A realistic flow phantom model of the carotid artery in preterm infants for training and research

Abstract

Introduction

Cerebral blood flow is increasingly monitored in preterm infants. Doppler ultrasound of the carotid artery is a widely available method but is operator dependent. Our aim was to design and produce a realistic flow phantom model of the carotid artery of preterm infants.

Methods

Data from cerebral blood flow measurements using Doppler ultrasound of the right common carotid artery from 21 premature newborn infants were used to produce a Doppler flow phantom model with three different vessel diameters. Vessel diameter, continuous and pulsatile flow volume measurements were performed by two blinded observers (with more than eight and 20 years of experience).

Results

Vessel diameter measurements using the phantom were underestimated by 7%. Continuous flow volume measurements were overestimated by 7% by both observers (observer 1 mean difference 1.5 ± 1.96 SD −3.3 to 6.3 ml/min versus observer 2, 1.9 ± 1.96 SD −3.6 to 7.4 ml/min). Pulsatile flow measurements were overestimated by 12.6% by observer 1 (2.7 ± 1.96 SD −0.6 to 5.9 ml/min) and by 7.8% by observer 2 (1.7 ± 1.96 SD −1.6 to 4.9 ml/min). There was good interobserver and intraobserver reliability for the majority of measurements using continuous and pulsatile flow.

Conclusion

It is feasible to produce a realistic flow phantom model of the neonatal carotid artery of preterm infants. Diameter measurements were underestimated and flow measurements were overestimated. These errors fell within acceptable limits for in vivo measurements. If these limitations were related to materials, this could be explored using a wall-less model. The flow phantom could be utilised for research and training clinicians in measuring cerebral blood flow using the carotid artery in this vulnerable group of infants.

Introduction

Despite advances in care given to preterm infants over the years, significant neurodisability is still found in those surviving the neonatal period.¹ Clinicians are increasingly reliant on real time monitoring of organ function to improve clinical care and thus long-term outcomes in preterm infants.² One parameter that is increasingly being monitored is cerebral blood flow (CBF)³ as low cerebral blood flow is associated with adverse neurodevelopmental outcomes.^4,5

CBF can be measured directly or using surrogate markers such as superior vena caval flow⁵ and cerebral tissue oxygen delivery.⁶ These methods are not without limitations.⁷ Several methods exist to measure CBF in clinical practice. Doppler ultrasound is a non-invasive method that has been used to measure CBF,³ cardiac output,⁸ renal blood flow⁹ and gut blood flow.¹⁰ The measurement of CBF using Doppler ultrasound has produced results comparable with invasive methods with reliable performance such as Xe clearance method³ used in adults and preterm infants.^11,12

Doppler ultrasound imaging using newer generation scanners has resulted in improved quality of images,¹³ and alternative transducer designs facilitate flow measurement from vessels which run close and parallel to the skin surface. Though this method is widely available, clinicians using Doppler ultrasound require a period of training before it can be safely and reliably used to measure CBF in preterm infants, and clinicians are understandably wary of performing flow measurements on small diameter vessels with large angles of insonation. A micro vessel flow phantom model exists to investigate the intracerebral circulation in preterm infants.¹⁴ To our knowledge, there are no flow phantom models of the carotid artery of preterm infants. Our aim was to design and produce a realistic flow phantom model of the carotid artery of preterm infants that can subsequently be used for training clinicians and for research purposes.

Methods

The phantom was designed and produced in the clinical physics department of the hospital.

Data collection for designing flow phantom

In order to determine the physical characteristics of the right common carotid artery (RCCA) in preterm infants, data for designing the flow phantom (see below) were collected from 21 infants who were admitted to the tertiary level neonatal intensive care unit with 600 annual admissions. As part of standard routine care, CBF measurements were also performed in some infants as part of haemodynamic assessment when functional echocardiography and cranial ultrasound scans were performed. Some of the scans (n = 12) were obtained from infants who were recruited to a blood pressure study that had ethics committee approval.

Data used for designing flow phantom

From images obtained with a transducer placed over the anterior triangle of the neck, the following data were collected about the physical characteristics of the RCCA (Figure 1(a) and (c)):

Figure 1.

