Assessment of wall shear stress in patients without aortic disease and with aortic dissection using velocity encoding 4D MRI

Transcription

1 Assessment of wall shear stress in patients without aortic disease and with aortic dissection using velocity encoding 4D MRI Poster No.: C-0841 Congress: ECR 2015 Type: Scientific Exhibit Authors: J. P. Rudolph, M. Rasper, C. Maegerlein, B. M. Gramer, M. Settles, C. Reeps, B. Lutz, E. J. Rummeny, A. Huber; Munich/DE Keywords: Pathology, Hemodynamics / Flow dynamics, Dissection, Statistics, Physics, Experimental investigations, MR-Angiography, MR, Experimental, Cardiovascular system, Cardiac, Arteries / Aorta DOI: /ecr2015/C-0841 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 20

2 Aims and objectives Wall shear stress (WSS) is a physical vector quantity consisting of two sub-component vectors, the axial (awss) and the circular (cwss) wall shear stress [1]. Its length or magnitude depends on local flow patterns. An oscillating or permanently lowered WSS is associated with vascular diseases such as atherosclerosis [2, 3]. To quantify this hemodynamic parameter by means of imaging technologies is challenging and at the moment limited to just a few techniques. Besides simulations based on computational fluid dynamics (CFD) [4], mainly velocity encoding 3-dimensional magnetic resonance imaging techniques offer the possibility to perform in vivo WSS measurements [5] with the advantage to measure patients' own parameters. Furthermore, 4D flow images can be reconstructed to show local hemodynamics by pathlines or streamlines. (see Fig. 1 on page 3 and Fig. 2 on page 3) Fig. 1: Velocity color-coded 4D flow reconstruction of a healthy aorta with pathlines during systole from a dorsal view. Magnitude images served as data source. References: Institut für Diagnostische und Interventionelle Radiologie, Klinikum Rechts der Isar der TU München - Munich/DE Page 2 of 20

3 Pathophysiologically, vessel diseases form an interesting field of application of 4D flow measurements. Fig. 3 on page 4 and Fig. 4 on page 5 show pathlines in a patient with an aortic dissection. The aim of this study was to determine differences in WSS magnitude between patients with aortic dissection and patients without any aortic disease using 4D phase contrast magnetic resonance imaging (4D PC MRI). Images for this section: Fig. 1: Velocity color-coded 4D flow reconstruction of a healthy aorta with pathlines during systole from a dorsal view. Magnitude images served as data source. Page 3 of 20

4 Fig. 2: Pathlines in the aortic arch of a patient without aortic disease from a dorsolateral view. The movie shows the velocity color-coded over the time period of a heart cycle. Page 4 of 20

5 Fig. 3: 4D flow reconstruction of the aorta in a patient with a chronic aortic dissection illustrating true and false lumen during systole from a dorsal view. Velocity is shown colorcoded. Magnitude images served as data source for reconstruction. Page 5 of 20

6 Fig. 4: Pathlines in the aortic arch of a patient with aortic dissection from a ventrolateral view. The movie shows the velocity color-coded over the time period of a heart cycle. Page 6 of 20

7 Methods and materials In the context of a prospective study, 18 patients (8 patients with aortic dissection and 10 patients without any aortic disease) underwent velocity encoding 3-dimensional magnetic resonance tomography (4D PC MRI) of the aorta. All aortic dissection patients had a chronic aortic dissection of the suprarenal descending aorta at the time of the investigation. The 4D PC sequence was carried out after contrast agent application (0.15 mmol/kg gadobenate dimeglumine) during high resolution contrast-enhanced MR angiography of the aorta. 4D flow measurements were acquired on a Philips Ingenia 3.0T with bodyphased array coil using ECG and navigator echo based respiratory gating. Data was collected with cartesian acquisition and accelerated by SENSE in two directions (AP x 3 RL= 1.5 x 2.5). The spatial resolution was 1.5 x 1.5 x 1.5 mm (FH x AP x RL). The temporal resolution was 40 ms. Velocity encoding in patients without aortic dissection was performed with Venc= cm/s. Venc in dissection patients was determined after measuring the maximum velocity in the region of interest by a 2D flow measurement prior to the 4D flow measurement. Therefore, velocity encoding in chronic aortic dissection patients was cm/s. The field of view (FoV) was 450 x 289 mm². Slices were arranged in a sagittal order and adapted to specific anatomic circumstances. In most cases 40 slices were reasonable (FoV= 450 x 289 x 120 mm³). Depending on the respiratory gating efficiency, the actual scan time was 7-13 min. After the acquisition, data underwent delayed reconstruction in 3 phase sensitive planes (FH, AP and RL) and were post-processed using the software GT-Flow (version , Gyrotools, Switzerland). In all study patients a reslice stack was arranged, intersecting the suprarenal descending aorta vertically in sagittal and coronal view. Along the vessel wall a contour was drawn (see Fig. 5 on page 9). Page 7 of 20

