Clinical-radiomics Nomogram for Risk Estimation of Early Hematoma Expansion after Acute Intracerebral Hemorrhage.
Acad Radiol
; 28(3): 307-317, 2021 03.
Article
in En
| MEDLINE
| ID: mdl-32238303
ABSTRACT
RATIONALE AND OBJECTIVES:
Noncontrast CT-based radiomics signature has shown ability for detecting hematoma expansion (HE) in spontaneous intracerebral hemorrhage (ICH). We sought to compare its predictive performance with clinical risk factors and develop a clinical-radiomics nomogram to assess the risk of early HE. MATERIALS ANDMETHODS:
In total, 1153 patients with ICH who underwent baseline cranial CT within 6 hours and follow-up scans within 72 hours of stroke onset were enrolled, of whom 864 (75%) were assigned to the derivation cohort and 289 (25%) to the validation cohort. Based on LASSO algorithm or stepwise logistic regression analysis, three models (clinical model, radiomics model, and hybrid model) were constructed to predict HE. The Akaike information criterion (AIC) and likelihood ratio test (LRT) were used for comparing the goodness of fit of the three models, and the AUC was used to evaluate their discrimination ability for HE.RESULTS:
The hybrid model (AICâ¯=â¯681.426; χ2= 128.779) was the optimal model with the lowest AIC and highest chi-square values compared to the radiomics model (AICâ¯=â¯767.979; χ2â¯=â¯110.234) or the clinical model (AICâ¯=â¯753.757; χ2â¯=â¯56.448). The radiomics model was superior in the prediction of HE to the clinical model in both derivation (pâ¯=â¯0.009) and validation (pâ¯=â¯0.022) cohorts. In both datasets, the clinical-radiomics nomogram showed satisfactory discrimination and calibration for detecting HE (AUCâ¯=â¯0.771, Sensitivityâ¯=â¯87.0%; AUCâ¯=â¯0.820, Sensitivityâ¯=â¯88.1%; respectively).CONCLUSION:
Among patients with acute ICH, noncontrast CT-based radiomics model outperformed the clinical-only model in the prediction of HE, and the established clinical-radiomics nomogram with favorable performance can offer a noninvasive tool for the risk stratification of HE.Key words
Full text:
1
Database:
MEDLINE
Main subject:
Tomography, X-Ray Computed
/
Nomograms
Type of study:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Acad Radiol
Journal subject:
RADIOLOGIA
Year:
2021
Type:
Article
Affiliation country:
China