A COMPARATIVE-STUDY OF 3 FAST ALGORITHMS TO ESTIMATE CEREBRAL BLOOD-FLOW AND DISTRIBUTION VOLUME USING N-ISOPROPYL-P-[I-123]IODOAMPHETAMINEAND 2 SPECT SCANS

To estimate regional cerebral blood Bow (rCBF) and distribution volume (V-d) using N-isopropyl-p-[I-123]iodomphetamine (IMP) and two SPECT d ata (early and delayed data) measured at two discrete time points, thr ee fast algorithms are implemented, which are the table look-up method (TLU), the linear least-squares fitting method (LLSF), and the linear search method (LS). A two-compartment model was used as the IMP kinet ic model. These algorithms were applied to the early and delayed data measured by the two scan protocols, t(1) = 12 min, t(2) = 54 min (scan A) and t(1) = 12 min, 12 = 85 min (scan B). The estimated rCBF and V- d values using the present three algorithms were in good agreement wit h those using the nonlinear least-squares fitting technique and dynami c SPECT data. The quantitative value and signal to noise (S/N) ratio o f rCBF images by TLU was not changed whether scan A or scan B was used . However, the S/N of the V-d image by TLU using scan B improved over that using scan A. The same tendency was observed in the results of LL SF and LS. The CPU times for the parametric imaging of CBF and V-d ima ges for one slice (64 x 64 matrix) were 0.04, 0.09, and 0.14 s using T LU, LLSF, and LS, respectively. In conclusion, the present three algor ithms gave reasonably accurate estimates of rCBF and V-d using two SPE CT data, and are well suited for parametric imaging because of their g ood statistical properties and high computational efficiency.