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Barbagallo GM, Paratore S, Caltabiano R, Palmucci S, Parra HS, Privitera G, et al. Longterm therapy with temozolomide is a feasible option for newly diagnosed glioblastoma: a single-institution experience with as many as 101 temozolomide cycles. Neurosurg Focus 2014; 37: E4. doi: 10.3171/2014.9.FOCUS14502BarbagalloGMParatoreSCaltabianoRPalmucciSParraHSPriviteraGet alLongterm therapy with temozolomide is a feasible option for newly diagnosed glioblastoma: a single-institution experience with as many as 101 temozolomide cyclesNeurosurg Focus201437E410.3171/2014.9.FOCUS1450225434389Open DOISearch in Google Scholar
Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJB, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005; 352: 987-96. doi: 10.1056/NEJMoa043330StuppRMasonWPvan denBent MJWellerMFisherBTaphoornMJBet alRadiotherapy plus concomitant and adjuvant temozolomide for glioblastomaN Engl J Med20053529879610.1056/NEJMoa04333015758009Open DOISearch in Google Scholar
Altieri R, Melcarne A, Soffietti R, Rudá R, Franchino F, Pellerino A, et al. Supratotal resection of glioblastoma: is less more? Surg Technol Int 2019; 35: 432-440. PMID: 31373379AltieriRMelcarneASoffiettiRRudáRFranchinoFPellerinoAet alSupratotal resection of glioblastoma: is less more?Surg Technol Int201935432440PMID: 31373379Search in Google Scholar
Certo F, Stummer W, Farah JO, Freyschlag C, Visocchi M, Morrone A, et al. Supramarginal resection of glioblastoma: 5-ALA fluorescence, combined intraoperative strategies and correlation with survival. J Neurosurg Sci 2019; 63: 625-32. doi: 10.23736/S0390-5616.19.04787-8CertoFStummerWFarahJOFreyschlagCVisocchiMMorroneAet alSupramarginal resection of glioblastoma: 5-ALA fluorescence, combined intraoperative strategies and correlation with survivalJ Neurosurg Sci2019636253210.23736/S0390-5616.19.04787-831355623Open DOISearch in Google Scholar
Louis DN, Ohgaki H, Wiestler OD, Cavenee WK. WHO classification of tumours of the central nervous system, Revise 4th edition. Lyon: IARC Press, 2016.LouisDNOhgakiHWiestlerODCaveneeWKWHO classification of tumours of the central nervous system, Revise 4th editionLyonIARC Press2016Search in Google Scholar
Altieri R, Hirono S, Duffau H, Ducati A, Fontanella M, LA Rocca G, et al. Natural history of de novo high grade glioma: first description of growth parabola. J Neurosurg Sci 2020; 64: 399-403. doi: 10.23736/S0390-5616.17.04067-XAltieriRHironoSDuffauHDucatiAFontanellaMRocca GLAet alNatural history of de novo high grade glioma: first description of growth parabolaJ Neurosurg Sci20206439940310.23736/S0390-5616.17.04067-X28748908Open DOISearch in Google Scholar
Sanai N, Alvarez-Buylla A, Berger MS. Neural stem cells and the origin of gliomas. N Engl J Med 2005; 353: 811-22. doi: 10.1056/NEJMra043666SanaiNAlvarez-BuyllaABergerMSNeural stem cells and the origin of gliomasN Engl J Med20053538112210.1056/NEJMra04366616120861Open DOISearch in Google Scholar
Gozé C, Blonski M, Le Maistre G, Bauchet L, Dezamis E, Page P, et al. Imaging growth and isocitrate dehydrogenase 1 mutation are independent predictors for diffuse low-grade gliomas. Neuro Oncol 2014; 16: 1100-9. doi: 10.1007/s11060-008-9680-8GozéCBlonskiMLe MaistreGBauchetLDezamisEPagePet alImaging growth and isocitrate dehydrogenase 1 mutation are independent predictors for diffuse low-grade gliomasNeuro Oncol2014161100910.1007/s11060-008-9680-818726074Open DOISearch in Google Scholar
