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Abstract
Purpose of the Review This article reviews common imaging modalities used in diagnosis and management of acute stroke. Each modality is discussed individually and clinical scenarios are presented to demonstrate how to apply these modalities in decision-making.
Recent Findings Advances in neuroimaging provide unprecedented accuracy in determining tissue viability as well as tissue fate in acute stroke. In addition, advances in machine learning have led to the creation of decision support tools to improve the interpretability of these studies.
Summary Noncontrast head computed tomography (CT) remains the most commonly used initial imaging tool to evaluate stroke. Its exquisite sensitivity for hemorrhage, rapid acquisition, and widespread availability make it the ideal first study. CT angiography (CTA), the most common follow-up study after noncontrast head CT, is used primarily to identify intracranial large vessel occlusions and cervical carotid or vertebral artery disease. CTA is highly sensitive and can improve accuracy of patient selection for endovascular therapy through delineations of ischemic core. CT perfusion is widely used in endovascular therapy trials and benefits from multiple commercially available machine-learning packages that perform automated postprocessing and interpretation. Magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) can provide valuable insights for outcomes prognostication as well as stroke etiology. Optical coherence tomography (OCT), positron emission tomography (PET), single-photon emission computerized tomography (SPECT) offer similar insights. In the clinical scenarios presented, we demonstrate how multimodal imaging approaches can be tailored to gain mechanistic insights for a range of cerebrovascular pathologies.
Glossary
- ADC=
- apparent diffusion coefficient;
- AI=
- artificial intelligence;
- AIS=
- acute ischemic stroke;
- ASPECTS=
- Alberta Stroke Program Early CT Score;
- CBF=
- cerebral blood flow;
- CBV=
- cerebral blood volume;
- CT=
- computed tomography;
- CTA=
- CT angiography;
- CTP=
- CT perfusion;
- CTV=
- CT venography;
- DSA=
- digital subtraction angiography;
- DWI=
- diffusion-weighted imaging;
- EDV=
- end-diastolic velocity;
- EIC=
- early ischemic change;
- EVT=
- endovascular thrombectomy;
- FLAIR=
- fluid-attenuated inversion recovery;
- GRE=
- gradient recalled echo;
- ICH=
- intracranial hemorrhage;
- LVO=
- large vessel occlusion;
- MCA=
- middle cerebral artery;
- ML=
- machine learning;
- MRA=
- magnetic resonance angiography;
- MRP=
- magnetic resonance perfusion;
- MRV=
- magnetic resonance venography;
- MTT=
- mean transit time;
- NCHCT=
- noncontrast head CT;
- OCT=
- optical coherence tomography;
- PET=
- positron emission tomography;
- rCBF=
- relative cerebral blood flow;
- rCBV=
- relative cerebral blood volume;
- SPECT=
- single-photon emission computerized tomography;
- SWI=
- susceptibility-weighted imaging;
- TCD=
- transcranial Doppler ultrasonography;
- Tmax=
- time to maximum of residue function;
- tPA=
- tissue plasminogen activator
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
- © 2021 American Academy of Neurology
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- Article
- Abstract
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- Optical Coherence Tomography
- Ultrasonography
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- Artificial Intelligence/Machine Learning
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- Study Funding
- Disclosure
- Appendix Authors
- Footnotes
- References
- Figures & Data
- Info & Disclosures
