9 research outputs found

    TangiWheel: A widget for manipulating collections on tabletop displays supporting hybrid Input modality

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    In this paper we present TangiWheel, a collection manipulation widget for tabletop displays. Our implementation is flexible, allowing either multi-touch or interaction, or even a hybrid scheme to better suit user choice and convenience. Different TangiWheel aspects and features are compared with other existing widgets for collection manipulation. The study reveals that TangiWheel is the first proposal to support a hybrid input modality with large resemblance levels between touch and tangible interaction styles. Several experiments were conducted to evaluate the techniques used in each input scheme for a better understanding of tangible surface interfaces in complex tasks performed by a single user (e.g., involving a typical master-slave exploration pattern). The results show that tangibles perform significantly better than fingers, despite dealing with a greater number of interactions, in situations that require a large number of acquisitions and basic manipulation tasks such as establishing location and orientation. However, when users have to perform multiple exploration and selection operations that do not require previous basic manipulation tasks, for instance when collections are fixed in the interface layout, touch input is significantly better in terms of required time and number of actions. Finally, when a more elastic collection layout or more complex additional insertion or displacement operations are needed, the hybrid and tangible approaches clearly outperform finger-based interactions.. ©2012 Springer Science+Business Media, LLC & Science Press, ChinaThe work is supported by the Ministry of Education of Spain under Grant No. TSI2010-20488. Alejandro Catala is supported by an FPU fellowship for pre-doctoral research staff training granted by the Ministry of Education of Spain with reference AP2006-00181.CatalĂĄ BolĂłs, A.; GarcĂ­a Sanjuan, F.; JaĂ©n MartĂ­nez, FJ.; Mocholi AgĂŒes, JA. (2012). TangiWheel: A widget for manipulating collections on tabletop displays supporting hybrid Input modality. Journal of Computer Science and Technology. 27(4):811-829. doi:10.1007/s11390-012-1266-4S811829274JordĂ  S, Geiger G, Alonso M, Kaltenbrunner M. The reacTable: Exploring the synergy between live music performance and tabletop tangible interfaces. In Proc. TEI 2007, Baton Rouge, LA, USA, Feb. 15-17, 2007, pp.139–146.Vandoren P, van Laerhoven T, Claesen L, Taelman J, Raymaekers C, van Reeth F. IntuPaint: Bridging the gap between physical and digital painting. In Proc. TABLETOP2008, Amterdam, the Netherlands, Oct. 1-3, 2008, pp.65–72.Schöning J, Hecht B, Raubal M, KrĂŒger A, Marsh M, Rohs M. Improving interaction with virtual globes through spatial thinking: Helping users ask “why?”. In Proc. IUI 2008, Canary Islans, Spain, Jan. 13-16, 2008, pp.129–138.Fitzmaurice GW, BuxtonW. An empirical evaluation of graspable user interfaces: Towards specialized, space-multiplexed input. In Proc. CHI 1997, Atlanta, USA, March 22-27, 1997, pp.43–50.Tuddenham P, Kirk D, Izadi S. Graspables revisited: Multitouch vs. tangible input for tabletop displays in acquisition and manipulation tasks. In Proc. CHI 2010, Atlanta, USA, April 10-15, 2010, pp.2223–2232.Lucchi A, Jermann P, Zufferey G, Dillenbourg P. An empirical evaluation of touch and tangible interfaces for tabletop displays. In Proc. TEI 2010, Cambridge, USA, Jan. 25-27, 2010, pp.177–184.Fitzmaurice G W, Ishii H, Buxton W. Bricks: Laying the foundations for graspable user interfaces. In Proc. CHI 1995, Denver, USA, May 7-11, 1995, pp.442–449.Ishii H, Ullmer B. Tangible bits: Towards seamless interfaces between people, bits and atoms. In Proc. CHI 1997, Atlanta, USA, March 22-27, 1997, pp.234–241.Ullmer B, Ishii H, Glas D. mediaBlocks: Physical containers, transports, and controls for online media. In Proc. SIGGRAPH1998, Orlando, USA, July 19-24, 1998, pp.379–386.Shen C, Hancock M S, Forlines C, Vernier F D. CoR2Ds: Context-rooted rotatable draggables for tabletop interaction. In Proc. CHI 2005, Portland, USA, April 2-7, 2005, pp.1781–1784.Lepinski G J, Grossman T, Fitzmaurice G. The design and evaluation of multitouch marking menus. In Proc. CHI 2010, Atlanta, USA, April 10-15, 2010, pp.2233–2242.Accot J, Zhai S. Beyond Fitts’ law: Models for trajectorybased HCI tasks. In Proc. CHI 1997, Atlanta, USA, March 22-27, 1997, pp.295–302.Song H, Kim B, Lee B, Seo J. A comparative evaluation on tree visualization methods for hierarchical structures with large fan-outs. In Proc. CHI 2010, Atlanta, USA, April 10-15, 2010, pp.223–232.Bailly G, Lecolinet E, Nigay L. Wave menus: Improving the novice mode of hierarchical marking menus. In Proc. INTERACT2007, RĂ­o de Janeiro, Brazil, Sept. 10-14, 2007, pp.475–488.Zhao S, Agrawala M, Hinckley K. Zone and polygon menus: Using relative position to increase the breadth of multi-stroke marking menus. In Proc. CHI 2006, Montreal, Canada, April 24-27, 2006, pp.1077–1086.Patten J, Recht B, Ishii H. Interaction techniques for musical performance with tabletop tangible interfaces. In Proc. ACE2006, Hollywood, USA, Jun. 14-16, 2006, Article No.27.Weiss M, Wagner J, Jansen Y, Jennings R, Khoshabeh R, Hollan J D, Borchers J. SLAP widgets: Bridging the gap between virtual and physical controls on tabletops. In Proc. CHI 2009, Boston, USA, April 4-9, 2009, pp.481–490.Hancock M, Hilliges O, Collins C, Baur D, Carpendale S. Exploring tangible and direct touch interfaces for manipulating 2D and 3D information on a digital table. In Proc. ITS 2009, Banff, Canada, Nov. 23-25, pp.77–84.Hilliges O, Baur D, Butz A. Photohelix: Browsing, sorting and sharing digital photo collections. In Proc. Horizontal Interactive Human-Computer Systems (TABLETOP2007), Newport, Rhode Island, USA, Oct. 10-12, 2007, pp.87–94.Hesselmann T, Flöring S, Schmidt M. Stacked half-Pie menus: Navigating nested menus on interactive tabletops. In Proc. ITS 2009, Banff, Canada, Nov. 23-25, 2009, pp.173–180.Gallardo D, JordĂ  S. Tangible jukebox: Back to palpable music. In Proc. TEI 2010, Boston, USA, Jan. 25-27, 2010, pp.199–202.Fishkin K. A taxonomy for and analysis of tangible interfaces. Personal and Ubiquitous Computing, 2004, 8(5): 347–358.Catala A, Jaen J, Martinez-Villaronga A A, Mocholi J A. AGORAS: Exploring creative learning on tangible user interfaces. In Proc. COMPSAC 2011, Munich, Germany, July 18-22, 2011, pp.326–335.Catala A, Garcia-Sanjuan F, Azorin J, Jaen J, Mocholi J A. Exploring direct communication and manipulation on interactive surfaces to foster novelty in a creative learning environment. IJCSRA, 2012, 2(1): 15–24.Catala A, Jaen J, van Dijk B, Jord`a S. Exploring tabletops as an effective tool to foster creativity traits. In Proc. TEI 2012, Kingston, Canada, Feb. 19-22, 2012, pp.143–150.Hopkins D. Directional selection is easy as pie menus. In: The Usenix Association Newsletter, 1987, 12(5): 103.Microsoft Surface User Experience Guidelines. http://msdn.microsoft.com/en-us/library/ff318692.aspx , May 2011.Maydak M, Stromer R, Mackay H A, Stoddard L T. Stimulus classes in matching to sample and sequence production: The emergence of numeric relations. Research in Developmental Disabilities, 1995, 16(3): 179–204