Stensjøen AL, Solheim O, Kvistad KA, Håberg AK, Salvesen Ø, Berntsen EM. Growth dynamics of untreated glioblastomas in vivo. Neuro Oncol 2015; 17: 1402-11. doi: 10.1093/neuonc/nov029StensjøenALSolheimOKvistadKAHåbergAKSalvesenØBerntsenEMGrowth dynamics of untreated glioblastomas in vivoNeuro Oncol20151714021110.1093/neuonc/nov029457857925758748Open DOISearch in Google Scholar
Hormuth DA, Weis JA, Barnes SL, Miga MI, Rericha EC, Quaranta V, et al. A mechanically coupled reaction–diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growth. J Royal Soc Interface 2017; 14: 20161010. doi: 10.1098/rsif.2016.1010HormuthDAWeisJABarnesSLMigaMIRerichaECQuarantaVet alA mechanically coupled reaction–diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growthJ Royal Soc Interface2017142016101010.1098/rsif.2016.1010537813628330985Open DOISearch in Google Scholar
Raman F, Scribner E, Saut O, Wenger C, Colin T, Fathallah-Shaykh HM. Computational trials: unraveling motility phenotypes, progression patterns, and treatment options for glioblastoma multiforme. PLoS One 2016; 11: e0146617. doi: 10.1371/journal.pone.0146617RamanFScribnerESautOWengerCColinTFathallah-ShaykhHMComputational trials: unraveling motility phenotypes, progression patterns, and treatment options for glioblastoma multiformePLoS One201611e014661710.1371/journal.pone.0146617471050726756205Open DOISearch in Google Scholar
Batchala PP, Muttikkal TJE, Donahue JH, Patrie JT, Schiff D, Fadul CE, et al. Neuroimaging-based classification algorithm for predicting 1p/19q-codeletion status in IDH -mutant lower grade gliomas. AJNR Am J Neuroradiol 2019; 40: 426-32. doi: 10.3174/ajnr.A5957BatchalaPPMuttikkalTJEDonahueJHPatrieJTSchiffDFadulCEet alNeuroimaging-based classification algorithm for predicting 1p/19q-codeletion status in IDH -mutant lower grade gliomasAJNR Am J Neuroradiol2019404263210.3174/ajnr.A5957702866730705071Open DOISearch in Google Scholar
Altieri R, Zenga F, Ducati A, Melcarne A, Cofano F, Mammi M, et al. Tumor location and patient age predict biological signatures of high-grade gliomas. Neurosurg Rev 2018; 41: 599-604. doi: 10.1007/s10143-017-0899-8AltieriRZengaFDucatiAMelcarneACofanoFMammiMet alTumor location and patient age predict biological signatures of high-grade gliomasNeurosurg Rev20184159960410.1007/s10143-017-0899-828856492Open DOISearch in Google Scholar
Compes P, Tabouret E, Etcheverry A, Colin C, Appay R, Cordier N, et al. Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016. J Neurooncol 2019; 142: 511-20. doi: 10.1007/s11060-019-03122-1CompesPTabouretEEtcheverryAColinCAppayRCordierNet alNeuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016J Neurooncol20191425112010.1007/s11060-019-03122-130756272Open DOISearch in Google Scholar
Mikkelsen VE, Stensjøen AL, Granli US, Berntsen EM, Salvesen Ø, Solheim O, et al. Angiogenesis and radiological tumor growth in patients with glioblastoma. BMC Cancer 2018; 18: 862. doi: 10.1186/s12885-018-4768-9MikkelsenVEStensjøenALGranliUSBerntsenEMSalvesenØSolheimOet alAngiogenesis and radiological tumor growth in patients with glioblastomaBMC Cancer20181886210.1186/s12885-018-4768-9612271030176826Open DOISearch in Google Scholar
