ABSTRACT
Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy. Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma. Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis. Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches.
ABSTRACT
RATIONALE AND OBJECTIVES: Regarding the most recent ischemic stroke treatment guideline, perfusion imaging has been recommended up to 24 hours after initial symptoms of brain infarction. Patients with a significant amount of salvageable peri-infarct ischemia and no contraindications benefit from delayed thrombolysis and intra-arterial thrombectomy. This approach causes increasingly more CT perfusion to be done in the subacute phase of ischemic stroke. CT perfusion findings in this "subacute phase" are slightly different from "hyper-acute" ischemic stroke. The interpreting radiologist must be confident in reporting the CT perfusion study in an urgent setting since these studies are under the umbrella of "code-stroke" and should be read in minutes. In addition, results of the CT perfusion have a critical effect on the patient's outcome and misinterpretation can be fatal in that underestimation of the salvageable ischemia excludes the patient from potential effective treatment. Underestimation of infarct volume may cause unnecessary thrombolysis/thrombectomy and potentially fatal intracranial hemorrhage. MATERIALS AND METHODS: In this review, we are trying to explain the basic concept of "code-stroke" CT perfusion, typical findings, and pitfalls in a practical way.
