2018
Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging
Chang K, Bai HX, Zhou H, Su C, Bi WL, Agbodza E, Kavouridis VK, Senders JT, Boaro A, Beers A, Zhang B, Capellini A, Liao W, Shen Q, Li X, Xiao B, Cryan J, Ramkissoon S, Ramkissoon L, Ligon K, Wen PY, Bindra RS, Woo J, Arnaout O, Gerstner ER, Zhang PJ, Rosen BR, Yang L, Huang RY, Kalpathy-Cramer J. Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging. Clinical Cancer Research 2018, 24: clincanres.2236.2017. PMID: 29167275, PMCID: PMC6051535, DOI: 10.1158/1078-0432.ccr-17-2236.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBrainBrain NeoplasmsDatasets as TopicFemaleGliomaHumansImage Processing, Computer-AssistedIsocitrate DehydrogenaseMagnetic Resonance ImagingMaleMiddle AgedMutationNeoplasm GradingNeural Networks, ComputerPredictive Value of TestsPreoperative PeriodRetrospective StudiesYoung AdultConceptsResidual convolutional neural networkConvolutional neural networkNeural networkDeep learning techniquesTesting setNeural network modelMulti-institutional data setCancer Imaging ArchiveLearning techniquesTesting accuracyNetwork modelTraining setPrediction accuracyPreoperative radiographic dataClin Cancer ResData setsConventional MR imagingHospital of UniversityIsocitrate dehydrogenase (IDH) mutationPreoperative imagingLonger survivalWomen's HospitalGrade IINetworkTreatment decisions
2017
Bi‐allelic alterations in DNA repair genes underpin homologous recombination DNA repair defects in breast cancer
Mutter RW, Riaz N, Ng CK, Delsite R, Piscuoglio S, Edelweiss M, Martelotto LG, Sakr RA, King TA, Giri DD, Drobnjak M, Brogi E, Bindra R, Bernheim G, Lim RS, Blecua P, Desrichard A, Higginson D, Towers R, Jiang R, Lee W, Weigelt B, Reis‐Filho J, Powell SN. Bi‐allelic alterations in DNA repair genes underpin homologous recombination DNA repair defects in breast cancer. The Journal Of Pathology 2017, 242: 165-177. PMID: 28299801, PMCID: PMC5516531, DOI: 10.1002/path.4890.Peer-Reviewed Original ResearchConceptsBreast cancerGermline BRCA1/BRCA2 mutationsBRCA1/BRCA2 mutationsPrecision medicine-based approachPrimary breast cancerTumour-specific DNA repair defectsSporadic breast cancerGermline genetic alterationsBi-allelic lossWhole-exome sequencingSpecific mutational signaturesComprehensive genetic assessmentBRCA2 mutationsLarge-scale state transitionsBi-allelic alterationsCancerGenetic alterationsDNA repair defectsMutational signaturesTherapyAlterationsRepair defectsGene expressionGenetic assessmentHR genes
2016
Adjuvant chemotherapy and overall survival in adult medulloblastoma
Kann BH, Lester-Coll NH, Park HS, Yeboa DN, Kelly JR, Baehring JM, Becker KP, Yu JB, Bindra RS, Roberts KB. Adjuvant chemotherapy and overall survival in adult medulloblastoma. Neuro-Oncology 2016, 19: 259-269. PMID: 27540083, PMCID: PMC5464064, DOI: 10.1093/neuonc/now150.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsCerebellar NeoplasmsChemoradiotherapy, AdjuvantChemotherapy, AdjuvantCraniospinal IrradiationFemaleFollow-Up StudiesHumansMaleMedulloblastomaMiddle AgedNeoplasm StagingPrognosisRadiotherapy, AdjuvantSurvival RateYoung AdultConceptsGy craniospinal irradiationCraniospinal irradiationOverall survivalM0 patientsAdjuvant chemotherapyAdult MBMultivariable Cox proportional hazard modelingHigh-dose craniospinal irradiationNational Cancer Data BaseCox proportional hazard modelingSuperior overall survivalPlanned subgroup analysisMultivariable logistic regressionNational database analysisLog-rank testProportional hazard modelingPediatric medulloblastoma patientsCSI dosesPostoperative chemotherapySurgical resectionSurvival impactYear OSMultivariable analysisSubgroup analysisRisk factors