Enabling free‐breathing background suppressed renal pCASL using fat imaging and retrospective motion correction

Abstract

Purpose For free‐breathing renal perfusion imaging using arterial spin labeling (ASL), retrospective image realignment has been found essential to reduce subtraction artifacts and, independently, background suppression has been demonstrated to reduce physiologic noise. However, negative results on ASL precision and accuracy have been reported for the combination of both. In this study, the effect of background suppression ‐level in combination with image registration on free‐breathing renal ASL signal quality, with registration either on ASL‐images themselves or guided by additionally acquired fat‐images, was investigated. The results from free‐breathing acquisitions were compared with the reference paced‐breathing motion compensation strategy. Methods Pseudocontinuous ASL (pCASL) data with additional fat‐images were acquired from 10 subjects at 1.5T with varying background suppression levels during free‐breathing and paced‐breathing. Images were registered using the ASL‐images themselves (ASLReg) or using their corresponding fat‐images (FatReg). Temporal signal‐to‐noise ratio (tSNR) served to evaluate precision and perfusion weighted signal (PWS) to assess accuracy. Results In combination with image registration, background suppression significantly improved tSNR by 50% ( P < .05). For heavy suppression, ASLReg and FatReg showed similar performance in terms of tSNR and PWS. Background suppression with two inversion pulses induced a small, nonsignificant ( P > .05) PWS reduction, but increased PWS accuracy. When applying heavy background suppression, free‐breathing acquisitions resulted in similar ASL‐quality to paced‐breathing acquisitions. Conclusion Background suppression was found beneficial for free‐breathing renal pCASL precision without compromising accuracy, despite motion challenges. In combination with ASLReg or FatReg, background suppression enabled clinically viable free‐breathing renal pCASL.

Consensus-based technical recommendations for clinical translation of renal ASL MRI

“…Issues such as repeatability and validation of ASL with alternative methods to measure renal perfusion were extensively addressed therewith and, therefore, will not be covered in the present manuscript. The previous literature review [8] as well as 12 studies published in the intervening period [11][12][13][14][15][16][17][18][19][20][21][22], the results of a series of surveys and the discussions that took place at the in-person meetings form the basis for the final recommendations presented here.…”

“…A labelling duration of 1.5-1.8 s is recommended [R5.2] [11,21,[55][56][57][58][59]. Longer labelling durations would provide higher SNR for a given image, but would also lengthen the TR, reducing the number of averages acquired per unit time and increasing the power deposition.…”

“…Longer labelling durations would provide higher SNR for a given image, but would also lengthen the TR, reducing the number of averages acquired per unit time and increasing the power deposition. A PLD of 1.2-1.5 s is recommended in single PLD acquisitions [R5.11] [11,21,55,[57][58][59][60]. This PLD should allow for all the labeled blood to arrive at the renal parenchyma before image acquisition in most subjects, thus providing perfusion weighted data which can be quantified to yield quantitative renal blood flow values.…”

“…However, the latter reported that in the body, in the presence of respiratory motion, this improvement was at the expense of SNR when compared to using image registration. Nevertheless, recent studies have demonstrated the capability of BGS to improve the temporal signal-to-noise ratio (tSNR) and image quality of ASL data and shown image registration to be effective even in data acquired with heavy BGS [11,21]. For these reasons, we recommend the use of BGS for renal ASL [R7.2], and generally 2 to 4 BGS adiabatic inversion pulses have been employed in previous studies.…”

“…Another class of preprocessing methods are motion correction techniques typically based on image registration, which can be used in conjunction with outlier rejection. These methods are widely used in renal ASL [11,18,63,75,76] (among others) to realign the kidneys and ensure their position is consistent throughout the ASL time series and, therefore, reduce subtraction errors. They have been shown to reduce image artefacts, reduce partial volume effects between cortex and medulla, and improve the SNR of the perfusion-weighted signal and the repeatability of perfusion measurements.…”