Joanne T. Vannah

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The SAIF Series Micro CT (III of VI)

• Joanne T. Vannah
• Longwood Small Animal Imaging Facility
• Beth Israel Deaconess Medical Center
• Boston, Massachusetts

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CT/CAT scans

• CT Computed tomography originally known as CAT
  Computed axial Tomography
• Tomography derived from the Greek root
  tomos (slice) and graphia (to write)
• Digital processing of X-ray data (2D) is used
  to geometrically generate a 3D image

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Strong penetrating ability of X-rays coupled with
spatial sectioning
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CT x-Ray and detector (gantry) sit 180º from each
other
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Micro CT x-ray detector standard components

• Scintillator screen of cesium iodide that
  converts x-rays into light
• An optical taper that concentrates the light onto
  the camera
• CCD camera records the image

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Three possible interactions of x-rays (photons)
with matter
X-ray Energy 10- 500 keV
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Photon-electron interactions
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Attenuation 1/Penetration
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The linear attenuation coefficient (µ) is the
signal measured
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Calibration and Hounsfield units

• X-ray attenuation unit for interpreting CT data
• Calibrate with every scan to define relative
  densities
• Each pixel is assigned a value between 1K and
  1K

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Tomographic image 2D pixels correspond to 3D
voxels in subject
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Series of rays projections
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Tomographic reconstruction

• Transmission measurement, where the detector
  measures an x-ray intensity, It
• The unattenuated intensity of the x-ray beam is
  also measured, Io
• It Io e-µt
• t Thickness of subject along the ray
• µ average linear attenuation coefficient along
  the ray
• ln (I0/It) µt

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Backprojection
Reconstruction algorithm produces image
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Filtration

• The selective attenuation of photons depends upon
  their energy
• Photons
• A value of 40 keV improves penetration
  substantially
• Lower keV for softer tissues, higher keV for
  denser tissues (e.g., breast tissue compared to
  bone)

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Controlling x-ray beam intensity
LAC are energy dependent After passing through a
given thickness of subject, lower energies are
attenuated to a greater extent than higher energy
x-rays. Aluminum filter used.
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Beam hardening
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Comparing tissue of similar density

• The challenge arises when attempting to compare
  tissues of similar composition
• Not enough physical contrast to discern
  differences
• To increase image contrast a dense fluid with a
  high atomic number may be used such as iodine

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Micro CT scanners
Current Modality GE eXplore Locus Micro CT
Incoming Modality Siemens Inveon Micro
CT/SPECT/PET
Max res 15 µm Min scan time 1 12 cm bore
Max res 27µm Min scan time 6 9 cm bore
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Scaling of dose for micro CT scans

• 1 rad 0.01 J/kg 0.01 Gy1 Gy 100 rad
• In any scan resolution, at 80 kV
• The standard dose delivered to mice is 2.1
  mGy/mAs
• The standard dose delivered to rats is 1.8
  mGy/mAs
• Compute mAs in a scan by multiplying the
  following parameters
• Number of views x number of frames x tube current
  (milliamps) x integration time (seconds)

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Typical rat scan

• 400 views
• 4 frames per view
• 450 microamp tube current
• 150 ms integration time
• 400 x 4 x 0.45 mA x 0.15s x 1.8 mGy/mAs 184 mGy
  (or 0.184 Gy)

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Micro CT experimental design
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Micro CT applications

• Measure the change in density over time of
  tissues, organs, and bones
• Observe of osteoporosis and arterial hardening
• Quantify the healing of fractures
• Determine microcalcifications in breast cancer
  tissue
• Track adipose tissue (diabetic/nutrition) models

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Calcified aorta in a transgenic mouse
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Calcified aorta in a transgenic mouse
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3D image of calcified aorta
A 3D volume rendering of a calcified aorta in a
transgenic mouse.
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Pros/Cons for micro CT

• Pros
• Generation of 3D images
• Comparison of tissues of different composition
• High resolution
• Cons
• Comparison of similar tissues difficult to
  distinguish
• Use of radiation

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Summary

• Micro CT is an efficient tool for monitoring the
  change of density over time
• The linear attenuation coefficient is the signal
  being measured by the extent of x-ray interaction
  with tissue
• 2D x-ray images are geometrically computed to
  produce a 3D image using a large data set