Advanced Neuroimaging in Brain Tumors : Diffusion, Spectroscopy, Perfusion and Permeability MR imaging for the evaluation of tumor characterization and surgical treatment planning.

Advanced Neuroimaging in Brain Tumors: Diffusion, Spectroscopy, Perfusion and Permeability for the evaluation of tumor characterization and surgical treatment planning. The current standard of neuroimaging for brain tumor evaluation is anatomy-based MRI. Unfortunately, MRI does not fully reflect the complicated biology of infiltrative glioma, and has a limited capacity to differentiate a high-grade glioma (HGG) from a single brain metastasis. Grading of gliomas is important for the determination of appropriate treatment strategies and in the assessment of prognosis. It is clinically important to distinguish HGG from a single brain metastasis, because medical staging, surgical planning, and therapeutic decisions are different for each tumor type. The basis for this thesis was 208 patients admitted at Oslo University Hospital-Ullevål with the diagnosis of brain tumor between 2006 and 2010. The aim of this thesis was to evaluate in terms of diagnostic examination performance in the clinical decision-making process the use of advanced MRI techniques, namely, diffusion-weighted imaging (DWI), magnetic resonance spectroscopic imaging (MRSI), and T2*-weighted first pass dynamic susceptibility contrast-enhanced perfusion MRI (DSC MRI) in the diagnosis and preoperative planning of brain tumors, with focus in the grading and characterization of gliomas, as well as in the assessment of the peri-enhancing region aiming to demonstrate tumor-infiltration and tumor-free edema. In this thesis, we have demonstrated that MRSI and DSC MRI can be helpful to discriminate HGG from solitary metastases, supporting the hypothesis that these advanced MRI techniques can detect infiltration of tumor cells in the peri-enhancing region. We have demonstrated that combining DWI and MRSI increases the accuracy in the determination of glioma grade. We identified differences among all glial tumor grades for the parameters cerebral blood volume (rCBV) and microvascular leakage (MVL) derived from DSC MRI. Our correlation analysis indicate that MVL, rCBV, and cerebral blood flow (rCBF) may be related to different aspects of tumor angiogeneseis

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications

The prognostic value of advanced MR in gliomas

This work examines the prognostic value of advanced MR at selected time points during the early stages of treatment in glioma patients. In this thesis, serial imaging of glioma patients was conducted using diffusion tensor imaging (DTI), dynamic contrast enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI. A methodology for the processing and registration of multiparametric MRI was developed in order to simultaneously sample whole tumour measurements of multiple MR parameters with the same volume of interest.Differences between glioma grades were investigated using functional MR parameters and tested using Kruskal-Wallis tests. A 2-stage logistic regression model was developed to grade lesions from the preoperative MR, with the model retaining the apparent diffusion coefficient, radial diffusivity, anisotropic component of diffusion, vessel permeability and extravascular extracellular space parameters for glioma grading. A multi-echo single voxel spectroscopic sequence was independently investigated for the classification of gliomas into different grades.From preoperative MR, progression-free survival was predicted using the multiparametric MR data. Individual parameters were investigated using Kaplan-Meier survival analysis, before Cox regression modelling was used for a multiparametric analysis. Radial diffusivity, spin–lattice relaxation rate and blood volume fraction calculated from the DTI and DCE MRI were retained in the final model.MR parameter values were also investigated during the early stages of adjuvant treatment. Patients were scanned before and after chemoradiotherapy, with the change in MR parameters as well as the absolute values investigated for their prognostic information. Cox regression analysis was also performed for the adjuvant treatment imaging, with measures of the apparent diffusion coefficient, spin–lattice relaxation rate, vessel permeability and extravascular extracellular space, derived from the DTI and DCE datasets most predictive of progression-free survival.In conclusion, this thesis demonstrates multiparametric MR of gliomas during the early stages of treatment contains useful prognostic information relating to grade and progression-free survival interval

Malignant gliomas: Current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12-15 months for glioblastomas and 2-5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies, and importantly, for facilitating patient management, sparing patients from weeks or months of toxicity and ineffective treatment. This review will present an overview of epidemiology, molecular pathogenesis and current advances in diagnoses, and management of malignant gliomas. © 2014 Ahmed et al

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

In vivo magnetic resonance spectroscopy: basic methodology and clinical applications

The clinical use of in vivo magnetic resonance spectroscopy (MRS) has been limited for a long time, mainly due to its low sensitivity. However, with the advent of clinical MR systems with higher magnetic field strengths such as 3 Tesla, the development of better coils, and the design of optimized radio-frequency pulses, sensitivity has been considerably improved. Therefore, in vivo MRS has become a technique that is routinely used more and more in the clinic. In this review, the basic methodology of in vivo MRS is described—mainly focused on 1H MRS of the brain—with attention to hardware requirements, patient safety, acquisition methods, data post-processing, and quantification. Furthermore, examples of clinical applications of in vivo brain MRS in two interesting fields are described. First, together with a description of the major resonances present in brain MR spectra, several examples are presented of deviations from the normal spectral pattern associated with inborn errors of metabolism. Second, through examples of MR spectra of brain tumors, it is shown that MRS can play an important role in oncology