Nuclear Medicine: Tomographic Imaging – SPECT, SPECT-CT and PET-CT Katrina Cockburn Nuclear Medicine Physicist

Image Acquisition Techniques  Static-(Bones, Lungs)  Dynamic-(Renography)  Gated-(Cardiac)  Tomography  SPECT  PET  List Mode-(Cardiac)

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast

Problems with Planar Imaging  Planar imaging  2D representation of 3D Distribution of activity  No depth information  Structures at different depths are superimposed  Loss of contrast Image contrast 2:1 Object Contrast 4:1

Single Photon Emission Computed Tomography  Collect multiple planar images at several angles around the patient  Typically views over 360°  Can be views over 180°

Single Photon Emission Computed Tomography  Image Reconstruction  2D images of selected planes within the 3D object  Better Contrast  Lower Spatial Resolution  Normal reconstruction techniques are Filtered Back Projection or Iterative Reconstruction

Back Projection  Back Project each planar image onto three dimensional image matrix

Back Projection  Back Project each planar image onto three dimensional image matrix

Back Projection  Back Project each planar image onto three dimensional image matrix

Back Projection  Back Project each planar image onto three dimensional image matrix

Back Projection  Back Project each planar image onto three dimensional image matrix

Back Projection  More views – better reconstruction  1/r blurring, even with infinite number of views

Filtered Back Projection  Filter planar views prior to back projection  Correction of 1/r blurring requires ‘Ramp’ Filter  Gives increasing weight to higher spatial frequencies  Amplifies Noise

Filtered Back Projection  In Practice  Use modifications of Ramp Filter  Compromise between Noise and Spatial Resolution

Modified Ramp Filter  Multiplication of the ramp filter by another function  Often a gaussian shape  Width of the gaussian affects the “roll off” of the ramp

Filtered Back Projection

Problems with Filtered Back Projection  Back projection is mathematically correct, but real life images require Filtered Back Projection  Back Projection can introduce noise and streaking artefacts  Not good with attenuation correction  Filtered Back Projection can reduce noise and artefacts, but may degrade resolution

Iterative Reconstruction  NOT a new technique  Pre-dates Filtered Back Projection  Computationally Intensive  Long Reconstruction Times  Requires fast computers for reconstruction  Takes around 1 min for a 16-frame gated 128 x 128 matrix cardiac scan

What is Iterative Reconstruction?  Iteration is process of successively better “guesses”  The image processing computer creates an image by refining the expected projections in comparison to those recorded  This form of IR is known as “Maximum Likelyhood Expectation Maximisation” (MLEM)

MLEM Algorithm

Benefits of IR  More accurate modelling of emission/detection  Can include attenuation correction and other information from MR, CT etc  Lower noise

Image Fusion  “Unclear Medicine” images can be registered to CT  Reduces attenuation artefacts  Allows localisation of “fuzzy blob” images  Can improve diagnostic accuracy

Attenuation Correction  X-Ray imaging essentially provides an attenuation “map”  Images formed by different attenuation patterns  NM imaging does not need attenuation  In fact do not want it!  Hybrid imaging (e.g.SPECT-CT) takes attenuation map of CT images and uses to correct for attenuation in 3D NM images

“Jordan”  6 x 500ml saline bags strapped to torso phantom (3 each side) to simulate breast attenuation  Positioned to cover anterior LV

Normal Perfusion: “Jordan” FBPFBPSCIR IRSC IRACIRACSC

Resolution Recovery  Resolution worsens with increasing distance from the collimator  If we can model how this happens, we can build this into our Iterative projections

Resolution Recovery  Better modelling means better images  Fewer counts needed to get acceptable images  Shorter acquisitions  Lower doses

NM Imaging: The PET Camera  PET camera invented in the 1970s  Positron Camera 1959

Early positron study (1953)

Why use positron emitters?  Many of the positron emitters occur in biological molecules (C, N, O, etc.)  Many have small molecular weights relative to the biological molecules they may be used to label (e.g., F) even if they aren’t found there naturally.  PET isotopes can be attached to biologically interesting molecules with no or minimal impact on the behaviour of those molecules in the body.

Positron Emission Tomography  PET isotopes emit positrons rather than gamma rays  Coincidence Imaging  Better Spatial Resolution (Typically 4mm)  Requires Dedicated Equipment  Limited Availability

Annihilation conservation of momentum: before: system at rest; momentum ~ 0 after: two photons created; must have same energy and travel in opposite direction. conservation of energy before: 2 electrons, each with a rest mass of 511keV after: 2 photons, each with 511keV.     decay via positron emission electron/positron annihilation photon annihilation photon

detector Coincidence Imaging line of response (LOR)

Detector Array

Coincidence Imaging - Detector Ring

Types of Coincidence Event

2D to 3D Imaging  Stack multiple rings behind each other  Allows for true 3D imaging  Shorter imaging time so better throughput and fewer motion artefacts

Time of Flight (TOF) PET  Because we are “timing” the arrivals of the photons, we can tell how far apart they are  All photons travel at the speed of light  Simultaneous equation to work out point of origin  Makes “line of response” more like a point

PET Camera Crystals  NaI has too poor stopping power for 511keV  BGO is main material used  Siemens patented LSO *this table was provided by Siemens…