Cerebral blood flow dynamics during cardiac surgery in infants | Pediatric Research – Nature.com

Patient selection

The study was conducted at the Department of Pediatric Cardiology, Oslo University Hospital (OUS), Oslo, Norway, in collaboration with the ultrasound group at the Department of Circulation and Medical Imaging, The Norwegian University of Science and Technology (NTNU), Trondheim, Norway. The study was approved by the Regional Committee for Medical and Health Research Ethics, REC Central (Reference 2017/314), the Norwegian directorate of Health and The Norwegian Medicines Agency (Reference 19/05458). Written informed consent was obtained from the parents of the participants.

Patients were recruited at OUS from October 2019 to April 2021 (with a recruitment pause in 2020 due to the global pandemic). Neonates and infants under one year of age who were scheduled for cardiac surgery with CPB were eligible for inclusion. We received consent from the parents of 16 children.

Patients who underwent cardiac surgery were monitored with NeoDoppler. Cerebral Doppler monitoring was initiated after intubation and continued until the end of the surgery, before transfer to the thoracic intensive care unit. A customized soft hat with a probe attachment mechanism was used to attach the probe over the anterior fontanelle, as described previously.18 The first author was present during the entire surgery in all patients and periodically checked the Doppler signal in order to ensure that the signal was adequate. The cerebral Doppler monitor display was otherwise blinded for the clinical personnel. Doppler data were recorded in intervals with 15-30min recordings with up to one-minute pauses to allow for data storage and to adhere to the ALARA principle (as low as reasonably achievable). The perioperative care was provided according to the institutional standards, the anesthesiologists and surgeons discretion.

NeoDoppler is a non-invasive ultrasound Doppler system developed by the ultrasound group at NTNU, Trondheim, Norway. The prototype system used in this study consists of a scanner (Manus EIM-A, Aurotech Ultrsaound AS, Tydal, Norway), a small ultrasound probe (Imasonic SAS, France), operating at 7.8MHz with plane wave transmissions covering a cylindrical shape with a diameter of 10mm and depth down to 38mm (Supplementary Table1).16 The system is connected to a PC with an in-house MATLAB (The MathWorks, Natick, MA) application and displays real-time high-frame-rate color M-mode Doppler and Doppler spectrogram simultaneously (Supplementary Video1). Analog invasive blood pressure was sampled from the monitoring equipment (Nihon Kohden, Tokyo, Japan) synchronized, calibrated and stored with the Doppler data. NIRS data, rScO2, was sampled from INVOS 5100c and the neonatal OxyAlert NIRSensor (Medtronic, MA) in approximately seven seconds intervals. Additional data (SpO2, FiO2, EtCO2, temperature, blood gasses, medications, CPB data) from the electronic patient chart (Metavision, iMDsoft, Tel Aviv, Israel) were retrospectively collected in one-minute intervals. In addition, the first author manually registered events in a time stamped document during the surgery.

The inhouse MATLAB application was used for post processing and detailed analysis of the Doppler recordings. It allows for adjustment of sample volume size and depth, gain, vertical scale, horizontal sweep through a menu system. Automatic Doppler tracings with calculation of peak systolic velocity, end diastolic velocity, time averaged maximum velocity (TAV) and resistive index (RI = (Peak systolic velocityend diastolic velocity)/peak systolic velocity) are generated based on the tracings. The Doppler signal was optimized in post processing. The sample volume was set to five mm, the depth selected for the Doppler tracings was kept constant through the entire surgical procedure for all individual patients and the gain was adjusted to allow for optimal Doppler tracing. A trend window was then generated to allow examination for the entire surgical period. The trend window displayed CBFV tracings and indices, invasive blood pressure, SpO2, FiO2, NIRS, body temperature, EtCO2, end tidal sevoflurane, end tidal isoflurane and heart rate. Blood gasses with partial pressure of carbon dioxide and hematocrit were also collected.

A quality metric (0100%) was calculated for each heartbeat, based on the correlation between consecutive heartbeats. Only quality >80% was considered as valid/high quality data. During CPB, valid data was instead defined as signal to noise ratio > six dB, since waveform correlation cannot be measured accurately during continuous non pulsatile flow. Valid fraction was defined as the time with valid data in percent of the total recording time.

Manual visual inspection and evaluation of all Doppler recordings was performed by the first author. Artifacts and signal interference were evaluated visually. Trend windows displaying the full monitoring period, as shown in the result section (Fig.2), were generated for all patients, and were visually evaluated by the first and last author. The monitoring data was divided in six time periods (Figs.1, 2).

