LAUSR

Renal fibrosis may start and silently progress for a long time before there are indications of kidney disease. Loss of peritubular capillaries and impaired oxygen diffusion due to fibrosis result in hypoxia and excessive inflammatory response, which, in turn, aggravate renal scarring. Currently, biopsy is the only clinically-accepted method for the assessment of the fibrotic burden, but it is used infrequently due to its invasive nature and the risk of complications. In addition, limitations of the frequency of collecting samples and their volumes prevent the acquisition of extensive information, especially given the heterogeneity of fibrosis. In contrast, imaging-based methods are generally noninvasive, and allow the frequent acquisition of comprehensive and detailed information. However, despite significant efforts, the development of a reliable imaging technique to assess renal fibrosis remains a work in progress. Perhaps magnetic resonance imaging (MRI) is the most promising modality for this challenge due to its ability to provide versatile morphology and function-associated, soft-tissue contrast. I encourage those interested in this topic to read the article entitled “Could MRI be used to image kidney fibrosis?” by Leung et al. To date, a broad range of surrogate markers have been examined, including tissue stiffness, diffusion, oxygenation, and perfusion. However, a common limitation to using surrogate markers is that their variations may not be specific only to the quantity of interest, but they also may be influenced by other factors. In recent years, several investigators have explored the use of magnetization transfer (MT) MRI to detect renal fibrosis. MT is sensitive to the exchange of water between the macromolecules and the surrounding pool of free water. Excessive collagen, deposited in fibrotic tissues, and the ability of MT to directly link that to the MR contrast have been the rationales behind choosing this approach. Early studies in mice and swine models of renal artery stenosis (RAS) demonstrated the ability of MT to detect fibrosis, and also showed a good spatial concordance of the MT ratio (MTR) maps with histology. However, a limitation of MTR is that it is dependent on some attributions of tissue relaxation and the pulse sequence. In addition, characterizing the z-spectrum generally requires tedious measurements over a broad set of off-resonance frequencies. To avoid this, in a mouse RAS model, we investigated the implementations of on-resonance MT in the quantitative framework that was proposed by Gloor et al. We used large regions of interest (ROIs) and found that the pool size ratio (PSR) in RAS tended to be higher than that in the control. Later, Wang et al used the quantitative MT (qMT) methodology of Ramani et al, and found significantly higher PSR values, even in animal models with a mild-to-moderate level of fibrosis, such as in the db/db mice model of diabetic nephropathy, when traditional large ROIs were replaced by threshold-based small ROIs. In hHBEGF mice, they found that threshold-based PSR had higher sensitivity and specificity compared with other relaxationand MT-driven markers. In this issue of JMRI, an article by Jiang et al demonstrates further promising results regarding the use of PSR as a biomarker for the quantification of the collagen content of renal tissue. The results of that study showed that a strong correlation exists between PSR and the renal fibrosis, quantified from histology in the cortex, the outer medulla, and the inner medulla plus papilla. Moreover, despite variations in tissue relaxations, the correlation had a consistent linear conversion slope in all three compartments. The growing interest in using qMT, promising results, and potential consensus over using PSR as the biomarker are good news and perhaps an indication of significant progress. While the studies mentioned above, including the current study by Jiang et al, have addressed many of the early issues regarding sensitivity and quantification, the concerns about the limited specificity of MT has been addressed less often. Although collagen is likely the foremost MT contributor in heavily fibrotic tissues, in early disease with mild and sporadic fibrosis, the impacts of MT by other macromolecules could potentially be significant, and should be taken into account. While the development of MT sequences with enhanced selectivity remains a challenge, developing models to identify and separate the MT effect from various contributors may be