Evaluation of cerebral arteriovenous malformation using 'dual vessel fusion' technology.
OBJECTIVE
This study explored the value of using a vessel fusion technique for visualizing and evaluating the vessel structure of patients diagnosed with arteriovenous malformations (AVMs).
methods 10 patients with AVMs supplied by multiple cerebral arteries were investigated. The three-dimensional structure of the AVM nidus, feeding arteries, and draining veins were reconstructed from rotational angiographic images and then displayed on a single image in a fused manner.


RESULTS
In the vessel fusion image, the tangled cluster of vessels surrounding the AVMs could be clearly visualized in three-dimensional space from a selected optimal viewing angle. Each AVM nidus component with its specific feeding arteries and venous drainage could be accurately identified.


CONCLUSIONS
The vessel fusion technique offered detailed anatomical information that enabled clinicians to better understand the AVM structure, which helped with treatment planning.
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Liuqing
L
Sheng
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Jun
J
Li
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Huanhuan
H
Li
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Guodong
G
Li
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Gang
G
Chen
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Weichu
W
Xiang
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Qiang
Q
Wang
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Zhiqiang
Z
Gan
Healthcare Sector, Siemens Ltd China, China.
Qi
Q
Sun
Healthcare Sector, Siemens Ltd China, China.
Bing
B
Yan
Healthcare Sector, Siemens Ltd China, China.
Janina
J
Beilner
Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Commend, PLA, Wuhan, China Institute for Neurosurgery of PLA, Wuhan, China.
Lian-Ting
LT
Ma
D000293:Adolescent; D000328:Adult; D015901:Angiography, Digital Subtraction / Q000379:methods*; D002343:Carotid Artery, Internal / Q000473:pathology; D002533:Cerebral Angiography / Q000379:methods*; D002536:Cerebral Arteries / Q000000981:diagnostic imaging* / Q000473:pathology*; D002648:Child; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D002538:Intracranial Arteriovenous Malformations / Q000000981:diagnostic imaging* / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D014057:Tomography, X-Ray Computed; D014711:Vertebral Artery / Q000473:pathology; D055815:Young Adult
Angiography; Arteriovenous Malformation; Artery