Differences in multi-echo chemical shift encoded MRI proton density fat fraction estimation based on multifrequency fat peaks selection in non-alcoholic fatty liver disease patients.

AIM: To compare the performance of multi-echo chemical-shift-encoded (MECSE) magnetic resonance imaging (MRI) proton density fat fraction (PDFF) estimation, considering three different fat frequency peak combinations, for the quantification of steatosis in patients with non-alcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS: The present study was a prospective cross-sectional research of 121 patients with metabolic syndrome and evidence of hepatic steatosis on ultrasound, who underwent a 3 T MRI examination. All patients were studied with a multifrequency MECSE sequence. The PDFF was calculated using six peaks (MECSEp123456), three peaks (MECSEp456), and a single peak (MECSEp5) model. The two simpler fat peak models were compared to the six peaks model, which was considered the reference standard. Linearity was evaluated using linear regression while agreement was described using Bland-Altman analysis. RESULTS: The mean age was 47 (±9) years and BMI was 29.9 (±2.9) kg/m2. Steatosis distribution was 15%/31%/54% (S1/S2/S3, respectively). Compared to MECSEp123456, both models provided linear PDFF measurements (R2= 0.99 and 0.97, MECSEp456 and MECSEp5 respectively). Regression slope (0.92; p<0.001) and mean Bland-Altman bias (-1.5%; 95% limits of agreement: -3.19%, 0.22%) indicated minimal underestimation by using PDFF-MECSEp456. Nonetheless, mean differences in PDFF estimations varied from -1.5% (MECSEp456,p=0.006) to -2.2% (MECSEp5,p<0.001) when compared to full six fat frequencies model. CONCLUSION: Although simpler spectral fat MECSE analysis shows a linear relationship with the standard six peaks model, their variation in estimated PDFF values introduces a low but clinically significant bias in fat quantification and steatosis grading in NAFLD patients.

Impact and risk factors of non-adherence to 5-aminosalicylates in quiescent ulcerative colitis evaluated by an electronic management system.

BACKGROUND AND OBJECTIVE: To determine the impact of non-adherence to 5-Aminosalicylates (5-ASA) on the risk of flares and to identify risk factors of non-adherence. METHODS: Observational, cohort study of ulcerative colitis (UC) patients in clinical remission at least 6 months on 5-ASA monotherapy maintenance prescribed by an electronic management program. Adherence was considered when 80% of the prescribed 5-ASA had been dispensed at the pharmacy. The study analyzed the existence and degree of 5-ASA adherence, disease course, UC phenotypic expression, and 5-ASA dose and regimen, and consumption of non-UC chronic drugs during 2-year follow-up. RESULTS: The study included 274 patients, 49% males with a median age of 38 (27-49) years old. Overall, 41% of patients were non-adherent to 5-ASA. Risk of flares was reduced in the adherent group (36% vs 54%; OR = 0,484; p = 0,004), mainly the mild ones (26% vs 38%; OR = 0,559; p = 0,031). Non-adherence was associated with younger age at diagnosis (32 (26-45) vs 41.5 (21-50), p = 0.000) and no-consumption of other chronic treatments (1.1 vs 2.1; OR = 1709; p = 0,048). CONCLUSION: Non-adherence to 5-ASA evaluated by the pharmaceutical management system was at 41% with a higher risk of relapse. Younger patients and patients who do not receive non-UC chronic treatments showed lower adherence rate.

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use.

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Imaging biomarkers in liver fibrosis. / Cuantificación de la fibrosis hepática mediante biomarcadores de imagen.

There is a need for early identification of patients with chronic liver diseases due to their increasing prevalence and morbidity-mortality. The degree of liver fibrosis determines the prognosis and therapeutic options in this population. Liver biopsy represents the reference standard for fibrosis staging. However, given its limitations and complications, different non-invasive methods have been developed recently for the in vivo quantification of fibrosis. Due to their precision and reliability, biomarkers' measurements derived from Ultrasound and Magnetic Resonance stand out. This article reviews the different acquisition techniques and image processing methods currently used in the evaluation of liver fibrosis, focusing on their diagnostic performance, applicability and clinical value. In order to properly interpret their results in the appropriate clinical context, it seems necessary to understand the techniques and their quality parameters, the standardization and validation of the measurement units and the quality control of the methodological problems.