Intracranial hemorrhage is a commonly acknowledged complication of interventional neuroradiology procedures, and the ability to image hemorrhage at the time of the procedure would be very beneficial. A new C-arm system with 3D functionality extends the capability of C-arm imaging to include soft-tissue applications by facilitating the detection of low-contrast objects. We evaluated its ability to detect small intracranial hematomas in a swine model.Intracranial hematomas were created in 7 swine by autologous blood injection of various hematocrits (19%-37%) and volumes (1.5-5 mL). Four animals received intravascular contrast before obtaining autologous blood (group 1), and 3 did not (group 2). We scanned each animal by using the C-arm CT system, acquiring more than 500 images during a 20-second rotation through more than 200 degrees . Multiplanar reformatted images with isotropic resolution were reconstructed on the workstation by using product truncation, scatter, beam-hardening, and ring-artifact correction algorithms. The brains were harvested and sliced for hematoma measurement and compared with imaging findings.Five intracranial hematomas were created in group 1 animals, and all were visualized. Six were created in group 2, and 3 were visualized. One nonvisualized hematoma was not confirmed at necropsy. All the others in both groups were confirmed. In group 1 (with contrast), small hematomas were detectable even when the hematocrit was 19%-20%. In group 2 (without contrast) C-arm CT was able to detect small hematomas (<1.0 cm(2)) created with hematocrits of 29%-37%. The area of hematoma measured from the C-arm CT data was, on average, within 15% of the area measured from harvested brain.The image quality obtained with this implementation of C-arm CT was sufficient to detect experimentally created small intracranial hematomas. This capability should provide earlier detection of hemorrhagic complications that may occur during neurointerventional procedures.
View details for DOI 10.3174/ajnr.A0898
View details for Web of Science ID 000255129700029
View details for PubMedID 18202240