PubMed Health⌕ Search

Biomedical subjects

Neil G Burnet

Publications and source records attributed to Neil G Burnet.

7 recordsLinked to original sources
PubMed2007

Predicting patterns of glioma recurrence using diffusion tensor imaging.

Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T(2)-weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials.

Adult↗
PubMed2006

A mathematical model of the treatment and survival of patients with high-grade brain tumours.

More years of life per patient are lost as the result of primary brain tumours than any other form of cancer. The most aggressive of these is known as glioblastoma (GBM). The median survival time of patients with GBM is under 10 months and the outlook has hardly improved over the past 20 years. Generally, these tumours are remarkably resistant to radiotherapy and yet about 2-3% of all GBMs appear to be cured. The objectives of this study were to formulate a mathematical and phenomenological model of tumour growth in a population of patients with GBM to predict survival, and to use the model to extract biological information from clinical data. The model describes the growth of the tumour and the resulting damage to the normal brain using simple concepts borrowed from chemical reaction engineering. Death is assumed to result when the amount of surviving normal brain falls to a critical level. Radiotherapy is assumed to destroy tumour but not healthy brain. Simple rules are included to represent approximately the clinician's decisions about what type of treatment to offer each patient. A population of patients is constructed by assuming that key parameters can be sampled from statistical distributions. Following Monte Carlo simulation, the model can be fitted to data from clinical trials. The model reproduces clinical data extremely accurately. This suggests that the long-term survivors are not a separate sub-population but are the 'lucky tail' of a unimodal distribution. The estimated values of radiation sensitivity (represented as SF2, the survival fraction after 2Gy) suggest the presence of severe hypoxia, which renders cells less sensitive to radiation. The model can predict the probable age distribution of tumours at presentation. The model shows the complicated effects of waiting times for treatment on the survival outcomes, and is used to predict the effects of escalation of radiotherapy dose. The model may aid the design of clinical trials using radiotherapy for patients with GBM, especially in helping to estimate the size of trial required. It is also designed in a generic form, and might be applicable to other tumour types.

Age Distribution↗
PubMed2005

Immunohistochemical estimation of cell cycle entry and phase distribution in astrocytomas: applications in diagnostic neuropathology.

An immunohistochemical method for assessing cell cycle phase distribution in neurosurgical biopsies would enable such data to be incorporated into diagnostic algorithms for the estimation of prognosis and response to adjuvant chemotherapy in glial neoplasms, without the requirement for flow cytometric analysis. Paraffin-embedded sections of intracerebral gliomas (n = 48), consisting of diffuse astrocytoma (n = 9), anaplastic astrocytoma (n = 8) and glioblastoma (n = 31), were analysed by immunohistochemistry using markers of cell cycle entry, Mcm-2 and Ki67, and putative markers of cell cycle phase, cyclins D1 (G1-phase), cyclin A (S-phase), cyclin B1 (G2-phase) and phosphohistone H3 (Mitosis). Double labelling confocal microscopy confirmed that the phase markers were infrequently coexpressed. Cell cycle estimations by immunohistochemistry were corroborated by flow cytometric analysis. There was a significant increase in Mcm-2 (P < 0.0001), Ki67 (P < 0.0001), cyclin A (P < 0.0001) and cyclin B1 (P = 0.002) expression with increasing grade from diffuse astrocytoma through anaplastic astrocytoma to glioblastoma, suggesting that any of these four markers has potential as a marker of tumour grade. In a subset of glioblastomas (n = 16) for which accurate clinical follow-up data were available, there was a suggestion that the cyclin A:Mcm-2 labelling fraction might predict a relatively favourable response to radical radiotherapy. These provisional findings, however, require confirmation by a larger study. We conclude that it is feasible to obtain detailed cell cycle data by immunohistochemical analysis of tissue biopsies. Such information may facilitate tumour grading and may enable information of prognostic value to be obtained in the routine diagnostic laboratory.

Adult↗
PubMed2004

Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas.

