Prediction of outcomes in patients with metabolic dysfunction-associated steatotic liver disease based on initial measurements and subsequent changes in magnetic resonance elastography

Abstract

Background The prognosis of metabolic dysfunction-associated steatotic liver disease (MASLD) is strongly associated with liver fibrosis. We aimed to investigate whether liver stiffness measurement (LSM) and changes in LSM (ΔLSM) on magnetic resonance elastography (MRE) can predict clinical events in patients with MASLD. Methods We included 405 patients with MASLD who underwent at least two MREs. The patients were divided into five groups corresponding to fibrosis stages (0–4) based on initial LSM and classified as progressors (ΔLSM ≥ 19%) or non-progressors (ΔLSM < 19%) based on the difference between the first and last LSM. Results The mean follow-up period was 72.6 months, and the mean interval between MREs was 23.5 months. There were 52 (12.8%) progressors and 353 (87.2%) non-progressors. The initial LSM was significantly associated with the cumulative probabilities of decompensated cirrhosis, hepatocellular carcinoma (HCC), liver-related events, extrahepatic malignancies, and overall mortality but not with cardiovascular disease. Progressors had significantly higher hazard ratios (HRs) for decompensated cirrhosis, HCC, and liver-related events but not for extrahepatic malignancies, cardiovascular disease, or overall mortality. Among patients without cirrhosis, the HR for developing cirrhosis among progressors was 60.15. Progressors had a significantly higher risk of liver-related events, even in the low initial LSM (fibrosis stage 0–2) subgroups. Conclusions Both initial LSM and ΔLSM can predict liver-related events in patients with MASLD, even for low initial LSM. This integrated assessment can allow more detailed risk stratification compared with single LSM assessments and identify high-risk patients with MASLD among those previously considered as low risk.

Liver Stiffness Values to Predict Occurrence and Recurrence of Hepatocellular Carcinoma

“…Future research directions in non-invasive evaluation techniques for HCC are probably represented by the development of multiparametric approaches or the integration of imaging modalities. A very recent study [ 49 ] in a larger cohort of Asian patients with MASLD evaluated whether the combined assessment of LSV at baseline and its changes during the follow-up period prognosticates outcomes. Kobayashi et al [ 49 ] found that baseline LSV was associated with decompensated cirrhosis, HCC, all liver-related events, extrahepatic malignancies, and all-cause mortality except cardiovascular mortality.…”

“…A very recent study [ 49 ] in a larger cohort of Asian patients with MASLD evaluated whether the combined assessment of LSV at baseline and its changes during the follow-up period prognosticates outcomes. Kobayashi et al [ 49 ] found that baseline LSV was associated with decompensated cirrhosis, HCC, all liver-related events, extrahepatic malignancies, and all-cause mortality except cardiovascular mortality. Meanwhile, ΔLSV was significantly associated with decompensated cirrhosis, HCC, and it could predict the development of cirrhosis.…”

Employing a Hybrid Convolutional Neural Network and Extreme Learning Machine for Precision Liver Disease Forecasting

“…The wolves are thought to comprehend it better since the location of the meal is never evident in advance. Equations ( 14), (15), and ( 16) are used to determine the victim's location by utilizing the wolves' positions.…”

“…In situations of end-stage liver diseases, early identification can also help ensure a timely liver transplant. Predictive models lessen the overall load on healthcare systems by helping recognize at-risk patients and allocating healthcare resources optimally [15]. By utilizing predictive analytics, healthcare professionals may proactively address the international problem of liver disease.…”