Tumour progression or pseudoprogression?:A review of post-treatment radiological appearances of glioblastoma

Glioblastoma (GBM) is a common brain tumour in adults, which, despite multimodality treatment, has a poor median survival. Efficacy of therapy is assessed by clinical examination and magnetic resonance imaging (MRI) features. There is now a recognised subset of treated patients with imaging features that indicate "progressive disease" according to Macdonald's criteria, but subsequently, show stabilisation or resolution without a change in treatment. In these cases of "pseudoprogression", it is believed that non-tumoural causes lead to increased contrast enhancement and conventional MRI is inadequate in distinguishing this from true tumour progression. Incorrect diagnosis is important, as failure to identify pseudoprogression could lead to an inappropriate change of effective therapy. The purpose of this review is to outline the current research into radiological assessment with MRI and molecular imaging of post-treatment GBMs, specifically the differentiation between pseudoprogression and tumour progression

Volumetry of [11C]-methionine PET uptake and MRI contrast enhancement in patients with recurrent glioblastoma multiforme

We investigated the relationship between three-dimensional volumetric data of the metabolically active tumour volume assessed using [(11)C]-methionine positron emission tomography (MET-PET) and the area of gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA) enhancement assessed using magnetic resonance imaging (MRI) in patients with recurrent glioblastoma (GBM).MET-PET and contrast-enhanced MRI with Gd-DTPA were performed in 12 uniformly pretreated patients with recurrent GBM. To calculate the volumes in cubic centimetres, a threshold-based volume-of-interest (VOI) analysis of the metabolically active tumour volume (MET uptake indexes of > or = 1.3 and > or = 1.5) and of the area of Gd-DTPA enhancement was performed after coregistration of all images.In all patients, the metabolically active tumour volume as shown using a MET uptake index of > or = 1.3 was larger than the volume of Gd-DTPA enhancement (30.2 + or - 22.4 vs. 13.7 + or - 10.6 cm(3); p = 0.04). Metabolically active tumour volumes as shown using MET uptake indexes of > or =1.3 and > or = 1.5 and the volumes of Gd-DTPA enhancement showed a positive correlation (r = 0.76, p = 0.003, for an index of > or =1.3, and r = 0.74, p = 0.005, for an index of > or =1.5).The present data suggest that in patients with recurrent GBM the metabolically active tumour volume may be substantially underestimated by Gd-DTPA enhancement. The findings support the notion that complementary information derived from MET uptake and Gd-DTPA enhancement may be helpful in developing individualized, patient-tailored therapy strategies in patients with recurrent GBM

MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis

Based on studies focusing on positron emission tomography (PET)-computed tomography (CT) combined with magnetic resonance imaging (MRI) in the diagnosis of glioma, we conducted a systematic review and meta-analysis evaluating the pros and cons and the accuracy of different examinations. PubMed and Cochrane Library were searched. The search was conducted until April 2017. Two reviewers independently conducted the literature search according to the criteria set initially. Based on the exclusion criteria, 15 articles are included in this study. Of all studies that used MRI examination, there are five involving 18F-fluorodeoxyglucose-PET, five involving 11C-methionine-PET, five involving 18F-fluoro-ethyl-tyrosine-PET, and three involving 18F-fluorothymidine-PET. Due to the limitations such as lack of data, small sample size, and unrepresentative studies, we use a non-quantitative methodology. MRI examination can provide the anatomy information of glioma more clearly. PET-CT examinations based on tumor metabolism using different tracers have more advantages in determining the degree of glioma malignancy and boundaries. However, information provided by PET-CT of different tracers is not the same. With respect to the novel hybrid MRI/PET examination equipment proposed in recent years, the combination of MRI and PET-CT can definitively improve the diagnostic accuracy of glioma

Multiparametric Imaging and MR Image Texture Analysis in Brain Tumors

Discrimination of tumor from radiation injured (RI) tissues and differentiation of tumor types using noninvasive imaging is essential for guiding surgical and radiotherapy treatments are some of the challenges that clinicians face in the course of treatment of brain tumors. The first objective in this thesis was to develop a method to discriminate between glioblastoma tumor recurrences and radiation injury using multiparametric characterization of the tissue incorporating conventional magnetic resonance imaging signal intensities and diffusion tensor imaging parameters. Our results show significant correlations in the RI that was missing in the tumor regions. These correlations may aid in differentiating between tumor recurrence and RI. The second objective of was to investigate whether texture based image analysis of routine MR images would provide quantitative information that could be used to differentiate between glioblastoma and metastasis. Our results demonstrate that first-order texture feature of standard deviation and second-order texture features of entropy, inertia, homogeneity, and energy show significant differences between the two groups. The third objective was to investigate whether quantitative measurements of tumor size and appearance on MRI scans acquired prior to helical tomotherapy (HT) type whole brain radiotherapy with simultaneous infield boost treatment could be used to differentiate responder and non-responder patient groups. Our results demonstrated that smaller size lesions may respond better to this type of radiation therapy. Measures of appearance provided limited added value over measures of size for response prediction. Quantitative measurements of rim enhancement and core necrosis performed separately did not provide additional predictive value

