Reproducibility of dynamic contrast‐enhanced MRI in human muscle and tumours: comparison of quantitative and semi‐quantitative analysis

Abstract

The purpose of this study was to determine the reproducibility of dynamic contrast-enhanced (DCE)-MRI and compare quantitative kinetic parameters with semi-quantitative methods, and whole region-of-interest (ROI) with pixel analysis. Twenty-one patients with a range of tumour types underwent paired MRI examinations within a week, of which 16 pairs were evaluable. A proton density-weighted image was obtained prior to a dynamic series of 30 T 1 -weighted spoiled gradient echo images every 11.9 s with an intravenous bolus of gadopentetate dimeglumine given after the third baseline data point. Identical ROIs around the whole tumour and in skeletal muscle were drawn by the same observer on each pair of examinations and used for the reproducibility analysis. Semiquantitative parameters, gradient, enhancement and AUC (area under the curve) were derived from tissue enhancement curves. Quantitative parameters (K trans , k ep , v e ) were obtained by the application of the Tofts' model. Analysis was performed on data averaged across the whole ROI and on the median value from individual pixels within the ROI. No parameter showed a significant change between examinations. For all parameters except K trans , the variability was not dependent on the parameter value, so the absolute values for the size of changes needed for significance should be used for future reference rather than percentages. The size of change needed for significance in a group of 16 in tumours for K trans , k ep and v e was À14 to 16%, AE0.20 ml/ml/min (15%) and AE1.9 ml/ml (6%), respectively (pixel analysis), and À16 to 19%, AE0.23 ml/ml/min (16%) and AE1.9 ml/ml (6%) (whole ROI analysis). For a single tumour, changes greater than À45 to 83%, AE 0.78 ml/ml/min (60%) and AE 7.6 ml/ml (24%), respectively, would be significant (pixel analysis). For gradient, enhancement and AUC the size of change needed for significance in tumours was AE0.24 (17%), AE0.05 (6%) and AE0.06 (8%), respectively for a group of 16 (pixel analysis), and AE0.96 (68%), AE0.20 (25%) and AE0.22 (32%) for individuals. In muscle, the size of change needed for significance in a group of 16 for K trans , k ep and v e was À30 to 44%, AE0.81 ml/ml/min (61%) and AE1.7 ml/ml (13%). For gradient, enhancement and AUC it was AE0.09 (20%), AE0.02 (8%) and AE0.03 (12%). v e , enhancement and AUC are highly reproducible DCE-MRI parameters. K trans , k ep and gradient have greater variability, with larger changes in individuals required to be statistically significant, but are nevertheless sufficiently reproducible to detect changes greater than 14-17% in a cohort of 16 patients. Pixel analyses slightly improve reproducibility estimates and retain information about spatial heterogeneity. Reproducibility studies are recommended when treatment effects are being monitored.

Comparative study into the robustness of compartmental modeling and model‐free analysis in DCE‐MRI studies

“…Our results compare reasonably well with other DCE-MRI reproducibility studies by Jackson et al (27), Galbraith et al (28), and Evelhoch et al (20). Jackson et al (27) studied kinetic parameters calculated in the brain and report CoV values of 7.7% for K trans and 6.7% for v e , compared with 7.8% and 14.8% for K trans and v e , respectively, in our brain data.…”

“…This compares with our results of 35%, 30%, and 55%, respectively, for our abdominal data. Our IAUC 60 results are similar to the IAUC 90 results in Galbraith et al (28), implying that our data may have had a better signal to noise ratio, as this was achieved with a 50% shorter dynamic time series. Our tighter 95% CI for K trans may be caused by our use of a longer data acquisition.…”

“…Jackson et al (27) studied kinetic parameters calculated in the brain and report CoV values of 7.7% for K trans and 6.7% for v e , compared with 7.8% and 14.8% for K trans and v e , respectively, in our brain data. Our current study bears similarities with Galbraith et al (28) in that we have studied a selection of abdominal tumors and applied the standard Tofts model (our method 2). They found that the individual 95% CI for K trans was approximately 64%, 17% for v e , and 61% for IAUC 90 .…”

“…Our tighter 95% CI for K trans may be caused by our use of a longer data acquisition. The worse performance of our v e measurement is likely to be caused by the fact that both Galbraith et al (28) and Jackson et al (27) discarded v e values above 1.0, as these indicate an unphysiological estimate of the EES volume (similarlymotivated thresholds were applied to K trans in these studies). However, we chose to keep these high values in our voxel-by-voxel analysis, as we judge these to be a genuine output from the modeling process.…”

DCE‐MRI pixel‐by‐pixel quantitative curve pattern analysis and its application to osteosarcoma

“…Therefore, between-patient and between-system comparisons are difficult. An improved heuristic parameter, called the initial area under the Gd concentration-time curve (IAUGC), has a higher reproducibility yet requires a baseline T 1 measurement (13,23).…”