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Research ArticleAdult Brain

Automated Cerebral Hemorrhage Detection Using RAPID

J.J. Heit, H. Coelho, F.O. Lima, M. Granja, A. Aghaebrahim, R. Hanel, K. Kwok, H. Haerian, C.W. Cereda, C. Venkatasubramanian, S. Dehkharghani, L.A. Carbonera, J. Wiener, K. Copeland and F. Mont’Alverne
American Journal of Neuroradiology February 2021, 42 (2) 273-278; DOI: https://doi.org/10.3174/ajnr.A6926
J.J. Heit
aFrom the Department of Radiology, Neuroimaging, and Neurointervention Division (J.J.H.), Stanford University School of Medicine, Stanford, California
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H. Coelho
bInterventional Radiology Service (H.C., F.M.)
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F.O. Lima
cDepartment of Neurology (F.O.L.), Hospital Geral de Fortaleza, R. Ávila Goulart, Fortaleza, Brazil
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M. Granja
dBaptist Neurological Institute (M.G., A.A., R.H.), Lyerly Neurosurgery/Baptist Health, Jacksonville, Florida
eDiagnostic Imaging Department (M.G., A.A., R.H.), Fundación Santa Fe de Bogota University Hospital, Bogotá, Colombia
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A. Aghaebrahim
dBaptist Neurological Institute (M.G., A.A., R.H.), Lyerly Neurosurgery/Baptist Health, Jacksonville, Florida
eDiagnostic Imaging Department (M.G., A.A., R.H.), Fundación Santa Fe de Bogota University Hospital, Bogotá, Colombia
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R. Hanel
dBaptist Neurological Institute (M.G., A.A., R.H.), Lyerly Neurosurgery/Baptist Health, Jacksonville, Florida
eDiagnostic Imaging Department (M.G., A.A., R.H.), Fundación Santa Fe de Bogota University Hospital, Bogotá, Colombia
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K. Kwok
fDepartment of Radiology (K.K.), Central Valley Imaging Medical Associates, Manteca, California
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H. Haerian
gDepartment of Radiology (H.H.), LifeBridge Health, Baltimore, Maryland
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C.W. Cereda
hDepartment of Neurology (C.W.C.), EOC Ospedale Regionale di Lugano, Lugano, Switzerland
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C. Venkatasubramanian
iNeurocritical Care and Stroke, Department of Neurology (C.V.), Stanford University, Palo Alto, California
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S. Dehkharghani
jDepartment of Radiology (S.D.), NY University Langone Health, New York, New York
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L.A. Carbonera
kHospital das Clínicas de Porto Alegre (L.A.C.), Bairro Santa Cecilia, Brazil
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J. Wiener
lDepartment of Radiology (J.W.), Boca Raton Regional Hospital, Boca Raton, Florida
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K. Copeland
mBoulder Statistics (K.C.), Steamboat Springs, Colorado
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F. Mont’Alverne
bInterventional Radiology Service (H.C., F.M.)
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    FIG 1.

    Representative imaging examples of ICH correctly detected by RAPID. A. Primary intraparenchymal hemorrhage within the right thalamus and posterior limb of the right internal capsule (red outline by RAPID). B. Small extra-axial subdural hematoma overlying the right cerebral hemisphere (red outline by RAPID). C. Subarachnoid hemorrhage (red outline by RAPID). D. Subarachnoid and intraventricular (right and left lateral, third, and fourth ventricles) hemorrhage (red outline by RAPID).

  • FIG 2.
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    FIG 2.

    Representative false-positive and false-negative ICH examples. A. RAPID incorrectly detected ICH (false-positive result) in a patient with volume averaging in the anterior cranial fossa and beam-hardening artifact in the posterior fossa (red outlines by RAPID). B. RAPID failed to detect ICH (false-negative result) in a patient intraparenchymal hemorrhage in the left thalamus (yellow arrow). C. RAPID failed to detect ICH (false-negative result) in a patient with a small amount of subarachnoid and intraventricular hemorrhage (yellow arrows).

  • FIG 3.
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    FIG 3.

    Intraparenchymal and intraventricular hemorrhage volumetric agreement between RAPID and expert interpretation. A and B, Representative example of an intraparenchymal hemorrhage in the right basal ganglia. Manual segmentation by a neuroradiologist (A, green outline) is well correlated with automated segmentation by RAPID ICH (B, red outline). C. Scatterplot denotes volumetric agreement between RAPID and expert evaluation for NCCT with isolated intraparenchymal or intraventricular hemorrhage.

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    Table 1:

    Patient demographic details

    AllICH−ICH+P Valuea
    Sex
     Female, n (%)117 (38.0)53 (33.5)64 (42.7)<.0002
     Male, n (%)164 (53.3)81 (51.3)83 (55.3)
     Unknown, n (%)27 (8.8)24 (15.2)3 (2.0)
    Age
     20–39 years, n (%)33 (10.9)15 (9.9)18 (12.0).5692
     40–59 years, n (%)78 (25.8)43 (28.3)35 (23.3)
     60+ years, n (%)191 (63.3)94 (61.8)97 (64.7)
    • ↵a For a Pearson chi-square test of independence.

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    Table 2:

    Performance of RAPID for ICH detection

    RAPID vs Consensus TruthConsensus = Truth
    n = 3081 (positive)0 (negative)Total
    RAPID1 (positive)1517158
    0 (negative)7143150
    Total158150308
    • View popup
    Table 3:

    RAPID ICH performance

    MeasureEstimateLower 95% CIUpper 95% CI
    Prevalence0.5130.4570.568
    Sensitivity0.9560.9110.978
    Specificity0.9530.9070.977
    PPV0.9560.9110.978
    NPV0.9530.9070.977
    Positive LR20.4799.92842.245
    Negative LR0.0460.0230.096
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American Journal of Neuroradiology: 42 (2)
American Journal of Neuroradiology
Vol. 42, Issue 2
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Cite this article
J.J. Heit, H. Coelho, F.O. Lima, M. Granja, A. Aghaebrahim, R. Hanel, K. Kwok, H. Haerian, C.W. Cereda, C. Venkatasubramanian, S. Dehkharghani, L.A. Carbonera, J. Wiener, K. Copeland, F. Mont’Alverne
Automated Cerebral Hemorrhage Detection Using RAPID
American Journal of Neuroradiology Feb 2021, 42 (2) 273-278; DOI: 10.3174/ajnr.A6926

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Automated Cerebral Hemorrhage Detection Using RAPID
J.J. Heit, H. Coelho, F.O. Lima, M. Granja, A. Aghaebrahim, R. Hanel, K. Kwok, H. Haerian, C.W. Cereda, C. Venkatasubramanian, S. Dehkharghani, L.A. Carbonera, J. Wiener, K. Copeland, F. Mont’Alverne
American Journal of Neuroradiology Feb 2021, 42 (2) 273-278; DOI: 10.3174/ajnr.A6926
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