The use of conventional and advanced magnetic resonance techniques in the assessment of primary brain tumours

The aim of the work described in this thesis was to investigate the value of conventional, perfusion- and diffusion-weighted magnetic resonance imaging (MRI) in patients with histology-proven low-grade gliomas (LGG), and the potential role of these methods in the management of patients with these brain tumours. Thirty-six patients were studied at the National Hospital for Neurology and Neurosurgery using conventional, perfusion-weighted and diffusion-weighted MRI at study entry and 6 monthly intervals thereafter. At each visit, tumour volume, maximum rCBV and ADC histogram measures were calculated. This is a unique cohort, as patients were treatment free until malignant transformation was diagnosed, which translates the natural history of these brain tumours. It is unlikely to find such a specific cohort as most of the patients receive treatment after the initial diagnosis of low grade gliomas. Chapters 1 and 2 of this thesis describe the theoretical basis of the MRI techniques used, and summarise the natural history and imaging aspects of cerebral gliomas. Chapter 3 describes a methodological study relating to tumour perfusion measurement: since the inclusion or exclusion of intratumoural vessels may influence the quantification of relative cerebral blood volume (rCBV), a study was conducted to choose the best ROI placement technique to be used for the rCBV measurements included in this thesis. It was shown that only the approach which excluded intratumoural vessels demonstrated a significant association between rCBV values and tumour subtypes (astrocytomas, oligodendrogliomas and oligoastrocytomas) and therefore this technique was used in all subsequent rCBV measurements

Characterising Peritumoural Progression of Glioblastoma using Multimodal MRI

Glioblastoma is a highly malignant tumor which mostly recurs locally around the resected contrast enhancement. However, it is difficult to identify tumor invasiveness pre-surgically, especially in non-enhancing areas. Thus, the aim of this thesis was to utilize multimodal MR technique to identify and characterize the peritumoral progression zone that eventually leads to tumor progression. Patients with newly diagnosed cerebral glioblastoma were included consecutively from our cohort between 2010 and2014. The presurgical MRI sequences included volumetric T1-weighted with contrast, FLAIR, T2-weighted, diffusion-weighted imaging, diffusion tensor and perfusion MR imaging. Postsurgical and follow-up MRI included structural and ADC images. Image deformation, caused by disease nature and surgical procedure, renders routine coregistration methods inadequate for MRIs comparison between different time points. Therefore, a two-staged non-linear semi-automatic coregistration method was developed from the modification of the linear FLIRT and non-linear FNIRT functions in FMRIB’s Software Library (FSL). Utilising the above mentioned coregistration method, a volumetric study was conducted to analyse the extent of resection based on different MR techniques, including T1 weighted with contrast, FLAIR and DTI measures of isotropy (DTI-p) and anisotropy (DTI-q). The results showed that patients can have a better clinical outcome with a larger resection of the abnormal DTI q areas. Further study of the imaging characteristics of abnormal peritumoural DTI-q areas, using MRS and DCS-MRI, showed a higher Choline/NAA ratio (p = 0.035), especially higher Choline (p = 0.022), in these areas when compared to normal DTI-q areas. This was indicative of tumour activity in the peritumoural abnormal DTI-q areas. The peritumoural progression areas were found to have distinct imaging characteristics. In these progression areas, compared to non-progression areas within a 10 mm border around the contrast enhancing lesion, there was higher signal intensity in FLAIR (p = 0.02), and T1C (p < 0.001), and there were lower intensity in ADC (p = 0.029) and DTI-p (p < 0.001). Further applying radiomics features showed that 35 first order features and 77 second order features were significantly different between progression and non-progression areas. By using supervised convolutional neural network, there was an overall accuracy of 92.4% in the training set (n = 37) and 78.5% in the validation set (n=14). In summary, multimodal MR imaging, particularly diffusion tensor imaging, can demonstrate distinct characteristics in areas of potential progression on preoperative MRI, which can be considered potential targets for treatment. Further application of radiomics and machine learning can be potentially useful when identifying the tumor invasive margin before the surgery.Chung Gung Medical Foundatio

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