Systemic transit time correlates with renal cortical perfusion: a preliminary study

Abstract

Abstract Funding Acknowledgements Type of funding sources: None. Introduction We sought to measure systemic transit time (STT) on MRI dynamic sequences of images in patients based on the recirculation time. In a subset of patients, using the same images, when the abdominal aorta and at least part of one kidney was available, we used a 2-compartment filtration model to approximate renal cortical plasma perfusion (RCPF). Methods This is a retrospective study in a single site MR unit. 218 patients underwent a standard myocardial MR imaging protocol on a 1.5 Tesla MRI system including a pulse-gated, free breathing, dynamic first-pass perfusion scan of 100 phases using a saturation recovery turbo-FLASH pulse sequence (TR = 172 ms / TE = 1.1 ms / flip angle = 5°). Motion correction was applied. All patients were injected intravenously with a bolus dose of gadoteratemeglumine followed by a 20 ml saline flush. On the 218 patients studied, 20 patients were excluded due to shunts:n=5, inadequate first pass perfusion signal:n=8, fitting script did not converge on a solution:n=7. Circular ROIs were placed in the RV (Right Ventricle) and LV (Left Ventricle)cavities. The time curves for each cavity’s signals were fitted to a time-sliding 3 component-LogNormal function using an in-house python script based on the lmfit package (Levenberg-Marquardt method) to determine systemic (STT) and pulmonary transit times (PTT). In a subset of 61 patients, an attempt to measure RCPF was undertaken. An elliptic ROI was drawn in the aorta to follow arterial input. A spline polygon ROI was placed on the visible renal cortical tissue. 14 sets of images were rejected for plasma perfusion analysis for different reasons (absence of suitable abdominal aorta image, absence of suitable renal cortical image, motion artifact, …). Plasma perfusion measurements were made using a 2-compartment filtration model. Results We studied 198 sets of MRI dynamic perfusion images. Our population consists of 65,7% men aged 53,0±16,9 (mean± SD) and 34,3% women aged 55,9 ± 14,1 (mean ± SD). Fitting of the experimental data was very good in most cases (mean R² for RV:0.981, max:0.997, min: 0.907, SD:0.014) (mean R² for LV: 0.994, max:0.999, min: 0.975, SD: 0.004). An example of experimental data fitting can be seen in fig. 1. STT values were as follows: mean = 14.3 s, SD = 3.0s, max = 27.1 s, min = 8.7 s. Measures of recirculation time were highly correlated on the RV and LV side (Pearson’s R =0,975; p < 0,001). We found a significant correlation between STT and PTT (Pearson’s R = 0,521; p < 0,001). In the 47 patients where RCPF could be calculated, a significant negative correlation was found between STT and RCPF (Pearson’s R = -0,578; p < 0,001) (fig. 2). Conclusions Systemic transit time can be accurately measured on standard MRI perfusion scans and is negatively correlated with cortical renal plasma perfusion. Assessing systemic transit time using MRI dynamic perfusion imaging of the heart could be a usable surrogate for end-organ perfusion.