2019
Assembling the brain trust: the multidisciplinary imperative in neuro-oncology
Ludmir EB, Mahajan A, Ahern V, Ajithkumar T, Alapetite C, Bernier-Chastagner V, Bindra RS, Bishop AJ, Bolle S, Brown PD, Carrie C, Chalmers AJ, Chang EL, Chung C, Dieckmann K, Esiashvili N, Gandola L, Ghia AJ, Gondi V, Grosshans DR, Harrabi SB, Horan G, Indelicato DJ, Jalali R, Janssens GO, Krause M, Laack NN, Laperriere N, Laprie A, Li J, Marcus KJ, McGovern SL, Merchant TE, Merrell KW, Padovani L, Parkes J, Paulino AC, Schwarz R, Shih HA, Souhami L, Sulman EP, Taylor RE, Thorp N, Timmermann B, Wheeler G, Wolden SL, Woodhouse KD, Yeboa DN, Yock TI, Kortmann RD, McAleer MF. Assembling the brain trust: the multidisciplinary imperative in neuro-oncology. Nature Reviews Clinical Oncology 2019, 16: 521-522. PMID: 31150024, DOI: 10.1038/s41571-019-0235-z.Peer-Reviewed Original ResearchNanoparticle-mediated intratumoral inhibition of miR-21 for improved survival in glioblastoma
Seo YE, Suh HW, Bahal R, Josowitz A, Zhang J, Song E, Cui J, Noorbakhsh S, Jackson C, Bu T, Piotrowski-Daspit A, Bindra R, Saltzman WM. Nanoparticle-mediated intratumoral inhibition of miR-21 for improved survival in glioblastoma. Biomaterials 2019, 201: 87-98. PMID: 30802686, PMCID: PMC6451656, DOI: 10.1016/j.biomaterials.2019.02.016.Peer-Reviewed Original ResearchConceptsEfficient intracellular deliveryDelivery systemPeptide nucleic acidNanoparticle productsNanoparticlesIntracellular deliveryConvection-enhanced deliveryDifferent delivery systemsNucleic acidsSignificant therapeutic efficacyMiR-21 suppressionTherapeutic efficacyLocal deliveryDeliverySystemic toxicityBlock copolymersDistinct advantagesPolyglycerolMiR-21
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