2 research outputs found
Recommended from our members
Unsupervised Segmentation of 5D Hyperpolarized Carbon-13 MRI Data Using a Fuzzy Markov Random Field Model
Hyperpolarized MRI with 13C-labelled compounds
is an emerging clinical technique allowing in vivo metabolic processes
to be characterized non-invasively. Accurate quantification
of 13C data, both for clinical and research purposes, typically
relies on the use of region-of-interest analysis to detect and
compare regions of altered metabolism. However, it is not clear
how this should be determined from the five-dimensional data
produced and most standard methodologies are unable to exploit
the multidimensional nature of the data. Here we propose a
solution to the novel problem of 13C image segmentation using a
hybrid Markov random field model with continuous fuzzy logic.
The algorithm fully utilizes the multi-dimensional data format in
order to classify each voxel into one of six distinct classes based
on its metabolic characteristics. Bayesian priors fully incorporate
spatial, temporal and ratiometric contextual information whilst
image contrast from multiple spectral dimensions are considered
concurrently by using an analogy from color image segmentation.
Performance of the algorithm is demonstrated on in silico
data where the superiority of the approach over a reference
thresholding method is consistently observed. Application to in
vivo animal data from a pre-clinical subcutaneous tumor model
illustrates the ability of the MRF algorithm to successfully detect
tumor location whilst avoiding image artefacts. This work has
the potential to assist the analysis of human hyperpolarized 13C
data in the future.CJD is jointly funded by the National Institute for Health Research (NIHR), Cambridge Biomedical Research Centre and GlaxoSmithKline (GSK). The authors acknowledge further research support from Cancer Research UK (C19212/A911376, C19212/A16628), the Cancer Research UK/Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and Manchester, the CRUK Cambridge Centre and Cambridge Experimental Cancer Medicine Centre
Recommended from our members
Novel approaches to MRI of glioma
Gliomas are extremely heterogeneous, both morphologically and biologically, which contributes to a very poor prognosis. Current imaging of glioma is insufficient for a thorough diagnosis, therapy assessment and prognosis prediction. Moreover, refined and more sophisticated imaging technique could help in furthering our knowledge of gliomas.
In order to facilitate proliferation, cancer cells undergo a change in structure and an increase in metabolism that results in distortion and disruption of tissue architecture. Gliomas are characterised by an increase in cells of variable sizes, as well as changes in the tissue microstructure. Diffusion-Weighted Imaging (DWI) and the apparent diffusion coefficient (ADC), have been extensively studied as potential imaging biomarkers for cellularity and tissue architecture. However, several studies have shown partial overlap in the measured values between tumour subtypes. Moreover, ADC is influenced by several factors and does not provide detailed information on the tissue microstructure. The Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) is a novel diffusion model that infers tissue microstructure compartment from conventional DWI measurements. This model derives metrics for the intracellular, intravascular and extracellular– extravascular spaces providing a more detailed interpretation of the tissue microstructure. To date, VERDICT has been applied to xenograft models of colorectal cancer, patient studies of prostate cancer and recently its feasibility in glioma has been shown. In this PhD I have applied a shortened version of the VERDICT method to image intratumoral and intertumoral heterogeneity in glioma. The results have also been validated with histology as part of a prospective study.
Gliomas also exhibit a significant increase in mitotic activity within the tumour. The increased number of mitosis alters cell density which, in turn, affects the total concentration of tissue sodium as the concentration of tissue sodium is approximately ten-fold higher in the extracellular compared to the intracellular space. In addition, there is a decrease in Na+/K+-ATPase activity in tumours due to ATP depletion, which contributes to disturb sodium homeostasis. Non-invasive detection of 23Na with MRI has the potential to quantify sodium concentration and therefore could be an imaging probe of cell morphology and membrane function within the tumour microenvironment, as well as a method of probing tissue heterogeneity. During my PhD, a novel 23Na-MRI technique has been used to evaluate sodium distribution within glioma and in the surrounding tissue.
Metabolic reprogramming is one of the major driving forces for determining glioma growth and invasion. Therefore, the non-invasive characterization of metabolic intratumoral, peritumoral and intertumoral heterogeneity in vivo could help to better stratify patients and to develop novel therapeutic strategies targeting cancer-specific metabolic pathways. 13C magnetic resonance imaging (MRI) using dynamic nuclear polarization (DNP) is a novel technique that allows non-invasive assessment of the metabolism of hyperpolarized (HP) 13C-labelled molecules in vivo, such as the exchange of [1-13C]pyruvate to [1-13C]lactate in tumours (Warburg effect). Part of my PhD has focused on developing and translating HP [1-13C]pyruvate MRI to explore metabolic reprogramming in glioma and the surrounding microenvironment.
The overall aim of my PhD has been to develop novel approaches to imaging glioma with MRI to probe both the architectural and metabolic changes of Glioma. The preliminary evidence suggests that these tools can more deeply phenotype tumours than conventional imaging approaches. Although the main focus of this work has been gliomas, the techniques developed and presented here may be applied to study other pathological conditions within the brain, which raises the possibility of other potential clinical applications for this work