Intratumoral uptake heterogeneity in 18 F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown to be a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types. Methods: A single database of 555 pretreatment 18 F-FDG PET images (breast, cervix, esophageal, head and neck, and lung cancer tumors) was assembled. Four robust and reproducible textural feature-derived parameters were considered. The issues associated with the calculation of textural features using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves, was investigated using Spearman rank coefficients for different volume ranges. The complementary prognostic value of MATV and textural features was assessed through multivariate Cox analysis in the esophageal and non-small cell lung cancer (NSCLC) cohorts. Results: A large range of MATVs was included in the population considered (3-415 cm 3 ; mean, 35; median,19; SD, 50). The correlation between MATV and textural features varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and calculation methods both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P 5 0.0053 and 0.0093, respectively) along with stage (P 5 0.002) in non-small cell lung cancer, but in the esophageal tumors, volume and heterogeneity had less complementary value because of smaller overall volumes. Conclusion: Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10 cm 3 , although the complementary information increases substantially with larger volumes. Fordi agnosis and staging in oncology, 18 F-FDG PET/CT is a powerful tool (1). Its use in therapy assessment (2,3) is increasing. Within this context, more emphasis is being given to image-derived indices (4). On the one hand, features extracted from PET images, including metabolically active tumor volume (MATV), mean standardized uptake value (SUV), and total lesion glycolysis, have provided potentially higher prognostic value than standard maximum SUV in various cancer types (5). On the other hand, more recently the heterogeneity of 18 F-FDG uptake within tumors has been associated with treatment failure (4,6-8). Proposed approaches to assessing the heterogeneity of intratumoral activity distribution include visual evaluation (9), SUV coefficient of variation (10), area under...

IDH mutation appears to be a significant marker of positive prognosis and chemosensitivity in low-grade gliomas, independently of 1p-19q codeletion, whereas its impact on the course of untreated tumors seems to be limited.

Diffuse low-grade gliomas are highly epileptogenic brain tumours. We aimed to explore the natural course of epileptic seizures, their predictors and the prognostic significance of their occurrence in adult patients harbouring a diffuse low-grade glioma. An observational retrospective multicentre study examined 1509 patients with diffuse low-grade gliomas to identify mutual interactions between tumour characteristics, tumour course and epileptic seizures. At diagnosis, 89.9% of patients had epileptic seizures. Male gender (P = 0.003) and tumour location within functional areas (P = 0.001) were independent predictors of a history of epileptic seizures at diagnosis. Tumour volume, growth velocity, cortical location, histopathological subtype or molecular markers did not significantly affect epileptic seizure occurrence probability. Prolonged history of epileptic seizures (P < 0.001), insular location (P = 0.003) and tumour location close to functional areas (P = 0.038) were independent predictors of uncontrolled epileptic seizures at diagnosis. Occurrence of epileptic seizures (P < 0.001), parietal (P = 0.029) and insular (P = 0.002) locations were independent predictors of uncontrolled epileptic seizures after oncological treatment. Patient age (P < 0.001), subtotal (P = 0.007) and total (P < 0.001) resections were independent predictors of total epileptic seizure control after oncological treatment. History of epileptic seizures at diagnosis and total surgical resection were independently associated with increased malignant progression-free (P < 0.001 and P < 0.001) and overall (P < 0.001 and P = 0.016) survivals. Epileptic seizures are independently associated with diffuse low-grade glioma prognosis. Patients diagnosed with epileptic seizures and those with complete and early surgical resections have better oncological outcomes. Early and maximal surgical resection is thus required for diffuse low-grade gliomas, both for oncological and epileptological purposes.

A recent computational model of brain tumor growth, developed to better describe how gliomas invade through the adjacent brain parenchyma, is based on two major elements: cell proliferation and isotropic cell diffusion. On the basis of this model, glioma growth has been simulated in a virtual brain, provided by a 3D segmented MRI atlas. However, it is commonly accepted that glial cells preferentially migrate along the direction of fiber tracts. Therefore, in this paper, the model has been improved by including anisotropic extension of gliomas. The method is based on a cell diffusion tensor derived from water diffusion tensor (as given by MRI diffusion tensor imaging). Results of simulations have been compared with two clinical examples demonstrating typical growth patterns of lowgrade gliomas centered around the insula. The shape and the kinetic evolution are better simulated with anisotropic rather than isotropic diffusion. The best fit is obtained when the anisotropy of the cell diffusion tensor is increased to greater anisotropy than the observed water diffusion tensor. The shape of the tumor is also influenced by the initial location of the tumor. Anisotropic brain tumor growth simulations provide a means to determine the initial location of a low-grade glioma as well as its cell diffusion tensor, both of which might reflect the biological characteristics of invasion. Key words: computational modeling; glioma; anisotropic growth; diffusion tensor; cell migration Low-grade (WHO grade II) gliomas are initially slowly evolving tumors, but can become rapidly fatal after anaplastic transformation. Because of their infiltrative characteristics, surgery alone fails to cure these tumors, even in their premalignant stage. Indeed, these tumors may not form a solid mass but may invade diffusely throughout the brain parenchyma as "gliomatosis cerebri."Recently, a biomathematical model (1) has been proposed to quantitatively describe the growth rates of gliomas visualized radiologically. This model takes into account the two major biological phenomena underlying the growth of gliomas at the cellular scale: proliferation and diffusion. The simplest choice for the proliferation term is a constant growth rate , leading to an exponentially growing total number of glioma cells. For the invasive properties of gliomas, cell migration is assumed to be a random walk, corresponding to a passive (Fickian) diffusion characterized by a single coefficient D. Simulations of this proliferation-diffusion equation are performed on a 3D T 1 MR structural image of the brain, with segmentation of CSF (which corresponds to the boundaries of the parenchyma), white matter, and gray matter images.In previous publications (2), the diffusion of cells in white matter is assumed to be 5 (to 100) times higher than in gray matter, consistent with observations that glioma cells migrate more quickly in white matter than in gray. Within white (or gray) matter, cell diffusion was considered an isotropic phenomenon. However, it is commonly accepted that gl...

