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INFORMATION FOR

Mariam Aboian, MD/PhD

Assistant Professor; Director, Clinical Advanced Image Processing Lab (CAIP), Radiology and Biomedical Imaging; Co-Director, Theranostics and Nuclear Medicine Clinical Trials, Radiology

Contact Information

Mariam Aboian, MD/PhD

Research Summary

My main area of research is integration of radiogenomics and molecular imaging in the study of primary and metastatic brain tumors, with particular focus on development and translation of novel PET tracers and theranostics into clinical practice. 

Coauthors

Research Interests

Brain Neoplasms; Glioblastoma; Nuclear Medicine; Radiotherapy; Informatics; Molecular Imaging; Cognitive Neuroscience; Machine Learning; Mentoring

Selected Publications

  • PropofolAboian M, Johnson J, Ginat D. Propofol 2022, 281-283. DOI: 10.1007/978-3-031-08774-5_40.
  • NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NETJekel L, Bousabarah K, Lin M, Merkaj S, Kaur M, Avesta A, Aneja S, Omuro A, Chiang V, Scheffler B, Aboian M. NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET Neuro-Oncology 2022, 24: vii162-vii162. PMCID: PMC9661012, DOI: 10.1093/neuonc/noac209.622.
  • NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERYKaur M, Varghese S, Jekel L, Tillmanns N, Merkaj S, Bousabarah K, Lin M, Bhawnani J, Chiang V, Aboian M. NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERY Neuro-Oncology 2022, 24: vii162-vii163. PMCID: PMC9660643, DOI: 10.1093/neuonc/noac209.626.
  • NIMG-20. INCORPORATION OF AI-BASED AUTOSEGMENTATION AND CLASSIFICATION INTO NEURORADIOLOGY WORKFLOW: PACS-BASED AI TO BUILD YALE GLIOMA DATASETLost J, Tillmans N, Merkaj S, von Reppert M, Lin M, Bousabarah K, Huttner A, Aneja S, Omuro A, Aboian M, Avesta A. NIMG-20. INCORPORATION OF AI-BASED AUTOSEGMENTATION AND CLASSIFICATION INTO NEURORADIOLOGY WORKFLOW: PACS-BASED AI TO BUILD YALE GLIOMA DATASET Neuro-Oncology 2022, 24: vii165-vii166. DOI: 10.1093/neuonc/noac209.638.
  • NIMG-04. LONGITUDINAL TRACKING OF PERITUMORAL EDEMA VOLUME USING PACS-INTEGRATED TOOLS PROVIDES CRITICAL INFORMATION IN TREATMENT ASSESSMENT OF NSCLC BRAIN METASTASES AFTER RADIOSURGERYKaur M, Petersen G, von Reppert M, Jekel L, de Santo I, Varghese S, Chiang V, Aboian M. NIMG-04. LONGITUDINAL TRACKING OF PERITUMORAL EDEMA VOLUME USING PACS-INTEGRATED TOOLS PROVIDES CRITICAL INFORMATION IN TREATMENT ASSESSMENT OF NSCLC BRAIN METASTASES AFTER RADIOSURGERY Neuro-Oncology 2022, 24: vii162-vii162. PMCID: PMC9661156, DOI: 10.1093/neuonc/noac209.624.
  • NIMG-102. RAPNO-DEFINED SEGMENTATION AND VOLUMETRIC ASSESSMENT OF PEDIATRIC BRAIN TUMORS ON MULTI-PARAMETRIC MRI SCANS USING DEEP LEARNING; A ROBUST TOOL WITH POTENTIAL APPLICATION IN TUMOR RESPONSE ASSESSMENTKazerooni A, Madhogarhia R, Arif S, Ware J, Bagheri S, Haldar D, Anderson H, Familiar A, Vidal L, Aboian M, Storm P, Resnick A, Vossough A, Davatzikos C, Nabavizadeh A. NIMG-102. RAPNO-DEFINED SEGMENTATION AND VOLUMETRIC ASSESSMENT OF PEDIATRIC BRAIN TUMORS ON MULTI-PARAMETRIC MRI SCANS USING DEEP LEARNING; A ROBUST TOOL WITH POTENTIAL APPLICATION IN TUMOR RESPONSE ASSESSMENT Neuro-Oncology 2022, 24: vii188-vii189. PMCID: PMC9660634, DOI: 10.1093/neuonc/noac209.720.
  • LGG-52. Volumetry-based response characterization of recurrent pediatric low-grade gliomas in PNOC clinical Neuro-oncology trialsvon Reppert M, Lin M, Bousabarah K, Familiar A, Velasco R, Waanders A, Vossough A, Haddock A, Nicolaides T, Swanson K, Kazerooni A, Kline C, Nabavizadeh A, Haas-Kogan D, Prados M, Rubin J, Mueller S, Aboian M. LGG-52. Volumetry-based response characterization of recurrent pediatric low-grade gliomas in PNOC clinical Neuro-oncology trials Neuro-Oncology 2022, 24: i100-i100. PMCID: PMC9165161, DOI: 10.1093/neuonc/noac079.364.
