Near-field focusing with optical phase antennas

We investigate the near-field focusing properties of three- dimensional phase antennas consisting of concentric rings designed to have source and image spots separated by several microns from the lens. Tight focal spots are obtained for silicon or gold rings patterned in a silica matrix. We analyze in detail the dependence of the performance of these lenses on geometrical parameters such as the number of rings, the ring thickness, and the focal distance. Subwavelength focal spots are found to form at distances of tens of wavelengths from the lens, thus suggesting applications to remote sensing and penlight microscopy and lithography. © 2009 Optical Society of America.This work has been supported by the Spanish MICINN (MAT2007-66050 and Consolider NanoLight.es) and by the EU (NMP4-2006-016881-SPANS and NMP4-SL-2008-213669- ENSEMBLE).Peer Reviewe

Evaluation of load-following reserves for power systems with significant RES penetration considering risk management

In this study a novel two-stage stochastic programming based day-ahead joint energy and reserve scheduling model is developed. Demand-side as a reserve resource is explicitly modeled through responsive load aggregations, as well as large industrial consumers that directly participate in the scheduling procedure. Furthermore, a risk-hedging measure is introduced, namely the Conditional Value-at-Risk (CVaR), to analyze the behavior of energy and reserve scheduling by both the generation and the demand-side for a risk-averse ISO. The proposed methodology is tested on the practical non-interconnected insular power system of Crete, Greece, which is characterized by a significant penetration of Renewable Energy Sources (RES).Es la versión aceptada del documento. Se puede consultar la versión final en el DOI 10.1109/SEGE.2015.732457

SECM imaging of the cut edge corrosion of galvanized steel as a function of pH

Scanning electrochemical microscopy (SECM) and the Scanning vibrating electrode technique (SVET) were employed to identify the local reactivity and the cathodes and anodes on a cut edge of galvanized steel. The SECM was used in the amperometric feedback mode (for the oxidation of ferrocenemethanol as mediator) for sensing the conductivity of the surface and in the redox competition mode for locating the depletion of the cathodic reactant. Good agreement was observed in acidic solution between the location of the conductive regions of the surface and the depletion of oxygen estimated from amperometric lines across the cut edge. In neutral medium, non-uniform activity of the steel surface was observed and correlated well with the ionic current flows in solution and with the accumulation of zinc corrosion products on steel. In alkaline medium, the entire metallic surface operated as electron source for the regeneration cycle of the redox mediator. Irrespective of the pH of the solution, a maximum of the feedback observed over the cut edge is consentaneous with the thermodynamic stability of iron in the reduced form. SECM provided useful information regarding the steel conductivity, whereas the zinc anodes could only be resolved by the SVE

Association of EWS-FLI1 Type 1 Fusion with Lower Proliferative Rate in Ewing’s Sarcoma

The Ewing's sarcoma (ES) family of tumors, including peripheral neuroectodermal tumor (PNET), is defined genetically by specific chromosomal translocations resulting in fusion of the EWS gene with a member of the ETS family of transcription factors, either FLI1 (90-95%) or ERG (5-10%). A second level of molecular genetic heterogeneity stems from the variation in the location of the translocation breakpoints, resulting in the inclusion of different combinations of exons from EWS and FLI1 (or ERG) in the fusion products. The most common type of EWS-FLI1 fusion transcript, type 1, is associated with a favorable prognosis and appears to encode a functionally weaker transactivator, compared to other fusion types. We sought to determine whether the observed covariation of structure, function, and clinical course correlates with tumor cell kinetic parameters such as proliferative rate and apoptosis, and with expression of the receptor for insulin-like growth factor I (IGF-1R). In a group of 86 ES/PNET with defined EWS-ETS fusions (45 EWS-FLI1 type 1, 27 EWS-FLI1 non-type 1, 14 EWS-ERG), we assessed proliferation rate by immunostaining for Ki-67 using MIB1 antibody (n = 85), apoptosis by TUNEL assay (n = 66), and IGF-1R expression by immunostaining with antibody 1H7 (n = 78). Ki-67 proliferative index was lower in tumors with EWS-FLI1 type 1 than those with non-type 1 EWS-FLI1, whether analyzed as a continuous (P = 0.049) or categorical (P = 0.047) variable. Logistic regression analysis suggests that this association was secondary to the association of type 1 EWS-FLI1 and lower IGF-1R expression (P = 0.04). Comparing EWS-FLI1 to EWS-ERG cases, Ki-67 proliferative index was higher in the latter (P = 0.01, Mann-Whitney test; P = 0.02, Fisher's exact test), but there was no significant difference in IGF-1R. TUNEL results showed no significant differences between groups. Our results suggest that clinical and functional differences between alternative forms of EWS-FLI1 are paralleled by differences in proliferative rate, possibly mediated by differential regulation of the IGF-1R pathway

