Objective: Post-operative brain injury in neonates may result from disturbed cerebral perfusion, but accurate peri-operative monitoring is lacking. High-frame-rate (HFR) cerebral ultrasound could visualize and quantify flow in all detectable vessels using spectral Doppler; however, automated quantification in small vessels is challenging because of low signal amplitude. We have developed an automatic envelope detection algorithm for HFR pulsed wave spectral Doppler signals, enabling neonatal brain quantitative parameter maps during and after surgery. Methods: HFR ultrasound data from high-risk neonatal surgeries were recorded with a custom HFR mode (frame rate = 1000 Hz) on a Zonare ZS3 system. A pulsed wave Doppler spectrogram was calculated for each pixel containing blood flow in the image, and spectral peak velocity was tracked using a max-likelihood estimation algorithm of signal and noise regions in the spectrogram, where the most likely cross-over point marks the blood flow velocity. The resulting peak systolic velocity (PSV), end-diastolic velocity (EDV) and resistivity index (RI) were compared with other detection schemes, manual tracking and RIs from regular pulsed wave Doppler measurements in 10 neonates. Results: Envelope detection was successful in both high- and low-quality arterial and venous flow spectrograms. Our technique had the lowest root mean square error for EDV, PSV and RI (0.46 cm/s, 0.53 cm/s and 0.15, respectively) when compared with manual tracking. There was good agreement between the clinical pulsed wave Doppler RI and HFR measurement with a mean difference of 0.07. Conclusion: The max-likelihood algorithm is a promising approach to accurate, automated cerebral blood flow monitoring with HFR imaging in neonates.

Background: Arterial pressure measurements are important to monitor vital function in neonates, and values are known to be dependent of gestational and postnatal age. Current reference ranges for mean arterial pressure in neonates have been derived from small samples and combined data of noninvasive and invasive measurements. We aimed to define reference values for noninvasive mean, systolic, and diastolic blood pressure during the first week of life in otherwise healthy preterm and term neonates defined by gestational and postnatal age. Methods: In this retrospective cohort study in a neonatal intensive care unit (NICU) in a Dutch tertiary paediatric hospital, we included the noninvasive blood pressures of neonates admitted between 2016 and 2018, with exclusion of those with severe comorbidities (major cardiac malformations, intracerebral haemorrhage, and tracheal intubation >6 h). We defined the median (P50) with −2 standard deviations (SD) (P0.23), −1 SD (P16), +1 SD (P84), and +2 SD (P97.7) for gestational age and postnatal age using quantile regression, percentiles provided online (http://bloodpressure-neonate.com/). Results: A total of 607 neonates, with 5885 measurements, fulfilled the inclusion criteria. The P50 values of mean noninvasive arterial blood pressure in extreme preterm infants steeply increased during the first day after birth and gradually increased within a week from 27 to 49 mm Hg at 24 h of gestational age, and from 49 to 61 mm Hg at 41 weeks of gestational age. Conclusions: These reference values for noninvasive blood pressure in neonates in the NICU for various gestational age groups provide guidance for clinical decision-making in healthy and diseased neonates during anaesthesia and sedation.