imgsrtm - tpcclib 0.7.8 © 2022 by Turku PET Centre

Computation of parametric image of binding potential (BPnd) from
dynamic PET image 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].
 
Dynamic PET image and reference region TAC must be corrected for decay.
 
Usage: imgsrtm [Options] imgfile rtacfile bpfile
 
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>
     Programs computes also an R1 image.
 -k2=<filename>
     Programs 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 (=BP+1) values.
 -end=<Fit end time (min)>
     Use data from 0 to end time; by default, model is fitted to all frames.
 -h, --help
     Display usage information on standard output and exit.
 -v, --version
     Display version and compile information on standard output and exit.
 -d[n], --debug[=n], --verbose[=n]
     Set the level (n) of debugging messages and listings.
 -q, --quiet
     Suppress displaying normal results on standard output.
 -s, --silent
     Suppress displaying anything except errors.
 
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, imgratio, imgunit, eframe, imgdecay, img2dft
 
Keywords: image, modelling, binding potential, SRTM, SRTM2, reference input