Konstantinos Fountas

Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T

Abstract Purpose: To assess the contribution of 1H-magnetic resonance spectroscopy (1H-MRS), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic susceptibility contrast-enhanced (DSCE) imaging metrics in the differentiation of glioblastomas from solitary metastasis, and particularly to clarify the controversial reports regarding the hypothesis that there should be a significant differentiation between the intratumoral and peritumoral areas. Methods: Conventional MR imaging, 1H-MRS, DWI, DTI and DSCE MRI was performed on 49 patients (35 glioblastomas multiforme, 14 metastases) using a 3.0-T MR unit. Metabolite ratios, apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) were measured in the intratumoral and peritumoral regions of the lesions. Receiver-operating characteristic analysis was used to obtain the cut-off values for the parameters presenting a statistical difference between the two tumor groups. Furthermore, we investigated the potential effect of the region of interest (ROI) size on the quantification of diffusion properties in the intratumoral region of the lesions, by applying two different ROI methods. Results: Peritumoral N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, Cho/NAA and rCBV significantly differentiated glioblastomas from intracranial metastases. ADC and FA presented no significant difference between the two tumor groups. Conclusions: 1H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases. The quantification of the diffusion properties in the intratumoral region is independent of the ROI size placed.

Distinct peak at 3.8 ppm observed by 3T MR spectroscopy in meningiomas, while nearly absent in high-grade gliomas and cerebral metastases

The purpose of the present study was to evaluate distinct metabolic features of meningiomas to distinguish them from other brain lesions using proton magnetic resonance spectroscopy. The study was performed on 17 meningiomas, 24 high-grade gliomas and 9 metastases. Elevated signal intensity at 3.8 ppm observed in low TE spectra adequately differentiated meningioma from other brain tumors while alanine was not indicative of meningioma occurrence; the presence of lipids and lactate did not provide a strong index for meningioma malignancy.

Classification methods for the differentiation of atypical meningiomas using diffusion and perfusion techniques at 3-T MRI.

The purpose was to investigate the contribution of machine learning algorithms using diffusion and perfusion techniques in the differentiation of atypical meningiomas from glioblastomas and metastases. Apparent diffusion coefficient, fractional anisotropy, and relative cerebral blood volume were measured in different tumor regions. Naive Bayes, k-Nearest Neighbor, and Support Vector Machine classifiers were used in the classification procedure. The application of classification methods adds incremental differential diagnostic value. Differentiation is mainly achieved using diffusion metrics, while perfusion measurements may provide significant information for the peritumoral regions.

18F-fluorothymidine PET imaging in gliomas: an update

Brain neoplasms constitute a group of tumors with discrete differentiation grades, and therefore, course of disease and prognosis. Magnetic resonance imaging (MRI) remains the gold standard method for the investigation of central nervous system tumors. However, MRI suffers certain limitations, especially if radiation therapy or chemotherapy has been previously applied. On the other hand, given the development of newer radiopharmaceuticals, positron emission tomography (PET) aims to a better investigation of brain tumors, assisting in the clinical management of the patients. In the present review, the potential contribution of radiolabeled fluorothymidine (FLT) imaging for the evaluation of brain tumors will be discussed. In particular, we will present the role of FLT-PET imaging in the depiction of well and poorly differentiated lesions, the assessment of patient prognosis and treatment response, and the recognition of disease recurrence. Moreover, related semi-quantitative and kinetic parameters will be discussed.

Management of Glial Tumor Recurrence

This chapter outlines the basic principles of management of patients with recurrent gliomas. These procedures pose certain technical, clinical, and psychological challenges. The diagnosis of glioma recurrence and its differentiation from a radiation and/or chemotherapy effect remain problematic despite the use of all advanced imaging methodologies. The role of conventional magnetic resonance imaging (MRI), MR-advanced techniques, positron emission tomography (PET), single photon emission computed tomography (SPECT), and emerging imaging techniques is evaluated, along with the advantages, disadvantages, and limitations of each imaging method. The surgical resection of a recurrent high-grade but also low-grade glioma as a treatment option is assessed. Special emphasis is given to the recognition of any prognostic factors that may identify good candidates for a reoperation. The potential role of reirradiation, either in the form of conventional or stereotactic radiation, chemotherapy (either systemic or local), immunotherapy, and combined salvage therapies is also examined.

