from subtle changes in facial and neurological features to characteristic facial shapes observed in craniofacial syndromes. Three-dimensional ultrasound (3D US) can provide more detailed information about the facial morphology of the fetus than the conventional 2D US, but its use for pre-natal diagnosis is challenging due to imaging noise, fetal movements, limited field-of-view, low soft-tissue contrast, and occlusions. METHODS: In this paper, we propose the use of a novel statistical morphable model of newborn faces, the BabyFM, for fetal face reconstruction from 3D US images. We test the feasibility of using newborn statistics to accurately reconstruct fetal faces by fitting the regularized morphable model to the noisy 3D US images. RESULTS: The results indicate that the reconstructions are quite accurate in the central-face and less reliable in the lateral regions (mean point-to-surface error of 2.35 mm vs 4.86 mm). The algorithm is able to reconstruct the whole facial morphology of babies from US scans while handle adverse conditions (e.g. missing parts, noisy data). CONCLUSIONS: The proposed algorithm has the potential to aid in-utero diagnosis for conditions that involve facial dysmorphology

Reconstruction of the fetus face from three-dimensional ultrasound using a newborn face statistical shape model

Background and objective: The fetal face is an essential source of information in the assessment of congenital malformations and neurological anomalies. Disturbance in early stages of development can lead to a wide range of effects, from subtle changes in facial and neurological features to characteristic facial shapes observed in craniofacial syndromes. Three-dimensional ultrasound (3D US) can provide more detailed information about the facial morphology of the fetus than the conventional 2D US, but its use for pre-natal diagnosis is challenging due to imaging noise, fetal movements, limited field-of-view, low soft-tissue contrast, and occlusions. Methods: In this paper, we propose the use of a novel statistical morphable model of newborn faces, the BabyFM, for fetal face reconstruction from 3D US images. We test the feasibility of using newborn statistics to accurately reconstruct fetal faces by fitting the regularized morphable model to the noisy 3D US images. Results: The results indicate that the reconstructions are quite accurate in the central-face and less reliable in the lateral regions (mean point-to-surface error of 2.35 mm vs 4.86 mm). The algorithm is able to reconstruct the whole facial morphology of babies from US scans while handle adverse conditions (e.g. missing parts, noisy data). Conclusions: The proposed algorithm has the potential to aid in-utero diagnosis for conditions that involve facial dysmorphology.This work is partly supported by the eSCANFace project (PID2020-114083GB-I00) funded by the Spanish Ministry of Science and Innovation, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R42HD081712. A. Alomar was supported by AGAUR under the FI scholarship and G. Piella was supported by ICREA under the ICREA Academia programme

3D fetal face reconstruction from ultrasound imaging

Comunicació presentada al VISIGRAPP 2021: The 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, celebrat del 8 al 10 de febrer de 2021 de manera virtual.The fetal face contains essential information in the evaluation of congenital malformations and the fetal brain function, as its development is driven by genetic factors at early stages of embryogenesis. Three-dimensional ultrasound (3DUS) can provide information about the facial morphology of the fetus, but its use for prenatal diagnosis is challenging due to imaging noise, fetal movements, limited field-of-view, low soft-tissue contrast, and occlusions. In this paper, we propose a fetal face reconstruction algorithm from 3DUS images based on a novel statistical morphable model of newborn faces, the BabyFM. We test the feasibility of using newborn statistics to accurately reconstruct fetal faces by fitting the regularized morphable model to the noisy 3DUS images. The algorithm is capable of reconstructing the whole facial morphology of babies from one or several ultrasound scans to handle adverse conditions (e.g. missing parts, noisy data), and it has the potential to aid in-utero di agnosis for conditions that involve facial dysmorphology.This work is partly supported by the Spanish Ministry of Economy and Competitiveness under project grant TIN2017-90124-P, and the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502)

