llsqrk2 - tpcclib 0.8.0 © 2023 by Turku PET Centre

LLSQ fitting of reference tissue input model in case of one tissue
compartment. Compartmental model is transformed into general linear least
squares functions.
 
Radioactivity concentration in region(s)-of-interest is given in TTAC file;
data must be corrected for physical decay.
Radioactivity concentration in reference region (RTAC) is given in separate
file, or as name or number of the reference region inside the TTAC file.
Sample times must be in minutes in all data files, unless specified inside
the files. TTAC file should include weights.
 
Usage: llsqrk2 [options] TTAC RTAC results
 
Options:
 -end=<Fit end time (min)>
     Use data from 0 to end time; by default, model is fitted to all frames.
 -w1 | -wf
     Sample weights are set to 1 (-w1) or to frame lengths (-wf);
     by default weights in TTAC file are used, if available.
 -model=<R1 | R2>
     Use two-parameter model (R1, default), or three-parameter model (R2).
 -svg=<Filename>
     Fitted and measured TACs are plotted in specified SVG file.
 -fit=<Filename>
     Fitted regional TTACs are written in specified file.
 -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.
 
References:
1. Blomqvist G. On the construction of functional maps in positron emission
   tomography. J Cereb Blood Flow Metab 1984;4:629-632.
2. Gjedde A, Wong DF. Modeling neuroreceptor binding of radioligands
   in vivo. In: Quantitative imaging: neuroreceptors, neurotransmitters,
   and enzymes. (Eds. Frost JJ, Wagner HM Jr). Raven Press, 1990, 51-79.
3. Lawson CL & Hanson RJ. Solving least squares problems.
   Prentice-Hall, 1974.
 
See also: lhsol, bfmsrtm, taccbv
 
Keywords: TAC, modelling, compartmental model, LLSQ