Enhanced visualization and quantification of magnetic resonance diffusion tensor imaging using the p:q tensor decomposition.
Many scalar measures have been proposed to quantify magnetic resonance diffusion tensor imaging (MR DTI) data in the brain. However, only two parameters are commonly used in the literature: mean diffusion (D) and fractional anisotropy (FA). We introduce a visualization technique which permits the simultaneous analysis of an additional five scalar measures. This enhanced diversity is important, as it is not known a priori which of these measures best describes pathological changes for brain tissue. The proposed technique is based on a tensor transformation, which decomposes the diffusion tensor into its isotropic (p) and anisotropic (q) components. To illustrate the use of this technique, diffusion tensor imaging was performed on a healthy volunteer, a sequential study in a patient with recent stroke, a patient with hydrocephalus and a patient with an intracranial tumour. Our results demonstrate a clear distinction between different anatomical regions in the normal volunteer and the evolution of the pathology in the patients. In the normal volunteer, the brain parenchyma values for p and q fell into a narrow band with 0.976<p<1.063 x 10(-3) mm2 s(-1) and 0.15<q<1.08 x 10(-3) mm2 s(-1). The noise appeared as a compact cluster with (p,q) components (0.011, 0.141) x 10(-3) mm2 s(-1), while the cerebrospinal fluid was (3.320, 0.330) x 10(-3) mm2 s(-1). In the stroke patient, the ischaemic area demonstrated a trajectory composed of acute, sub-acute and chronic phases. The components of the lesion were (0.824, 0.420), (0.884, 0.254), (2.624, 0.325) at 37 h, 1 week and 1 month, respectively. The internal capsule of the hydrocephalus patient demonstrated a larger dispersion in the p:q plane suggesting disruption. Finally, there was clear white matter tissue destruction in the tumour patient. In summary, the p:q decomposition enhances the visualization and quantification of MR DTI data in both normal and pathological conditions.
Department of Neurosurgery, Addenbrooke's Hospital and the University of Cambridge, UK.
A
A
Peña
H A L
HA
Green
T A
TA
Carpenter
S J
SJ
Price
J D
JD
Pickard
J H
JH
Gillard
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D001932:Brain Neoplasms / Q000473:pathology; D003625:Data Collection; D038524:Diffusion Magnetic Resonance Imaging / Q000592:standards*; D006801:Humans; D006849:Hydrocephalus / Q000473:pathology; D020521:Stroke / Q000473:pathology