(a, c) Ultrasound of the RCCA in a preterm human infant, where Tp is the proximal depth of the vessel from the skin surface, Td is the distal depth from the skin surface and L is the distance between Tp and Td. (b) Doppler ultrasound of flow measurements where the red dot illustrates the peak systolic velocity of the peak velocity envelope (PSV_PVE), red line illustrates the TAPV, green dot illustrates the peak systolic velocity of the intensity weighted mean (PSV_IWM) and green line illustrates the intensity weighted mean (IWM).

d – cross-sectional diameter of the blood vessel (mm)

Tp – proximal depth of the blood vessel from skin surface (mm)

Td – distal depth of the blood vessel from skin surface (mm)

L – distance between Tp and Td measuring points

Φ – angle formed between blood vessel and skin surface, calculated using the following formula

$$\Phi ={\text{tan}}^{-\text{1}}\left(\text{Td}-\text{Tp}\right)/\text{L}$$

The various velocity measurements obtained (Figure 1(b)) include:

PSV_PVE – Peak systolic velocity of the peak velocity envelope (cm/s)

PSV_IWM – Peak systolic velocity of the intensity weighted mean (cm/s)

TAPV – Time averaged peak velocity (cm/s)

IWMV – Intensity weighted mean velocity (cm/s)

Only the PSV_IWMV and IWMV readings were used for calculating flow. The PSV_IWMV was used to calculate peak systolic flow (Q_max) and IWMV was used to calculate mean flow (Q)

$$\begin{array}{c}{\text{Q}}_{\text{max}}={\text{PSV}}_{\text{IWMV}}\times \left(\pi {\text{d}}^{\text{2}}/\text{4}\right)\text{in}\text{ml}/\text{min}\\ \text{Q}=\text{IWMV}\times \left(\pi {\text{d}}^{\text{2}}/\text{4}\right)\text{in}\text{ml}/\text{min}\end{array}$$

Production of the flow phantom

Three 3-chamber models as shown in Figure 2, with each chamber having a different Φ and d, were created using agar and glycerol based tissue mimicking material¹⁵ (TMM) which was encased in a Perspex casing. The tubing (Adtech Polymer Engineering Ltd, Glos., UK) had a wall thickness of 0.31 mm and was made from polytetrafluoroethylene (PTFE). PTFE was preferred over silicone as it was more likely to maintain its circular shape in the TMM and has density close to that of biological tissues.¹⁶ The various phantom vessel internal diameters used were 1.58, 1.96 and 2.44 mm at a Φ of 10°, 15° and 20°. The phantom vessel was embedded in the TMM at a depth of 10 mm from the phantom surface to the upper point of the tubing (supplementary Figure 1).

Figure 2.

(a, b) The three-chamber flow phantom model once fully setup along with a schematic representation of the model. Arrows in the schema show the direction of flow of BMM. (c) Profile view and (d) top view of the three-chamber phantom. AD: bridge circuit and analogue to digital converter; BMM: blood mimicking material; TMM: tissue mimicking material.

The flow phantom was set up in the neonatal unit where the ultrasound scanner was housed. Blood mimicking material (Model 707, ATS Laboratories, Norfolk, VA USA) with a density of 1004 ± 10 kg/m³ was run through the model. The flow was adjusted by varying the height of the reservoir containing the blood mimicking fluid or by adjusting the outflow valve attached to the end of the line. This produced continuous flow through the circuit. Pulsatile flow, simulating physiological flow, was achieved by incorporating a peristaltic pump (Watson Marlow, model MHRE 72) into the circuit. The pump was run at speeds that produced a pulsatile flow of 120–150 pulses per minute in keeping with the physiological heart rates in premature infants.

The clinical physics data were used wherein the measurement of the flow was achieved by independently measuring the accumulation of the mass of the blood mimicking fluid as follows. The fluid was collected in a container placed on a sensitive load cell (Compression Load Cell, model 1004, Tedea Huntleigh) that acted to dynamically measure the accumulative mass of the blood mimicking fluid. The load cell output was measured as one arm of a classical resistance bridge circuit set within a full bridge module (National Instruments NI 9237). The module was connected via a USB link to a monitoring laptop that was running data acquisition and visualisation software LabVIEW real-time software (v. 14.0.1, National Instruments, Newbury, UK).