Lung function in young adults born small for gestational age at term

Moderate to extreme prematurity is associated with lower lung function in adults1 while evidence is poorer and controversial for late prematurity.2 Likewise, the potential long-term impact on adult lung function of being born small for gestational age (SGA) at term is not well established since most previous studies in this field have been done in groups with participants enrolled by birthweight and not by SGA per se.2 This may be important because not all infants born SGA have experienced intrauterine growth restriction (IUGR) and, the other way round, early IUGR does not necessarily bring fetal growth down below the 10th percentile (the definition of SGA). We recently showed that young adults born SGA at term had markedly reduced exercise capacity, mostly of cardiovascular origin.3 In particular, they showed lower maximal workload, peak oxygen consumption and oxygen pulse, as well as higher minute ventilation/carbon dioxide production equivalent at the anaerobic threshold, than age-matched controls.3 Here, we extend and complement these previously published observations3 with the analysis of pulmonary physiology (spirometry and carbon monoxide diffusing capacity [DLCO]) and the measurement of circulatory markers of abnormal lung development, including surfactant protein A and D (SP-A and SP-D) and club cell protein 16 (CC16). We conducted an ambispective, controlled, cohort study whose detailed methodology has been published elsewhere.3 Briefly, from the birth records of our institution, we identified individuals born at term (≥37 weeks of gestation) between 1975 and 1995 with either appropriate weight for gestational age (AGA) or SGA (<10th centile for gestational age). Distinction between constitutionally small and growth-restricted participants was not possible since Doppler ultrasound, which is the tool allowing to differentiate between these two groups, was not widely used when these individuals were born, so their medical records do not include this data. Exclusion criteria were twins, congenital malformations, genetic syndromes, macrosomia, mental disorder, current pregnancy or professional sports practice. Demographics and medical history were recorded. Forced spirometry and DLCO were determined following international standards. Reference values were those of Roca et al.4, 5 The serum concentrations of SP-A, SP-D and CC16 were determined using ELISA or Luminex following manufacturer's instructions. Results are presented as mean ± SD, median [interquartile range—IQR] or number (%). Comparisons of perinatal and demographic data were performed using the Student's t-test, Wilcoxon rank-sum test, Chi-square or Fisher's exact tests, as appropriate. Comparisons of pulmonary results were adjusted by age, sex, body surface area and smoking exposure using multivariate linear regression models. A p-value < 0.05 was considered statistically significant. Analyses were performed using Stata/IC 15.1. We compared individuals born at term with SGA (n = 61) or AGA (n = 66) in their early thirties (Table 1). All participants were of Caucasian origin and were born in Barcelona (Spain). By design, birthweight was lower in SGA. The number of males and females was similar in both groups. In adulthood, weight was similar but height was significantly lower in SGA. The proportion of smokers was also similar in both groups (Table 1). There were three AGA-born and six SGA-born individuals with asthma at the time of study (one and three requiring treatment, respectively) but this difference was not statistically significant. Although absolute values of forced expiratory volume in the first second (FEV1) were significantly lower in the SGA group, when expressed as % of reference values, spirometric and DLCO values were similar and normal in both groups. Differences in absolute DLCO values did not reach statistical significance but sample size was smaller. The circulating levels of SP-A, SP-D and CC-16 were also similar in both groups. The results of the multivariate analysis did not show any further differences in the analysed parameters

Death and severe morbidity in isolated periviable small-for-gestational-age fetuses

Objective: This study aims to predict perinatal death or severe sequelae in isolated small-for-gestational-age fetuses, diagnosed at a periviable gestational age, based on ultrasound and Doppler parameters at diagnosis. Design: Observational study. Setting: A tertiary perinatal centre. Population: A cohort of singleton non-malformed fetuses suspected to be small for gestational age (estimated fetal weight, EFW, <10th centile) diagnosed at 22.0-25.6 weeks of gestation. The following parameters were recorded at diagnosis: severe smallness (<3rd centile); absent or reversed end-diastolic velocity in umbilical artery; abnormal middle cerebral artery Doppler; abnormal cerebroplacental ratio; abnormal uterine artery Doppler; and absent or reversed end-diastolic velocity in the ductus venosus. Methods: Logistic regression analysis. Main outcome measures: Predictive performance of EFW and Doppler parameters for short-term adverse outcome of perinatal morbimortality and composite serious adverse outcomes (death, neurological impairment or severe bronchopulmonary dysplasia). Results: A total of 155 pregnancies were included. There were 13 (8.4%) intrauterine and 11 (7.7%) neonatal deaths. A short-term adverse perinatal outcome occurred in 40 (25.8%) pregnancies. There were 31 (20%) cases of serious adverse outcomes. For the prediction of serious adverse outcomes, the combination of absent or reversed end-diastolic velocity in the umbilical artery and impaired middle cerebral artery detected by Doppler evaluation achieved a detection rate of 87%, with a false-positive rate of 14% (accuracy 86%). Conclusion: In periviable isolated small-for-gestational-age fetuses, a Doppler evaluation of the umbilical and fetal brain circulation can accurately predict short-term adverse perinatal complications and serious adverse outcomes

Pulmonary vascular reactivity in growth restricted fetuses using computational modelling and machine learning analysis of fetal Doppler waveforms

Abstract The aim of this study was to investigate the pulmonary vasculature in baseline conditions and after maternal hyperoxygenation in growth restricted fetuses (FGR). A prospective cohort study of singleton pregnancies including 97 FGR and 111 normally grown fetuses was carried out. Ultrasound Doppler of the pulmonary vessels was obtained at 24–37 weeks of gestation and data were acquired before and after oxygen administration. After, Machine Learning (ML) and a computational model were used on the Doppler waveforms to classify individuals and estimate pulmonary vascular resistance (PVR). Our results showed lower mean velocity time integral (VTI) in the main pulmonary and intrapulmonary arteries in baseline conditions in FGR individuals. Delta changes of the main pulmonary artery VTI and intrapulmonary artery pulsatility index before and after hyperoxygenation were significantly greater in FGR when compared with controls. Also, ML identified two clusters: A (including 66% controls and 34% FGR) with similar Doppler traces over time and B (including 33% controls and 67% FGR) with changes after hyperoxygenation. The computational model estimated the ratio of PVR before and after maternal hyperoxygenation which was closer to 1 in cluster A (cluster A 0.98 ± 0.33 vs cluster B 0.78 ± 0.28, p = 0.0156). Doppler ultrasound allows the detection of significant changes in pulmonary vasculature in most FGR at baseline, and distinct responses to hyperoxygenation. Future studies are warranted to assess its potential applicability in the clinical management of FGR