Extraoperative Cortical Stimulation and Mapping

Accurate identification of eloquent cortical areas is of paramount importance for safe surgical resection in cases of medically intractable epilepsy or in glioma cases. Despite all the recent advances in functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) as well as in magnetic source imaging and high-density surface EEGs, direct electrical cortical stimulation remains the gold standard for accurately outlining cortical eloquent areas. Intraoperatively employed cortical stimulation and mapping through an awake craniotomy is not always feasible. Patients with anxiety or fear of undergoing an awake surgical procedure, those with conditions contraindicating an awake procedure, and pediatric patients may not be suitable for mapping through an awake craniotomy. In these cases, and also in cases of medically refractory epilepsy in which invasive EEG monitoring is required for localizing any epileptogenic focus/i, cortical mapping may safely be accomplished through an extraoperative stimulation via implanted subdural and/or depth electrodes. This chapter presents the surgical preparation, the preoperative planning, the surgical procedure, and the extraoperative stimulation and mapping processes and their nuances. The associated complications with the electrode implantation and the invasive EEG monitoring and stimulation are also presented. Moreover, the future perspectives of invasive EEG monitoring and extraoperative cortical stimulation and mapping are briefly presented.

Exploiting morphology and texture of 3D tumor models in DTI for differentiating glioblastoma multiforme from solitary metastasis

Abstract Ambiguous imaging appearance of Glioblastoma Multiforme (GBM) and solitary Metastasis (MET) is a challenge to conventional Magnetic Resonance Imaging (MRI) based diagnosis, leading to exploitation of advanced MRI techniques, such as Diffusion Tensor Imaging (DTI). In this study, 3D tumor models are generated by a DTI clustering segmentation technique, providing up to 16 brain tissue diffusivities, complemented by T1 post-contrast imaging, resulting in the identification of tumor core, whose surface is refined by a Morphological Morphing interpolation technique. The 3D models are analyzed in terms of their surface and internal signal variations characteristics towards identification of discriminant features for differentiation between GBMs and METs, utilizing a case sample composed of 10 GBMs and 10 METs. Morphology analysis of tumor core surface is assessed by 5 local curvature features. Texture analysis considers 11 first and 16 second order 3D textural features. From the 16 second order features, 11 are based on Gray Level Co-Occurrence Matrices (GLCM) and 5 on Gray Level Run Length Matrices (GLRLM), calculated from DTI isotropic and anisotropic parametric maps, corresponding to 3D tumor core segmented from the clustering technique. Also, 3 different image quantization levels (QL) were tested for both GLCM and GLRLM analysis, while 1–4 pixel displacements (D) in case of GLCM analysis. Case sample distributions of morphology and texture features were analyzed using the Mann-Whitney U test, with a cut-off value of 0.05 to identify discriminant features. The discriminatory performance of the derived features was analyzed with Receiver Operating Characteristic (ROC) curve analysis. Results highlight the value of all 5 local curvature descriptors to capture differences between the boundary of GBMs and METs. Histogram analysis of isotropy maps revealed statistical significant differences for median value and kurtosis, while 7 out of the 11 GLCM features were capable of discriminating heterogeneity of anisotropic diffusion properties of GBMs and METs, at QL = 6 and D = 2. Finally, all 5 GLRLM features extracted from diffusion isotropy maps seem to discriminate structural properties of GBMs and METs, at QL = 5. Results demonstrate the potential of surface morphology and texture analysis of 3D tumor imaging appearance in pre-treatment brain MRI tumor differentiation.

The Role of Magnetic Resonance Spectroscopy in the Diagnosis of Ring Enhancing Lesions

Ring-enhancing intracranial lesions constitute a common and quite puzzling diagnostic dilemma. These lesions may present as solitary or multiple on a routine brain MRI, and are characterized by a contrast enhancing halo and a non enhancing center. The central part may present with low signal intensity on T1, and high signal intensity on T2 weighted images. They are usually surrounded by a variable amount of edema. They may be located anywhere in the brain, although the junctional zone of gray-white matter is their most common location [Omuroet al., 2006; Smirniotopoulos et al., 2007]. Their size may vary from a few millimetres to several centimetres. The differential diagnosis of ring enhancing lesions is quite large. It may include neoplasms, infections, inflammatory processes, or vascular pathologies. The incidence of each pathological entity depends highly on the geographical region and the study population. It is well documented that infections and inflammatory processes are more common in developing countries, while neoplasms and demyelinating lesions are more frequent in developed countries. Clinical history is not always helpful in their differential diagnosis, since more than 50% of CNS infections may present without fever and no obvious inflicting incident. Moreover, other laboratory tests may not be able to help in their differential diagnosis. In addition, the presenting symptomatology and the clinical examination of these patients are non-specific and frequently overlapping, making thus the establishment of an accurate diagnosis quite difficult. Routine brain MR imaging is very sensitive in the identification of ring enhancing lesions but it cannot distinguish between neoplastic and non neoplastic lesions, in a large percentage of these cases. Frequently, the differentiation of a tumor from an infection is quite difficult, based solely on conventional MRI. Therefore, advanced MR imaging