Transcript Nuclear Medicine Physics

Nuclear Medicine Physics
•
Single Photon Emission Computed
Tomography (SPECT)
Jerry Allison, Ph.D.
Department of Radiology
Medical College of Georgia
A note of thanks to
Z. J. Cao, Ph.D.
Medical College of Georgia
And
Sameer Tipnis, Ph.D.
G. Donald Frey, Ph.D.
Medical University of South Carolina
for
Sharing nuclear medicine presentation content
Tomographic NM imaging
(SPECT)
Single Photon Emission Computed Tomography
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Scintillation Camera
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps, 4th edition, 2012
Scintillation Camera
PMT Event Positioning Network
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps, 4th edition, 2012
Tomographic imaging (SPECT)
 Produce tomographic images by acquiring
conventional gamma camera projection data
at several angles around the patient

Similar to CT
SPECT
Provide 3-D images to eliminate
overlaying and underlying activity of a
slice

better contrast

more accurate lesion localization

more demanding technically and longer data
acquisition

more severe image noise
SPECT data acquisition
Generally, two detectors mounted at 180 or
90 on a rotation gantry
SPECT data acquisition
 a sequence of 2-D static images at
different angular positions (views)
 detector rotation range
180º with 2 perpendicular detectors or
360º with 2 opposite detectors
SPECT data acquisition
 Circular or elliptical orbit, which is better?
closer to the patient  better spatial
resolution
SPECT Image Acquisition
(Improves spatial
resolution)
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Data Collection: Configuration
 Non Cardiac
• Cardiac
SPECT Image Acquisition
• Typically 2 camera
heads, rotating around
patient
• Projection images every
3 – 6 degrees
• ~ 30 s / projection, ~ 15
minutes total
• Matrix - 64 x 64 or 128 x
128
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Data Collection: Angular Stops
 3 to 6 degrees is common
 a lesser number causes streaking
 a larger number does not improve image
quality
 Step-shoot or continuous acquisition,
which is better??????

Step & Shoot Characteristics


Some loss of time
Less Blur
View number for 360º SPECT
128 views
64 views
number of views
= matrix size
43 views
32 views
An image with 128 x 128 matrix
• Contains 128 projections
• Each projection has 128 data
points
• Equivalent to 128 slice CT
(i.e., 128 tomographic slices per
rotation)
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Sinogram (for one of many slices)
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps
Back Projection
 Leads to blurring in image (streaks and
star-like artifacts)
Filtered Backprojection
 Suppress blurring through filtering the
projections
 A high-pass filter (ramp filter) can be used
to suppress blurring
Filtered Back Projection (of noiseless
data)
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps
Amplitude
Filter
Ramp filter
Ramp w/ rolloff filter
Frequency


In the absence of noise, a ramp filter
works well
For noisy images, a ramp filter with
roll-off is required
Filter
 Ramp
 Suppresses blurring but enhances noise
 Ramp with some roll-off filter
 Smoothes the image and suppresses noise
 Trade off noise vs resolution
 Roll-off filter characteristics are adjustable
Filter Types
© Physics in Nuclear Medicine: Cherry, Sorenson and Phelps
Filter Types
(A) Butterworth: (less
noise, more smooth)
2015
(B) Butterworth: (more
noise, less smooth)
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Filter
 Applied filter is the product of:
 Ramp
 User selected/characterized filter






Shepp-Logan
Hahn
Butterworth
Weiner
Hamming
Hanning (MCG: Philips, generally turned off)
Filter
 Applied filter is the product of:
 Ramp
 User selected/characterized filter



Shepp-Logan (cut-off freq)
Hann (cut-off freq)
Butterworth (order (slope), critical freq (0.707 response)
 Procedure for applying filter

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
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1D projection of each view is converted to spatial
frequency using a Fourier transform
Ramp filter with roll-off is applied in spatial frequency
space (k-space)
Filtered projection is recovered with inverse Fourier
transform
Back projections performed to reconstruct image
Selection of Filters for SPECT
 Filters trade noise for resolution
 No standard way to optimize filter choice
 Patient to patient variation
 Physician preferences
 Vendor recommendation
Iterative Reconstruction (IR)
 Filtered Back Projection has some limits
 Various corrections needed


