Carson Anthony Hoffman1, Eric Schrauben1, and Oliver Wieben1,2
1Medical Physics, University of Wisconsin Madison, Madison, WI, United States, 2Radiology, University of Wisconsin Madison, Madison, WI, United States
Synopsis
The comprehensive information on vessel
anatomy and hemodynamics presented by 4D Flow MRI can be difficult to
visualize. We introduce a new viewing mode using a ‘slice tool’. The use of this display algorithm can provide
benefits for scalar visualization by preserving spatial location and avoiding
ambiguities in cases of overlapping vessels. This
novel approach can thus offer an improved understanding of complex hemodynamics
within the body when used in conjunction with previously existing visualization
methods eg. MIP images, pathline, and streamline visualizations.
Purpose
4D
Flow MRI can provide comprehensive information on vessel anatomy and
hemodynamics. However, the visualization of time-resolved hemodynamics (velocity
vector fields and scalars) over a large imaging volume in an intuitive and
clinically useful form on a 2D display is challenging. The visualization of
scalar properties, such as velocity magnitude, pressure difference, or kinetic
energy have unique challenges. Often, algorithms such as maximum intensity
projection (MIP) images are used to highlight the peak values (‘hot spots’) of such
scalar quantities. However, the distribution of the scalar inside the vessels
is lost with such a display and ambiguities can occur in the presence of vessel
crossings in projections. Here we
introduce a novel approach designed to visualize scalar properties within the
vessels along each vessel path. The visualization scheme automatically ‘slices’
vessels open through a center line and displays the scalar parameter of
interest. This allows for scalar parameters to be displayed inside vessels
while maintaining the correct localization and distribution.Methods
Fig1.
Summarizes the processing steps for the generation of ‘slice views’. 3D grayscale data are converted into a
binary vessel data set through simple thresholding, leaving the anatomical vessel
section of interest identified. The binary image set is used to create a 3D
skeleton via 3D medial surface axis thinning algorithms. In the
centerline method used, Euler characteristics and connectivity are preserved to
guarantee the invariance of number of connected objects, cavities, and holes in
the original shape.1 The spurs on the resulting 3D skeleton are removed
until there is a single centerline present for each path. 2 For each
point along the centerline, a tangent vector and the associated normal basis
plane is calculated. Viewing vectors created from centerline points to the current
camera location are projected onto the associated normal basis planes. Projected
vectors are normalized and rotated along the basis plane by 90 degrees.
Centerline points are shifted in the direction of the rotated projected vectors
creating a single line for each centerline point. The resulting lines are
connected to create a smooth plane located in the center of the vessel. The
resulting 3D image scene can be interactively displayed (zoom, pan, rotate) with
scalar information on the sliced vessel. This
method was applied with in vivo cranial, cardiac, and hepatic scans with IRB
approval and subject consent. All algorithm development, and visualization was
completed using commercial software (MatLab R2015a).Results
Comparisons
between MIP images and slice views are shown for a cranial case (Fig2). The
zoomed MIP image in Fig2 presents vessel overlap errors (black arrow) and
misleading velocity distributions (red arrow). The slice views 1 and,2 in Fig2
clearly show the existence of multiple vessels and correctly display the
velocity distributions within them. Two viewing modes for the slice tool are
shown in Fig3: in one mode, the displayed slice is calculated once and the visible
section of that slice depends on the viewing angle. In a second mode, the orientation
and contents of the sliced view is recalculated for each viewing angle. The
application of the slice tool algorithm in different body locations including
the cardiac, cranial, and hepatic vasculature can be seen in Fig4. Discussion
This
new visualization method allows the viewer to explore scalar data profiles such
as velocity, kinetic energy, or pressure gradients in the vasculature while
preserving localization. Application of the slice tool throughout the body can
be completed once vessel segmentation is accomplished. Fig2 show that the slice
tool can omit MIP vessel overlap ambiguities which are common in complex
vascular systems, e.g. cranial and hepatic vasculature. The ability to
differentiate vessels in the slice view becomes more apparent when using an
interactive 3D viewer. The slice view presents the ability to correctly
display features such as asymmetric flow profiles within the cut plane while a
MIP view is better suited to identify ‘hot spots’ in a volume, albeit with loss
of spatial information in terms of depth. Conclusion
This
work introduces a new visualization scheme for the display of scalars obtained
from 4D velocity fields. We have shown that easy segmentation along with real
time image updates for scalar data is achievable using this new visualization method.
Future work will improve centerline connectivity to eliminate missing sections
in areas of ambiguity. The application of this method could provide additional
insight into 4D flow features when used with other visualization methods. We will investigate whether this additional
visualization feature improves the diagnostic workflow and decision making of
4D Flow analysis in a clinical setting through GUI implementation.Acknowledgements
No acknowledgement found.References
1)
T. C. Lee, et al CVGIP:
Graphical Models and Image Processing 56.6
(1994): 462-478. 2) E. Schrauben, et al J Magn Reson Imaging. 2015 Nov;42(5):1458-64