Literature DB >> 25996300

Physiological Correlates and Predictors of Functional Recovery After Chiasmal Decompression.

Noa Raz1, Atira S Bick, Alexander Klistorner, Sergey Spektor, Daniel S Reich, Tamir Ben-Hur, Netta Levin.   

Abstract

BACKGROUND: The intrinsic abilities and limits of the nervous system to repair itself after damage may be assessed using a model of optic chiasmal compression, before and after a corrective surgical procedure.
METHODS: Visual fields (VFs), multifocal visual evoked potentials (mfVEP), retinal nerve fiber layer (RNFL) thickness, and diffusion tensor imaging were used to evaluate a patient before and after removal of a meningioma compressing the chiasm. Normally sighted individuals served as controls. The advantage of each modality to document visual function and predict postoperative outcome (2-year follow-up) was evaluated.
RESULTS: Postsurgery visual recovery was best explained by critical mass of normally conducting fibers and not associated with average conduction amplitudes. Recovered VF was observed in quadrants in which more than 50% of fibers were identified, characterized by intact mfVEP latencies, but severely reduced amplitudes. Recovery was evident despite additional reduction of RNFL thickness and abnormal optic tract diffusivity. The critical mass of normally conducting fibers was also the best prognostic indicator for functional outcome 2 years later.
CONCLUSIONS: Our results highlight the ability of the remaining normally conductive axons to predict visual recovery after decompression of the optic chiasm. The redundancy in anterior visual pathways may be explained, neuroanatomically, by overlapping receptive fields.

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Mesh:

Year:  2015        PMID: 25996300      PMCID: PMC5078717          DOI: 10.1097/WNO.0000000000000266

Source DB:  PubMed          Journal:  J Neuroophthalmol        ISSN: 1070-8022            Impact factor:   3.042


  15 in total

1.  Compressive lesions of the optic nerves and chiasm. Pattern of recovery of vision following surgical treatment.

Authors:  A Kayan; C J Earl
Journal:  Brain       Date:  1975-03       Impact factor: 13.501

2.  Relationship between retinal nerve fiber layer and visual field sensitivity as measured by optical coherence tomography in chiasmal compression.

Authors:  Helen V Danesh-Meyer; Stuart C Carroll; Rod Foroozan; Peter J Savino; Jennifer Fan; Yannan Jiang; Stephen Vander Hoorn
Journal:  Invest Ophthalmol Vis Sci       Date:  2006-11       Impact factor: 4.799

3.  Evaluation of early visual recovery in pituitary macroadenomas after endoscopic endonasal transphenoidal surgery: Quantitative assessment with diffusion tensor imaging (DTI).

Authors:  Ihsan Anik; Yonca Anik; Kenan Koc; Savas Ceylan; Hamza Genc; Ozgul Altintas; Dilek Ozdamar; Duygu Baykal Ceylan
Journal:  Acta Neurochir (Wien)       Date:  2011-01-26       Impact factor: 2.216

4.  Visual recovery after treatment for pituitary adenoma.

Authors:  G Lennerstrand
Journal:  Acta Ophthalmol (Copenh)       Date:  1983-12

5.  The effects of chiasmal compression on the pattern visual evoked potential.

Authors:  G E Holder
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1978-08

6.  Stages of improvement in visual fields after pituitary tumor resection.

Authors:  J B Kerrison; M J Lynn; C A Baer; S A Newman; V Biousse; N J Newman
Journal:  Am J Ophthalmol       Date:  2000-12       Impact factor: 5.258

7.  Multifocal visual evoked potential recordings in compressive optic neuropathy secondary to pituitary adenoma.

Authors:  Manju Jayaraman; S Ambika; Rashmin Anilkumar Gandhi; Shikha Rajesh Bassi; Priya Ravi; Parveen Sen
Journal:  Doc Ophthalmol       Date:  2010-09-04       Impact factor: 2.379

8.  ConTrack: finding the most likely pathways between brain regions using diffusion tractography.

Authors:  Anthony J Sherbondy; Robert F Dougherty; Michal Ben-Shachar; Sandy Napel; Brian A Wandell
Journal:  J Vis       Date:  2008-07-29       Impact factor: 2.240

Review 9.  Chiasmal syndromes.

Authors:  Rod Foroozan
Journal:  Curr Opin Ophthalmol       Date:  2003-12       Impact factor: 3.761

10.  Tract profiles of white matter properties: automating fiber-tract quantification.

Authors:  Jason D Yeatman; Robert F Dougherty; Nathaniel J Myall; Brian A Wandell; Heidi M Feldman
Journal:  PLoS One       Date:  2012-11-14       Impact factor: 3.240

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  2 in total

1.  Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI.

Authors:  Jianzhong He; Fan Zhang; Guoqiang Xie; Shun Yao; Yuanjing Feng; Dhiego C A Bastos; Yogesh Rathi; Nikos Makris; Ron Kikinis; Alexandra J Golby; Lauren J O'Donnell
Journal:  Hum Brain Mapp       Date:  2021-05-12       Impact factor: 5.399

2.  Using Deep Learning for the Classification of Images Generated by Multifocal Visual Evoked Potential.

Authors:  Nidan Qiao
Journal:  Front Neurol       Date:  2018-08-03       Impact factor: 4.003

  2 in total

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