    Test-Retest Reliability of Kinematic Parameters of Timed Up and Go in People with Type 2 Diabetes

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    Diabetes mellitus is a chronic disease defined as a state of hyperglycaemia in fasting or postprandial states. Patients with type 2 diabetes mellitus (T2DM) often show reduced physical function, including low levels of strength, balance or mobility. In this regard, the timed up and go (TUG) is a widely used physical fitness test in people with T2DM. However, there is a lack of studies evaluating the properties TUG in this population. The present study aimed to evaluate the test-retest reliability of kinetic and kinematic parameters obtained from TUG in the diabetic population with different levels of diabetic neuropathy. A total of 56 patients with T2DM participated in the study. They were divided into three groups according to the vibration threshold: (a) severe neuropathy, (b) moderate neuropathy and (c) normal perception. The TUG was performed using two force platforms to assess kinematic measurements. The results show that both kinetic and kinematic variables had good to excellent reliability. The reliability of TUG was excellent for the whole sample and the groups with non-severe neuropathy. However, it was just good for the group with severe neuropathy

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

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    [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 GarcĂ­a, E.; Juan -AlbarracĂ­n, J.; SĂĄez 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),182-189MörĂ©n L.; Bergenheim A.T.; Ghasimi S.; BrĂ€nnström 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.; GraciĂĄn 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-AlbarracĂ­n J.; Fuster-Garcia E.; ManjĂłn 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-naĂŻve 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

    Reliability and validity of lumbar and abdominal trunk muscle endurance tests in office workers with nonspecific subacute low back pain

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    BACKGROUND AND OBJECTIVE: Despite the widespread use of trunk endurance tests, the reliability and validity of these tests in office workers with subacute nonspecific low back pain are unknown. MATERIALS AND METHODS: This cross-sectional study involved 190 subjects: 30 men and 42 women without low back pain and 47 men and 71 women with low back pain. All subjects underwent timed prone and supine isometric lumbar and abdominal trunk endurance tests that were performed until subjective fatigue occurred. All subjects also completed the Roland Morris and Oswestry self-reported disability questionnaires. A test-retest study (7 days) was conducted with 31 participants with low back pain from the study. RESULTS: For the abdominal trunk endurance test, males and females with low back pain had mean (SD) values of 62.06 (36.87) and 46.06 (29.28) seconds, respectively, both significantly lower than the asymptomatic workers. For the lumbar test, males and females with low back pain had mean (SD) values of 79.57 (30.66) and 75.49 (28.97) seconds, respectively, again, both significantly lower than the asymptomatic workers. The intraclass correlation coefficients of both tests exceeded 0.90 and the Kappa indices were excellent for both men and women. Receiver-operating curve analyses revealed areas under the curve very close to or exceeding 0.70 for both men and women for both tests. CONCLUSIONS: The lumbar and abdominal trunk muscle endurance tests appeared to be reliable and valid measures in office workers with subacute low back pain

    Cost-Utility Analysis of a Six-Weeks <i>Ganoderma Lucidum-</i>Based Treatment for Women with Fibromyalgia: A Randomized Double-Blind, Active Placebo-Controlled Trial

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    <p><b>Purpose:</b> To determine the effectiveness of adding <i>Ganoderma lucidum</i> (GL) to standard care for patients with fibromyalgia (FM), and to examine the costs per quality-adjusted life year (QALY) gained from this nutritional supplementation.</p> <p><b>Materials and methods:</b> This was a randomised controlled trial with a random allocation of participants to two groups; experimental group and active-placebo controlled group. A total of 26 women with FM participated in the experimental group. These participants were instructed to take 3 g of micromilled GL twice a day for six weeks. EQ-5D-5L was used to obtain the utilities and a non-parametric bootstrap was used to plot the acceptability curve.</p> <p><b>Results:</b> Of the women initially recruited, over 81% completed the experimental treatment. The incremental QALY in the GL group was 0.177, and the incremental QALY in the active placebo group was 0.101. Therefore, the difference in terms of QALYs was 0.076 and the incremental cost-utility ratio was €1348.55/QALYs. The cost-utility acceptability curve showed 90% probability that the addition of GL to the standard care as a nutritional supplement is cost-effective.</p> <p><b>Conclusions:</b> The GL as nutritional supplementation in patients with FM is cost-effective in women with FM. To authors’ knowledge, the current study reports the first cost-utility analysis of GL as a nutritional supplement.</p

    Learning semantically-annotated routes for context-aware recommendations on map navigation systems

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    Modern technology has brought many changes to our everyday lives. Our need to be in constant touch with others has been met with the cellphone, which has become our companion and the convergence point of many technological advances. The combination of capabilities such as browsing the Internet and GPS reception has multiplied the services and applications based on the current location of the user. However, providing the user with these services has certain drawbacks. Although map navigation systems are the most meaningful way of displaying this information, the user still has to manually set up the filter in order to obtain a non-bloated visualization of the map and the available services. To tackle this problem, we present here a semantic multicriteria ant colony algorithm capable of learning the user's routes, including associated context information, and then predicting the most likely route a user is following, given his current location and context data. This knowledge could then be used as the basis for offering services related to his current (or most likely future) context data close to the path he is following. Our experimental results show that our algorithm is capable of obtaining consistent solutions sets even when multiple objective ontological terms are included in the process

    Cost-Effectiveness of a Whole-Body Vibration Program in Patients with Type 2 Diabetes: A Retrospective Study Protocol

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    Background: Type 2 diabetes mellitus (T2DM) is a chronic disorder, with patients exhibiting hyperglycemia in fasting and postprandial states. T2DM has several complications, including loss of sensation in more distal body parts. Good peripheral sensitivity is essential as this affects different parameters related to activities of daily living, such as leg strength and balance. The objectives of this project were to assess the effects of an 8-week whole-body vibration (WBV) training program on (1) vibration perception threshold (VPT), (2) balance, (3) strength, (4) lipidic profile, (5) health-related quality of life, (6) diabetic neuropathy, and (7) body composition in T2DM patients. Methods/Design: A double-blind, randomized controlled study, with WBV and placebo groups, was carried out. Both groups performed 8 weeks of intervention, with 3 sessions per week, completing a total of 24 sessions. There were two groups: the experimental group, i.e., the WBV group, who received WBV therapy; and the placebo group, who completed a simulated training program that was developed on a Galileo Fitness platform, connected to software displayed on a screen. The participant could see the parameters of the simulated vibration training (duration, amplitude, and frequency), but it was the software that controlled the speakers placed inside the vibration platform. Ninety patients with T2DM (56 males and 34 females) were recruited for the intervention. Participants were assigned equally to the WBV (n = 45) and placebo (n = 45) groups. Primary outcome measures were (1) HbA1c and (2) vibration threshold. Secondary measures were (1) health-related quality of life, (2) balance, (3) strength, (4) body composition, (5) blood pressure, (6) diabetic neuropathy, and (7) lipidic profile. Statistical analysis was carried out by treatment intention and protocol. Discussion: This project aimed to investigate the effects of WBV training on HbA1c, vibration threshold, and incremental cost-effectiveness ratio in T2DM patients. In future, guidelines will be provided for the incorporation of the main obtained conclusions into the social-sanitary system and businesses
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