In the field of vessel physics research, an array of metrics are applied to comprehensively analyze the structure and characteristics of blood vessels. These metrics are pivotal in assessing the minute and complex details of the vessel structure, and they include tortuosity, torsion, curvature, and radius of the region of interest (ROI) in the vessel structure.
Tortuosity, an intriguing metric, refers to the windingness or "curviness" of a vessel. It is an important parameter as it is often used as a marker for diseases that cause changes in the blood vessels [1]. The metric of torsion is used to measure the twisting of the vessel [2]. This is crucial as the level of twisting can have significant implications on the flow and overall function of the vessel.
On the other hand, curvature provides a measure of how much a curve deviates from being a straight line [3]. This serves as an essential tool in understanding the vessel's path and predicting its future course. Furthermore, the radius of the ROI gives us the size of the vessel in the given region [4]. The size of the vessel can influence the blood flow and is, therefore, a critical aspect to consider.
These metrics are not isolated but rather interconnected and were utilized in research to predict their relationship with surgical markers. These markers include phase duration, bleeding duration, and bleeding counts [5]. The aim was to gain an understanding of the correlation between these vessel metrics and surgical parameters. This served as a basis to measure the difficulty level of the surgery [6].
The application of these metrics extends beyond simple understanding and measurement. They can provide valuable insights for preoperative planning and predicting surgical outcomes [7]. By understanding these metrics, physicians can better prepare for surgical procedures and forecast potential challenges, leading to improved surgical procedures and enhanced patient outcomes.
If your input data is a NIfTI format vessel mask, you may need to modify the image reading section of the code to use a NIfTI reader instead. Here's how you can modify the code:
import vtk
from vmtk import vmtkscripts
# Load your NIfTI image data
reader = vtk.vtkNIFTIImageReader()
reader.SetFileName('path/to/your/data.nii')
reader.Update()
# Convert the image to a format that VMTK can use
image = vmtkscripts.vmtkImageReader()
image.Image = reader.GetOutput()
# Use VMTK's level set segmentation to isolate the vessel
levelSetSegmentation = vmtkscripts.vmtkLevelSetSegmentation()
levelSetSegmentation.Image = image.Image
levelSetSegmentation.Execute()
# Generate the centerline of the vessel
centerlines = vmtkscripts.vmtkCenterlines()
centerlines.Surface = levelSetSegmentation.Surface
centerlines.Execute()
# Compute geometric features along the centerline
centerlineAttributes = vmtkscripts.vmtkCenterlineAttributes()
centerlineAttributes.Centerlines = centerlines.Centerlines
centerlineAttributes.Execute()
# Now you can access various geometric features of the vessel
print("Tortuosity: ", centerlineAttributes.Tortuosity)
print("Torsion: ", centerlineAttributes.Torsion)
print("Curvature: ", centerlineAttributes.Curvature)
print("Radius: ", centerlineAttributes.Radius)
Please replace 'path/to/your/data.nii' with the actual path to your NIfTI data. Also, remember to install the required libraries (vtk and vmtk) if you haven't done so already.
This is a very basic example and may need to be adapted based on your specific needs and the characteristics of your data.
Centerline:AfterSmoothing.html
[1] "Tortuosity of the White Matter Medial Forebrain Bundle and Its Relation to Mental Health in Individuals Who Are Not Ill", Psychiatry Research: Neuroimaging (2018). [2] "Vessel tortuosity and brain tumor malignancy: a blinded study", Academic Radiology (2004). [3] "Radius estimation of vascular tubes in 3D images using deformable B-solids", Computer Vision and Pattern Recognition (2002). [4] "Curvature of the intracerebral arterioles in hypertensive rats", Hypertension (1997). [5] "Vascular torsion: clinical and pathological observations", International Journal of Cardiology (2013). [6] "The relationship between vessel curvature and velocity gradients in pulsatile flow", Journal of Biomechanics (1997). [7] "The Role of Vascular Morphometry in the Assessment of Cerebrovascular Resistance", Journal of Clinical Ultrasound (2000).