Background: Pharmacokinetic (PK) models can describe microvascular density and integrity. An essential component of PK models is the arterial input function (AIF) representing the time-dependent concentration of contrast agent (CA) in the blood plasma supplied to a tissue.
Purpose/hypothesis: To evaluate a novel method for subject-specific AIF estimation that takes inflow effects into account.
Study Type: Retrospective study.
Subjects: Thirteen clinical patients referred for spine-related complaints; 21 patients from a study into luminal Crohn's disease with known Crohn's Disease Endoscopic Index of Severity (CDEIS).
Field Strength/sequence: Dynamic fast spoiled gradient echo (FSPGR) at 3T.
Assessment: A population-averaged AIF, AIFs derived from distally placed regions of interest (ROIs), and the new AIF method were applied. Tofts' PK model parameters (including v and K ) obtained with the three AIFs were compared. In the Crohn's patients K was correlated to CDEIS.
Statistical Tests: The median values of the PK model parameters from the three methods were compared using a Mann-Whitney U-test. The associated variances were statistically assessed by the Brown-Forsythe test. Spearman's rank correlation coefficient was computed to test the correlation of K to CDEIS.
Results: The median v was significantly larger when using the distal ROI approach, compared to the two other methods (P < 0.05 for both comparisons, in both applications). Also, the variances in v were significantly larger with the ROI approach (P < 0.05 for all comparisons). In the Crohn's disease study, the estimated K parameter correlated better with the CDEIS (r = 0.733, P < 0.001) when the proposed AIF was used, compared to AIFs from the distal ROI method (r = 0.429, P = 0.067) or the population-averaged AIF (r = 0.567, P = 0.011).
Data Conclusion: The proposed method yielded realistic PK model parameters and improved the correlation of the K parameter with CDEIS, compared to existing approaches.
Level Of Evidence: 3 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2018;47:1197-1204.
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