Asymmetric Dark Matter and Dark Radiation

Asymmetric Dark Matter (ADM) models invoke a particle-antiparticle asymmetry, similar to the one observed in the Baryon sector, to account for the Dark Matter (DM) abundance. Both asymmetries are usually generated by the same mechanism and generally related, thus predicting DM masses around 5 GeV in order to obtain the correct density. The main challenge for successful models is to ensure efficient annihilation of the thermally produced symmetric component of such a light DM candidate without violating constraints from collider or direct searches. A common way to overcome this involves a light mediator, into which DM can efficiently annihilate and which subsequently decays into Standard Model particles. Here we explore the scenario where the light mediator decays instead into lighter degrees of freedom in the dark sector that act as radiation in the early Universe. While this assumption makes indirect DM searches challenging, it leads to signals of extra radiation at BBN and CMB. Under certain conditions, precise measurements of the number of relativistic species, such as those expected from the Planck satellite, can provide information on the structure of the dark sector. We also discuss the constraints of the interactions between DM and Dark Radiation from their imprint in the matter power spectrum.Comment: 22 pages, 5 figures, to be published in JCAP, minor changes to match version to be publishe

Role of a cryptic tRNA gene operon in survival under translational stress

As compared to eukaryotes, bacteria have a reduced tRNA gene set encoding between 30 and 220 tRNAs. Although in most bacterial phyla tRNA genes are dispersed in the genome, many species from distinct phyla also show genes forming arrays. Here, we show that two types of arrays with distinct evolutionary origins exist. This work focuses on long tRNA gene arrays (L-arrays) that encompass up to 43 genes, which disseminate by horizontal gene transfer and contribute supernumerary tRNA genes to the host. Although in the few cases previously studied these arrays were reported to be poorly transcribed, here we show that the L-array of the model cyanobacterium Anabaena sp. PCC 7120, encoding 23 functional tRNAs, is largely induced upon impairment of the translation machinery. The cellular response to this challenge involves a global reprogramming of the transcriptome in two phases. tRNAs encoded in the array are induced in the second phase of the response, directly contributing to cell survival. Results presented here show that in some bacteria the tRNA gene set may be partitioned between a housekeeping subset, which constantly sustains translation, and an inducible subset that is generally silent but can provide functionality under particular conditions.Ministerio de Ciencia, Innovación y Universidades [BFU2016-77097-P to I.L., A.H.; BIO2017-84066-R to F.J.R-C.]; Agencia Estatal de Investigación [PID2019-104784RJ-100/AEI/10.13039/501100011033 to R.L.I.]; National Science Foundation [MCB-1715840 to M.I.]. RB-M's lab at University of Alicante is a member of Proteored, PRB3 and is supported by grant PT17/0019, of the PE I+D+i 2013-2016, funded by ISCIII and ERDF. Funding for open access charge: Consejo Superior de Investigaciones Científicas

Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non-coding RNAs

Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases

Bladder cancer index: cross-cultural adaptation into Spanish and psychometric evaluation

BACKGROUND: The Bladder Cancer Index (BCI) is so far the only instrument applicable across all bladder cancer patients, independent of tumor infiltration or treatment applied. We developed a Spanish version of the BCI, and assessed its acceptability and metric properties. METHODS: For the adaptation into Spanish we used the forward and back-translation method, expert panels, and cognitive debriefing patient interviews. For the assessment of metric properties we used data from 197 bladder cancer patients from a multi-center prospective study. The Spanish BCI and the SF-36 Health Survey were self-administered before and 12 months after treatment. Reliability was estimated by Cronbach's alpha. Construct validity was assessed through the multi-trait multi-method matrix. The magnitude of change was quantified by effect sizes to assess responsiveness. RESULTS: Reliability coefficients ranged 0.75-0.97. The validity analysis confirmed moderate associations between the BCI function and bother subscales for urinary (r = 0.61) and bowel (r = 0.53) domains; conceptual independence among all BCI domains (r ≤ 0.3); and low correlation coefficients with the SF-36 scores, ranging 0.14-0.48. Among patients reporting global improvement at follow-up, pre-post treatment changes were statistically significant for the urinary domain and urinary bother subscale, with effect sizes of 0.38 and 0.53. CONCLUSIONS: The Spanish BCI is well accepted, reliable, valid, responsive, and similar in performance compared to the original instrument. These findings support its use, both in Spanish and international studies, as a valuable and comprehensive tool for assessing quality of life across a wide range of bladder cancer patients