Flow phantom measurements

All diameter and flow measurements were performed with a 7–15 MHz ‘hockey-stick’ linear array transducer using the Philips iE33 ultrasound system (Bothwell, USA). Flow phantom measurements were performed by two observers: SP (observer 1, with more than eight years of experience) and SK (observer 2, with more than 20 years of experience) who were blinded to each other’s measurements and to the characteristics of the chamber (vessel diameter and Φ). As the internal and external walls of the tubing gave a brighter echogenic signal than that normally obtained from human tissues, the scanner gain settings were adjusted to ensure that the echogenic signals were dampened to visualise the lumen of the vessel. A bright echogenic focus was seen at the internal and external sides of the wall of the tubing.

Diameter, d, was measured from the brightest focus to brightest focus on the internal sides of the walls of the vessel for all measurements (Figure 3(a)). The scanner wall filter was set to minimum to ensure that low flow velocities were visualised and processed. The velocity measurements were automatically calculated from the waveforms by the ultrasound scanner.

Figure 3.

(a) Cross-sectional view of the vessel phantom, (b) with continuous flow and (c) pulsatile flow pattern.

Continuous and pulsatile flow measurements were performed at varying velocities and speeds based on the typical neonate clinical flow ranges (Figure 3(b) and (c)). The vessel diameter, intensity weighted mean and angle of insonation performed by each observer were recorded for each measurement.

Statistical analysis

Data were summarised using mean (standard deviation) for normally distributed data and median (interquartile range) for non-normal data. The correlation between the two observers was examined and validity of measurements was examined using Bland–Altman plot.¹⁷ Reliability between two observers was checked using intraclass correlation (ICC) using two-way mixed ANOVA with observers being fixed factors and measurements being random factors. The coefficient of variation ((SD/Mean)×100) was also calculated as an additional measure of agreement and results expressed as percentage. The grading of strength of correlation was assessed using previously described methods.¹⁸ All statistical analyses were performed using IBM SPSS v22 (Chicago, IL, USA).

Results

Characteristics of human neonatal RCCA used to design phantom

Measurements of RCCA diameter and depth were collected from 21 neonatal patients, with median (interquartile range) corrected gestational age 31.2 (26.6–33.9) weeks and current body weight 1.03 (0.77–2.0) kg.

The median (range) diameter of the RCCA was 2.07 (1.35–2.98) mm; this was significantly related to gestation (Spearman’s rho 0.777, p < 0.001). Median angle of the vessel to the skin was 19 (0–31) degrees, with the distal section of the vessel deeper than the proximal section. Median blood flow was 19.2 (range 5.3–69.3) ml/min.

Continuous flow measurements taken from phantom

The mean (SD) vessel diameters of the 18 measurements for observer 1 and observer 2 were 1.83 (0.32) mm and 1.85 (0.32) mm, respectively. Overall, vessel diameters were underestimated, with the Bland–Altman plot (Figure 4(a) and (b)) for both observers showing that the absolute error was greater for larger diameters. The mean (SD) proportional difference for observer 1 was −7.66 (1.5)% and for observer 2 was −7.26 (1.2)%.

Figure 4.

Bland–Altman plot for various vessel diameter measurements by (a) observer 1 (SP) and (b) observer 2 (SK), continuous flow measurements for (c) observer 1 and (d) observer 2, and pulsatile flow measurements for (e) observer 1 and (f) observer 2. Solid lines represent mean with 1.96 SD whereas upper and lower dashed lines represent upper and lower 95% confidence intervals, respectively.

The mean (SD) for flow measurements for observer 1 and observer 2 were 25.2 (14.1) ml/min and 26.1 (14.4) ml/min, respectively. Overall, flow measurements were overestimated, with the Bland–Altman plot (Figure 4(c) and (d)) for both observers showing that the absolute error was greater for higher flow volumes. The mean (SD) proportional difference in flow for observer 1 was 7.14 (11.5)% and for observer 2 was 7.64 (11.0)%.

