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Keywords:

  • accuracy;
  • fontanelle;
  • phantom;
  • rendering;
  • reproducibility;
  • validity

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

Objective

Cranial sutures and fontanelles can be reliably demonstrated using three-dimensional (3D) ultrasound with rendering. Our objective was to assess the repeatability and validity of fontanelle surface area measurement on rendered 3D images.

Methods

This was an in-vitro phantom validation study. Four holes, representing fontanelles, were cut on a flat vinyl tile. The phantom was scanned in a test-tank by two sonographers, at four different depths and using two different 3D sweep directions. The surface areas were measured on scan images and also directly from the phantom for comparison. Coefficients of variation (CVs), intraclass correlation coefficients (ICCs) and Bland–Altman plots were used for repeatability analysis. Validity was expressed as the percentage difference of the measured area from the true surface area.

Results

Validity of measurement was satisfactory with a mean percentage difference of − 5.9% (median = − 3.5%). The 95% limits of agreement were − 23.9 to 12.1%, suggesting that random error is introduced during image generation and measurement. Repeatability of caliper placement on the same image was higher (intraobserver CV = 1.6%, ICC = 0.999) than for measurement of a newly generated scan image (intraobserver CV = 5.5%, ICC = 0.992). Reduced accuracy was noted for the smallest shape tested.

Conclusion

Surface area measurements on rendered 3D ultrasound images are accurate and reproducible in vitro. Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

Fetal biometry usually relies on two-dimensional (2D) imaging planes of fetal organs, amenable to linear measurements only (length or circumference). Three-dimensional (3D) ultrasound permits the visualization of complex structures or entire organs, whereby volume or surface area measurements may be performed. One particular area of interest is assessment of the fetal skull, cranial sutures and fontanelles1–4. Most fontanelles and sutures can be reliably demonstrated using rendering techniques throughout the second half of gestation1. Visualization of fontanelles on rendered 3D images may be affected negatively by advancing gestational age and cephalic presentation, owing to increasing difficulty of scan acquisition of the entire fetal head1. A pocket of amniotic fluid between the transducer and the fetal skull often optimizes the rendered image and therefore reduced amniotic fluid volume is also likely to affect the visibility of these structures1.

Surface area measurements of the anterior fontanelle, using rendered 3D ultrasound, have been described and relevant nomograms have been published4. Potential clinical applications include screening for Down syndrome, as these fetuses have larger fontanelles5, or in the diagnosis of various craniosynostosis syndromes6, 7. Fetal fontanelle size and development may also be influenced by maternal vitamin D status8. However, the use of 3D ultrasound has not been validated for fetal biometry on rendered images.

While volume calculation using 3D ultrasound has high reproducibility and validity9, surface area measurements when using rendered images cannot be assumed to have the same accuracy. Rendered scan images are reconstructed pictures, whereby several points of ultrasound reflected from different depths are projected onto a single imaging plane, and this has the potential to lead to significant error.

In general, sources of measurement variation may include error during caliper placement and variability during generation of the scan image, for example, as the result of an incorrect plane or the effect of fetal breathing on abdominal circumference. For rendered 3D images in particular, measurement error may be the result of fetal movement artifacts during volume acquisition. There is also the possibility of true biologic variation; thus, the head diameters and fontanelle size may vary as a result of moulding and external pressure because the calvarial bones and fontanelles are compressible structures.

The aim of this study was to assess the repeatability and validity of surface area calculation on rendered 3D images, using an in-vitro phantom that simulates skull fontanelles.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

This was an in-vitro phantom validation study. A commercially available ultrasound scan machine with a mechanical 3D transducer was used (Philips HD-9 with a V7-3 transducer; Philips Ultrasound, Bothell, WA, USA). A glass test-tank containing a solution of 7% glycerol in water was the scanning medium9, 10. The phantom consisted of a flat tile made of rigid vinyl plastic (1-mm thickness) to simulate skull bone. Four holes of standard geometrical shapes were cut out on the tile to represent fontanelles (Figure 1). The shapes chosen were a regular pentagon, trapezoid, isosceles triangle and a parallelogram. The phantom was positioned horizontally into the test-tank and time was allowed for the solution to de-gas. The ultrasound transducer was then immersed 2 cm into the solution and a volume scan for every shape was obtained with a vertical angle of insonation. In order to assess whether the direction of the sweep has an effect on measurement, the 3D acquisition was repeated with the transducer rotated by 90° (Figure 1, x- and y-axes). This process was repeated with the phantom positioned at four different depths (10, 8, 6 and 4 cm) from the transducer. A second sonographer scanned the phantom independently and in a blinded manner, using the above protocol.

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Figure 1. A flat vinyl tile with four holes of perfect geometrical shapes was scanned in a test-tank by two sonographers, in four different depths and using two sweep directions: along the x-axis and then along the y-axis.