Multi-parametric MR Imaging Biomarkers Associated to Clinical Outcomes in Gliomas: A Systematic Review

[EN] Purpose: To systematically review evidence regarding the association of multi-parametric biomarkers with clinical outcomes and their capacity to explain relevant subcompartments of gliomas. Materials and Methods: Scopus database was searched for original journal papers from January 1st, 2007 to February 20th , 2017 according to PRISMA. Four hundred forty-nine abstracts of papers were reviewed and scored independently by two out of six authors. Based on those papers we analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes. Similarly, eighteen studies defining subcompartments within the tumor region were also highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised according to the QUADAS-2 criteria. Results: It has been demonstrated that multi-parametric biomarkers are prepared for surrogating diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular profiling and response to treatment in gliomas. Quantifications and radiomics features obtained from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion (DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation, mass effect and pseudo flush, relapse compartments, gross tumor volumes, and high-risk regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences, we found no evidence to assert that observed co-occurrences were significantly different from their expected co-occurrences (Binomial test with False Discovery Rate correction, alpha=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual prevalence and trends in the literature. Conclusion: Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI exams have demonstrated their capability to predict clinical outcomes in different management moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during the last ten years, new multi-parametric MRI approaches have also been proposed to discover specific subcompartments of the tumors. MR biomarkers from those subcompartments show the local behavior within the heterogeneous tumor and may quantify the prognosis and response to treatment of gliomas.This work was supported by the Spanish Ministry for Investigation, Development and Innovation project with identification number DPI2016-80054-R.Oltra-Sastre, M.; Fuster García, E.; Juan -Albarracín, J.; Sáez Silvestre, C.; Perez-Girbes, A.; Sanz-Requena, R.; Revert-Ventura, A.... (2019). Multi-parametric MR Imaging Biomarkers Associated to Clinical Outcomes in Gliomas: A Systematic Review. Current Medical Imaging Reviews. 15(10):933-947. https://doi.org/10.2174/1573405615666190109100503S9339471510Louis D.N.; Perry A.; Reifenberger G.; The 2016 world health organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 2016,131(6),803-820Ostrom Q.T.; Gittleman H.; Fulop J.; CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008-2012. Neuro-oncol 2015,17(Suppl. 4),iv1-iv62Yachida S.; Jones S.; Bozic I.; Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 2010,467(7319),1114-1117Gerlinger M.; Rowan A.J.; Horswell S.; Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 2012,366(10),883-892Sottoriva A.; Spiteri I.; Piccirillo S.G.M.; Intratumor heterogeneityin human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci USA 2013,110(10),4009-4014Whiting P.F.; Rutjes A.W.; Westwood M.E.; QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011,155(8),529-536Stupp R.; Mason W.P.; van den Bent M.J.; Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005,352(10),987-996Ponte K.F.; Berro D.H.; Collet S.; In vivo relationship between hypoxia and angiogenesis in human glioblastoma: a multimodal imaging study. J Nucl Med 2017,58(10),1574-1579Pope W.B.; Kim H.J.; Huo J.; Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment. Radiology 2009,252(1),182-189Mörén L.; Bergenheim A.T.; Ghasimi S.; Brännström T.; Johansson M.; Antti H.; Metabolomic screening of tumor tissue and serum in glioma patients reveals diagnostic and prognostic information. Metabolites 2015,5(3),502-520Prager A.J.; Martinez N.; Beal K.; Omuro A.; Zhang Z.; Young R.J.; Diffusion and perfusion MRI to differentiate treatment-related changes including pseudoprogression from recurrent tumors in high-grade gliomas with histopathologic evidence. AJNR Am J Neuroradiol 2015,36(5),877-885Kickingereder P.; Burth S.; Wick A.; Radiomic profiling of glioblastoma: identifying an imaging predictor of patient survival with improved