Introduction:
Preeclampsia (PE) is associated with acute kidney injury, carrying an increased risk of future renal disease. Whilst serum creatinine informs the diagnosis of PE, renal biomarkers are not routinely used for prediction and prognosis of PE. Magnetic resonance imaging (MRI) biomarkers can non-invasively quantify tissue characteristics such as inflammation, oedema and fibrosis. We evaluated maternal renal MRI biomarkers in women at high risk of developing PE to see if they could provide mechanistic insight and improved risk stratification in PE.
Methods:
MRI scans as part of the DAPHNE study were analysed (REC (22/YH/01/44)). DAPHNE is a prospective cohort of women at high-risk of developing PE undergoing serial, longitudinal cardio-placental MRI. Regions of interest (ROIs) were drawn on T1/T2 maps around kidneys captured incidentally. Paired blood and urine samples were analysed to assess biomarkers correlations, and relation to clinical outcomes.
Results:
44 participants underwent 118 scans. 18 had a normal pregnancy outcome, 14 had CHT and 12 developed PE. None had underlying chronic kidney disease. The PE cohort had significantly higher blood creatinine than the normotensive (p=0.0021) and CHT (p=0.0095) cohorts. In PE, there was a trend towards increased T1 and T2 of the renal cortex, and medullary T2 shortening. Some blood biomarkers correlated with these changes, and there were differences in these correlations depending on pregnancy outcome.
Conclusions:
MRI biomarkers show promise for characterising renal injury in PE, showing increased cortical T2, which may represent inflammation, fluid accumulation and fibrosis as seen in non-pregnant imaging studies. In our PE cohort, this may reflect glomerular endotheliosis which is identified on renal histopathology in PE. Renal medullary T2 shortening may represent hypoxia due to an excess of deoxyhaemoglobin present in the tissues. Confirmation of these findings is needed in larger prospective cohort studies. This abstract has also been submitted to Macdonald Obstetric Medicine Society annual meeting.
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.