Pallud J, Taillandier L, Capelle L, Fontaine D, Peyre M, Ducray F, et al. Quantitative morphological magnetic resonance imaging follow-up of low-grade glioma: a plea for systematic measurement of growth rates. Neurosurgery 2012; 71: 729-39. doi: 10.1227/NEU.0b013e31826213dePalludJTaillandierLCapelleLFontaineDPeyreMDucrayFet alQuantitative morphological magnetic resonance imaging follow-up of low-grade glioma: a plea for systematic measurement of growth ratesNeurosurgery2012717293910.1227/NEU.0b013e31826213de22668885Open DOISearch in Google Scholar
Pallud J, Mandonnet E, Duffau H, Kujas M, Guillevin R, Galanaud D, et al. Prognostic value of initial magnetic resonance imaging growth rates for world health organization grade II gliomas. Ann Neurol 2006; 60: 380-3. doi: 10.1002/ana.20946PalludJMandonnetEDuffauHKujasMGuillevinRGalanaudDet alPrognostic value of initial magnetic resonance imaging growth rates for world health organization grade II gliomasAnn Neurol200660380310.1002/ana.2094616983683Open DOISearch in Google Scholar
Mandonnet E, Delattre J, Tanguy M-L, Swanson KR, Carpentier AF, Duffau H, et al. Continuous growth of mean tumor diameter in a subset of grade II gliomas. Ann Neurol 2003; 53: 524-8. doi: 10.1002/ana.10528MandonnetEDelattreJTanguyM-LSwansonKRCarpentierAFDuffauHet alContinuous growth of mean tumor diameter in a subset of grade II gliomasAnn Neurol200353524810.1002/ana.1052812666121Open DOISearch in Google Scholar
Mandonnet E, Pallud J, Clatz O, Taillandier L, Konukoglu E, Duffau H, et al. Computational modeling of the WHO grade II glioma dynamics: principles and applications to management paradigm. Neurosurg Rev 2008; 31: 263-9. doi: 10.1007/s10143-008-0128-6MandonnetEPalludJClatzOTaillandierLKonukogluEDuffauHet alComputational modeling of the WHO grade II glioma dynamics: principles and applications to management paradigmNeurosurg Rev200831263910.1007/s10143-008-0128-618299912Open DOISearch in Google Scholar
Pallud J, Blonski M, Mandonnet E, Audureau E, Fontaine D, Sanai N, et al. Velocity of tumor spontaneous expansion predicts long-term outcomes for diffuse low-grade gliomas. Neuro Oncol 2013; 15: 595-606. doi: 10.1093/neuonc/nos331PalludJBlonskiMMandonnetEAudureauEFontaineDSanaiNet alVelocity of tumor spontaneous expansion predicts long-term outcomes for diffuse low-grade gliomasNeuro Oncol20131559560610.1093/neuonc/nos331363551323393207Open DOISearch in Google Scholar
Mandonnet E, Wait S, Choi L, Teo C. The importance of measuring the velocity of diameter expansion on MRI in upfront management of suspected WHO grade II glioma - case report. Neurochirurgie 2013; 59: 89-92. doi: 10.1016/j.neuchi.2013.02.005MandonnetEWaitSChoiLTeoCThe importance of measuring the velocity of diameter expansion on MRI in upfront management of suspected WHO grade II glioma - case reportNeurochirurgie201359899210.1016/j.neuchi.2013.02.00523623033Open DOISearch in Google Scholar
Zeppa P, Neitzert L, Mammi M, Monticelli M, Altieri R, Castaldo M, et al. How reliable are volumetric techniques for high-grade gliomas? A comparison study of different available tools. Neurosurgery 2020; nyaa282. [Ahead of print]. doi: 10.1093/neuros/nyaa282ZeppaPNeitzertLMammiMMonticelliMAltieriRCastaldoMet alHow reliable are volumetric techniques for high-grade gliomas? A comparison study of different available toolsNeurosurgery2020nyaa282. [Ahead of print]10.1093/neuros/nyaa28232629469Open DOISearch in Google Scholar
