SAT-667 The Relationship Between Metabolic Dysfunction-Associated Steatotic Liver Disease and Renal Steatosis in Terms of MRI Findings, Biochemical Fibrosis Scoring Systems and Metabolic Markers

Abstract Disclosure: D.T. Atikcan Simsek: None. T. Cankurtaran: None. B. Yagdiran: None. F. Akbiyik: None. E. Kose Hamidi: None. A. Sık: None. M. Senay Ozcalik: None. O. Turhan İyidir: None. A. Nar: None. A. Agildere: None. N. Bascil Tutuncu: None. Introduction: The aim of this study is to determine the correlations between magnetic resonance imaging (MRI) and ultrasound (US) parameters, The Fibrosis-4 (FIB4) and Enhanced Liver Fibrosis (ELF) scores, and metabolic markers in diabetic and prediabetic patients, with the goal of improving diagnostic strategies for Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). MASLD needs non-invasive diagnostic methods. FIB4 score, MRI and US evaluations are part of this approach, while ELF test, which assesses hyaluronic acid, procollagen III amino-terminal peptide (PIIINP), and tissue inhibitor of metalloproteinases-1, provides information about fibrosis. It is also aimed to investigate the correlation between liver steatosis, fibrosis, renal steatosis, and microalbuminuria in diabetic and prediabetic cases. Method: In our center, clinical data were prospectively collected from diabetic (n=149) and pre-diabetic, (n=48), including MRI and US hepatosteatosis and renal steatosis grading, metabolic parameters (insulin, fasting blood glucose, plasma lipids, microalbuminuria, HOMA-IR score), and ELF and FIB-4 scores. Correlations among these variables were investigated using Pearson correlation, logistic regression and ANOVA. Results: In our patients, no correlation was found between HbA1c and ELF or FIB4. Hepatosteatosis on US showed a positive correlation with MRI hepatosteatosis staging values. In diabetic patients, as hepatosteatosis increased on US, microalbuminuria also increased. No correlation was found between steatosis and fibrosis. The degree of liver steatosis is not correlated with renal steatosis. However, the development of liver fibrosis, particularly an increase in PIIINP levels, is associated with renal steatosis. Also a correlation exists between renal steatosis and microalbuminuria. There is no significant difference in the degree of renal steatosis between diabetic and prediabetic. Conclusion: In our study, a strong correlation was found between MRI and US for MASLD. The lack of significant correlation between MRI hepatosteatosis grade and fibrosis markers supports the idea that the mechanisms of steatosis and fibrosis development in the liver involve different pathological processes. A noteworthy finding was the correlation between the FIB4 score, which is more sensitive in diabetic patients, and the ELF score. Independent of glucose regulation, especially in cases with insulin resistance, MASLD can be detected through MRI and US. However, advanced analyses like ELF, are required for the detection of fibrosis. Liver fibrosis, renal steatosis, and microalbuminuria are pathological conditions that are interrelated. PIIINP could serve as a potential marker for demonstrating the liver-kidney relationship. Further comprehensive studies are needed to explore these connections. Presentation: Saturday, July 12, 2025

Authors

Institutions

Publication Details

Journal
Journal of the Endocrine Society
Published
2025-10-01
DOI
https://doi.org/10.1210/jendso/bvaf149.102
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SAT-667 The Relationship Between Metabolic Dysfunction-Associated Steatotic Liver Disease and Renal Steatosis in Terms of MRI Findings, Biochemical Fibrosis Scoring Systems and Metabolic Markers

Ayhan Şık, Filiz Akbıyık, Tijen Cankurtaran, Neslihan Başçıl Tütüncü et al.
Journal of the Endocrine Society
Liver Disease Diagnosis and Treatment
article

SAT-667 The Relationship Between Metabolic Dysfunction-Associated Steatotic Liver Disease and Renal Steatosis in Terms of MRI Findings, Biochemical Fibrosis Scoring Systems and Metabolic Markers

Ayhan Şık, Filiz Akbıyık, Tijen Cankurtaran, Neslihan Başçıl Tütüncü, Merve Şenay Özçalık, Burak Yağdıran, Aslı Nar, Özlem Turhan İyidir, Deniz Turkum Atikcan Şimşek, Ahmet Muhteşem Ağıldere, Ece Gul Kose Hamidi
article en

Abstract

Abstract Disclosure: D.T. Atikcan Simsek: None. T. Cankurtaran: None. B. Yagdiran: None. F. Akbiyik: None. E. Kose Hamidi: None. A. Sık: None. M. Senay Ozcalik: None. O. Turhan İyidir: None. A. Nar: None. A. Agildere: None. N. Bascil Tutuncu: None. Introduction: The aim of this study is to determine the correlations between magnetic resonance imaging (MRI) and ultrasound (US) parameters, The Fibrosis-4 (FIB4) and Enhanced Liver Fibrosis (ELF) scores, and metabolic markers in diabetic and prediabetic patients, with the goal of improving diagnostic strategies for Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). MASLD needs non-invasive diagnostic methods. FIB4 score, MRI and US evaluations are part of this approach, while ELF test, which assesses hyaluronic acid, procollagen III amino-terminal peptide (PIIINP), and tissue inhibitor of metalloproteinases-1, provides information about fibrosis. It is also aimed to investigate the correlation between liver steatosis, fibrosis, renal steatosis, and microalbuminuria in diabetic and prediabetic cases. Method: In our center, clinical data were prospectively collected from diabetic (n=149) and pre-diabetic, (n=48), including MRI and US hepatosteatosis and renal steatosis grading, metabolic parameters (insulin, fasting blood glucose, plasma lipids, microalbuminuria, HOMA-IR score), and ELF and FIB-4 scores. Correlations among these variables were investigated using Pearson correlation, logistic regression and ANOVA. Results: In our patients, no correlation was found between HbA1c and ELF or FIB4. Hepatosteatosis on US showed a positive correlation with MRI hepatosteatosis staging values. In diabetic patients, as hepatosteatosis increased on US, microalbuminuria also increased. No correlation was found between steatosis and fibrosis. The degree of liver steatosis is not correlated with renal steatosis. However, the development of liver fibrosis, particularly an increase in PIIINP levels, is associated with renal steatosis. Also a correlation exists between renal steatosis and microalbuminuria. There is no significant difference in the degree of renal steatosis between diabetic and prediabetic. Conclusion: In our study, a strong correlation was found between MRI and US for MASLD. The lack of significant correlation between MRI hepatosteatosis grade and fibrosis markers supports the idea that the mechanisms of steatosis and fibrosis development in the liver involve different pathological processes. A noteworthy finding was the correlation between the FIB4 score, which is more sensitive in diabetic patients, and the ELF score. Independent of glucose regulation, especially in cases with insulin resistance, MASLD can be detected through MRI and US. However, advanced analyses like ELF, are required for the detection of fibrosis. Liver fibrosis, renal steatosis, and microalbuminuria are pathological conditions that are interrelated. PIIINP could serve as a potential marker for demonstrating the liver-kidney relationship. Further comprehensive studies are needed to explore these connections. Presentation: Saturday, July 12, 2025

Journal of the Endocrine SocietyVol. 9(Supplement_1)
Bilkent University (TR), Başkent University (TR), Başkent University Hospital (TR)
Openalex Percentile: Top 59%
Liver Disease Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.