Camilla Scabbio1, Orazio Zoccarato2, Simona Malaspina3, Giovanni Lucignani3,4, Angelo Del Sole5,6, Michela Lecchi1. 1. Health Physics, San Paolo Hospital, Milan, Italy. 2. Unit of Nuclear Medicine, I.C.S. Maugeri S.p.A. SB, Scientific Institute of Veruno IRCCS, Veruno, NO, Italy. 3. Nuclear Medicine Unit, Department of Diagnostic Services, ASST Santi Paolo e Carlo, Milan, Italy. 4. Department of Health Sciences, University of Milan, Milan, Italy. 5. Nuclear Medicine Unit, Department of Diagnostic Services, ASST Santi Paolo e Carlo, Milan, Italy. angelo.delsole@unimi.it. 6. Department of Health Sciences, University of Milan, Milan, Italy. angelo.delsole@unimi.it.
Abstract
AIM: To evaluate the impact of non-specific normal databases on the percent summed rest score (SR%) and stress score (SS%) from simulated low-dose SPECT studies by shortening the acquisition time/projection. METHODS: Forty normal-weight and 40 overweight/obese patients underwent myocardial studies with a conventional gamma-camera (BrightView, Philips) using three different acquisition times/projection: 30, 15, and 8 s (100%-counts, 50%-counts, and 25%-counts scan, respectively) and reconstructed using the iterative algorithm with resolution recovery (IRR) AstonishTM (Philips). Three sets of normal databases were used: (1) full-counts IRR; (2) half-counts IRR; and (3) full-counts traditional reconstruction algorithm database (TRAD). The impact of these databases and the acquired count statistics on the SR% and SS% was assessed by ANOVA analysis and Tukey test (P < 0.05). RESULTS: Significantly higher SR% and SS% values (> 40%) were found for the full-counts TRAD databases respect to the IRR databases. For overweight/obese patients, significantly higher SS% values for 25%-counts scans (+19%) are confirmed compared to those of 50%-counts scan, independently of using the half-counts or the full-counts IRR databases. CONCLUSIONS: AstonishTM requires the adoption of the own specific normal databases in order to prevent very high overestimation of both stress and rest perfusion scores. Conversely, the count statistics of the normal databases seems not to influence the quantification scores.
AIM: To evaluate the impact of non-specific normal databases on the percent summed rest score (SR%) and stress score (SS%) from simulated low-dose SPECT studies by shortening the acquisition time/projection. METHODS: Forty normal-weight and 40 overweight/obesepatients underwent myocardial studies with a conventional gamma-camera (BrightView, Philips) using three different acquisition times/projection: 30, 15, and 8 s (100%-counts, 50%-counts, and 25%-counts scan, respectively) and reconstructed using the iterative algorithm with resolution recovery (IRR) AstonishTM (Philips). Three sets of normal databases were used: (1) full-counts IRR; (2) half-counts IRR; and (3) full-counts traditional reconstruction algorithm database (TRAD). The impact of these databases and the acquired count statistics on the SR% and SS% was assessed by ANOVA analysis and Tukey test (P < 0.05). RESULTS: Significantly higher SR% and SS% values (> 40%) were found for the full-counts TRAD databases respect to the IRR databases. For overweight/obesepatients, significantly higher SS% values for 25%-counts scans (+19%) are confirmed compared to those of 50%-counts scan, independently of using the half-counts or the full-counts IRR databases. CONCLUSIONS: AstonishTM requires the adoption of the own specific normal databases in order to prevent very high overestimation of both stress and rest perfusion scores. Conversely, the count statistics of the normal databases seems not to influence the quantification scores.
Authors: Ernest V Garcia; Tracy L Faber; C David Cooke; Russell D Folks; Ji Chen; Cesar Santana Journal: J Nucl Cardiol Date: 2007-07 Impact factor: 5.952
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