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Each scan was obtained using a varying sweep angle in order to acquire one shape per image and a default sweep speed of 5 seconds for a 65° sweep. A low gain setting was used during scanning to minimize ultrasound artifacts caused by reflection from the tank walls. The 3D image was displayed using the maximum rendering mode. Brightness and contrast were adjusted during post-processing in order to enhance the shape demarcation: image bias (contrast) was set at the maximum setting and image position (brightness) was kept at an average setting. Each rendered image was extracted in a digital format (jpeg file) and analyzed on a PC using image viewing software for measurement (Escape Medical Viewer, version 3.2.3, Escape OE, Thessaloniki, Greece). Every image was calibrated for measurement using the scale displayed on the left side of the scan image. Manual tracing of the phantom fontanelle was then performed using the polygon measuring tool (Figure 2).

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Figure 2. Appearance and measurement of the phantom on rendered three-dimensional (3D) ultrasound.

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Images were processed by two operators (C.I. and I.S.) independently of each other; the operators were blinded to each other's results and also to the true size of the fontanelles. In order to assess intraobserver and interobserver repeatability, all images were traced twice by Observer 1 and once by Observer 2. In order to assess validity, scan measurements were compared with the true surface areas; the shape dimensions (sides, base and height) were measured by both observers directly onto the phantom and the true surface areas were calculated using standard geometric equations (Table 1).

Table 1. Shapes and their true surface areas calculated using standard mathematical equations
ShapeEquationSurface area (mm2)
  1. b, base; h, height; S, surface area; t, side length.

Pentagon (regular)equation image654.2
Trapezoid½h(b1 + b2)325.5
Triangle (isosceles)½ bh95.3
ParallelogramS = bh471.9

Data were analyzed with PASW Statistics 18.0 (SPSS Inc., Chicago, IL, USA). Intraobserver and interobserver measurement repeatability were expressed as within-subject coefficients of variation (CV)11 and as intraclass correlation coefficient (ICC) with 95% CI12. Interobserver percentage differences were also plotted using the method described by Bland and Altman13. Validity was expressed as the percentage difference of the measured surface area from the true surface area. Percentage differences at different scan conditions (depth, shape, sonographer and sweep direction) were assessed for normality of distribution using Kolmogorov–Smirnov and Shapiro–Wilk tests. As data were not normally distributed, they were compared using non-parametric significance tests: the Kruskal–Wallis test was used for comparisons between multiple groups (depth and shape effect) and the Mann–Whitney U-test was used for paired comparisons (sonographer and sweep direction). The Mann–Whitney U-test was also used post-hoc, to test all six possible paired comparisons of four depths and of four shapes. In the latter case, significance was set at P = 0.05/6 = 0.008 using the simple Bonferroni correction method14.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

There were a total of 64 volume scans; four shapes scanned at four depths, by two sonographers using two transducer orientations. The true surface areas of the four phantom fontanelles are listed in Table 1. Intraobserver and interobserver repeatability measures were all satisfactory (Table 2). Coefficients of variation ranged from 1.6 to 5.5% and ICCs were in excess of 0.99. Bland–Altman plots of the interobserver percentage differences showed that the 95% limits of agreement between two observers were 6.2 to − 14.9% when measuring the same scan image; while for measuring an independently acquired scan image the limits of agreement were 16.2 to − 17.5% (Figure 3).

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Figure 3. Bland–Altman plots of interobserver percentage differences when tracing the same scan image (a) and on a newly acquired image (b).

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Table 2. Intraobserver and interobserver repeatability of surface area measurement
Repeatability measureTracing same scan imageTracing new scan image
  1. CV, within-subject coefficient of variation; ICC, intraclass correlation coefficient.

Intraobserver  
 CV (%)1.65.5
 ICC (95% CI)0.999 (0.999–0.999)0.992 (0.974–0.999)
Interobserver  
 CV (%)3.15.0
 ICC (95% CI)0.997 (0.975–0.999)0.992 (0.981–0.996)

In order to assess validity, the first ultrasound scan measurement by the first observer was compared with the true surface area. The median percentage difference from the true surface area was − 3.5%, the mean percentage difference was − 5.9% and the 95% limits of agreement were − 23.9 to 12.1%. The largest percentage difference, however, was noted for the triangle, which was the smallest shape tested: the median difference for the triangle was − 12.1% vs. − 0.6% for the trapezoid (P < 0.0001) and vs. − 2.4% for the pentagon (P = 0.002) (Figure 4). Depth also affected measurement accuracy to some extent (P = 0.044). The highest measurement error (median − 8.1%) was noted when the phantom was furthest away (10 cm) from the transducer, although none of the pairwise post-hoc comparisons reached Bonferroni-corrected statistical significance (Figure 4). The smallest median percentage differences were noted for intermediate depths (−2.2% at 8 cm and—2.6% at 6 cm). Neither the operator performing the scan (P = 0.727) nor the direction of the 3D sweep (P = 0.101) had any appreciable effect on the validity of the technique (Figure 5).

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Figure 4. Validity expressed as percentage difference between measured surface area and true surface area vs. shape (in order of size: smallest to largest) (a) and depth (b). Box-plots demonstrate median and interquartile range (IQR), whiskers demonstrate values within 1.5 IQR, outliers (○) are values between 1.5 and 3 IQR and extremes (*) are values beyond 3 IQR. (a) P < 0.0001 and (b) P = 0.044 (Kruskal–Wallis test).

