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Hepatic Failure in COVID-19: Is Iron Overload the Dangerous Trigger?

ABSTRACT: Liver injury in COVID-19 patients has progressively emerged, even in those without a history of liver disease, yet the mechanism of liver pathogenicity is still controversial. COVID-19 is frequently associated with increased serum ferritin levels, and hyperferritinemia was shown to correlate with illness severity. The liver is the major site for iron storage, and conditions of iron overload have been established to have a pathogenic role in development of liver diseases. We presented here six patients who developed severe COVID-19, with biochemical evidence of liver failure. Three cases were survived patients, who underwent liver biopsy; the other three were deceased patients, who were autopsied. None of the patients suffered underlying liver pathologies. Histopathological and ultrastructural analyses were performed. The most striking finding we demonstrated in all patients was iron accumulation into hepatocytes, associated with degenerative changes. Abundant ferritin particles were found enclosed in siderosomes, and large aggregates of hemosiderin were found, often in close contact with damaged mitochondria. Iron-caused oxidative stress may be responsible for mitochondria metabolic dysfunction. In agreement with this, association between mitochondria and lipid droplets was also found. Overall, our data suggest that hepatic iron overload could be the pathogenic trigger of liver injury associated to COVID-19.

SUBMITTER: Del Nonno F

PROVIDER: S-EPMC8147922 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Hepatic Failure in COVID-19: Is Iron Overload the Dangerous Trigger?

Del Nonno Franca F Nardacci Roberta R Colombo Daniele D Visco-Comandini Ubaldo U Cicalini Stefania S Antinori Andrea A Marchioni Luisa L D'Offizi Gianpiero G Piacentini Mauro M Falasca Laura L

Cells 20210504 5

Liver injury in COVID-19 patients has progressively emerged, even in those without a history of liver disease, yet the mechanism of liver pathogenicity is still controversial. COVID-19 is frequently associated with increased serum ferritin levels, and hyperferritinemia was shown to correlate with illness severity. The liver is the major site for iron storage, and conditions of iron overload have been established to have a pathogenic role in development of liver diseases. We presented here six pa ...[more]

PMID: 34064487

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Project description:BackgroundMRI T2* and R2* mapping have gained clinical acceptance for noninvasive assessment of iron overload. Lower field MRI may offer increased measurement dynamic range in patients with high iron concentration and may potentially increase MRI accessibility, but it is compromised by lower signal-to-noise ratio that reduces measurement precision.PurposeTo characterize a high-performance 0.55 T MRI system for evaluating patients with liver iron overload.Study typeProspective.PopulationForty patients with known or suspected iron overload (sickle cell anemia [n = 5], ß-thalassemia [n = 3], and hereditary spherocytosis [n = 2]) and a liver iron phantom.Field strength/sequenceA breath-held multiecho gradient echo sequence at 0.55 T and 1.5 T.AssessmentPatients were imaged with T2*/R2* mapping 0.55 T and 1.5 T within 24 hours, and 16 patients returned for follow-up exams within 6-16 months, resulting in 56 paired studies. Liver T2* and R2* measurements and standard deviations were compared between 0.55 T and 1.5 T and used to validate a predictive model between field strengths. The model was then used to classify iron overload at 0.55 T.Statistical testsLinear regression and Bland-Altman analysis were used for comparisons, and measurement precision was assessed using the coefficient of variation. A P-value < 0.05 was considered statistically significant.ResultsR2* was significantly lower at 0.55 T in our cohort (488 ± 449 s-1 at 1.5 T vs. 178 ± 155 s-1 at 0.55 T, n = 56 studies) and in the patients with severe iron overload (937 ± 369 s-1 at 1.5 T vs. 339 ± 127 s-1 at 0.55 T, n = 23 studies). The coefficient of variation indicated reduced precision at 0.55 T (3.5 ± 2.2% at 1.5 T vs 6.9 ± 3.9% at 0.55 T). The predictive model accurately predicted 1.5 T R2* from 0.55 T R2* (Bland Altman bias = -6.6 ± 20.5%). Using this model, iron overload at 0.55 T was classified as: severe R2* > 185 s-1 , moderate 81 s-1 < R2* < 185 s-1 , and mild 45 s-1 < R2* < 91 s-1 .Data conclusionWe demonstrated that 0.55 T provides T2* and R2* maps that can be used for the assessment of liver iron overload in patients.Evidence level2 TECHNICAL EFFICACY: Stage 2.

Project description:BackgroundExtraction of liver parenchyma is an important step in the evaluation of R2*-based hepatic iron content (HIC). Traditionally, this is performed by radiologists via whole-liver contouring and T2*-thresholding to exclude hepatic vessels. However, the vessel exclusion process is iterative, time-consuming, and susceptible to interreviewer variability.PurposeTo implement and evaluate an automatic hepatic vessel exclusion and parenchyma extraction technique for accurate assessment of R2*-based HIC.Study typeRetrospective analysis of clinical data.SubjectsData from 511 MRI exams performed on 257 patients were analyzed.Field strength/sequenceAll patients were scanned on a 1.5T scanner using a multiecho gradient echo sequence for clinical monitoring of HIC.AssessmentAn automated method based on a multiscale vessel enhancement filter was investigated for three input data types-contrast-optimized composite image, T2* map, and R2* map-to segment blood vessels and extract liver tissue for R2*-based HIC assessment. Segmentation and R2* results obtained using this automated technique were compared with those from a reference T2*-thresholding technique performed by a radiologist.Statistical testsThe Dice similarity coefficient was used to compare the segmentation results between the extracted parenchymas, and linear regression and Bland-Altman analyses were performed to compare the R2* results, obtained with the automated and reference techniques.ResultsMean liver R2* values estimated from all three filter-based methods showed excellent agreement with the reference method (slopes 1.04-1.05, R2 > 0.99, P < 0.001). Parenchyma areas extracted using the reference and automated methods had an average overlap area of 87-88%. The T2*-thresholding technique included small vessels and pixels at the vessel/tissue boundaries as parenchymal area, potentially causing a small bias (<5%) in R2* values compared to the automated method.Data conclusionThe excellent agreement between reference and automated hepatic vessel segmentation methods confirms the accuracy and robustness of the proposed method. This automated approach might improve the radiologist's workflow by reducing the interpretation time and operator dependence for assessing HIC, an important clinical parameter that guides iron overload management.Level of evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1542-1551.

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Hepatic Failure in COVID-19: Is Iron Overload the Dangerous Trigger?

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Hepatic Failure in COVID-19: Is Iron Overload the Dangerous Trigger?

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