The inherent invasiveness of malignant cells is a major determinant of the poor prognosis of cerebral gliomas. Diffusion tensor MRI (DTI) can identify white matter abnormalities in gliomas that are not seen on conventional imaging. By breaking down DTI into its isotropic (p) and anisotropic (q) components, we can determine tissue diffusion "signatures". In this study we have characterised these abnormalities in peritumoural white matter tracts. Thirty-five patients with cerebral gliomas and seven normal volunteers were imaged with DTI and T2-weighted sequences at 3 T. Displaced, infiltrated and disrupted white matter tracts were identified using fractional anisotropy (FA) maps and directionally encoded colour maps and characterised using tissue signatures. The diffusion tissue signatures were normal in ROIs where the white matter was displaced. Infiltrated white matter was characterised by an increase in the isotropic component of the tensor (p) and a less marked reduction of the anisotropic component (q). In disrupted white matter tracts, there was a marked reduction in q and increase in p. The direction of water diffusion was grossly abnormal in these cases. Diffusion tissue signatures may be a useful method of assessing occult white matter infiltration.

Adult↗
PubMed2003

Quantitative assessment of inter-clinician variability of target volume delineation for medulloblastoma: quality assurance for the SIOP PNET 4 trial protocol.

BACKGROUND AND PURPOSE: To assess inter-clinician variability amongst specialist paediatric radiation oncologists in delineating clinical target volumes for treating medulloblastoma as a quality assurance exercise prior to the introduction of the SIOP PNET 4 trial protocol of conformal radiotherapy to the posterior fossa and tumour bed. PATIENTS AND METHODS: Participants from 17 UK centres attended an educational meeting and then completed a clinical planning exercise to outline: (1) the whole posterior fossa and (2) the tumour bed. Quantitative analysis of the volumes, lengths, spatial positioning and axial planes for each individual was carried out and variation between individuals analysed. RESULTS: Outlining of the posterior fossa was reasonably consistent, although most variation was seen in defining the superior border of the tentorium. A major difference was the decision whether or not to include the post-surgical meningocoele in the clinical target volume (CTV). The CTV for the tumour bed was under treated by all participants due to lack of inclusion of pre-operative tumour extent. CONCLUSIONS: This exercise demonstrated several ambiguities in the draft protocol and highlighted particular areas of inter-clinician variation. Consequently the protocol was revised and improved to take account of these findings. We recommend that planning exercises, in conjunction with education and training, should be implemented before the start of any new radiotherapy trial. In the future, the use of image transfer will allow prospective peer review of target volumes before treatment commences. These measures are essential to ensure that alterations in clinical practice are achieved in a uniform way.

Cerebellar Neoplasms↗
PubMed2003

A method for reducing ovarian doses in whole neuro-axis irradiation for medulloblastoma.

BACKGROUND AND PURPOSE: Cranio-spinal irradiation for medulloblastoma can impair fertility in girls. The literature indicates that an ovarian dose of 4 Gy causes permanent infertility in 30% of young females and that doses of <1.5 Gy over the whole treatment are desirable. We report a modified radiotherapy technique using a non-divergent beam edge inferiorly to reduce the ovarian dose. PATIENTS AND METHODS: Eight female patients with medulloblastoma had magnetic resonance imaging (MRI) studies in the treatment position to identify the position of their ovaries relative to the radiation field. The information was transferred to the radiotherapy planning system and plans were generated using conventional spinal fields and modified fields with a half beam block at the inferior border. RESULTS: Identifying the position of the ovaries by MRI enabled the dose to be estimated for the two techniques. Using a non-divergent beam inferiorly, the mean ovarian dose was reduced in all cases by a median value of 2.45 Gy (range 0.6-19.5 Gy) and the median percentage reduction was 66.8% (range 2.6-84.6%). The position of the ovary relative to the beam edge was critical in determining the dose reduction for each case. The modified technique doubled the number of patients receiving <4 Gy to a single ovary from three to six. With this alteration, three patients also had an ovary receiving <1.5 Gy whereas all exceeded this dose with conventional treatment. CONCLUSION: We recommend using asymmetry at the inferior spinal border to achieve a non-divergent edge to the treatment field to reduce the dose to the ovary. Using MRI to localise the ovaries is important in estimating their dose and in assisting the counselling of patients and their families about future fertility.

Adolescent↗