Diagnostic methods and treatment options for focal cortical dysplasia.

Our inability to adequately treat many patients with refractory epilepsy caused by focal cortical dysplasia (FCD), surgical inaccessibility and failures are significant clinical drawbacks. The targeting of physiologic features of epileptogenesis in FCD and colocalizing functionality has enhanced completeness of surgical resection, the main determinant of outcome. Electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) and magnetoencephalography are helpful in guiding electrode implantation and surgical treatment, and high-frequency oscillations help defining the extent of the epileptogenic dysplasia. Ultra high-field MRI has a role in understanding the laminar organization of the cortex, and fluorodeoxyglucose-positron emission tomography (FDG-PET) is highly sensitive for detecting FCD in MRI-negative cases. Multimodal imaging is clinically valuable, either by improving the rate of postoperative seizure freedom or by reducing postoperative deficits. However, there is no level 1 evidence that it improves outcomes. Proof for a specific effect of antiepileptic drugs (AEDs) in FCD is lacking. Pathogenic mutations recently described in mammalian target of rapamycin (mTOR) genes in FCD have yielded important insights into novel treatment options with mTOR inhibitors, which might represent an example of personalized treatment of epilepsy based on the known mechanisms of disease. The ketogenic diet (KD) has been demonstrated to be particularly effective in children with epilepsy caused by structural abnormalities, especially FCD. It attenuates epigenetic chromatin modifications, a master regulator for gene expression and functional adaptation of the cell, thereby modifying disease progression. This could imply lasting benefit of dietary manipulation. Neurostimulation techniques have produced variable clinical outcomes in FCD. In widespread dysplasias, vagus nerve stimulation (VNS) has achieved responder rates >50%; however, the efficacy of noninvasive cranial nerve stimulation modalities such as transcutaneous VNS (tVNS) and noninvasive (nVNS) requires further study. Although review of current strategies underscores the serious shortcomings of treatment-resistant cases, initial evidence from novel approaches suggests that future success is possible.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Cerebral Lactate Metabolism After Traumatic Brain Injury.

Cerebral energy dysfunction has emerged as an important determinant of prognosis following traumatic brain injury (TBI). A number of studies using cerebral microdialysis, positron emission tomography, and jugular bulb oximetry to explore cerebral metabolism in patients with TBI have demonstrated a critical decrease in the availability of the main energy substrate of brain cells (i.e., glucose). Energy dysfunction induces adaptations of cerebral metabolism that include the utilization of alternative energy resources that the brain constitutively has, such as lactate. Two decades of experimental and human investigations have convincingly shown that lactate stands as a major actor of cerebral metabolism. Glutamate-induced activation of glycolysis stimulates lactate production from glucose in astrocytes, with subsequent lactate transfer to neurons (astrocyte-neuron lactate shuttle). Lactate is not only used as an extra energy substrate but also acts as a signaling molecule and regulator of systemic and brain glucose use in the cerebral circulation. In animal models of brain injury (e.g., TBI, stroke), supplementation with exogenous lactate exerts significant neuroprotection. Here, we summarize the main clinical studies showing the pivotal role of lactate and cerebral lactate metabolism after TBI. We also review pilot interventional studies that examined exogenous lactate supplementation in patients with TBI and found hypertonic lactate infusions had several beneficial properties on the injured brain, including decrease of brain edema, improvement of neuroenergetics via a "cerebral glucose-sparing effect," and increase of cerebral blood flow. Hypertonic lactate represents a promising area of therapeutic investigation; however, larger studies are needed to further examine mechanisms of action and impact on outcome.

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.

Prognostic value of baseline total metabolic tumor volume (TMTV0) measured on FDG-PET/CT in patients with peripheral T-cell lymphoma (PTCL).

BACKGROUND: Most peripheral T-cell lymphoma (PTCL) patients have a poor outcome and the identification of prognostic factors at diagnosis is needed. PATIENTS AND METHODS: The prognostic impact of total metabolic tumor volume (TMTV0), measured on baseline [(18)F]2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography, was evaluated in a retrospective study including 108 PTCL patients (27 PTCL not otherwise specified, 43 angioimmunoblastic T-cell lymphomas and 38 anaplastic large-cell lymphomas). All received anthracycline-based chemotherapy. TMTV0 was computed with the 41% maximum standardized uptake value threshold method and an optimal cut-off point for binary outcomes was determined and compared with others prognostic factors. RESULTS: With a median follow-up of 23 months, 2-year progression-free survival (PFS) was 49% and 2-year overall survival (OS) was 67%. High TMTV0 was significantly associated with a worse prognosis. At 2 years, PFS was 26% in patients with a high TMTV0 (>230 cm(3), n = 53) versus 71% for those with a low TMTV0, [P < 0.0001, hazard ratio (HR) = 4], whereas OS was 50% versus 80%, respectively, (P = 0.0005, HR = 3.1). In multivariate analysis, TMTV0 was the only significant independent parameter for both PFS and OS. TMTV0, combined with PIT, discriminated even better than TMTV0 alone, patients with an adverse outcome (TMTV0 >230 cm(3) and PIT >1, n = 33,) from those with good prognosis (TMTV0 ≤230 cm(3) and PIT ≤1, n = 40): 19% versus 73% 2-year PFS (P < 0.0001) and 43% versus 81% 2-year OS, respectively (P = 0.0002). Thirty-one patients (other TMTV0-PIT combinations) had an intermediate outcome, 50% 2-year PFS and 68% 2-year OS. CONCLUSION: TMTV0 appears as an independent predictor of PTCL outcome. Combined with PIT, it could identify different risk categories at diagnosis and warrants further validation as a prognostic marker.

Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: systematic review and meta-analysis.

BACKGROUND: For the past decade (18)F-fluoro-ethyl-l-tyrosine (FET) and (18)F-fluoro-deoxy-glucose (FDG) positron emission tomography (PET) have been used for the assessment of patients with brain tumor. However, direct comparison studies reported only limited numbers of patients. Our purpose was to compare the diagnostic performance of FET and FDG-PET. METHODS: We examined studies published between January 1995 and January 2015 in the PubMed database. To be included the study should: (i) use FET and FDG-PET for the assessment of patients with isolated brain lesion and (ii) use histology as the gold standard. Analysis was performed on a per patient basis. Study quality was assessed with STARD and QUADAS criteria. RESULTS: Five studies (119 patients) were included. For the diagnosis of brain tumor, FET-PET demonstrated a pooled sensitivity of 0.94 (95% CI: 0.79-0.98) and pooled specificity of 0.88 (95% CI: 0.37-0.99), with an area under the curve of 0.96 (95% CI: 0.94-0.97), a positive likelihood ratio (LR+) of 8.1 (95% CI: 0.8-80.6), and a negative likelihood ratio (LR-) of 0.07 (95% CI: 0.02-0.30), while FDG-PET demonstrated a sensitivity of 0.38 (95% CI: 0.27-0.50) and specificity of 0.86 (95% CI: 0.31-0.99), with an area under the curve of 0.40 (95% CI: 0.36-0.44), an LR+ of 2.7 (95% CI: 0.3-27.8), and an LR- of 0.72 (95% CI: 0.47-1.11). Target-to-background ratios of either FDG or FET, however, allow distinction between low- and high-grade gliomas (P > .11). CONCLUSIONS: For brain tumor diagnosis, FET-PET performed much better than FDG and should be preferred when assessing a new isolated brain tumor. For glioma grading, however, both tracers showed similar performances.