8 Fig. 5: This figure demonstrates in which way contours were drawn in patients without aortic diseases. (a) and (b) show how the reslice stack is angled vertically to the suprarenal descending aorta in sagittal and coronal magnitude images at a time point during systole. A contour is drawn along the vessel wall of the aorta at a middle slice of the reslice stack to form 8 segments similar in radian in clockwise order (c, blue contour). The position of the contour can be controlled in a 3D reconstruction of the aorta, either vessels only (d) or with pathlines switched on (e). The blue arrows in (d) and (e) point to the contour. References: Institut für Diagnostische und Interventionelle Radiologie, Klinikum Rechts der Isar der TU München - Munich/DE In patients with aortic dissection the contour includes both, true lumen (TL) and false lumen (FL) (see Fig. 6 on page 9). By the use of B-spline interpolation [1] two timeresolved variables can be calculated: 1st) the time resolved variable average velocity (av(t)) 2nd) Derived from the pattern of the contour, the software is able to divide the contour into 8 segments (see (c) in Fig. 5 on page 9 and Fig. 6 on page 9) identic in radian to get time-resolved WSS magnitude variables for each of the 8 segments, the segmental average WSS magnitude (sawssm(t)) functions. These functions can be plotted to form a WSS profile (see Fig. 7 on page 10). Page 8 of 20

9 (In order to reduce the probability of statistical outliers, we preferred average numbers to the use of maximum ones.) The highest value of av(t) and the highest value to be found in one of the segmental functions sawssm(t), the functions assume during time t, were defined as peak Values (p). The resulting parameters for each study patient are pav (peak average velocity) and pawssm (peak average WSS magnitude, also see Fig. 7 on page 10). Values for pav and pawssm were noted and tested for statistically significant differences between patients with aortic dissection and patients without aortic disease using t-tests for unpaired samples. Images for this section: Fig. 5: This figure demonstrates in which way contours were drawn in patients without aortic diseases. (a) and (b) show how the reslice stack is angled vertically to the suprarenal descending aorta in sagittal and coronal magnitude images at a time point during systole. A contour is drawn along the vessel wall of the aorta at a middle slice of the reslice stack to form 8 segments similar in radian in clockwise order (c, blue contour). The position of the contour can be controlled in a 3D reconstruction of the aorta, either vessels only (d) or with pathlines switched on (e). The blue arrows in (d) and (e) point to the contour. Page 9 of 20

10 Fig. 6: This is an illustration of how contours were drawn in patients with aortic dissection. (a) and (b) show how the reslice stack is angled vertically to the suprarenal descending aorta in sagittal and coronal magnitude images at a time point during systole. A contour is drawn along the vessel wall of the aorta at a middle slice of the reslice stack including both lumina, true (TL) and false lumen (FL) (c, red contour). 8 segements similar in radian are formed in clockwise order along the contour (c, numbers). The position of the contour can be controlled with the use of 3D reconstructions of the aorta, either vessels only (d) or with pathlines switched on (e). The red arrows in (d) and (e) point to the contour. Page 10 of 20

11 Fig. 7: WSS profiles, plotting the segmental average wall shear stress magnitude functions (sawssm(t)) over time t, for (a) a patient without any aortic disease and (b) a patient with aortic dissection. The highest value to be found in one of the segments was defined as the peak value to form the peak average wall shear stress magnitude (pawssm). Page 11 of 20

12 Results Peak average wall shear stress magnitude (pawssm): 2 The pawssm is 0.69 ± 0.17 N/m in patients without aortic disease and 0.15 ± 0.05 N/ 2 m in patients with aortic dissection. Shapiro-Wilk test results p>0.05 for both groups, patients without aortic disease and patients with aortic dissection. The result of Levene's test for equality of variances shows p<0.05. Under the assumption of missing equality of variances, t-test for unpaired samples shows a statistically significant difference between patients without aortic disease and patients with aortic dissection (p<0.001). Page 12 of 20

13 Fig. 8: Boxplots of peak average WSS magnitude (pawssm) comparing the two groups of diagnosis: patients without aortic disease (healthy) and patients with aortic dissection (chronic aortic dissection) References: Institut für Diagnostische und Interventionelle Radiologie, Klinikum Rechts der Isar der TU München - Munich/DE Peak average velocity (pav): The peak average velocity is 71.2 ± 10.8 cm/s in patients without aortic disease and 20.6 cm/s ± 3.8 cm/s in patients with aortic dissection. Shapiro-Wilks test results p>0.05 in both groups. Levene's test for equality of variances shows p>0.05. t-test for unpaired samples shows a statistically significant difference between the patients without aortic disease and patients with aortic dissection (p< ). Page 13 of 20