The clinical physics data produced flow rates of 6.9–45.6 ml/min for continuous flow measurements.

Pulsatile flow measurements taken from phantom

The mean (SD) vessel diameter for observer 1 was 1.85 (0.32) mm and that for observer 2 was 1.85 (0.32) mm. As in continuous flow measurements, the absolute error was greater for larger diameters. The mean (SD) proportional difference for observer 1 was −6.92 (2.4)% and for observer 2 was −6.92 (2.0)%.

The mean (SD) flow volumes for observer 1 were 24.2 (2.5) ml/min and that for observer 2 were 23.1 (2.4) ml/min. The flow measurements were overestimated by both observers. The Bland–Altman plot (Figure 4(e) and (f)) for observer 1 shows that for lower volumes, the mean difference was lower compared to that for higher flow volumes. The mean (SD) proportional difference in flow for observer 1 was 12.6 (7.7)% and for observer 2 was 7.8 (7.6)%.

The clinical physics data produced flow rates of 17.7–24.0 ml/min for pulsatile flow measurements.

The relationship between the angle of insonation and difference in flow measurements showed that for smaller angles of insonation, the difference in flow was smaller when compared to for larger angles of insonation (Figure 5).

Figure 5.

Scatter plot illustrating the relationship between proportional difference in flow and the angle of insonation.

Interobserver reliability

Interobserver reliability (Table 1) using ICC (3,1)^18,19 was ‘almost perfect’²⁰ for all measurements except pulsatile flow volume measurements where it was ‘moderate’.

Table 1.

Interobserver reliability for continuous and pulsatile flow measurements.

Type of flow	Parameter	Observer 1 (SP)Mean (SD)	Observer 2 (SK)Mean (SD)	Interobserver reliability ICC(95% CI)
Continuous (n = 18)	Vessel diameter (mm)	1.83 (0.32)	1.85 (0.3)	0.99 (0.99–1.00)
	IWMV (cm/s)	15.5 (7.5)	15.8 (7.4)	0.98 (0.96–0.99)
	Angle of insonation (degrees)	43.7 (4.8)	42.2 (4.8)	0.84 (0.56–0.94)
	Calculated flow (ml/min)	25.2 (14.1)	26.1 (14.4)	0.98 (0.96–0.99)
Pulsatile (n = 24)	Vessel diameter (mm)	1.85 (0.3)	1.85 (0.3)	0.99 (0.99–1.00)
	IWMV (cm/s)	16.3 (6.2)	15.7 (6.2)	0.98 (0.94–0.99)
	Angle of insonation (degrees)	43.3 (3.9)	43.9 (4.7)	0.82 (0.64–0.92)
	Calculated flow (ml/min)	24.2 (2.5)	23.1 (2.3)	0.57 (0.22–0.79)

ICC: intra class correlation; IWMV: intensity weighted mean velocity.

The mean interobserver coefficient of variation for vessel diameter measurements was 1.5%.

Intraobserver reliability

Intraobserver reliability was performed for parameters measured in the continuous and pulsatile flow groups. Paired measurements of the vessel diameter, IWMV, angle of insonation and pulsatile flow volume measurements from both observers were compared.

Intraobserver reliability (Table 2) using ICC (3,1)^18,19 was ‘almost perfect’ for both continuous and pulsatile flow parameters. For pulsatile flow, observer 1 had ‘moderate’ intraobserver reliability whereas observer 2 had ‘substantial’ intraobserver reliability.

Table 2.

Intraobserver reliability for continuous and pulsatile flow measurements.

