Intraoperative ultrasound (IOUS) has been increasingly used as a guiding tool during neurosurgical procedures. In this study
we aimed to evaluate the potential application of IOUS-assisted surgery in the resection of small
deepseated
or ill-defined lesions.
Methods:
Eighty-six consecutive patients with small
deep-seated
or ill-defined intracerebral lesions were studied prospectively. An improved intraoperative imaging technique and surgical setup were practiced during the surgery. IOUS was performed in three orthogonal imag
ing planes (horizontal
coronal and sagittal).
Results:
Histopathological diagnoses of these 86 cases included cavernomas
metastases
hemangioblastomas
gliomas
and radiation necrosis. Forty-seven of the 86 lesions (54.7%) were small and deep-seated
34 (39.5%) were ill-defined
and 5 (5.8%) were small
deep-seated
and ill-defined. Sonograms in the horizontal plane were obtained in all 86 cases. Sonograms in the sagittal plane and in the coronal plane were obtained only in 52 cases and in 46 cases
respectively
due to technical limitation. In 13 cases
sonograms in all three orthogonal planes were available. All lesions were successfully identified and localized by IOUS. Total resection was performed in 67 lesions (77.9%) and partial resection was performed in 19 lesions (22.1%).
Conclusion:
We propose IOUS to be performed in three orthogonal planes when surgery is planned for small
deep-seated
or ill-defined brain lesions. By applying this simple
improved technique
surgeons can perform resection of these lesions precisely.
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Related Author
HUANG Xing
LIANG Yan
YI Chuang
WANG Yan
REN Junjie
LI Weilan
BA Zhufei
LIU Tao
Related Institution
Department of Radiology, Jilin Provincial People's Hospital
Department of Medical Imaging, North China University of Science and Technology Affiliated Hospital
Department of Cardiothoracic Surgery, KaiLuan General Hospital
Department of Radiology, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital & Institute
Department of Computing Science and Artificial Intelligence, Liaoning Normal University