lhsrtm 2.0.2 © 2002-2005 by Turku PET Centre
Estimates the BP from simplified reference tissue model [1]:
______ K1' ___________
| | --> | | dCt(t)=
| | <-- | Cr | +R1*dCr(t)
| | k2'|___________| +k2*Cr(t)
| | ____________________ -(k2/(1+BP))*Ct(t)
| Cp | K1 | k3 | | Ct(t)=Cf(t)+Cb(t)
| | --> | Cf -------> Cb |
| | <-- | <------- |
| | k2 | | k4 | R1=K1/K1'=k2/k2'
|______| |___________|________| BP=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]. BP is estimated directly without division [4], but if
fitted TACs are saved, those are calculated from original model setting.
Parameters:
1) Tissue TAC file (*.dft)
2) Name of reference region in tissue file, or name of file
containing reference tissue TAC
3) Fit end time (duration)
4) Result file (existing file is overwritten)
5) Fitted regional TAC file (optional)
Options:
-DVR
Reports BP+1=DVR instead of BP.
-mid[=<y|n>]
Mid frame times are used (y) or not used (n, default) even if frame
start and end times are available.
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. Oikonen V. Model equations for reference tissue compartmental models.
http://www.turkupetcentre.net/reports/tpcmod0002.pdf
Warning! BP seems to be underestimated with noisy data.
Weights are used if found in TAC data file.
See also:
dftweigh,
logan,
regbfbp,
imgsrtm,
fit_srtm,
dft2ps
Keywords: DFT, modelling, binding potential, distribution volume