Cross-sectional reference values of cerebral ventricle for Chinese neonates born at 25-41 weeks of gestation

Nomograms and Reference Ranges for Intra-Cranial Ventricular Dimensions in Indian Neonates

OBJECTIVES

To establish normal reference values for commonly used ventricular indices - Anterior Horn Width (AHW), Ventricular Index (VI) and Thalamo-Occipital Distance (TOD)-against common variables including gestational age, birth weight and head circumference in Indian newborns.

METHODS

This was a cross-sectional study. Cranial ultrasound was performed between post-natal days 3 to 7. Anterior fontanelle was taken as the acoustic window. Data were analyzed to determine correlation, coefficient of determination (R2), regression equations and plotted against gestational age (GA).

RESULTS

Total 2200 newborns were included in the study. The study observed that there is an increase in VI, AHW and TOD with an increase in gestational age (p-value < 0.001) and birth weight (p-value < 0.001). No significant correlation of gender and singleton or multiple gestation-with the intraventricular dimensions was observed (p-value > 0.05). All the three ventricular parameters were found to have a significantly lower mean value in the normal vaginal delivery group as compared to the LSCS group. There was a good correlation between ventricular indices of the left and right side. Nomograms of AHW, TOD, and VI were prepared with respect to gestational age.

CONCLUSIONS

Intracranial ventricular size dimensions vary significantly with increasing gestational age and birth weight. The new nomograms for various ventricular indices of Indian neonates can assist in objectively assessing ventricular sizes.

New ultrasound features in diagnosing fetal anal atresia: a multicenter prospective cohort study

This research aimed to assess the validity of ultrasound scans with new features in detecting fetal anal atresia and verify the effectiveness of these new features. Additionally, we aimed at investigating the perinatal incidence of anal atresia. This multicenter prospective study recruited 94,617 normal gravidas and 84 gravidas with anal atresia fetuses. The gold standard for diagnosing perinatal anal atresia is routine neonatal anus examinations. The incidence calculation was based on the results of the gold standard. The validity of our new approach was evaluated via a diagnostic test involving all 94,701 subjects. The effectiveness of our new features was assessed through an ablation study in a randomly established new dataset, with the ratio of anal atresia to non-anal atresia cases of 1:4. The annual perinatal incidence of anal atresia between 2019 and 2023 ranges from 0.57‰ to 1.29‰. Our new method performed great regarding the Youden index, diagnostic odds ratio (DOR), area under the curve (AUC) of the receiver operating characteristic curve (ROCC), AUC of the precision-recall curve (PRC), F1-score, and Cramer's V. In the ablation study, our new approach surpassed its competitors concerning Youden index, DOR, AUC of the ROCC, and AUC of the PRC. Ultrasound scans show high validity and clinical value in detecting fetal anal atresia. Our new ultrasound features significantly promote the detection of fetal anal atresia.

Improving Delphi Process in Acupuncture Decision Making: Overall Descriptions and Quality Assessment of Delphi Reports

Background

Clinical acupuncture decisions are highly operator-dependent and require physician-patient interactions. The Delphi method allows subjective factors such as expert experience and preference of patients to be taken into account in clinical decision making, which is particularly applicable to acupuncture. Currently, the Delphi method is widely used to support clinical decisions in acupuncture. Therefore, it is necessary to provide high-quality and complete descriptions of the Delphi process when making clinical decisions. This study aims to evaluate the quality of the Delphi process in acupuncture, facilitate its standardization and rigor for further clinical decision making in acupuncture.

Methods

Articles sourced from six databases were searched systematically to assess the quality of the Delphi consensus process based on the standards for conducting and reporting Delphi studies (CREDES). Descriptive statistics and analysis were presented according to the percentage of each item. Five-score Likert scale was used to evaluate the reporting quality of four domains as well as each item in CREDES by two independent researchers, combined with ICC-value to assess the consistency.

Results

A total of 37 qualified articles were included according to eligibility criteria. As for the low reporting rate, the item "External validation" was reported as the lowest positive rate at 32.43% and the item "Prevention of bias" was 48.65%. The item "Adequacy of conclusions", "Definition and attainment of consensus", and "Discussion of limitations" were reported at a positive ratio of 62.16%, 64.86%, and 67.57% individually. The average scores of the four domains based on CREDES from highest to lowest were, respectively, as follows: planning and design (68.75%), reporting (66.07%), rationale for the choice of the Delphi technique (65.54%), study conduct (45.10%).

Conclusion

The reporting quality of the Delphi consensus process in acupuncture is acceptable currently, but the reporting rate on some items is still low. Further standardization, including either clearer checklists or study reports, should be developed and strengthened to guide clinical decisions in acupuncture.

High-level feature-guided attention optimized neural network for neonatal lateral ventricular dilatation prediction

BACKGROUND

Periventricular-intraventricular hemorrhage can lead to posthemorrhagic ventricular dilatation or even posthemorrhagic hydrocephalus if not detected promptly. Sequential cranial ultrasound scans are typically used for their diagnoses. Nonetheless, manual image audit has numerous disadvantages.

