Abstract
OBJECTIVE: The purpose of this study was to assess as a potential means of limiting radiation exposure the effect on perfusion CT values of increasing sampling intervals in lung perfusion CT acquisition. SUBJECTS AND METHODS: Lung perfusion CT datasets in patients with lung tumors (> 2.5 cm diameter) were analyzed by distributed parameter modeling to yield tumor blood flow, blood volume, mean transit time, and permeability values. Scans were obtained 2-7 days apart with a 16-MDCT scanner without intervening therapy. Linear mixed-model analyses were used to compare perfusion CT values for the reference standard sampling interval of 0.5 second with those of datasets obtained at sampling intervals of 1, 2, and 3 seconds, which included relative shifts to account for uncertainty in preenhancement set points. Scan-rescan reproducibility was assessed by between-visit coefficient of variation. RESULTS: Twenty-four lung perfusion CT datasets in 12 patients were analyzed. With increasing sampling interval, mean and 95% CI blood flow and blood volume values were increasingly overestimated by up to 14% (95% CI, 11-18%) and 8% (95% CI, 5-11%) at the 3-second sampling interval, and mean transit time and permeability values were underestimated by up to 11% (95% CI, 9-13%) and 3% (95% CI, 1-6%) compared with the results in the standard sampling interval of 0.5 second. The differences were significant for blood flow, blood volume, and mean transit time for sampling intervals of 2 and 3 seconds (p ≤ 0.0002) but not for the 1-second sampling interval. The between-visit coefficient of variation increased with subsampling for blood flow (32.9-34.2%), blood volume (27.1-33.5%), and permeability (39.0-42.4%) compared with the values in the 0.5-second sampling interval (21.3%, 23.6%, and 32.2%). CONCLUSION: Increasing sampling intervals beyond 1 second yields significantly different perfusion CT parameter values compared with the reference standard (up to 18% for 3 seconds of sampling). Scan-rescan reproducibility is also adversely affected.