Attenuation
Compton Scatter
 Ordered Subsets Expectation
Maximization (OSEM) is a common
iterative reconstruction algorithm
Assume
Some Image (I)
Calculate
Projections (P’)
Calculation Includes:
Attenuation
Scatter
Blur with depth
Compare to
Measured Projection (P)
Use P’ & P
to form corrections
Form New
Image (I’)
Is I-I’< *
Done
Iterative Reconstruction
 Slow compared to filtered back projection
 Commonly used for PET
 Being used increasingly in SPECT
 IR used for ~all Philips SPECT at MCG
 Siemens C-Cam??????
Image recon - Iterative
Common IR
recon is the
OSEM
For OSEM, #
iterations (I)
and # subsets
(S) affect
image quality
 # (I/S)  
noise, but
sharper
images
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Iteration 1
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Iteration 5
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Iteration 10
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Brain
Phantom
IR
OSEM
FBP
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Non-filter Noise Factors
 Collimator
 Matrix
 64 x 64
 128 x128
 Slice thickness
 Time per stop/ Number of Stops
 Administered Dose
Data Collection
 Whole Image is
collected for each
view

64 x 64 or 128 x 128
 Each row makes a
slice
 Multiple slices can
be added to reduce
noise
Data Collection: Counts
 Determination of Number of Image Counts
 Activity in patient
 Time per stop
 Number of Stops
Attenuation Correction
 Like all radionuclide imaging
there is a problem due to
attenuation.
 Correction can be important for
judging the activity of lesions
Attenuation correction
 s traveling smaller paths through pt (nearer to
camera) have less attenuation compared to those from
deeper in pt
  for AC can be assumed or measured

Chang (assumed), Measured - Gd rods (older) or CT (new)

CT can be non-diagnostic (low power, cone-beam) or fully
diagnostic depending on the scanner model
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Attenuation in SPECT
D1
I1 = I0e-a
I0 = I1e+a
a
t
(attenuation corrected intensity)
Probability of detection / correct intensity I0, dependent
on the depth at which  originates  need to know “a”
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Chang’s AC method
 Image first reconstructed without AC
 Contours of image used to estimate t for
each projection,  assumed to be constant
 Average ACF determined for each pixel (x,y)
from all projections
 Reconstructed image corrected pixel-bypixel
 Works well for area with approximately
constant attenuation like head, abdomen but
not for areas like chest / thorax
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Chang’s Method
 Assume
-x
uniform
0
attenuation
(x is thickness of tissue
  linear
attenuation between pixel & detector)
coefficient
  is ~0.15/cm
 In Chang’s method, 
for Tc-99m for
is often set to ~0.12/cm
soft tissue
to better account for
Compton scatter
I(x) = I e
Uniform phantom with evenly
distributed 99mTc
Low counts
in center
2015
Chang
method
Proper AC
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
SPECT/CT
AC in SPECT/CT
 Accurate / realistic -map obtained for each
projection using CT
  values used in Chang’s algorithm to correct
pixel-by-pixel
 AC here is more realistic (since  is not
assumed to be constant)
 Current SPECT/CT systems use this method
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Philips Astonish NM Recon Software
 The Astonish: Ordered Subsets
Expectation Maximization (OSEM)
 Compensation for the blurring effects of
the collimator built into the reconstruction
 Resolution Recovery allows recovery of
some of the original resolution
 Astonish uses the distance from the
detector to the object of interest recorded
as a function of angle by the camera
during acquisition and geometric
properties of the specific collimator
Philips Astonish NM Recon Software
 Used on essentially all Philips NM SPECT
images at MCG
 Iterations: 4
 Subsets: 16
 CT data used for attenuation correction
(except brains due to EEG electrode
artifacts)
 Chang’s AC invoked for brains
Common SPECT Problems
 Patient motion
 System Alignment (Center of rotation
issues)
 Collimator issues
 Distance issues

Loss of resolution with distance
Center of Rotation
 SPECT assumes heads always look at a
constant central rotation point
COR (Spatial Alignment)


Image will have blurring and circular artifacts
 COR must be tested periodically for all
heads

SPECT of three point sources
 Generally done with system QC software
COR correction
SPECT image
of a uniform
phantom on a
camera with
poor COR
correction
2015
Incorrect COR
correction
introducing a ring
artifact, degrading
spatial resolution
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
COR correction
 COR correction is used when reconstructing
tomo-graphic data to correct for minor
misalignment between the center of the image
and the axis of rotation.
 COR corrections are stored in a correction
table and are applied automatically after a data
set has been acquired.
2015
Nuclear Medicine Physics for Radiology Residents
Sameer Tipnis, PhD, DABR
Collimator Issues
 Collimators are not completely uniform
 A high count flood must be stored to
correct for collimator non-uniformities
 20 M for 5% for 128 x128
Patient Studies
 Advantages
 No overlapping structures
 3 dimensional lesion locations
 Fusion with high resolution images (CT, MRI)
 Disadvantages
 Time consuming (motion)
 Images are noisy