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Figure 5. Validity expressed as percentage difference between measured surface area and true surface area vs. sonographer (a) and direction of three-dimensional sweep (b). Box-plots demonstrate median and interquartile range (IQR), whiskers demonstrate values within 1.5 IQR, outliers (○) are values between 1.5 and 3 IQR and extremes (*) are values beyond 3 IQR. (a) P = 0.727 and (b) P = 0.101 (Mann–Whitney U-test).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

This study demonstrates that surface measurement on rendered 3D ultrasound images is accurate and reproducible in vitro. To the best of our knowledge this is the first attempt to validate surface area measurements on rendered scan images.

Fontanelles are not entirely flat structures. Even though they can be demonstrated in part with B-mode ultrasound, scanning on a single plane may not achieve adequate and consistent visualization. Using rendered 3D ultrasound instead, successful visualization is feasible in 82–100% of cases1. Fetal anterior fontanelle measurement using this technique has been described previously, and ICCs for intraobserver and interobserver repeatability were 0.87 and 0.83, respectively5. These are lower than the ICC for volume calculation, quoted in the literature as being in excess of 0.997 in vitro9 and in vivo15, 16. Volume calculations are achieved using measurements performed on the constituent 2D planes of a 3D scan; conversely, fontanelle area measurements are taken on the rendered image. The different ICC values therefore support the hypothesis that those two different methodologies are subject to different measurement bias.

Our study makes a clear distinction between the following two sources of measurement variation: manual tracing of the scan image and measurement of a newly generated image. Repeatability of tracing the same image was overall excellent both within and between observers. Variability of tracing a newly acquired scan image was considerably greater. The measurement variation introduced during the generation of a scan image was probably caused by movement artifact, which is an inherent limitation of 3D ultrasound. A 3D volume acquisition usually takes 2–5 seconds, depending on the settings of the scan machine (sweep angle and speed). Any fetal or transducer movement during acquisition may result in image distortion, which may affect measurement reproducibility. In this experiment there were no ‘fetal’ movements. However, movement artifact may still be caused by the sonographer holding the transducer while obtaining the 3D volume.

This study shows a systematic underestimation, of an average of − 5.9%, of the true surface area. This compares reasonably to the percentage error, published elsewhere, of between + 1.4% and + 4.1% for volume measurement using 3D ultrasound9. There is also a degree of random error, as evidenced by wide limits of agreement. Despite these figures for random and systematic error, this technique generated a satisfactory ICC, of 0.992. This means that within-subject measurement error was very small when compared with the size variation between subjects in our experiment. The phantom shapes were purposely designed so that the range of surface areas (95.3–654.2 mm2) matched the reported values of the anterior fontanelle surface area in vivo4. It is interesting that reduced accuracy was noted for the smallest fontanelle (< 100 mm2). There was no difference in accuracy between different sonographers or when using a different direction of sweep. The effect of depth was difficult to evaluate: while, overall, there seemed to be a significant difference between groups, pairwise comparison showed a non-significant trend for reduced accuracy at the greatest depth, and this would be logical. However, depth is generally dictated by patient characteristics and this may not be a correctable factor in normal practice; where feasible it would be preferable to avoid surface area measurements at great distances from the transducer, in keeping with the general principles of ultrasound.

There are some limitations to this study. It was carried out using only one ultrasound scanner and a mechanical transducer, as specified in the Methods. However, there is not a standard digital format for saving, analyzing and reporting 3D ultrasound data; and image-encoding and rendering algorithms vary amongst ultrasound manufacturers. It is therefore possible that different ultrasound equipment may demonstrate different measurement accuracy. We also explored the effect on accuracy of the sonographer, depth, sweep direction and phantom shape using a univariate model. It is possible that a mixed interaction exists among those four factors; however, the experiment was not designed to explore a four-factor interaction model. Finally, this experiment cannot account for any temporal size variation of the surface area of interest, as a source of bias. The phantoms were made of non-compressible vinyl material. It can therefore be assumed that the surface area of each hole was constant throughout the experiment. It is possible, however, that the fontanelle size may vary in vivo owing to moulding of skull bones, fetal position or external abdominal pressure. It is also possible that the demarcation between skull bones and the fontanelle is less clear in vivo and this would make tracing less reproducible. These effects can only be investigated by performing an in vivo reproducibility study, acquiring and measuring multiple scan images for each fetus.

In conclusion, we demonstrate that surface area measurement in vitro, using rendered 3D ultrasound of a phantom simulating fetal fontanelles, is subject to a low measurement error. This technique is therefore accurate enough to be applied in vivo.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES

We would like to thank Philips Healthcare for providing the HD9 ultrasound machine and technical assistance. A. T. Papageorghiou and C. Ioannou are supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the Department of Health NIHR Biomedical Research Centres funding scheme.

REFERENCES

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. REFERENCES