PURPOSE: To estimate if CT perfusion parameter values of the esophageal cancer, which were obtained with the deconvolution-based software and maximum slope algorithm are in agreement, or at least interchangeable. METHODS: 278 esophageal tumor ROIs, derived from 35 CT perfusion studies that were performed with a 64-MDCT, were analyzed. "Slice-by-slice" and average "whole-covered-tumor-volume" analysis was performed. Tumor blood flow and blood volume were manually calculated from the arterial tumor-time-density graphs, according to the maximum slope methodology (BF(ms) and BV(ms)), and compared with the corresponding perfusion values, which were automatically computed by commercial deconvolution-based software (BF(deconvolution) and BV(deconvolution)), for the same tumor ROIs. Statistical analysis was performed using Wilcoxon matched-pairs test, paired-samples t-test, Spearman and Pearson correlation coefficients, and Bland-Altman agreement plots. RESULTS: BF(deconvolution) (median: 74.75 ml/min/100g, range, 18.00-230.5) significantly exceeded the BF(ms) (25.39 ml/min/100g, range, 7.13-96.41) (Z=-14.390, p<0.001), while BV(deconvolution) (median: 5.70 ml/100g, range: 2.10-15.90) descended the BV(ms) (9.37 ml/100g, range: 3.44-19.40) (Z=-13.868, p<0.001). Both pairs of perfusion measurements significantly correlated with each other: BF(deconvolution), versus BF(ms) (rS=0.585, p<0.001), and BV(deconvolution), versus BV(ms) (rS=0.602, p<0.001). Geometric mean BF(deconvolution)/BF(ms) ratio was 2.8 (range, 1.1-6.8), while geometric mean BV(deconvolution)/BV(ms) ratio was 0.6 (range, 0.3-1.1), within 95% limits of agreement. CONCLUSIONS: Significantly different CT perfusion values of the esophageal cancer blood flow and blood volume were obtained by deconvolution-based and maximum slope-based algorithms, although they correlated significantly with each other. Two perfusion-measuring algorithms are not interchangeable because too wide ranges of the conversion factors were found.
PURPOSE: To estimate if CT perfusion parameter values of the esophageal cancer, which were obtained with the deconvolution-based software and maximum slope algorithm are in agreement, or at least interchangeable. METHODS: 278 esophageal tumor ROIs, derived from 35 CT perfusion studies that were performed with a 64-MDCT, were analyzed. "Slice-by-slice" and average "whole-covered-tumor-volume" analysis was performed. Tumor blood flow and blood volume were manually calculated from the arterial tumor-time-density graphs, according to the maximum slope methodology (BF(ms) and BV(ms)), and compared with the corresponding perfusion values, which were automatically computed by commercial deconvolution-based software (BF(deconvolution) and BV(deconvolution)), for the same tumor ROIs. Statistical analysis was performed using Wilcoxon matched-pairs test, paired-samples t-test, Spearman and Pearson correlation coefficients, and Bland-Altman agreement plots. RESULTS: BF(deconvolution) (median: 74.75 ml/min/100g, range, 18.00-230.5) significantly exceeded the BF(ms) (25.39 ml/min/100g, range, 7.13-96.41) (Z=-14.390, p<0.001), while BV(deconvolution) (median: 5.70 ml/100g, range: 2.10-15.90) descended the BV(ms) (9.37 ml/100g, range: 3.44-19.40) (Z=-13.868, p<0.001). Both pairs of perfusion measurements significantly correlated with each other: BF(deconvolution), versus BF(ms) (rS=0.585, p<0.001), and BV(deconvolution), versus BV(ms) (rS=0.602, p<0.001). Geometric mean BF(deconvolution)/BF(ms) ratio was 2.8 (range, 1.1-6.8), while geometric mean BV(deconvolution)/BV(ms) ratio was 0.6 (range, 0.3-1.1), within 95% limits of agreement. CONCLUSIONS: Significantly different CT perfusion values of the esophageal cancer blood flow and blood volume were obtained by deconvolution-based and maximum slope-based algorithms, although they correlated significantly with each other. Two perfusion-measuring algorithms are not interchangeable because too wide ranges of the conversion factors were found.
Authors: Inga Zaborienė; Giedrius Barauskas; Antanas Gulbinas; Povilas Ignatavičius; Saulius Lukoševičius; Kristina Žvinienė Journal: Open Med (Wars) Date: 2021-02-05
Authors: Sven Schneeweiß; Marius Horger; Anja Grözinger; Konstantin Nikolaou; Dominik Ketelsen; Roland Syha; Gerd Grözinger Journal: Cancer Imaging Date: 2016-12-15 Impact factor: 3.909