PURPOSE

This study aimed to develop a predictive model utilizing modified inception (MI) and high-level feature-guided attention (HFA) modules for predicting neonatal lateral ventricular dilation via ultrasound images.

METHODS

The MI modules reduced input data sizes and dimensions, while the HFA modules effectively delved into semantic information through supervision from high-level feature images to low-level feature images. The process facilitated the accurate identification of dilated lateral ventricles. A total of 710 neonates, corresponding to 1420 lateral ventricles, were recruited in this study. Each lateral ventricle was captured in two images, one on the parasagittal plane and the other on the coronal plane. The combination of anterior horn width, ventricular index, thalamo-occipital distance, and ventricular height served as the gold standard. A lateral ventricle would be considered dilatated if any of these four indices exceeded its upper reference value. These lateral ventricles were randomly split into training and testing sets at a 7:3 ratio. We evaluated the validity of our proposed approach and its competitors across the coronal plane, parasagittal plane, and overall performance. We also determined the impact of subjects' baseline characteristics on the overall performance of the proposed approach. Additionally, ablation analyses were conducted to ensure the efficacy of the proposed approach.

RESULTS

Our proposed approach achieved the largest Youden index (0.65, 95% CI: 0.58-0.72), DOR (27.11, 95% CI: 15.89-46.26), area under curves (AUC) of receiver operating characteristic curve (ROC) (0.84, 95% CI: 0.80-0.88), and AUC of precision-recall curve (PRC) (0.81, 95% CI: 0.74-0.86) in the overall performance assessment and ablation analyses. Moreover, it boasted the biggest Cramer's V values on the coronal (Cramer's V = 0.488, p < 0.001) and parasagittal (Cramer's V = 0.713, p < 0.001) planes individually. Factors such as left side, male sex, singleton birth, and vaginal delivery were positively correlated with higher performance regarding the proposed algorithm, except for the gestational age.

CONCLUSION

This work provides a novel attention optimized algorithm for rapid and accurate ventricular dilatation predictions. It surpasses the traditional algorithms in terms of validity whether concerning the coronal plane, parasagittal plane, or overall performance. The overall performance of algorithms will be influenced by the baseline characteristics of populations.

New reference nomograms for the study of ventricular size in preterm infants

INTRODUCTION

Transfontanellar brain ultrasound is an essential tool for monitoring the size of the ventricles in preterm neonates and has many advantages over other alternative diagnostic techniques, including its accessibility and non-use of ionizing radiation. When considering the normal ventricular size, it is essential to have reference measurements based on age-matched populations. The objective of this article is to present our reference measures, based on a sample of preterm infants that we have studied.

METHODS

A retrospective observational study was conducted. Measurements of the Levene index, frontal horn thickness, and Evans index were obtained in preterm neonates from 25 to 45 weeks, over a period of 5 years, between January 2016 and December 2020. After applying the exclusion criteria, a sample of 199 patients and 350 ultrasound scans were obtained. The independent samples t-test and the Mann-Whitney test were used for the comparison of samples.

RESULTS

The distribution of the right and left Levene indices was normal (Shapiro-Wilk test with p = 0.16 and 0.05, respectively), unlike the thickness distribution of the frontal horns (p < 0.05 on both sides). No significant differences were detected between the sexes (p = 0.08). A linear correlation was found between the biparietal diameter and the Levene index.

CONCLUSION

From the results obtained in our study, we present reference tables for ventricular size, with the 3rd, 25th, 50th, 75th, and 97th, being the first ones made in our country.

Automatic measurement of fetal anterior neck lower jaw angle in nuchal translucency scans

This study aims at suggesting an end-to-end algorithm based on a U-net-optimized generative adversarial network to predict anterior neck lower jaw angles (ANLJA), which are employed to define fetal head posture (FHP) during nuchal translucency (NT) measurement. We prospectively collected 720 FHP images (half hyperextension and half normal posture) and regarded manual measurement as the gold standard. Seventy percent of the FHP images (half hyperextension and half normal posture) were used to fit models, and the rest to evaluate them in the hyperextension group, normal posture group (NPG), and total group. The root mean square error, explained variation, and mean absolute percentage error (MAPE) were utilized for the validity assessment; the two-sample t test, Mann-Whitney U test, Wilcoxon signed-rank test, Bland-Altman plot, and intraclass correlation coefficient (ICC) for the reliability evaluation. Our suggested algorithm outperformed all the competitors in all groups and indices regarding validity, except for the MAPE, where the Inception-v3 surpassed ours in the NPG. The two-sample t test and Mann-Whitney U test indicated no significant difference between the suggested method and the gold standard in group-level comparison. The Wilcoxon signed-rank test revealed significant differences between our new approach and the gold standard in personal-level comparison. All points in Bland-Altman plots fell between the upper and lower limits of agreement. The inter-ICCs of ultrasonographers, our proposed algorithm, and its opponents were graded good reliability, good or moderate reliability, and moderate or poor reliability, respectively. Our proposed approach surpasses the competition and is as reliable as manual measurement.