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Distance informed Track-Weighted Imaging (diTWI): A framework for sensitising streamline information to neuropathology

Overview of attention for article published in NeuroImage, August 2013
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Title
Distance informed Track-Weighted Imaging (diTWI): A framework for sensitising streamline information to neuropathology
Published in
NeuroImage, August 2013
DOI 10.1016/j.neuroimage.2013.07.077
Pubmed ID
Authors

Christopher Bell, Kerstin Pannek, Michael Fay, Paul Thomas, Pierrick Bourgeat, Olivier Salvado, Yaniv Gal, Alan Coulthard, Stuart Crozier, Stephen Rose

Abstract

Track-Weighted Imaging (TWI), where voxel intensity is based on image metrics encoded along streamline trajectories, provides a mechanism to study white matter disease. However, with generalised streamline weighting, it is difficult to localise the precise anatomical source and spread of injury or neuropathology. This limitation can be overcome by modulating the voxel weight based on the distance of the voxel from a given anatomical location along the tract, which we term diTWI: distance informed Track-Weighted Imaging. The location of known neuropathology can be delineated on any given imaging modality (e.g. MRI or PET). To demonstrate the clinical utility of this approach, we measured tumour cell infiltration along WM fibre tracts in 13 patients with newly diagnosed glioblastoma and 1 patient with Anaplastic Astrocytoma. TWI and diTWI maps were generated using information obtained from dynamic contrast enhanced MRI (area under the curve, AUC) and diffusivity maps (ADC and FA) with tumour boundaries automatically extracted using a logistic regression classifier. The accuracy of the derived tumour volumes was compared to those generated using 3,4-dihydroxy-6-[(18)F]-fluoro-l-phenylalanine (FDOPA) PET imaging. The accuracy of the tumour volumes generated from the diTWI maps was superior to volumes derived from the TWI, geometric distance or baseline AUC, FA and ADC maps. The relative overlap and relative dissimilarity rates for the diTWI generated tumour volumes after classification were found to be 82.3±15.3% (range 69.1-91.9) and 16.9±8.8% (range 7.9-37.5), respectively. These findings show that diTWI maps provide a useful framework for localising neuropathological processes occurring along WM pathways.

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Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Netherlands 1 2%
Italy 1 2%
United Kingdom 1 2%
Japan 1 2%
United States 1 2%
Unknown 51 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 21%
Student > Ph. D. Student 9 16%
Student > Master 8 14%
Student > Doctoral Student 4 7%
Professor > Associate Professor 4 7%
Other 9 16%
Unknown 11 19%
Readers by discipline Count As %
Medicine and Dentistry 12 21%
Engineering 10 18%
Neuroscience 7 12%
Computer Science 4 7%
Agricultural and Biological Sciences 2 4%
Other 5 9%
Unknown 17 30%