Journal of Clinical Medicine (Jul 2024)

Magnetic Resonance Imaging in Uremic Encephalopathy: Identifying Key Imaging Patterns and Clinical Correlations

  • Federico Greco,
  • Andrea Buoso,
  • Laura Cea,
  • Valerio D’Andrea,
  • Caterina Bernetti,
  • Bruno Beomonte Zobel,
  • Carlo Augusto Mallio

DOI
https://doi.org/10.3390/jcm13144092
Journal volume & issue
Vol. 13, no. 14
p. 4092

Abstract

Read online

Background/Objectives: Magnetic Resonance Imaging (MRI) is essential in diagnosing neurological conditions, offering detailed insights into brain pathology. Uremic encephalopathy (UE) is a severe neurological disorder resulting from renal failure, characterized by cognitive impairments and brain abnormalities due to the accumulation of uremic toxins (UTs). Despite extensive research on UTs, there is a significant gap in the detailed characterization of MRI findings in UE patients. This study aims to bridge this gap by conducting a comprehensive literature review of cerebral MRI findings in UE. We hypothesize that specific MRI patterns correlate with the severity and clinical manifestations of UE, thereby enhancing diagnostic accuracy and improving patient outcomes. Methods: A literature review was performed using PubMed, Cochrane Library, and Google Scholar. The search terms included “uremic encephalopathy MRI”, “uremia and kidney failure MRI”, and “toxic and metabolic or acquired encephalopathies MRI”. The inclusion criteria were original articles on UE and MRI findings published in English. Results: Common MRI sequences include T1-weighted, T2-weighted, FLAIR, and DWI. Frequent MRI findings in UE are cytotoxic and vasogenic brain edema in regions such as the basal ganglia and periventricular white matter. Patterns like the “lentiform fork sign” and basal ganglia involvement are key indicators of UE. Conclusions: MRI plays a crucial role in diagnosing UE by identifying characteristic brain edema and specific patterns. A comprehensive diagnostic approach, incorporating clinical, laboratory, and imaging data, is essential for accurate diagnosis and management. The study calls for larger well-designed cohorts with long-term follow-up to improve the understanding and treatment of UE.

Keywords