Probabilistic MRI tractography of the optic radiation using constrained spherical deconvolution: a feasibility study.
OBJECTIVE
Imaging the optic radiation (OR) is of considerable interest in studying diseases affecting the visual pathway and for pre-surgical planning of temporal lobe resections. The purpose of this study was to investigate the clinical feasibility of using probabilistic diffusion tractography based on constrained spherical deconvolution (CSD) to image the optic radiation. It was hypothesized that CSD would provide improved tracking of the OR compared with the widely used ball-and-stick model.


METHODS
Diffusion weighted MRI (30 directions) was performed on twenty patients with no known visual deficits. Tractography was performed using probabilistic algorithms based on fiber orientation distribution models of local white matter trajectories. The performance of these algorithms was evaluated by comparing computational times and receiver operating characteristic results, and by correlation of anatomical landmark distances to dissection estimates.


RESULTS
The results showed that it was consistently feasible to reconstruct individual optic radiations from clinically practical (4.5 minute acquisition) diffusion weighted imaging data sets using CSD. Tractography based on the CSD model resulted in significantly shorter computational times, improved receiver operating characteristic results, and shorter Meyer's loop to temporal pole distances (in closer agreement with dissection studies) when compared to the ball-and-stick based algorithm.


CONCLUSIONS
Accurate tractography of the optic radiation can be accomplished using diffusion MRI data collected within a clinically practical timeframe. CSD based tractography was faster, more accurate and had better correlation with known anatomical landmarks than ball-and-stick tractography.
Department of Radiology, The University of Melbourne, Victoria 3050, Australia; Department of Radiology, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Jeremy C
JC
Lim
Department of Radiology, The University of Melbourne, Victoria 3050, Australia; Department of Radiology, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Pramit M
PM
Phal
Department of Radiology, The University of Melbourne, Victoria 3050, Australia; Department of Radiology, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Patricia M
PM
Desmond
Department of Surgery, The University of Melbourne, Victoria 3050, Australia; Department of Neurosurgery, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Andrew D
AD
Nichols
Department of Radiology, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Chris
C
Kokkinos
Department of Surgery, The University of Melbourne, Victoria 3050, Australia; Department of Ophthalmology, The University of Auckland, Auckland, New Zealand.
Helen V
HV
Danesh-Meyer
Department of Surgery, The University of Melbourne, Victoria 3050, Australia; Department of Neurosurgery, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Andrew H
AH
Kaye
Department of Radiology, The University of Melbourne, Victoria 3050, Australia; Department of Radiology, The Royal Melbourne Hospital, Grattan Street, Parkville, Victoria 3050, Australia.
Bradford A
BA
Moffat
D001921:Brain / Q000033:anatomy & histology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D011336:Probability; D014795:Visual Pathways