Type of flow	Parameter	Observer 1 (SP) Mean (SD)		Observer	Observer 2 (SK) Mean (SD)		Observer
		Measurement (a)	Measurement (b)	1 Intraobserver reliability (95% CI)	Measurement (a)	Measurement (b)	2 Intraobserver reliability (95% CI)
Continuous (n = 9)	Vessel diameter (mm)	1.83 (0.3)	1.84 (0.3)	0.99 (0.99–1.00)	1.85 (0.3)	1.84 (0.3)	0.99 (0.99–1.00)
	Angle of insonation (θ)	43.6 (4.5)	43.8 (5.3)	0.83 (0.56–0.97)	42.7 (5)	41.8 (4.9)	0.91 (0.68–0.98)
Pulsatile (n = 12)	Vessel diameter (mm)	1.86 (0.3)	1.85 (0.3)	0.99 (0.99–1.00)	1.85 (0.3)	1.86 (0.3)	0.99 (0.99–1.00)
	IWMV (cm/s)	16.2 (6)	16.5 (6.6)	0.97 (0.91–0.99)	15.4 (6.0)	16.0 (6.7)	0.98 (0.93–0.99)
	Angle of insonation (θ)	43.0 (3.6)	43.4 (4.5)	0.71 (0.27–0.91)	43.7 (4.7)	44.2 (4.9)	0.82 (0.49–0.94)
	Calculated flow (ml/min)	24.3 (2.4)	24.1 (2.8)	0.48 (−0.13 to 0.82)	22.7 (2.2)	23.5 (2.5)	0.75 (0.36–0.92)

IWMV: intensity weighted mean velocity.

In the continuous flow group, the intraobserver coefficient of variation for vessel diameter measurements for observer 1 (SP) was 1.5% and that of observer 2 (SK) was 1.1%.

As for pulsatile flow group, the intraobserver coefficient of variation for vessel diameter measurements within observers for observer 1 (SP) was 0.9% and that of observer 2 (SK) was 1.0%. The intraobserver coefficient of variation for pulsatile flow measurements for observer 1 (SP) was 10.5% and that of observer 2 (SK) was 10%.

Test–retest reliability

Vessel diameter measurements measured on two separate occasions by both observers were examined. The vessel diameter measurements obtained from work done, a few months apart, using continuous and pulsatile flow were analysed. As the flow between the two experiments varied, the IWMV and the angle of insonation were not considered for test–retest reliability work. Two measurements from all the nine chambers within three phantoms that were taken by both observers were examined to ensure equal measurement numbers for each observer.

The mean (SD) difference in vessel diameter measurements for observer 1 was −0.02 (0.05) mm and that for observer 2 was −0.01 (0.04) mm. The vessel diameter measurements from both observers were compared and a Bland–Altman plot was used to assess the mean difference along with the limits of agreement for both observers.

Test–retest reliability for both the observers was ‘almost perfect’ with a reliability of 0.989 and 0.994 for observer 1 and observer 2, respectively.

Discussion

We have designed and constructed a flow phantom model of the common carotid artery, a first of its kind to our knowledge, that produces both continuous and pulsatile flow mimicking the physiological flow patterns seen in preterm infants. The phantom had vessel diameters, depths, angle of insonation and flow rates comparable with real preterm infants, with the main observable difference being brighter reflections from the internal and external vessel walls on ultrasound imaging.

There was very good interobserver and intraobserver reliability for the majority of measurements using continuous and pulsatile flow. The measurements used to calculate the flow volume demonstrated very good intraobserver reliability for both observers. Test–retest measurements showed that these were valid with very good reliability.

The interobserver coefficient of variation for vessel diameter measurement was 1.5%, which was lower than the 3.9% reported by Sinha et al.³ who used Doppler ultrasound to measure carotid blood flow in more mature infants. This difference could be attributed to the difference in vessel wall thickness and material used. The intraobserver coefficient of variation for vessel diameter measurements for observer 1 was 1.5% and for observer 2 was 1.1%. The intraobserver coefficient of variation for pulsatile flow measurements for observer 1 was 10.5% and that for observer 2 was 10.1%. These values were comparable to 10.5 and 15.4% for the two observers reported by Sinha et al.³ The intraobserver coefficient of variation for pulsatile flow vessel diameter measurements for observer 1 was 0.9% and that for observer 2 was 1.0%. These values were lower than the one obtained when using continuous flow, which may reflect the observers becoming more familiar with the equipment as the pulsatile flow measurements were done a few months later than the continuous flow measurements.