Radiation therapy induces DNA damage and inflammation leading to fibrosis. Fibrosis can occur 4 to 12 months after radiation therapy. This process worsens with time and years. Radiation-induced fibrosis is characterized by fibroblasts proliferation, myofibroblast differentiation, and synthesis of collagen, proteoglycans and extracellular matrix. Myofibroblasts are non-muscle cells that can contract and relax. Myofibroblasts evolve towards irreversible retraction during fibrosis process. In this review, we discussed the interplays between transforming growth factor-β1 (TGF-β1), canonical WNT/β-catenin pathway and peroxisome proliferator-activated receptor gamma (PPAR γ) in regulating the molecular mechanisms underlying the radiation-induced fibrosis, and the potential role of PPAR γ agonists. Overexpression of TGF-β and canonical WNT/β-catenin pathway stimulate fibroblasts accumulation and myofibroblast differentiation whereas PPAR γ expression decreases due to the opposite interplay of canonical WNT/β-catenin pathway. Both TGF-β1 and canonical WNT/β-catenin pathway stimulate each other through the Smad pathway and non-Smad pathways such as phosphatidylinositol 3-kinase/serine/threonine kinase (PI3K/Akt) signaling. WNT/β-catenin pathway and PPAR γ interact in an opposite manner. PPAR γ agonists decrease β-catenin levels through activation of inhibitors of the WNT pathway such as Smad7, glycogen synthase kinase-3 (GSK-3 β) and dickkopf-related protein 1 (DKK1). PPAR γ agonists also stimulate phosphatase and tensin homolog (PTEN) expression, which decreases both TGF-β1 and PI3K/Akt pathways. PPAR γ agonists by activating Smad7 decrease Smads pathway and then TGF-β signaling leading to decrease radiation-induced fibrosis. TGF-β1 and canonical WNT/β-catenin pathway promote radiation-induced fibrosis whereas PPAR γ agonists can prevent radiation-induced fibrosis.

Alzheimer's disease (AD) is a neurodegenerative disease, in which the primary etiology remains unknown. AD presents amyloid beta (Aβ) protein aggregation and neurofibrillary plaque deposits. AD shows oxidative stress and chronic inflammation. In AD, canonical Wingless-Int (Wnt)/β-catenin pathway is downregulated, whereas peroxisome proliferator-activated receptor γ (PPARγ) is increased. Downregulation of Wnt/β-catenin, through activation of glycogen synthase kinase-3β (GSK-3β) by Aβ, and inactivation of phosphatidylinositol 3-kinase/Akt signaling involve oxidative stress in AD. Cannabidiol (CBD) is a non-psychotomimetic phytocannabinoid from Cannabis sativa plant. In PC12 cells, Aβ-induced tau protein hyperphosphorylation is inhibited by CBD. This inhibition is associated with a downregulation of p-GSK-3β, an inhibitor of Wnt pathway. CBD may also increase Wnt/β-catenin by stimulation of PPARγ, inhibition of Aβ and ubiquitination of amyloid precursor protein. CBD attenuates oxidative stress and diminishes mitochondrial dysfunction and reactive oxygen species generation. CBD suppresses, through activation of PPARγ, pro-inflammatory signaling and may be a potential new candidate for AD therapy.

Independent of the molecular status, the spontaneous velocity of diametric expansion allows the identification of rapidly growing diffuse low-grade gliomas (at higher risk of worsened evolution) during the pretherapeutic period and without delaying treatment.

A consecutive series of 143 unselected adult patients with histologically proved World Health Organization grade II gliomas was reviewed to assess the prognostic value of growth rates of mean tumor diameters on successive magnetic resonance images before treatment. There is an inverse correlation between growth rates and survival (p < 0.001; median survival at 5.16 years for a growth rate of 8mm/year or more; median survival >15.0 years for a growth rate <8mm/year). Thus, individual magnetic resonance imaging tumor growth rates should be incorporated in the planning of the initial therapeutic strategy of grade II gliomas.