Acute infarction of brain
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Acute Infarction of the Brain: Insights from Recent Research
Prevalence and Predictors of Acute Brain Infarcts Post-Intracerebral Hemorrhage
Acute brain infarction is a notable complication following spontaneous intracerebral hemorrhage (ICH). A study utilizing diffusion-weighted imaging (DWI) found that 22.9% of patients with spontaneous ICH exhibited acute brain infarcts. These infarcts were predominantly small, subcortical, and subclinical. Key predictors of DWI abnormalities included a history of ischemic stroke, significant mean arterial pressure (MAP) reduction, and craniotomy for ICH evacuation.
Infarction Patterns in the Lower Brainstem
Infarcts in the lower brainstem present with distinct clinical and topographical characteristics. Six types of infarcts were identified, with small midlateral, dorsolateral, inferolateral, and inferodorsolateral infarcts being the most common. These infarcts were often associated with Wallenberg's syndrome. The study highlighted that atheromatosis was the predominant cause, with vertebral artery dissection and cardioembolism also contributing.
Remote Effects of Acute Ischemic Infarcts
Acute ischemic infarcts can lead to secondary degeneration in connected brain regions. Research demonstrated that cortical thinning occurs in areas connected to the infarcted region, with the extent of thinning correlating with microstructural damage in connecting white matter tracts. This secondary degeneration underscores the importance of understanding structural and functional reorganization post-stroke.
Cerebral Infarction Following Subarachnoid Hemorrhage
Cerebral infarction is a severe complication of aneurysmal subarachnoid hemorrhage (SAH). In a cohort study, 3% of patients exhibited acute infarction on admission CT. These infarcts were associated with global cerebral edema, coma, intraventricular hemorrhage, and loss of consciousness at onset. The presence of early cerebral infarction significantly increased mortality and disability rates.
Machine Learning in Detecting Early Infarction
Machine learning (ML) has shown promise in detecting early infarction in acute ischemic stroke using non-contrast-enhanced CT scans. An ML algorithm demonstrated good agreement with diffusion-weighted MRI scans in identifying infarct volume, suggesting its potential utility in clinical settings to guide treatment decisions.
Severe Brain Swelling in Massive Cerebral Infarction
Massive cerebral infarction can lead to severe brain swelling, often resulting in rapid fatality due to transtentorial herniation and brain-stem edema or hemorrhage. A review of postmortem cases revealed that 78% of patients with severe brain swelling died within seven days of infarction onset. This highlights the critical role of managing increased intracranial pressure in patients with severe strokes.
Lesion Size and Clinical Outcomes
The size of cerebral infarcts, as measured by computed tomography, correlates with clinical outcomes. Larger infarcts were associated with worse neurological scores at admission and one week post-stroke. This emphasizes the importance of early and accurate measurement of infarct size in predicting patient prognosis.
Early Consciousness Disorder in Large Hemispheric Infarction
Large hemispheric infarction (LHI) often leads to early consciousness disorder (ECD). Quantitative EEG and brain network analyses revealed that higher levels of consciousness were associated with more alpha and beta oscillations and greater brain connectivity. These findings suggest that EEG characteristics could serve as diagnostic markers for ECD in LHI patients.
Strategic Infarct Locations and Post-Stroke Cognitive Impairment
Post-stroke cognitive impairment (PSCI) is influenced by the location of the infarct. Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI. A location impact score derived from these findings can predict PSCI risk, aiding in early identification and management of at-risk patients.
Concurrent Brain Infarcts in Monocular Visual Loss
Patients with monocular visual loss (MVL) of presumed ischemic origin may also have concurrent acute brain infarcts. This suggests that embolism to the retinal circulation could indicate a higher risk of embolism to the hemispheric circulation, necessitating comprehensive evaluation in MVL patients.
Conclusion
Acute brain infarction presents with diverse clinical manifestations and complications, influenced by factors such as infarct location, size, and associated conditions. Advances in imaging techniques and machine learning are enhancing early detection and management, potentially improving outcomes for stroke patients. Understanding the predictors and effects of acute infarcts is crucial for developing targeted interventions and improving patient care.
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