Year: 2025
Type: article
Study design: Case Report
Abstract: Objective Magnetic-resonance-imaging (MRI) after brain injury is crucial for providing therapeutic strategies and prognosis. Serial MRI increases the prognostic value by revealing changes present at different time points after the initial injury and aids to study pathology and potential therapeutic strategies. Mobile ultralow-field MRI provides a unique opportunity to offer both bed-side and serial MRI in seriously sick patients. Design We investigated whether serial bedside MRI, including quantitative Apparent Diffusion Coefficient (ADC) measurements are feasible in an infant with hypoxic-ischemic brain injury and how the appearance of brain injury evolves on MRI sequences. Setting/patients/interventions We performed serial bed-side ultralow-field MRI with ADC measurements in an infant with hypoxic-ischemic brain injury over 11 days. Main results We demonstrated that morphological changes associated with hypoxic-ischemic brain injury detected using standard MRI could be verified in an ultralow-field scan. We documented how hypoxic-ischemic brain injury develops in T1, T2, FLAIR and DWI sequences over a time span of 11 days and how signal intensity changes over this period. We show that ultralow-field imaging visualizes the pathophysiology known by experimental data. We report quantitative serial ADC-measurement in lesions. Conclusion Ultralow-field MRI enables the detection of hypoxic-ischemic brain injury in infants and has the potential to significantly broaden access to MRI. Its application may provide more timely, comprehensive diagnostic information related to hypoxic-ischemic brain injury. Serial ultralow-field MRI enables quantitative assessment of ADC values, which may support the establishment of clinically relevant cutoff values. This not only enhances diagnostic and prognosis precision in hypoxic-ischemic brain injury, but also provides a framework for evaluating the efficacy of emerging therapeutic strategies.
Institutions: University of Bonn, King's College London
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,090
OpenAlex ID: W4414094583