Micro-CT based quantification of Mouse Brain Vasculature:
The effects of acquisition technique and contrast materialAuthors: Camrin Tipton, MS; Zhihua Qi, PhD; Michael Lamba, PhD; Kathleen LaSance, MS*University of Cincinnati, Cincinnati OH, §Precision Radiotherapy, West Chester OH

Introduction
It is understood that radiotherapy of the brain results in cognitivedeficits. The causes of the deficits are not well-known, but reduced
vascularity may be a significant component of the source ofcognitive decline. Animal models to study these effects may assist
with understanding the mechanisms. If mouse brain vasculature canbe accurately quantified, the effects of radiation on the vasculaturemight be studied, along with the effects of radiation modifiers suchas radio-protectants. This study investigates µCT based
quantification of normal mouse brain vasculature, focusing on theeffect of two acquisition techniques and contrast material.

Space for Images

Methods
Four mice were scanned on a µCT scanner (Siemens Inveon) using
the acquisition and reconstruction parameters listed below.
Acquisition

Reconstruction

Siemens Inveon Multimodal Imager
Inveon Acquisition Workplace v2.0.0.1050
Axial acquisition
80/50 kVp
500 µA
720 projections
1300 ms per projection
17.56 µm slice thickness

Fig 1- Cropped brain image of a mouse injected withgold nanoparticles

Fig 2- Contoured brain image with the externalremovedFig 3- Contoured brain image only showing pixels
with a CT number in the range of the contrast
injectedFig 4- 3D visualization of the vessels

HU Calibrated
Feldkamp algorithm
Noise reduction – slight
Shepp-Logan filtration
Mouse beam hardening correction applied
18 µm3 voxel size reconstruction
16 bit per voxel~3 Gb per data set

The mice were injected with 40 mg of gold nanoparticles(MediLumine) or 100 µl of Exitron 12000 (Miltenyi Biotec) iodine
contrast. Two acquisition techniques were also performed, a singlekVp and a dual kVp technique. The single kVp technique scanned
the mouse once at 80kVp. The dual kVp technique scanned themouse twice using 50kVp and 80kVp. The brain was contoured
axially and using MatLab the region outside the contour wasremoved to create just an image of the brain without the high HUskull (Figure 2). For single kVp acquisition, a threshold was appliedso the contrast was selectively segmented (Figure 3). For the dualkVp acquistion, the segmentation was based on the ratio of HU
between the two kVps. A 3D rendering of the segmented vessels canis displayed (Figure 4). Once a segmented binary image of thevessels was obtained the vasculature fraction was calculated as thenumber of segmented voxels divided by the total number of voxels
brain voxels after removing the skull. this segmentation was basedon the ratio of the HU value of the two kVps.

Results and Discussion
The dual kVp acquisition amplified noise of the resultant image
and the dual energy technique was not explored further. A second
complication was found to be due to the high-resolution
acquisition resulting in imperfect source/detector position
calibration producing ring artifacts.
For the single kVp acquisition the brain blood volume had an
average of 3.5% for gold nanoparticles and 4.0% for Exitron
12000. The contrast-noise ratio was significantly better forimages acquired with the gold nanoparticles (2.0) than for thoseacquired with the iodine contrast (1.4).

Conclusion
The effects of acquisition technique and contrast material for quantification of mouse brain
vasculature showed that gold nanoparticles produced more consistent segmentation of brain
vasculature than iodine contrast. Dual kVp acquisition holds some promise for segmenting thecontrast agent excluding the boney anatomy, avoiding the need for manual segmentation of theskull although contrast-to-noise remains an issue.

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