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Brain retraction and thickness of cerebral neocortex: an automated technique for detecting retraction-induced anatomic changes using magnetic resonance imaging

Authors :
Andrew S. Little
Leland S. Hu
Tejas Sankar
Scott C. Beeman
Mark C. Preul
Leslie C. Baxter
Seban Liu
Kris A. Smith
Source :
Neurosurgery. 67(3 Suppl)
Publication Year :
2010

Abstract

BACKGROUND: Treating deep-seated cerebral lesions often requires retracting the brain. Retraction, however, causes clinically significant postoperative neurological deficits in 3% to 9% of intracranial cases. OBJECTIVE: This pilot study used automated analysis of postoperative magnetic resonance images (MRIs) to determine whether brain retraction caused local anatomic changes to the cerebral neocortex and whether such changes represented sensitive markers for detecting brain retraction injury. METHODS: Pre- and postoperative maps of whole-brain cortical thickness were generated from 3-dimensional MRIs of 6 patients who underwent selective amygdalohippocampectomy for temporal lobe epilepsy (5 left hemispheres, 1 right hemisphere). Mean cortical thickness was determined in the inferior temporal gyrus (ITG test), where a retractor was placed during surgery, and in 2 control gyri—the posterior portion of the inferior temporal gyrus (ITG control) and motor cortex control. Regions of cortical thinning were also compared with signs of retraction injury on early postoperative MRIs. RESULTS: Postoperative maps of cortical thickness showed thinning in the inferior temporal gyrus where the retractor was placed in 5 patients. Postoperatively, mean cortical thickness declined from 4.1 ± 0.4 mm to 2.9 ± 0.9 mm in ITG test (P = .03) and was unchanged in the control regions. Anatomically, the region of neocortical thinning correlated with postoperative edema on MRIs obtained within 48 hours of surgery. CONCLUSION: Postoperative MRIs can be successfully interrogated for information on cortical thickness. Brain retraction is associated with chronic local thinning of the neocortex. This automated technique may be sensitive enough to detect regions at risk for functional impairment during craniotomy that cannot be easily detected on postoperative structural imaging.

Details

ISSN :
15244040
Volume :
67
Issue :
3 Suppl
Database :
OpenAIRE
Journal :
Neurosurgery
Accession number :
edsair.doi.dedup.....4564963468d393b30a1355470f140d3f