Biomedical subjects

H A L Green

Publications and source records attributed to H A L Green.

3 recordsLinked to original sources

PubMed2006

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.

Algorithms↗

PubMed2005

Cerebral haemodynamic disturbances in patients with moderate carotid artery stenosis.

OBJECTIVE: Dynamic MR perfusion imaging can detect cerebral perfusion deficits resulting from severe internal carotid artery (ICA) stenosis. It is unknown, however, whether moderate ICA stenosis (50-69%) also causes haemodynamic disturbance. We investigated whether cerebral perfusion deficits were detectable in patients with moderate ICA stenosis. METHODS: Eighteen patients underwent T2* weighted cerebral MR perfusion imaging with a gadolinium based contrast agent. Differences in mean time to peak (mTTP) and relative cerebral blood volume (rCBV) between cerebral hemispheres were calculated for middle cerebral artery territory regions by a reader blinded to the angiographic and clinical findings. RESULTS: There were significant differences in mTTP between cerebral hemispheres in 15 patients with a mean inter-hemispheric delay in mTTP of 0.49 s (95% confidence intervals, 0.25 and 0.72 s) which was statistically significant ( p <0.001). In 1 patient with bilateral moderate stenosis there was no difference in mTTP. CONCLUSIONS: Moderate ICA stenosis results in significant ipsilateral cerebral perfusion delays detectable by dynamic susceptibility MRI. Follow-up studies might reveal whether these delays improve following carotid endarterectomy.

Aged↗

PubMed2003

Diffusion tensor imaging of brain tumours at 3T: a potential tool for assessing white matter tract invasion?

AIM: To determine whether diffusion tensor imaging (DTI) of brain tumours can demonstrate abnormalities distal to hyperintensities on T2-weighted images, and possibly relate these to tumour grade. MATERIALS AND METHODS: Twenty patients with histologically confirmed supratentorial tumours, both gliomas (high and low grade) and metastases, were imaged at 3T using T2-weighted and DTI sequences. Regions of interest (ROI) were drawn within the tumour, in white matter at various distances from the tumour and in areas of abnormality on DTI that appeared normal on T2-weighted images. The relative anisotropy index (RAI)-a measure of white matter organization, was calculated for these ROI. RESULTS: The abnormality on DTI was larger than that seen on T2-weighted images in 10/13 patients (77%) with high-grade gliomas. New abnormalities were seen in the contralateral white matter in 4/13 (30%) of these cases. In these high-grade tumours the RAI in areas of white matter disruption with normal appearance on T2-weighted images was reduced (0.19+/-0.04). Even excluding patients with previous radiotherapy this difference remains significant. In all non high-grade tumours (WHO grade II gliomas and metastases) the tumour extent on DTI was identical to the abnormalities shown on T2-weighted imaging and RAI measurements were not reduced (0.3+/-0.04). CONCLUSIONS: Subtle white matter disruption can be identified using DTI in patients with high-grade gliomas. Such disruption is not identified in association with metastases or low-grade gliomas despite these tumours producing significant mass effect and oedema. We suggest the changes in DTI may be due to tumour infiltration and that the DTI may provide a useful method of detecting occult white matter invasion by gliomas.

Adult↗