Fibrosis, defined as the excessive accumulation of extracellular matrix proteins, is a key feature in most chronic inflammatory diseases (1). Fibrosis can affect nearly all tissues and organs in the body. While fibrosis is typically reversible, for example as part of normal wound healing, it can become irreversible when the tissue injury is chronic, severe or repetitive. Permanent scarring can lead to organ failure and ultimately even to death. It is therefore of key importance that patients are routinely monitored to evaluate the severity of fibrosis for effective management of their disease. The reference standard for detection and staging of fibrosis is pathological sampling. However, next to being invasive, needle biopsy procedures only sample a small part of the tissue, while fibrogenesis has shown to be a highly heterogenous process (2). Therefore, there is increasing interest in the development of noninvasive imaging methods for assessment of fibrosis.
From the evaluated imaging techniques, elastography methods measuring tissue stiffness have proved particularly promising to evaluate fibrosis, especially in the liver (3). However, an increase in stiffness is not specific to fibrosis, as other pathological changes including inflammation may also increase tissue stiffness (4). In addition, elastography methods require propagation of external mechanical waves into the tissue of interest. Wave propagation may be limited in obese patients or when applying the elastography method for imaging of organs located deeper in the body. Thus, there remains a need for an alternative imaging method that is more specific to fibrosis and is more widely applicable in all patients and all organs.
The paper by Zhao et al. (5) evaluates the sensitivity of MRI relaxation parameter T1ρ to liver fibrosis in a rat model of non-alcoholic fatty liver disease (NAFLD). T1ρ, defined as the longitudinal relaxation time in the rotating frame, is a measure of the decay of magnetization in the transverse plane in the presence of a spin-lock pulse that is applied parallel to the magnetization vector. As T1ρ is sensitive to low-frequency interactions between macromolecules and bulk water, there has been significant interest in application of T1ρ for measurement of collagen deposition in fibrotic tissues, including in the liver (6,7), kidney (8), myocardium (9) and spleen (10). A significant positive correlation of collagen content with T1ρ has been observed in both kidney (8) and liver tissues (11). While T1ρ has consistently shown an increase in the presence of fibrosis (6-8,11), the exact mechanism of this T1ρ elevation has not been determined. Intuitively, one would expect a decrease in T1ρ in fibrotic tissues, due to increased interactions between extracellular matrix proteins and water protons. The observed increase in T1ρ may therefore be related to other concomitant pathological processes, including inflammation and steatosis in the context of liver fibrosis.
The elegant design of the study by Zhao et al. allowed for more detailed elucidation of the pathological changes that drive T1ρ elevation in NAFLD. MRI and histopathological evaluation of the liver were performed at several time points during methionine and choline-deficient (MCD) diet in the NAFLD group. A separate control group was also included. This study design allowed for separate analysis of the influence of fibrosis, inflammation and steatosis on liver T1ρ. A highly significant positive correlation was found between collagen content and liver T1ρ (r=0.82, P<0.0001), while the correlation of liver T1ρ with inflammation was nonsignificant (P=0.1). In a subgroup of rats, with similar collagen content, trends toward negative correlation of liver T1ρ with fat content were observed. Interestingly, another subset analysis was performed in rats without positive inflammation score. There continued to be a high significantly positive correlation of collagen content with liver T1ρ in this subset of rats, suggesting that the T1ρ elevation in liver fibrosis is indeed directly related to collagen deposition.
While this study provides convincing data on the direct association of T1ρ with collagen content, the underlying biophysical mechanism of collagen causing an increase in T1ρ was not evaluated. In several studies, it has been suggested that changes in chemical exchange rates due to collagen deposition could explain the observed T1ρ contrast in fibrotic tissues (12,13). However, the previous studies in which T1ρ was evaluated at a single spin-lock strength do not allow for quantitative analysis of exchange rates. For such analysis, a so-called T1ρ dispersion analysis is needed, which includes T1ρ measurements at a multitude of spin-lock strengths. Recently, a first report on T1ρ dispersion analysis in the context of kidney fibrosis was published (14). A drop in R2 (1/T2) and R1ρ (1/T1ρ) at different spin-lock strengths was observed in fibrosis. In addition, it was found that parameters related to chemical exchange significantly changed during the progression of fibrosis. A highly significant reduction in the exchange parameter was observed, which is thought to be related to the slow exchange rate of hydroxyl protons in collagen (14). This dispersion analysis thus provides strong evidence on the sensitivity of T1ρ to collagen deposition. Nevertheless, other pathological changes such as inflammation could also have contributed to the overall reduction of R2 and R1ρ. The evaluated exchange parameters may therefore be more specific to collagen deposition, as this dispersion analysis is highly sensitive to the chemical components present in the tissue of interest.
In summary, these recent studies provide further evidence on the sensitivity of T1ρ to collagen deposition in fibrosis. Nevertheless, confounding factors including inflammation and other pathological features dependent on the disease and tissue of interest may not be ignored. Analysis of chemical exchange rates from T1ρ dispersion analysis seems to be an elegant solution to improve the specificity of T1ρ metrics to fibrosis. Further research in this field is clearly warranted, including additional optimization of the performance of T1ρ for fibrosis imaging as well as reduction in acquisition times in particular when a multitude of spin lock strengths needs to be acquired.
Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims-20-1089). The author has no conflicts of interest to declare.
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