Aortic centreline tracking for PWV measurements in multiple MRI sequences

Arna van Engelen¹, Torben Schneider², Hubrecht de Bliek³, Miguel Silva Vieira⁴, Isma Rafiq⁴, Tarique Hussain⁴, Rene Botnar¹, and Jordi Alastruey¹

¹Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom, ²Philips Healthcare, Guidford, United Kingdom, ³Philips Healthcare, HSDP Clinical Platforms, Best, Netherlands, ⁴Department of Cardiovascular Imaging, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom

Synopsis

Accurate 3D length measurements through the aorta are required for Pulse Wave Velocity (PWV) measurements. We evaluate automatic centreline tracking, requiring only a start and end point, on three different types of MR data (balanced-SSFP, contrast-enhanced and black-blood MRI), in 12 elderly subjects and 10 patients post-coarctation repair. Our algorithm uses vesselness filtering, fast marching and centreline refinement. Length differences between manual and automatic centrelines are generally below 1cm, with corresponding PWV differences well below 0.5m/s. This shows that with minimal user interaction, accurate PWV measurements can be performed using automatic centreline tracking, on commonly used types of MR data.

Purpose

Aortic stiffness is an important biomarker for a variety of cardiovascular diseases, and can be assessed by pulse wave velocity (PWV). PWV can be derived from MRI by computing the blood flow profile at two locations in the aorta and the distance between those locations. For accurate distance measurements, the aortic centrelines need to be extracted from 3D images. Automatic aortic centreline tracking has extensively been evaluated on CTA data¹, but limited studies exist for MRI². The performance of automatic algorithms depends on the input provided and often needs to be optimised for different MR contrasts. The aim of this study was to develop an aortic centreline tracking algorithm that performs accurately on images from the most common cardiac MRI sequences.

Methods

Data

We included 12 subjects from a twin cohort³ and 10 non-stented patients post-coarctation repair. All subjects underwent phase-contrast velocity-encoded cine in the ascending and diaphragmatic aorta (125 reconstructed phases). Anatomical sequences used for 3D centreline tracking included DIR-TSE black-blood images for the twins and both 3D balanced SSFP (bSSFP) and 3D contrast-enhanced MRA (CE-MRA) timed for optimal aortic enhancement, for the coarctation patients (Figure 1). All images were acquired on a 1.5T Philips Ingenia scanner.

Centreline tracking

This consists of three steps: 1) vesselness filter, 2) fast marching and 3) centreline refinement. The potential of the vesselness filter has been demonstrated before⁴. It uses the Hessian matrix, composed of local second-order derivatives of the image, to enhance vessel-like structures. We compared several scale settings for the Hessian matrix: 4 scales, ranging from 4 to 7mm, and 2 scales being either 4 and 6 or 6 and 8mm. The start and end points for centreline tracking were defined by taking the centre of the aorta on the first phase of the phase-contrast images. An ellipse was fitted on the 3D data at these points and the centres were used as start and end points, to account for patient displacement during scanning. Bi-directional fast marching⁵ was performed from both start and end. Finally, the obtained centrelines were centred and smoothed by an open active contour⁶. Intensity of the black-blood images was inverted before centreline tracking.

Flow waveforms and PWV

Volumetric flow waveforms were obtained from phase-contrast MRI at the ascending and diaphragmatic aorta, by fitting the vessel edge along a number of ray casts from a propagated centre point on all phases⁷. The arrival of the pulse wave was determined by determining the foot of the curve, and transit time was determined by taking the time difference between the two feet⁸. PWV was calculated as the ratio of the centreline length to the transit time.

Evaluation

Manual centrelines were annotated three times by the same observer in all anatomical scans using all three imaging planes. Centrelines were resampled to 0.1mm and the manual centrelines were cropped from the points closest to the end points of the automatic centrelines. Centrelines were evaluated based on success (remaining inside the lumen), length, point-based distance to the manual centreline, and the effect on PWV measurements. For the coarctation patients the difference in length between bSSFP and CE-MRA was also evaluated.

Results and discussion

Quantitative results are provided in Tables 1 and 2, and examples of obtained centrelines are shown in Figures 2 and 3.

For the black-blood and CE-MRA data, length differences generally stay below 1cm, resulting in PWV differences well below 0.5m/s, being clinically acceptable. For bSSFP data the differences are slightly larger, which is mostly attributable to one case where the tracked centreline followed a wrong path. Computing the Hessian at two scales (4-6mm) yielded best accuracy for all image types. Length differences between bSSFP and CE-MRA can be due to differences in centreline accuracy and image characteristics, as well as patient displacement (Fig 2). However, these differences stay within acceptable ranges.

In practice, manual correction of inaccuracies on the obtained centrelines is feasible, so a semi-automatic approach is possible and would improve PWV accuracy in such cases.

Conclusion

This semi-automatic aortic centreline tracking technique performs well for the three most commonly used cardiac MRI sequences. The obtained centrelines are suitable for accurate aortic PWV measurements.

Acknowledgements

This research has been supported by an EPSRC Technology Strategy Board CR&D Grant (EP/L505304/1).

References

1. Worz et al., IEEE Trans Biomed Eng 2010

2. Babin et al., Conf Proc IEEE EMBS 2012

3. Moayyeri et al., Int J of Epidemiology 2013

4. Frangi et al., MICCAI 1998

5. Wink et al., PhD thesis 2004

6. Lobregt et al., IEEE Trans Med Imaging 1995

7. Wink et al., IEEE Trans Med Imaging 2000

8. Gaddum et al., Ann Biomed Eng 2012

Figures

Figure 1: Examples of the three image types used.

Table 1: All results for centreline accuracy: success, length, point-based centreline distances, and corresponding PWV accuracy. Out of the three manual centrelines the one with median length was used for comparisons with the automatic centrelines.

Table 2: differences between measurements on CE-MRA and bSSFP for coarctation patients. For reference image resolution is provided (resolution for black-blood images is 1.12x1.12x5.0mm)

Figure 2: Four examples of coarctation centrelines. Projections (centreline 2 scales, 4-6mm) are shown on the CE-MRA maximum intensity projection, and a multiplanar reformat of the bSSFP images. For D a slice perpendicular to the centreline is shown where the centreline leaves the lumen on bSSFP image.

Figure 3: Four examples of centrelines on the black-blood data. Top row: 3D plots. Bottom row: multiplanar reformats and the result using 2 scales (4-6mm).

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)

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