2022
Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
Petersen G, Shatalov J, Verma T, Brim WR, Subramanian H, Brackett A, Bahar RC, Merkaj S, Zeevi T, Staib LH, Cui J, Omuro A, Bronen RA, Malhotra A, Aboian MS. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment. American Journal Of Neuroradiology 2022, 43: 526-533. PMID: 35361577, PMCID: PMC8993193, DOI: 10.3174/ajnr.a7473.Peer-Reviewed Original ResearchMeSH KeywordsGliomaHumansLymphomaMachine LearningMagnetic Resonance ImagingReproducibility of ResultsConceptsMachine learning-based methodsLearning-based methodsBalanced data setData setsVector machine modelMachine learningClassification algorithmsMachine modelMachineAlgorithmData basesPrediction modelPromising resultsPrimary CNS lymphomaPrediction model study RiskRisk of biasRadiomic featuresClassifierSetCNS lymphomaWebLearningFeaturesQualitySystematic review
2019
Sequencing and curation strategies for identifying candidate glioblastoma treatments
Frank MO, Koyama T, Rhrissorrakrai K, Robine N, Utro F, Emde AK, Chen BJ, Arora K, Shah M, Geiger H, Felice V, Dikoglu E, Rahman S, Fang A, Vacic V, Bergmann EA, Vogel JLM, Reeves C, Khaira D, Calabro A, Kim D, Lamendola-Essel MF, Esteves C, Agius P, Stolte C, Boockvar J, Demopoulos A, Placantonakis DG, Golfinos JG, Brennan C, Bruce J, Lassman AB, Canoll P, Grommes C, Daras M, Diamond E, Omuro A, Pentsova E, Orange DE, Harvey SJ, Posner JB, Michelini VV, Jobanputra V, Zody MC, Kelly J, Parida L, Wrzeszczynski KO, Royyuru AK, Darnell RB. Sequencing and curation strategies for identifying candidate glioblastoma treatments. BMC Medical Genomics 2019, 12: 56. PMID: 31023376, PMCID: PMC6485090, DOI: 10.1186/s12920-019-0500-0.Peer-Reviewed Original ResearchConceptsPotential treatment optionClinical research studiesWhole-genome sequencingPharmacologic interventionsCancer patientsTreatment optionsClinical resultsPatientsConclusionThese resultsGlioblastoma treatmentPotential cancer treatmentPanel sequencingActionable variantsCancer treatmentGlioblastoma tumorsSame variantSequencing assaysDrug targetsRNA sequencingRNA-seqTreatmentNew York CitySequencingTumorsClinicians
2013
Potential Role of Preoperative Conventional MRI Including Diffusion Measurements in Assessing Epidermal Growth Factor Receptor Gene Amplification Status in Patients with Glioblastoma
Young R, Gupta A, Shah A, Graber J, Schweitzer A, Prager A, Shi W, Zhang Z, Huse J, Omuro A. Potential Role of Preoperative Conventional MRI Including Diffusion Measurements in Assessing Epidermal Growth Factor Receptor Gene Amplification Status in Patients with Glioblastoma. American Journal Of Neuroradiology 2013, 34: 2271-2277. PMID: 23811973, PMCID: PMC4712068, DOI: 10.3174/ajnr.a3604.Peer-Reviewed Original ResearchAdolescentAdultAgedAged, 80 and overBiomarkers, TumorBrain NeoplasmsErbB ReceptorsFemaleGene AmplificationGlioblastomaHumansMagnetic Resonance ImagingMaleMiddle AgedMolecular ImagingPreoperative CarePrognosisReproducibility of ResultsSensitivity and SpecificityTissue DistributionUp-RegulationYoung Adult
2012
A prognostic gene expression signature in infratentorial ependymoma
Wani K, Armstrong TS, Vera-Bolanos E, Raghunathan A, Ellison D, Gilbertson R, Vaillant B, Goldman S, Packer RJ, Fouladi M, Pollack I, Mikkelsen T, Prados M, Omuro A, Soffietti R, Ledoux A, Wilson C, Long L, Gilbert MR, Aldape K, For the Collaborative Ependymoma Research Network. A prognostic gene expression signature in infratentorial ependymoma. Acta Neuropathologica 2012, 123: 727-738. PMID: 22322993, PMCID: PMC4013829, DOI: 10.1007/s00401-012-0941-4.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAge FactorsAntigens, NeoplasmChildCluster AnalysisDatabases, GeneticDNA Topoisomerases, Type IIDNA-Binding ProteinsEpendymomaFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansInfratentorial NeoplasmsLongitudinal StudiesMaleOligonucleotide Array Sequence AnalysisPrognosisReproducibility of ResultsSex FactorsSurvival AnalysisYoung AdultConceptsRecurrence-free survivalInfratentorial ependymomaClinical outcomesReal-time reverse transcriptase-polymerase chain reaction assaysReverse transcriptase-polymerase chain reaction assaysGroup 1 tumorsPrognostic gene expression signaturesTranscriptase-polymerase chain reaction assaysGroup 2 tumorsGene expression subgroupsPolymerase chain reaction assaysClinical factorsGene expression signaturesIndependent predictorsPrognostic significanceInfratentorial compartmentHistological factorsClinical behaviorChain reaction assaysClinical aggressivenessPrognostic signatureExpression subgroupsEpendymomaMolecular alterationsMultivariate analysis