Purpose: CT hyperattenuation arising from iodinated contrast has a different temporal evolution than that arising due to hemorrhage. This paper presents a method for optimal discrimination between hemorrhage and iodinated contrast in a postintervention CT in stroke patients.
Methods: We analyzed the brain computed tomography (CT) scans of consecutive patients with intraparenchymal hyperattenuation due to hemorrhage (n= 41), those due to iodinated contrast alone (n= 24), and those due to contrast mixed with hemorrhage after reperfusion therapy (n= 14) in stroke patients. The difference between the maximum enhancement in hyperattenuation in the affected area and the corresponding contralateral area, dubbed Relative Maximum Enhancement (RME), was tracked over time. We fitted regression models to the RME changes due to hemorrhage and contrast to describe their temporal decay, and then derived the optimal discriminant curve that distinguishes the two. A computer algorithm coregistered the baseline and follow-up CT scans and performed pixel-by-pixel comparison to determine hemorrhage and iodinated contrast based on the RME changes with respect to the discriminant curve.
Results: For both hemorrhage (k= − 0.004, R2 = 0.7) and iodinated contrast (k= − 0.064, R2 = 0.9), the temporal evolution of RMEs were best fitted by exponential decay curves, with respective half-lives of 192.3 and 10.7 h. An exponential decay model (k= − 0.026) for optimal discrimination of hemorrhage vs. contrast was fitted. The computer algorithm implementing this model was successful in predicting the presence of hemorrhage in a hyperdense lesion with sensitivity = 93 % and specificity = 91 %.
Conclusion: Intraparenchymal hemorrhage and contrast have markedly different decay half-lives that can be used to assess hemorrhage in a hyperdense lesion on a CT scan after intra-arterial therapy.
- Computed tomography
- Conventional CT
- Intra-arterial thrombolysis
- Intraparenchymal hemorrhage
- Ischemic stroke
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Clinical Neurology