Diffusion tensor imaging with tractography in surgical resection of brainstem cavernous malformations: a systematic review and meta-analysis
Brainstem cavernous malformations are benign subset of cerebral cavernous malformations, which need a special intervention owing to being vital and complex. The diffusion tensor imaging technique, a well-recognized neuroimaging tool, can visualize the white matter tracts and their surroundings and provide promising surgical outcomes. This systematic review and meta-analysis evaluated the effect of preoperative diffusion tensor imaging in patients undergoing surgical resection of brainstem cavernous malformations. Five databases, including PubMed, Scopus, Web of Science, Cochrane Library, and Google Scholar, were searched using a comprehensive search strategy to find any article matching our inclusion criteria. We used Comprehensive Meta-Analysis (CMA) software to analyze the collected data, get the evidence, and report the results as event rate (ER), with their 95% confidence interval (CI). Twenty-eight studies involving 467 patients matched our criteria and 19 studies entered the analysis. Our analysis showed that, in patients undergoing surgical resection of brainstem cavernous malformations assisted by preoperative diffusion tensor imaging, 82.21% achieved total resection. About 12.4% of patients achieved partial resection, 65.65% improved, 8.07% worsened, 25.04% showed no change, 3.59% experienced postoperative re-bleeding, and 0.87% died. The utilization of preoperative diffusion tensor imaging significantly increased the proportion of improved patients and decreased the proportion of worsened patients. However, further controlled research is needed to draw a definite conclusion about the usefulness of its role.
Other Information
Published in: International Journal of Neuroscience
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1080/00207454.2023.2214696
Funding
Open Access funding provided by the Qatar National Library.
History
Language
- English
Publisher
RoutledgePublication Year
- 2023
License statement
This Item is licensed under the Creative Commons Attribution 4.0 International License.Institution affiliated with
- Hamad Medical Corporation
- Hamad General Hospital - HMC