PATH61 Structural plasticity of white matter networks following anterior temporal lobe resection. Issue 11 (22nd October 2010)

• Record Type: Journal Article
• Authors: Yogarajah, M; McEvoy, A; Focke, N; Duncan, J; Koepp, M; Symms, M; Bonelli, S; Thompson, P; Vollmar, C
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 81:Issue 11(2010)
• Page Start: e24
• Page End: e24
• Publication Date: 2010-10-22
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp.2010.226340.29
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Anterior temporal lobe resection (ATLR) is an effective treatment for temporal lobe epilepsy (TLE). The structural consequences of ATLR and how these relate to language function after surgery remain unknown. We applied diffusion tensor imaging in 26 left and 20 right TLE patients before and 5 months after surgery. We used whole brain analysis techniques to compare preoperative and postoperative data. We observed a 7% decrease in fractional anisotropy (FA) in white matter networks connected to the area of resection, following surgery. We also observed an 8% increase in FA after left ATLR in the ipsilateral frontotemporal white matter. Post-operative tractography seeded from this area suggests that it is part of the ventromedial language network. The mean preoperative and postoperative FA and parallel diffusivity (PaD) in this cluster were significantly correlated with postoperative verbal fluency and naming test scores. Further, the percentage change in PaD in this cluster was correlated with the percentage change in verbal fluency after anterior temporal lobe resection, such that the bigger the increase in PaD, the smaller the fall in language proficiency after surgery. These findings may represent reorganisation in the ventromedial language network in response to ATLR which may damage the more susceptible dorsolateral language pathway. This has important implications for our understanding of brain injury, and the prediction of postoperative language deficits.