performance over established clinical and radiologic risk models. Radiology 2016,280(3),880-889Yoo R-E.; Choi S.H.; Cho H.R.; Tumor blood flow from arterial spin labeling perfusion MRI: a key parameter in distinguishing high-grade gliomas from primary cerebral lymphomas, and in predicting genetic biomarkers in high-grade gliomas. J Magn Reson Imaging 2013,38(4),852-860Liberman G.; Louzoun Y.; Aizenstein O.; Automatic multi-modal MR tissue classification for the assessment of response to bevacizumab in patients with glioblastoma. Eur J Radiol 2013,82(2),e87-e94Ramadan S.; Andronesi O.C.; Stanwell P.; Lin A.P.; Sorensen A.G.; Mountford C.E.; Use of in vivo two-dimensional MR spectroscopy to compare the biochemistry of the human brain to that of glioblastoma. Radiology 2011,259(2),540-549Xintao H.; Wong K.K.; Young G.S.; Guo L.; Wong S.T.; Support vector machine multi-parametric MRI identification of pseudoprogression from tumor recurrence in patients with resected glioblastoma. J Magn Reson Imaging 2011,33(2),296Ingrisch M.; Schneider M.J.; Nörenberg D.; Radiomic Analysis reveals prognostic information in T1-weighted baseline magnetic resonance imaging in patients with glioblastoma. Invest Radiol 2017,52(6),360-366Ulyte A.; Katsaros V.K.; Liouta E.; Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients. Neuroradiology 2016,58(12),1197-1208O’Neill A.F.; Qin L.; Wen P.Y.; de Groot J.F.; Van den Abbeele A.D.; Yap J.T.; Demonstration of DCE-MRI as an early pharmacodynamic biomarker of response to VEGF Trap in glioblastoma. J Neurooncol 2016,130(3),495-503Kickingereder P.; Bonekamp D.; Nowosielski M.; Radiogenomics of glioblastoma: machine learning-based classification of molecular characteristics by using multiparametric and multiregional mr imaging features. Radiology 2016,281(3),907-918Roberto S-R.; Antonio R-V.; Luis M-B.; Angel A-B.; Gracián G-M.; Quantitative mr perfusion parameters related to survival time in high-grade gliomas. European Radiology 2013,23(12),3456-3465Jain R.; Poisson L.; Narang J.; Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers. Radiology 2013,267(1),212-220Fathi K.A.; Mohseni M.; Rezaei S.; Bakhshandehpour G.; Saligheh R.H.; Multi-parametric (ADC/PWI/T2-W) image fusion approach for accurate semi-automatic segmentation of tumorous regions in glioblastoma multiforme. MAGMA 2015,28(1),13-22Caulo M.; Panara V.; Tortora D.; Data-driven grading of brain gliomas: a multiparametric MR imaging study. Radiology 2014,272(2),494-503Alexiou G.A.; Zikou A.; Tsiouris S.; Comparison of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT for the detection of recurrent high-grade glioma. Magn Reson Imaging 2014,32(7),854-859Van Cauter S.; De Keyzer F.; Sima D.M.; Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro-oncol 2014,16(7),1010-1021Seeger A.; Braun C.; Skardelly M.; Comparison of three different MR perfusion techniques and MR spectroscopy for multiparametric assessment in distinguishing recurrent high-grade gliomas from stable disease. Acad Radiol 2013,20(12),1557-1565Chawalparit O.; Sangruchi T.; Witthiwej T.; Diagnostic performance of advanced mri in differentiating high-grade from low-grade gliomas in a setting of routine service. J Med Assoc Thai 2013,96(10),1365-1373Li Y.; Lupo J.M.; Parvataneni R.; Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging. Neuro-oncol 2013,15(5),607-617Shankar J.J.S.; Woulfe J.; Silva V.D.; Nguyen T.B.; Evaluation of perfusion CT in grading and prognostication of high-grade gliomas at diagnosis: a pilot study. AJR Am J Roentgenol 2013,200(5)Zinn P.O.; Mahajan B.; Sathyan P.; Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme. PLoS One 2011,6(10)Matsusue E.; Fink J.R.; Rockhill J.K.; Ogawa T.; Maravilla K.R.; Distinction between glioma progression and post-radiation change by combined physiologic MR imaging. Neuroradiology 2010,52(4),297-306Juan-Albarracín J.; Fuster-Garcia E.; Manjón J.V.; Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification. PLoS One 2015,10(5)Itakura H.; Achrol A.S.; Mitchell L.A.; Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities. Sci Transl Med 2015,7(303)Ion-Margineanu A.; Van Cauter S.; Sima D.M.; Tumour relapse prediction using multiparametric MR data recorded during follow-up of GBM patients. BioMed Res Int 2015,2015Durst C.R.; Raghavan P.; Shaffrey M.E.; Multimodal MR imaging model to predict tumor infiltration in patients with gliomas. Neuroradiology 2014,56(2),107-115Yoon