Utilizing Quantitative Analysis of CSF Volume from Clinical T1-Weighted MRI to Predict Thrombectomy Outcomes.

Background And Purpose: Endovascular thrombectomy (EVT) is the standard for acute ischemic stroke from large vessel occlusion, but post-EVT functional independence varies. Brain atrophy, linked to higher cerebrospinal fluid volume (CSFV), may affect outcomes. Baseline CSFV could predict EVT benefit by assessing brain health.

Reduced Cortical Excitability is Associated with Cognitive Symptoms in Concussed Adolescent Football Players.

Background: American tackle football is associated with high rates of concussion, leading to neurophysiological disturbances and debilitating clinical symptoms. Previous investigations of the neurophysiological effects of concussion have largely ignored aperiodic neurophysiological activity, which is a marker of cortical excitability.

Purpose: We examined whether concussion during a season of high school football is related to changes in aperiodic and periodic neurophysiological activity and whether any such changes are associated with clinical outcomes.

Genomic signature for oligometastatic disease in non-small cell lung cancer patients with brain metastases.

Purpose/objectives: Biomarkers for extracranial oligometastatic disease remain elusive and few studies have attempted to correlate genomic data to the presence of true oligometastatic disease.

Methods: Patients with non-small cell lung cancer (NSCLC) and brain metastases were identified in our departmental database. Electronic medical records were used to identify patients for whom liquid biopsy-based comprehensive genomic profiling (Guardant Health) was available.

ChatGPT and Large Language Models in Radiology: Perspectives From the Field.

Generative artificial intelligence (AI) and large language models (LLMs) are increasingly being recognized as tools with the potential to transform many industries, including health care. Implementation and use of these tools among radiologists is likely variable, driven by radiology practice and institutional factors. Radiologists from various practices were asked about their perspectives on generative AI and LLMs in radiology.