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Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images.
Treiber, Jeffrey Mark; White, Nathan S; Steed, Tyler Christian; Bartsch, Hauke; Holland, Dominic; Farid, Nikdokht; McDonald, Carrie R; Carter, Bob S; Dale, Anders Martin; Chen, Clark C.
Afiliação
  • Treiber JM; School of Medicine, University of California San Diego, San Diego, California, United States of America.
  • White NS; Center for Theoretical and Applied Neuro-Oncology, University of California San Diego Moores Cancer Center, San Diego, California, United States of America.
  • Steed TC; Multimodal Imaging Laboratory, University of California San Diego, San Diego, California, United States of America.
  • Bartsch H; School of Medicine, University of California San Diego, San Diego, California, United States of America.
  • Holland D; Center for Theoretical and Applied Neuro-Oncology, University of California San Diego Moores Cancer Center, San Diego, California, United States of America.
  • Farid N; Neurosciences Graduate Program, University of California San Diego, San Diego, California, United States of America.
  • McDonald CR; Multimodal Imaging Laboratory, University of California San Diego, San Diego, California, United States of America.
  • Carter BS; Multimodal Imaging Laboratory, University of California San Diego, San Diego, California, United States of America.
  • Dale AM; Multimodal Imaging Laboratory, University of California San Diego, San Diego, California, United States of America.
  • Chen CC; Department of Radiology, University of California San Diego, San Diego, California, United States of America.
PLoS One ; 11(3): e0152472, 2016.
Article em En | MEDLINE | ID: mdl-27027775
INTRODUCTION: Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD: We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. RESULTS: Evaluation of the algorithm's performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5th and 95th percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. CONCLUSION: Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Neoplasias Encefálicas / Imagem de Difusão por Ressonância Magnética Tipo de estudo: Diagnostic_studies / Guideline Limite: Female / Humans / Male Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Neoplasias Encefálicas / Imagem de Difusão por Ressonância Magnética Tipo de estudo: Diagnostic_studies / Guideline Limite: Female / Humans / Male Idioma: En Ano de publicação: 2016 Tipo de documento: Article