14 Fig. 9: Boxplots of peak average velocity (pav) comparing the two groups of diagnosis: patients without aortic disease (healthy) and patients with aortic dissection (chronic aortic dissection) References: Institut für Diagnostische und Interventionelle Radiologie, Klinikum Rechts der Isar der TU München - Munich/DE Images for this section: Page 14 of 20

15 Fig. 8: Boxplots of peak average WSS magnitude (pawssm) comparing the two groups of diagnosis: patients without aortic disease (healthy) and patients with aortic dissection (chronic aortic dissection) Page 15 of 20

16 Fig. 9: Boxplots of peak average velocity (pav) comparing the two groups of diagnosis: patients without aortic disease (healthy) and patients with aortic dissection (chronic aortic dissection) Page 16 of 20

17 Conclusion In this study we investigated with the use of 4D PC MRI, if patients with aortic dissection show differences to persons without aortic diseases in terms of WSS magnitude and velocity. Post-processing of the acquired data showed lower values in peak average WSS magnitude and peak average velocities in patients with chronic aortic dissections, measured at the suprarenal descending aorta. This observation is consistent with modern time-resolved WSS measurements at false lumina (FL) performed using computational fluid dynamics (CFD) in simulations of dissection-like dilatations [6]. Absolute values in magnitude WSS are smaller than in CFD models, but overprediction of flow rates in CFD measurements over phase contrast MRI has been mentioned in literature [7]. Limitations: Limitations of this study can be found in the low count of cases, the 4D flow protocol and in the procedure of post-procession (e.g. free-hand drawing of contours). Regarding the 4D flow protocol, recent acquisition techniques such as radial undersampling (e.g. PC-VIPR [8]) or acceleration techniques like kt-blast, kt-sense or compressed sensing [9-11] have promising advantages. Multi-Venc attempts made in the past [12] might be a possible solution to the occurrence of low signals in false lumina of aortic dissections. Personal information Jan Rudolph Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München jan.p.rudolph@tum.de Dr. Michael Rasper Page 17 of 20

18 Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München Dr. Christian Maegerlein Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München Dr. Bettina Gramer Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München Dr. Marcus Settles Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München PD Dr. Christian Reeps Klinik und Poliklinik für Vaskuläre und Endovaskuläre Chirurgie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße 22 Page 18 of 20

19 81675 München Brigitta Lutz Klinik und Poliklinik für Vaskuläre und Endovaskuläre Chirurgie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München Prof. Dr. Ernst J. Rummeny Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München Prof. Dr. Armin Huber Institut für Diagnostische und Interventionelle Radiologie Klinikum Rechts der Isar der Technischen Universität München Ismaninger Straße München References [1] Stalder, A.F., et al., Quantitative 2D and 3D phase contrast MRI: optimized analysis of blood flow and vessel wall parameters. Magn Reson Med, (5): p [2] Ku, D.N., et al., Pulsatile flow and atherosclerosis in the human carotid bifurcation. Positive correlation between plaque location and low oscillating shear stress. Arteriosclerosis, (3): p Page 19 of 20

20 [3] McGregor, R.H., D. Szczerba, and G. Szekely, A multiphysics simulation of a healthy and a diseased abdominal aorta. Med Image Comput Comput Assist Interv, (Pt 2): p [4] Karmonik, C., et al., Computational hemodynamics in the human aorta: a computational fluid dynamics study of three cases with patient-specific geometries and inflow rates. Technol Health Care, (5): p [5] Markl, M., et al., 4D flow MRI. J Magn Reson Imaging, (5): p [6] Karmonik, C., et al., Computational fluid dynamics investigation of chronic aortic dissection hemodynamics versus normal aorta. Vasc Endovascular Surg, (8): p [7] Cheng, Z., et al., Predicting flow in aortic dissection: comparison of computational model with PC-MRI velocity measurements. Med Eng Phys, (9): p [8] Gu, T., et al., PC VIPR: a high-speed 3D phase-contrast method for flow quantification and high-resolution angiography. AJNR Am J Neuroradiol, (4): p [9] Baltes, C., et al., Accelerating cine phase-contrast flow measurements using k-t BLAST and k-t SENSE. Magn Reson Med, (6): p [10] Lustig, M., D. Donoho, and J.M. Pauly, Sparse MRI: The application of compressed sensing for rapid MR imaging. Magn Reson Med, (6): p [11] Stadlbauer, A., et al., Accelerated time-resolved three-dimensional MR velocity mapping of blood flow patterns in the aorta using SENSE and k-t BLAST. Eur J Radiol, (1): p. e [12] Goyen, M. and L.J. Heuser, Improved peripheral MRA using multi-velocity-encoding phase contrast-enhanced MRA techniques. Acta Radiol, (2): p Page 20 of 20