The clinical potential of radiomics to predict hematoma expansion in spontaneous intracerebral hemorrhage: a narrative review

• Published in: Frontiers in neurology 2024-07, Vol.15, p.1427555
• Main Authors: Tenhoeve, Samuel A, Findlay, Matthew C, Cole, Kyril L, Gautam, Diwas, Nelson, Jayson R, Brown, Julian, Orton, Cody J, Bounajem, Michael T, Brandel, Michael G, Couldwell, William T, Rennert, Robert C
• Format: Article
• Language: English
• Subjects: hematoma expansion; machine learning; Neurology; noncontrast CT imaging; radiomics; spontaneous intracerebral hemorrhage
• ISSN: 1664-2295; 1664-2295
• DOI: 10.3389/fneur.2024.1427555

Spontaneous intracerebral hemorrhage (sICH) is associated with significant morbidity and mortality, with subsequent hematoma expansion (HE) linked to worse neurologic outcomes. Accurate, real-time predictions of the risk of HE could enable tailoring management-including blood pressure control or surgery-based on individual patient risk. Although multiple radiographic markers of HE have been proposed based on standard imaging, their clinical utility remains limited by a reliance on subjective interpretation of often ambiguous findings and a poor overall predictive power. Radiomics refers to the quantitative analysis of medical images that can be combined with machine-learning algorithms to identify predictive features for a chosen clinical outcome with a granularity beyond human limitations. Emerging data have supported the potential utility of radiomics in the prediction of HE after sICH. In this review, we discuss the current clinical management of sICH, the impact of HE and standard imaging predictors, and finally, the current data and potential future role of radiomics in HE prediction and management of patients with sICH.