The figure illustrates the research setup with the NeoDoppler probe monitoring cerebral blood flow velocities through the open fontanelle during cardiac surgery with cardiopulmonary bypass. Near-infrared spectroscopy, electrocardiogram, pulse oximetry and invasive blood pressure are also monitored. The six surgical periods were defined as S1: a baseline period before start of surgery; S2: start of surgery before cardiopulmonary bypass (CPB); S3: from start of CPB, during cooling; S4: during CPB at minimal temperature; S5: during CPB while rewarming; S6: after CPB before transfer to thoracic intensive care. CPB cardiopulmonary bypass, ET CO2 end-tidal carbon dioxide, rSO2 regional oxygen saturation, SpO2 pulse oximetry oxygen saturation.

An entire surgical period for one patient with cerebral blood flow velocity (CBFV) time averaged velocity, blood pressure (BP) mean arterial pressure, mean flow index (Mxa) with a cut off above 0.3, resistive index (RI), near-infrared spectroscopy (NIRS), oxygen saturation (SpO2) and temperature measurements illustrated. RI cannot be calculated during CPB due to the non-pulsatile flow. S1 to S6 illustrates the different periods of surgery; S1: a baseline period before start of surgery; S2: start of surgery before cardiopulmonary bypass (CPB); S3: from start of CPB, during cooling; S4: during CPB at minimal temperature; S5: during CPB while rewarming; S6: after CPB before transfer to thoracic intensive care. At the bottom of the figure, Doppler spectrograms show pre-CPB, CPB, and post-CPB flow patterns. BP blood pressure, CBFV cerebral blood flow velocity, CPB cardiopulmonary bypass, MAP mean arterial pressure, Mxa mean flow index, NIRS near-infrared spectroscopy, RI resistive index, SpO2 pulse oximetry oxygen saturation, TAV time averaged velocity, Temp temperature.

The mean flow index (Mxa) was used to evaluate dynamic autoregulation. Mxa was calculated with a custom-made Matlab script as the moving Pearson correlation coefficient between the BP and CBFV with 10s averages calculated over 300s for all patients, then plots were created (Fig.3). Periods with selective cerebral circulation or deep hypothermic circulatory arrest were excluded from these analyses. Mxa ranges from minus one to one, where higher values indicate impaired autoregulation. The exact threshold of Mxa to indicate impaired autoregulation varies in studies with 0.3 most used but higher values are also reported.19,20 We therefore calculated percentage of time with Mxa >0.3 and >0.45 for the entire surgical course for all patients.

The figure illustrates the mean flow index (Mxa) for the patients with the lowest and highest percentage of time with Mxa >0.3/0.45. Panel a shows a 2.8-month-old patient with complete atrioventricular defect who had 56.9%/45.0% of the time with Mxa >0.3/0.45. Panel b shows a 3.8-month-old patient with ventricular septal defect who had 84.5%/79% of the time with Mxa >0.3/0.45. A selected period (marked with a square) of CBFV and corresponding BP measurements with high Mxa is displayed. BP blood pressure, CBFV cerebral blood flow velocity, Mxa mean flow index.

Percentage of time with NIRS<63% was calculated to describe time with cerebral hypoxia and percentage of time with mean arterial BP<-2SD for age to describe time with hypotension.21,22

Common trends in the whole patient group were analyzed. The data for each patient were grouped in six different surgical periods (Fig.1).

Major cerebrovascular events were described based on visual impressions of the trend curves and Doppler tracings.

Statistical analysis was performed using IBM SPSS Statistics for Windows version 28 (IBM, Armonk, NY). Categorical variables are presented as count (percent). Continuous variables are presented as meanstandard deviation for normally distributed data. The normality assumption was assessed by visual inspection of Q-Q plots. Statistical differences between surgical periods compared to baseline were tested with paired Students t test; a p value<0.05 was considered statistically significant.

The safety of this cerebral Doppler monitoring system has previously been elaborated.16,17 The temperature increase is highest at the skin surface; due to the unfocused beam, the temperature diminishes with increasing depth. Thermal and mechanical indices were continuously displayed on the display unit. The skin where the probe was attached was inspected after removal to assess for local adverse effects.

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Cerebral blood flow dynamics during cardiac surgery in infants | Pediatric Research - Nature.com