Validity work on the vessel diameter measurements revealed an underestimation of 7% for both continuous and pulsatile flow models. On comparing flow volume measurements, we found that this was overestimated by 7% using continuous flow when compared to pulsatile flow where it was12.8 and 7.8% for observer 1 and 2, respectively. This is well within the 30% acceptance limit which was found from a large meta-analysis of 25 studies examining bias and precision statistics when comparing cardiac output measurements using different techniques.²¹

The clinical physics method was used for recording all the fluid exiting the phantom and this allowed accurate flow rate measurements. In contrast, the ultrasound method measured the velocity, which may have been influenced by the angle of insonation, sampling gate and region even though every care was taken to accurately measure these. In addition, the velocity of fluid, which may be relatively higher in the centre when compared to the edges, could influence measurements carried out using ultrasound.

Our work examining vessel diameter measurements showed the presence of a systemic error with underestimation of the diameter by both observers. This could be an inherent error in the ultrasound method at the small diameters, but could also be explained by the material used for the vessel differing from the biological materials the ultrasound system was designed to visualise. PTFE tubing of varying diameter was used to ensure it maintained its diameter throughout the entire length of the tube whilst being embedded in the TMM. PTFE being denser than human tissue is prone to acoustic attenuation and brighter echogenic signals. Alternative tubing that would be more similar to human tissue is silicone, but this was prone to losing its circular shape in the TMM. Hence, for this model, PTFE tubing was preferable. The large hyperechoic shadow produced by PTFE on cross-sectional view could possibly be a cause for error in estimation of the precise diameter. This could be due to difficulties by the observers in estimating the exact boundary of the vessel lumen. Alternative solution to the issue of attenuation associated would be to consider wall-less phantom models.²²

Other factors examined in this study included the effect of insonation angle, with angles over 60° resulting in an underestimation of the flow volumes. Care should be taken to ensure that the smallest possible angle of insonation is achieved. This is possible by utilising the ultrasound scanner’s angle steer function and using a thick gel wedge. Lastly, the wall filter should be adjusted to the minimum level in order to capture low velocity signals. Failure to adjust the wall filter to the lowest possible value would result in low velocity flow not being measured, thus resulting in underestimation of flow volumes.

This flow phantom is a realistic in vitro model of the common carotid artery of preterm infants and which could provide useful information on fluid dynamics and help to train clinicians in measuring flow volumes involving very small caliber vessels. The model could be explored further with the use of a wall-less model where errors associated with acoustic attenuation could be eliminated thus improving accuracy in diameter measurement, but this could reduce the stability of bore diameter. The model allows operators to explore the way in which different settings, such as insonation angle and low frequency filter settings, may affect the accuracy of measurements.

Conclusion

We found that flow phantom studies produced acceptable reliability and validity measurements. Though the diameter measurements were lower than the actual measurements, this model can be improved by using wall-less phantom models. This work has shown that it is feasible to design and produce a realistic model of the carotid artery of the preterm infant that can be used for training and research purposes.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Approval

The majority of scans were done as part of standard routine care for which verbal consent was obtained. Some of the scans were from infants recruited to a blood pressure study that had received ethics committee approval from the London-Surrey Borders research ethics committee (reference 12/LO/ 1553) on 21 November 2012.

Guarantor

SP and SK.

Contributors

SP, AS, JR, MB and SK researched literature and conceived the study. SK, SP, AS and KV collected data for designing the flow phantom. SK, AS, JR, MB, KV, SFJ and RK designed the flow phantom and JR and MB built the flow phantom. SP, AS, KV, RK, SFJ and SK did the data analysis. SP wrote the first draft of the manuscript. AS, SFJ, RK, KV, JR, MB and SK wrote the final version of the manuscript. All authors reviewed and approved the final version of the manuscript.

ORCID iDs

Sujith Pereira https://orcid.org/0000-0001-7104-6872

Sakthi F James https://orcid.org/0000-0001-8641-0278

Supplemental Material

Supplemental material for this article is available online.