J.H.; Kim J.H.; Kang W.J.; Grading of cerebral glioma with multi-parametric MR Imaging and 18F-FDG-PET: concordance and accuracy. European Radiol 2014,24(2),380-389Demerath T.; Simon-Gabriel C.P.; Kellner E.; Mesoscopic imaging of glioblastomas: are diffusion, perfusion and spectroscopic measures influenced by the radiogenetic phenotype? Neuroradiol J 2017,30(1),36-47Qin L.; Li X.; Stroiney A.; Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma. Neuroradiology 2017,59(2),135-145Boult J.K.R.; Borri M.; Jury A.; Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd-DTPA and USPIO-enhanced imaging. NMR Biomed 2016,29(11),1608-1617Server A.; Kulle B.; Gadmar Ø.B.; Josefsen R.; Kumar T.; Nakstad P.H.; Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas. Eur J Radiol 2011,80(2),462-470Chang P.D.; Chow D.S.; Yang P.H.; Filippi C.G.; Lignelli A.; Predicting glioblastoma recurrence by early changes in the apparent diffusion coefficient value and signal intensity on FLAIR images. AJR Am J Roentgenol 2017,208(1),57-65Yi C.; Shangjie R.; Volume of high-risk intratumoralsubregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma. Eur Radiol 2017,27,3583-3592Khalifa J.; Tensaouti F.; Chaltiel L.; Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation. Eur Radiol 2016,26(11),4194-4203Prateek P.; Jay P.; Partovi S.; Madabhushi A.; Tiwari P.; Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastomamultiforme: preliminary findings. Eur Radiol 2017,27(10),4188-4197Lemasson B.; Chenevert T.L.; Lawrence T.S.; Impact of perfusion map analysis on early survival prediction accuracy in glioma patients. Transl Oncol 2013,6(6),766-774Inano R.; Oishi N.; Kunieda T.; Visualization of heterogeneity and regional grading of gliomas by multiple features using magnetic resonance-based clustered images. Sci Rep 2016,6,30344Delgado-Goñi T.; Ortega-Martorell S.; Ciezka M.; MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis. NMR Biomed 2016,29(6),732-743Cui Y.; Tha K.K.; Terasaka S.; Prognostic imaging biomarkers in glioblastoma: development and independent validation on the basis of multiregion and quantitative analysis of MR images. Radiology 2016,278(2),546-553Price S.J.; Young A.M.H.; Scotton W.J.; Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas. J Magn Reson Imaging 2016,43(2),487-494Sauwen N.; Acou M.; Van Cauter S.; Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI. Neuroimage Clin 2016,12,753-764Jena A.; Taneja S.; Gambhir A.; Glioma recurrence versus radiation necrosis: single-session multiparametric approach using simultaneous O-(2-18F-Fluoroethyl)-L-Tyrosine PET/MRI. Clin Nucl Med 2016,41(5),e228-e236Kim H.S.; Goh M.J.; Kim N.; Choi C.G.; Kim S.J.; Kim J.H.; Which combination of MR imaging modalities is best for predicting recurrent glioblastoma? Study of diagnostic accuracy and reproducibility. Radiology 2014,273(3),831-843Christoforidis G.A.; Yang M.; Abduljalil A.; “Tumoral pseudoblush” identified within gliomas at high-spatial-resolution ultrahigh-field-strength gradient-echo MR imaging corresponds to microvascularity at stereotactic biopsy. Radiology 2012,264(1),210-217Wang S.; Kim S.; Chawla S.; Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging. AJNR Am J Neuroradiol 2011,32(3),507-514Hanahan D.; Weinberg R.A.; Hallmarks of cancer: the next generation. Cell 2011,144(5),646-674Macdonald D.R.; Cascino T.L.; Schold S.C.; Cairncross J.G.; Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 1990,8(7),1277-1280Wen P.Y.; Macdonald D.R.; Reardon D.A.; Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 2010,28(11),1963-1972Sorensen A.G.; Batchelor T.T.; Wen P.Y.; Zhang W-T.; Jain R.K.; Response criteria for glioma. Nat Clin Pract Oncol 2008,5(11),634-644Rosenkrantz A.B.; Friedman K.; Chandarana H.; Current status of hybrid PET/MRI in oncologic imaging. AJR Am J Roentgenol 2016,206(1),162-172Castiglioni I.; Gallivanone F.; Canevari C.; Hybrid PET/MRI for In vivo imaging of cancer: current clinical experiences and recent advances. Curr Med Imaging 2016,12,106Mainta I.C.; Perani D.; Delattre B.M.A.; FDG PET/MR imaging in major neurocognitive disorders. Curr Alzheimer Res 2017,14,186-197Marner L.; Henriksen O.M.; Lundemann M.; Larsen V.A.; Law I.; Clinical PET/MRI in neurooncology: opportunities and challenges from a single-institution perspective. Clin Transl Imaging 2017,5(2),135-149R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2015. Available from: https://www.R-project.org