title: Use of the BasGan algorithm for [123I]FP-CIT SPECT quantification: a phantom study.
abstract: OBJECTIVE
  The BasGan algorithm has been specifically developed for semi-automatic quantification of [123I]FP-CIT SPECT studies. The aim of this work was to evaluate the software linearity and its dependence on the main acquisition parameters of the SPECT study.
  
  
  METHODS
  The anthropomorphic Striatal Phantom filled with different striatal to background activity concentration ratios was used to verify software linearity. The software response was studied with different acquisition parameters and system configurations. For this purpose, phantom studies were performed with varying radius of rotation, pixel size, number of projections and with different collimator types. For each configuration the tomographic spatial resolution was also determined using the Triple Line Source Phantom. The reconstructed SPECT images were corrected for attenuation and scatter.
  
  
  RESULTS
  The BasGan outcome highly correlates with the real Specific Binding Ratio when fixed gamma camera configuration and reconstruction method are used. However, the software quantification depends on system configuration and decreases with increasing partial volume effect. A comparison of the BasGan output with tomographic spatial resolution data for each configuration shows that the software response highly correlates with this quantity.
  
  
  CONCLUSIONS
  The BasGan algorithm is a free, easy-to-use and solid tool for quantification of [123I]FP-CIT images. The software outcome depends on system configuration, but highly correlates with tomographic spatial resolution. Then, the measurement of this quantity turns out to be a simple method to normalize the BasGan quantification for different imaging devices, making it possible the use of available reference values for normal subjects and multicentre studies.
authors.affiliation: Department of Health Physics, Ospedali Riuniti di Bergamo, Bergamo, Italy - glpoli@ospedaliriuniti.bergamo.it.
authors.forename: G L
authors.initials: GL
authors.lastname: Poli
authors.forename: C
authors.initials: C
authors.lastname: Bianchi
authors.forename: U P
authors.initials: UP
authors.lastname: Guerra
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003342:Corpus Striatum / Q000000981:diagnostic imaging* / Q000378:metabolism*; D050483:Dopamine Plasma Membrane Transport Proteins / Q000378:metabolism*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008959:Models, Neurological; D019047:Phantoms, Imaging; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014018:Tissue Distribution; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation / Q000379:methods*; D014326:Tropanes / Q000493:pharmacokinetics*
chemical_list: D050483:Dopamine Plasma Membrane Transport Proteins; D019275:Radiopharmaceuticals; D014326:Tropanes; C087552:2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane