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

Bell, Christopher, Pannek, Kerstin, Fay, Michael, Thomas, Paul, Bourgeat, Pierrick, Salvado, Olivier, Gal, Yaniv, Coulthard, Alan, Crozier, Stuart and Rose, Stephen (2014) Distance informed Track-Weighted Imaging (diTWI): a framework for sensitising streamlines information to neuropathology. Neuroimage, 86 60-66. doi:10.1016/j.neuroimage.2013.07.077

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Author Bell, Christopher
Pannek, Kerstin
Fay, Michael
Thomas, Paul
Bourgeat, Pierrick
Salvado, Olivier
Gal, Yaniv
Coulthard, Alan
Crozier, Stuart
Rose, Stephen
Title Distance informed Track-Weighted Imaging (diTWI): a framework for sensitising streamlines information to neuropathology
Journal name Neuroimage   Check publisher's open access policy
ISSN 1053-8119
Publication date 2014-02-01
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.neuroimage.2013.07.077
Open Access Status
Volume 86
Start page 60
End page 66
Total pages 7
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2014
Language eng
Formatted abstract
• Points on streamlines can be modulated based on their distance from target regions.
• Target ROIs can be generated from multimodal images (e.g. MRI and PET).
• diTWI maps provide information about pathology along white matter pathways.
• diTWI maps can be used to delineate tumour infiltration in high-grade gliomas.

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-[18F]-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.
Keyword HARDI
Diffusion imaging
PET imaging
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online: 3 August 2013.

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Created: Mon, 14 Oct 2013, 12:01:00 EST by Dr Yaniv Gal on behalf of Centre for Medical Diagnostic Technologies in Qld