imgsrtm 1.4.4 © 2003-2013 by Turku PET Centre
Computation of parametric images of binding potential (BPnd) from dynamic
PET images in ECAT, NIfTI, or Analyze format applying simplified reference
tissue model (SRTM) [1]:
______ K1' ___________
| | --> | | dCt(t)=
| | <-- | Cr | +R1*dCr(t)
| | k2'|___________| +k2*Cr(t)
| | ____________________ -(k2/(1+BPnd))*Ct(t)
| Cp | K1 | k3 | | Ct(t)=Cf(t)+Cb(t)
| | --> | Cf -------> Cb |
| | <-- | <------- |
| | k2 | | k4 | R1=K1/K1'=k2/k2'
|______| |___________|________| BPnd=k3/k4
The model is transformed to general linear least squares functions [2],
which are solved using Lawson-Hanson non-negative least squares (NNLS)
algorithm [3]. BPnd is estimated directly without division [4].
Parameters:
1) Dynamic image file (corrected for decay)
2) Reference region TAC file
3) Parametric BPnd image file
Options:
-SRTM2
STRM2 method (5) is applied; in brief, traditional SRTM method is
used first to calculate median k2' from all pixels where BPnd>0; then
SRTM is run another time with fixed k2'
-R1=<filename>
Program computes also an R1 image
-k2=<filename>
Program computes also a k2 image
-k2s=<filename>
Program computes also a k2' image
-theta3=<filename> or -t3=<filename>
Program computes also a theta3 image; theta3 = k2/(1+BPnd)+lambda
-rp=<filename>
Program writes regression parameters in the specified image file
-dual=<filename> or -du=<filename>
Program writes number of i in set p in NNLS dual solution vector in
the specified image file
-thr=<threshold%>
Pixels with AUC less than (threshold/100 x ref AUC) are set to zero
default is 0%
-DVR
Instead of BP, program saves the DVR (=BPnd+1) values
-end=<Fit end time (min)>
Use data from 0 to end time; by default, model is fitted to all frames
-h or --help
Print this message and exit
--version or --build
Print software build information and exit
--silent
Program works silently, printing only error and warning messages
--verbose
Program prints more information about what it is doing.
Example:
imgsrtm ua2918dy1.v ua2918cer.dft ua2918bp.v
References:
1. Lammertsma AA, Hume SP. Simplified reference tissue model for PET
receptor studies. NeuroImage 1996;4:153-158.
2. Blomqvist G. On the construction of functional maps in positron emission
tomography. J Cereb Blood Flow Metab 1984;4:629-632.
3. Lawson CL & Hanson RJ. Solving least squares problems.
Prentice-Hall, 1974.
4. Zhou Y, Brasic J, Endres CJ, Kuwabara H, Kimes A, Contoreggi C, Maini A,
Ernst M, Wong DF. Binding potential image based statistical mapping for
detection of dopamine release by [11C]raclopride dynamic PET.
NeuroImage 2002;16:S91.
5. Wu Y, Carson RE. Noise reduction in the simplified reference tissue
model for neuroreceptor functional imaging. J Cereb Blood Flow Metab.
2002;22:1440-1452.
See also:
imgdv,
imgbfbp,
ecat2tif,
imgratio,
ecatunit
Keywords: image, modelling, binding potential, SRTM, SRTM2
This program comes with ABSOLUTELY NO WARRANTY. This is free software, and
you are welcome to redistribute it under GNU General Public License.