1. Gated Myocardial SPECT
Technical overview and our experiences
J O’Brien & WH Thomson, City Hospital, Dudley Road, Birmingham

2. Introduction Began gating SPECT MPI studies in 2002.
Gating has proved useful to patient management.
However , some technical pitfalls came up along the way!
MPI protocol adjusted to minimise such problems
Would like to share these with PNUG, with discussion (hopefully!) to help us optimise our protocol.

3. Introduction to Gating
During a myocardial perfusion SPECT acquisition, the gamma camera records the photons at multiple projections around the patient.
In an UNGATED acquisition, at each projection one static image is acquired
In an ECG GATED acquisition, at each projection several dynamic images spanning the length of the cardiac cycle are acquired at equal time intervals
Gating enables us to track the motion of the heart.

4. Introduction to Gating (cont)
Gated SPECT data can be used by special software packages to give extra information on the heart such as:
Ejection Fraction (EF)
End Diastolic Volume (EDV)
End Systolic Volume (ESV)
Regional wall motion

5. What about our Ungated data used for stress/rest perfusion images?
Its not lost (hopefully!). Simply sum up gated data
Gated data
Ungated data

6. Patient Setup
Connect patient to ECG trigger unit with electrodes at left leg (LL) , right arm (RA) , and left arm (LA) (MCL1 - modified central lead one)
Connect trigger unit to R-wave input on camera.

7. General theory of gated acquisition
The acquisition starts with the R-wave on the ECG, corresponding to End Diastole.
One cardiac cycle, represented by the R-R interval is divided into multiple frames of equal duration.
Image data for each of the frames are acquired repeatedly, over many cardiac cycles and stored separately on computer.

8. A gated acquisition ECG Trace
BEAT 3
BEAT n
BEAT 2
BEAT 1
BEAT 4
ECG Trace
e.g. R-R interval = 800msec
8 dynamic time frames each equal to 800 / 8 = 100msec
8 dynamic time frames produced at each beat
To achieve adequate counts per frame, must acquire gated data over several cardiac cycles
Images courtesy of: Gated Myocardial Perfusion SPECT: Basic Principles, Technical Aspects, and Clinical Applications. J Nucl Med Technol 2004; 32:179–187

9. Heartbeat Variation and Tolerance
Several cardiac cycles per projection are needed.
If patient R-R interval varies significantly during these cycles, then ‘mixing’ of counts from adjacent time frames occurs degrading the gated data.
We can combat this by rejecting beats that are significantly shorter and longer than mean R-R interval
Achieve this by setting ‘limits’ around the Mean R-R interval
Typical limits ± 20% of the Mean R-R interval

10. How do we determine the Mean R-R and its limits?
Philips Odyssey computers have the ability to plot a histogram illustrating the range of R-R intervals
R-R Interval in milliseconds
Height of peak indicates how many beats fell into that interval
Accepted
Rejected
By acquiring the histogram over seconds, the user may visually find mean R-R and set limits before acquisition starts.
This also determines time per frame

11. Tuning
R-R Interval in milliseconds
R-R Interval in milliseconds

12. Other parameters to set..
How many frames.. 8 or 16 ?

13. How many frames?
Try to balance ‘temporal resolution’ against counts per frame
Too many frames and counts per frame will be too low , leading to ‘noisy’ images.
Too few frames will result in ‘temporal blurring’ – resulting in the inability to correctly visualise cardiac motion
Routinely 8 frames are sufficient

14. Other parameters to set..
How many frames.. 8 or 16 ?
Set length of each projection to be based on Time or Gated beats..?

15. Time or Gated beats?
Time per projection ensures consistent acquisition time per patient. But in Arrhythmia, a loss of counts will occur (see later)
Gated beats per projection ensure adequate and consistent count density in the presence of Arrhythmia. But acquisition time will increase (very bad for patient).
Locally we use Time because extra time is already required to do attenuation correction.

17. End results
For the majority everything is all OK!

18. Experiences to share!
Heart rate can slow down during scan as patient relaxes.
Make use of R-R Tracking option on Philips Axis. This moves R-R limits at each projection, over the average R-R interval from previous projection. AUTOTUNE!

19. Tracking
Projection 12 of 68
Projection 13 of 68

20. Experiences to share!
Heart rate can slow down during scan as patient relaxes.
Make use of R-R Tracking option on Philips Axis. This moves R-R limits at each projection, over the average R-R interval from previous projection. AUTOTUNE!
Also, we display the R-R Histogram on the odyssey acquisition screen during the scan.

21. R-R Histogram during scan
But histogram is NOT stored for later viewing (as far as we’re aware)

22. Experiences to share!
Watch out for loose ECG lead or poor electrode-skin contact
A poor R-R signal (or even no R-R signal!) results in reduced / zero counts. This adversely affects gated and ungated data to various degrees ….

