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Chen ZF, Zhang L, Carrington AM, Thornhill R, Miguel O, Auriat AM, Omid-Fard N, Hiremath S, Tshemeister Abitbul V, Dowlatshahi D, Demchuk A, Gladstone D, Morotti A, Casetta I, Fainardi E, Huynh T, Elkabouli M, Talbot Z, Melkus G, Aviv RI. Clinical Features, Non-Contrast CT Radiomic and Radiological Signs in Models for the Prediction of Hematoma Expansion in Intracerebral Hemorrhage. Can Assoc Radiol J 2023; 74:713-722. [PMID: 37070854 DOI: 10.1177/08465371231168383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023] Open
Abstract
PURPOSE Rapid identification of hematoma expansion (HE) risk at baseline is a priority in intracerebral hemorrhage (ICH) patients and may impact clinical decision making. Predictive scores using clinical features and Non-Contract Computed Tomography (NCCT)-based features exist, however, the extent to which each feature set contributes to identification is limited. This paper aims to investigate the relative value of clinical, radiological, and radiomics features in HE prediction. METHODS Original data was retrospectively obtained from three major prospective clinical trials ["Spot Sign" Selection of Intracerebral Hemorrhage to Guide Hemostatic Therapy (SPOTLIGHT)NCT01359202; The Spot Sign for Predicting and Treating ICH Growth Study (STOP-IT)NCT00810888] Patients baseline and follow-up scans following ICH were included. Clinical, NCCT radiological, and radiomics features were extracted, and multivariate modeling was conducted on each feature set. RESULTS 317 patients from 38 sites met inclusion criteria. Warfarin use (p=0.001) and GCS score (p=0.046) were significant clinical predictors of HE. The best performing model for HE prediction included clinical, radiological, and radiomic features with an area under the curve (AUC) of 87.7%. NCCT radiological features improved upon clinical benchmark model AUC by 6.5% and a clinical & radiomic combination model by 6.4%. Addition of radiomics features improved goodness of fit of both clinical (p=0.012) and clinical & NCCT radiological (p=0.007) models, with marginal improvements on AUC. Inclusion of NCCT radiological signs was best for ruling out HE whereas the radiomic features were best for ruling in HE. CONCLUSION NCCT-based radiological and radiomics features can improve HE prediction when added to clinical features.
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Affiliation(s)
| | - Liying Zhang
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - André M Carrington
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
- Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Rebecca Thornhill
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Olivier Miguel
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Angela M Auriat
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Nima Omid-Fard
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Shivaprakash Hiremath
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Vered Tshemeister Abitbul
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Dar Dowlatshahi
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Medicine (Neurology), University of Ottawa, Ottawa, ON, Canada
| | - Andrew Demchuk
- Department of Medicine (Neurology), Foothills Medical Center, Calgary, AB, Canada
| | - David Gladstone
- Department of Medicine (Neurology), University of Toronto, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Andrea Morotti
- Neurology Unit, Department of Neurological Sciences and Vision, ASST Spedali Civili di Brescia, Brescia, Italy
| | - Ilaria Casetta
- Neurological Clinic, University of Ferrara, Ferrara, Italy
| | - Enrico Fainardi
- Neuroradiology Unit, Department of Experimental and Clinical Biomedical Sciences, University of Florence, Italy
| | - Thien Huynh
- Departments of Radiology and Neurosurgery, Mayo Clinic, Jacksonville, FL, USA
| | | | - Zoé Talbot
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Gerd Melkus
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Richard I Aviv
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, ON, Canada
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