Background: Liver fibrosis is a public health problem worldwide. There is a need of noninvasive imaging based methods for better diagnosis of this disease. In the current study, we aim to evaluate the potential of T1ρ MRI technique in detecting and characterizing different grades of liver fibrosis in vivo in humans.
Methods: Healthy subjects and patients with liver fibrosis were prospectively recruited for T1ρ MRI of liver on a 1.5 T MR scanner. Single slice T1ρ weighted images were acquired at different spin lock duration (0, 10, 20 and 30 ms) with spin lock amplitude of 500 Hz in a single breath-hold. Additionally, liver's T1ρ images were acquired from five healthy subjects on the same day (n = 2) and different day (n = 2) sessions for test-retest study. Liver biopsy samples from patients were obtained and used to calculate the METAVIR score to define the stage of fibrosis and inflammation grade. T1ρ maps were generated followed by computation of mean and standard deviation (SD) values. Coefficient of variation (COV) of T1ρ values between two MRI scans was computed to determine reproducibility in liver. T test was used to compare T1ρ values between healthy and fibrotic liver. Pearson correlation was performed between stages of liver fibrosis and T1ρ values.
Results: The mean (SD) T1ρ value among subject with healthy liver was 51.04 (3.06) ms. The COV of T1ρ values between two repetitions in the same day session was 0.83 ± 0.8% and in different day session was 5.4 ± 2.7%. T1ρ values in fibrotic liver were significantly higher compared to those of healthy liver (p < 0.05). A statically significant correlation between stages of fibrosis and T1ρ values was observed (r = 0.99, p < 0.05). Inflammation score for one patient was 2 and for remaining patients it was 1.
Conclusions: Proposed T1ρ pulse sequence design and protocol enabled acquisition of a single slice T1ρ weighted images in a single breath-hold and hence mitigated breathing motion related artifacts. Preliminary results have shown the sensitivity of T1ρ values to changes induced by liver fibrosis, and may potentially be used as a clinical biomarker to delineate the stages of liver fibrosis. Further, studies on a large number of subjects are required to validate the observations of the current study. Nevertheless, T1ρ imaging can be easily setup on a clinical scanner to monitor the progression of liver fibrosis and to the evaluate efficacy of anti-fibrotic drugs.