23. Experiences to share! Cine looks OK Sinogram and linogram look odd
streaks are present in many projections
Why? Poor electrode connection during the scan
New electrodes fitted

24. Experiences to share! Repeat scan shows no streaks Cine looks OK
Sinogram and linogram look odd
streaks are present in many projections
Why? Poor electrode connection during the scan
New electrodes fitted
Repeat scan shows no streaks
Repeated Study

25. Shorts
Poor
Good
V L As
Poor
Good

26. Experiences to share! To improve gating technique, we..
Use the sinogram to check quality of gating
Do not trust cine for checking
Try to get good electrode-skin contact
Position leads so that they can’t be moved or pulled.

27. Experiences to share! You can get away with a few poor projections..!
Example with a single poor projection on both heads
Use ‘average of two nearest neighbours’ function available in Image Algebra program to help out.

28. Make new frame based on average of two neighbours

29. Experiences to share! How many poor projections can we get away with?!
Use ‘replace counts’ function to artificially degrade good ungated data to understand effect.
Removed 1, 2, 3, 4, and 5 pairs of projections!

30. Normal
1 pair removed
2 pairs..
3 pairs..
4 pairs..
5 pairs..

31. Experiences to share! How many poor projections can we get away with?!
Use ‘replace counts’ function to artificially degrade good ungated data to understand effect.
Removed 1, 2 , 3 , 4, and 5 pairs of projections
Hard to spot the difference! Slight degradation in inferior wall.
Quite robust probably because AXIS acquires 204 degrees worth of data in cardiac mode

32. Experiences to share!
Check edge detection has worked with ungated and gated data in Software analysis package
Bowel activity near inferior wall can play havoc with gated data, severely affecting results:

33. Good detection

34. Bad detection

35. Reasonable results
Contours look OK
Typical results
Typical shape

36. Poor results
Contours look wrong
strange results
Weird shape!

37. Experiences to share!
Check edge detection has worked with ungated and gated data in Software analysis package
Bowel activity can play havoc with gated data, severely affecting results:
Always check edge detection is correct in the packages for all data that is inserted in to them.

38. Experiences to share! What to do with Arrhythmia patients?
Amount of rejected beats not displayed during acquisition setup. However it is displayed during acquisition!
How many bad beats to classify patient as having Arrhythmia?
How many can we get away with? Don’t know!
The general consensus is to avoid gating Arrhythmic patients! Principle of test is to detect reversible ischemia. This ‘could be’ severely compromised.
Often Arrhythmia is not marked on refferal card and is picked up at first visit by stress-room staff, who forewarn imaging room staff.
Technicians understand that if they’re unsure about amount of Arrhythmia, call second opinion. Its OK not to gate patient.

39. Summary of local protocol changes
Always check sinogram for motion AND gating errors
Avoid patients with Arrhythmia. Sometimes not mentioned on referral so imaging staff tend to be forewarned by stress-room staff.
Ok to lose some frames (but not too many!)
Improve ECG connection technique
Always check edge detection in gated analysis software
Display the R-R Histogram during aquisition
Make use of R-R Tracking option
Ask for help if unsure about gating – its OK not to gate patient

40. - Future optimisations - QC of a Gated System
Few recommendations in literature. None in IPEM 86
Our EBME dept placed test input with known R-R interval (bpm) into trigger unit. Check R-R histogram for correlation.
Looking to custom designed phantoms, such as those being developed at Coventry Walsgrave in partnership with Durex™.

41. - Future optimisations - Motion correct gated data
Tricky to motion correct gated data using sinogram due to poor counts Solution already done by Philips Batch correct ungated and gated data together Available in Odyssey LX System

42. - Future optimisations - Check professional body advice
Techniques Covered – slide nicked from M Smith
BNCS
SNM
ASNC
MPI -Planar 
MPI - SPECT
MPI - Gated 
MUGA
First Pass
All downloadable free of charge off net.
 = Covered in detail  = Mentioned

43. - Future optimisations - 3D post filtering
Currently filter the gated data using ungated settings Gated data has more noise, so it seems reasonable to change cutoff to smooth data more. Bill’s the expert on this!

44. - Future optimisations - More Choice of Acquisition Parameters
Beat rejection options:
None (what we use already)
Single bin
Percentage
Interval
- end up with three sets of projection cardiac data. Short , normal, long.
Single F/B
- Real time gated list mode

45. Single F/B – gated list mode
This menu choice is only offered when you set the SiteEnv variable FB_GATED to use gated list mode (why?).
Data is acquired in list mode and then re-framed in real time into images of equal duration.
Two separate gated sequences are created.
One is created by gating forward from the R-wave that marks the beginning of the cardiac cycle.
The other is created by gating backward from the R-wave that marks the end of the cardiac cycle.
The first 2/3 of the forward sequence is added to the last 1/3 of the backward sequence. The composite sequence is then added to the summed gated sequence.
Sounds good.