The Impact of Intracranial Tumor Proximity to White Matter Tracts on Morbidity and Mortality: A Retrospective Diffusion Tensor Imaging Study.
Neurosurgery
; 80(2): 193-200, 2017 02 01.
Article
em En
| MEDLINE
| ID: mdl-28173590
Background: Using diffusion tensor imaging (DTI) in neurosurgical planning allows identification of white matter tracts and has been associated with a reduction in postoperative functional deficits. Objective: This study explores the relationship between the lesion-to-tract distance (LTD) and postoperative morbidity and mortality in patients with brain tumors in order to evaluate the role of DTI in predicting postoperative outcomes. Methods: Adult patients with brain tumors (n = 60) underwent preoperative DTI. Three major white matter pathways (superior longitudinal fasciculi [SLF], cingulum, and corticospinal tract) were identified using DTI images, and the shortest LTD was measured for each tract. Postoperative morbidity and mortality information was collected from electronic medical records. Results: The ipsilesional corticospinal tract LTD and left SLF LTD were significantly associated with the occurrence rate of total postoperative motor (P = .018) and language (P < .001) deficits, respectively. The left SLF LTD was also significantly associated with the occurrence rate of new postoperative language deficits (P = .003), and the LTD threshold that best predicted this occurrence was 1 cm (P < .001). KaplanMeier log-rank survival analyses in patients having high-grade tumors demonstrated a significantly higher mortality for patients with a left SLF LTD <1 cm (P = .01). Conclusion: Measuring tumor proximity to major white matter tracts using DTI can inform clinicians of the likelihood of postoperative functional deficits. A distance of 1 cm or less from eloquent white matter structures most significantly predicts the occurrence of new deficits with current surgical and imaging techniques.
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MEDLINE
Assunto principal:
Neoplasias Encefálicas
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Imagem de Tensor de Difusão
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Substância Branca
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article