Jbabdi S, Mandonnet E, Duffau H, Capelle L, Swanson KR, Pélégrini-Issac M, et al. Simulation of anisotropic growth of low-grade gliomas using diffusion tensor imaging. Magn Reson Med 2005; 54: 616-24. doi: 10.1002/mrm.20625JbabdiSMandonnetEDuffauHCapelleLSwansonKRPélégrini-IssacMet alSimulation of anisotropic growth of low-grade gliomas using diffusion tensor imagingMagn Reson Med2005546162410.1002/mrm.20625Open DOISearch in Google Scholar
Gui C, Kosteniuk SE, Lau JC, Megyesi JF. Tumor growth dynamics in serially-imaged low-grade glioma patients. J Neurooncol 2018; 139: 167-75. doi: 10.1007/s11060-018-2857-xGuiCKosteniukSELauJCMegyesiJFTumor growth dynamics in serially-imaged low-grade glioma patientsJ Neurooncol20181391677510.1007/s11060-018-2857-xOpen DOISearch in Google Scholar
Yamashita T, Kuwabara T. Estimation of rate of growth of malignant brain tumors by computed tomography scanning. Surg Neurol 1983; 20: 464-70. doi: 10.1016/0090-3019(83)90029-0YamashitaTKuwabaraTEstimation of rate of growth of malignant brain tumors by computed tomography scanningSurg Neurol1983204647010.1016/0090-3019Open DOISearch in Google Scholar
Schwartz M. A biomathematical approach to clinical tumor growth. Cancer 1961; 14: 1272-94. doi: 10.1002/1097-0142(196111/12)14:6<1272::aid-cncr2820140618>3.0.co;2-hSchwartzMA biomathematical approach to clinical tumor growthCancer19611412729410.1002/1097-0142(196111/12)14:6<1272::aid-cncr2820140618>3.0.co;2-h10.1002/1097-0142(196111/12)14:6<1272::AID-CNCR2820140618>3.0.CO;2-HSearch in Google Scholar
Harpold HLP, Alvord EC, Swanson KR. The evolution of mathematical modeling of glioma proliferation and invasion. J Neuropathol Exp Neurol 2007; 66: 1-9. doi: 10.1097/nen.0b013e31802d9000HarpoldHLPAlvordECSwansonKRThe evolution of mathematical modeling of glioma proliferation and invasionJ Neuropathol Exp Neurol2007661910.1097/nen.0b013e31802d9000Open DOISearch in Google Scholar
Laird AK. Dynamics of tumor growth. Br J Cancer 1964; 13: 490-502. doi: 10.1038/bjc.1964.55LairdAKDynamics of tumor growthBr J Cancer19641349050210.1038/bjc.1964.55Open DOISearch in Google Scholar
Chignola R, Foroni RI. Estimating the growth kinetics of experimental tumors from as few as two determinations of tumor size: implications for clinical oncology. IEEE Transactions on Biomed Eng 2005; 52: 808-15. doi: 10.1109/TBME.2005.845219ChignolaRForoniRIEstimating the growth kinetics of experimental tumors from as few as two determinations of tumor size: implications for clinical oncologyIEEE Transactions on Biomed Eng2005528081510.1109/TBME.2005.845219Open DOISearch in Google Scholar
Cochereau J, Herbet G, Rigau V, Duffau H. Acute progression of untreated incidental WHO Grade II glioma to glioblastoma in an asymptomatic patient. J Neurosurg 2016; 124: 141-5. doi: 10.3171/2014.12.JNS141851CochereauJHerbetGRigauVDuffauHAcute progression of untreated incidental WHO Grade II glioma to glioblastoma in an asymptomatic patientJ Neurosurg2016124141510.3171/2014.12.JNS141851Open DOISearch in Google Scholar
Shah AH, Madhavan K, Heros D, Raper DMS, Iorgulescu JB, Lally BE, et al. The management of incidental low-grade gliomas using magnetic resonance imaging: systematic review and optimal treatment paradigm. Neurosurg Focus 2011; 31: E12. doi: 10.3171/2011.9.FOCUS11219ShahAHMadhavanKHerosDRaperDMSIorgulescuJBLallyBEet alThe management of incidental low-grade gliomas using magnetic resonance imaging: systematic review and optimal treatment paradigmNeurosurg Focus201131E1210.3171/2011.9.FOCUS11219Open DOISearch in Google Scholar