  • TRAF7 Mutated Subgroups Differ in Sphenoid Wing Meningiomas with HyperostosisJin L, Vetsa S, Vasandani S, Nadar A, Youngblood M, Gupte T, Barak T, Yalcin K, Aguilera S, Mishra-Gorur K, Blondin N, Gorelick E, Omay S, Pointdujour-Lim R, Judson B, Alperovich M, Aboian M, Marianayagam N, McGuone D, Gunel M, Erson-Omay Z, Fulbright R, Moliterno J. TRAF7 Mutated Subgroups Differ in Sphenoid Wing Meningiomas with Hyperostosis Journal Of Neurological Surgery Part B Skull Base 2022, 83: s1-s270. DOI: 10.1055/s-0042-1743640.
  • PET Image Denoising Using a Deep-Learning Method for Extremely Obese PatientsLiu H, Yousefi H, Mirian N, Lin M, Menard D, Gregory M, Aboian M, Boustani A, Chen M, Saperstein L, Pucar D, Kulon M, Liu C. PET Image Denoising Using a Deep-Learning Method for Extremely Obese Patients IEEE Transactions On Radiation And Plasma Medical Sciences 2021, 6: 766-770. DOI: 10.1109/trpms.2021.3131999.
  • Pediatric SpinePedersen C, Link H, Aboian M. Pediatric Spine 2021, 765-777. DOI: 10.1007/978-3-030-82367-2_65.
  • Amino Acid PET/MRI in Neuro-oncologyShooli H, Assadi M, Nabavizadeh S, Aboian M. Amino Acid PET/MRI in Neuro-oncology 2021, 137-165. DOI: 10.1007/978-3-030-82367-2_14.
  • Pediatric PET/MRI Neuroimaging: OverviewPedersen C, Messina S, Daldrup-Link H, Aboian M. Pediatric PET/MRI Neuroimaging: Overview 2021, 737-740. DOI: 10.1007/978-3-030-82367-2_62.
  • Pediatric Epilepsy: Non-oncologic Applications of PET/MRIMessina S, Pedersen C, Daldrup-Link H, Aboian M. Pediatric Epilepsy: Non-oncologic Applications of PET/MRI 2021, 741-751. DOI: 10.1007/978-3-030-82367-2_63.
  • Pediatric Brain and Head-Neck OncologyPedersen C, Messina S, Daldrup-Link H, Aboian M. Pediatric Brain and Head-Neck Oncology 2021, 753-764. DOI: 10.1007/978-3-030-82367-2_64.
  • [18F]-FDG PET/MR Neuroimaging: Focus on Neuro-Oncology ApplicationsShooli H, Assadi M, Aboian M. [18F]-FDG PET/MR Neuroimaging: Focus on Neuro-Oncology Applications 2021, 89-98. DOI: 10.1007/978-3-030-82367-2_10.
  • NIMG-64. TYPE OF BONY INVOLVEMENT PREDICTS GENOMIC SUBGROUP IN SPHENOID WING MENINGIOMASJin L, Youngblood M, Gupte T, Vetsa S, Nadar A, Barak T, Yalcin K, Aguilera S, Mishra-Gorur K, Blondin N, Omay S, Pointdujour-Lim R, Judson B, Alperovich M, Aboian M, McGuone D, Gunel M, Erson-Omay Z, Fulbright R, Moliterno J. NIMG-64. TYPE OF BONY INVOLVEMENT PREDICTS GENOMIC SUBGROUP IN SPHENOID WING MENINGIOMAS Neuro-Oncology 2021, 23: vi144-vi144. PMCID: PMC8598770, DOI: 10.1093/neuonc/noab196.562.
  • NIMG-23. MACHINE LEARNING METHODS IN GLIOMA GRADE PREDICTION: A SYSTEMATIC REVIEWBahar R, Merkaj S, Brim W, Subramanian H, Zeevi T, Kazarian E, Lin M, Bousabarah K, Payabvash S, Ivanidze J, Cui J, Tocino I, Malhotra A, Aboian M. NIMG-23. MACHINE LEARNING METHODS IN GLIOMA GRADE PREDICTION: A SYSTEMATIC REVIEW Neuro-Oncology 2021, 23: vi133-vi133. PMCID: PMC8598529, DOI: 10.1093/neuonc/noab196.523.
  • NIMG-35. MACHINE LEARNING GLIOMA GRADE PREDICTION LITERATURE: A TRIPOD ANALYSIS OF REPORTING QUALITYMerkaj S, Bahar R, Brim W, Subramanian H, Zeevi T, Kazarian E, Lin M, Bousabarah K, Payabvash S, Ivanidze J, Cui J, Tocino I, Malhotra A, Aboian M. NIMG-35. MACHINE LEARNING GLIOMA GRADE PREDICTION LITERATURE: A TRIPOD ANALYSIS OF REPORTING QUALITY Neuro-Oncology 2021, 23: vi136-vi136. PMCID: PMC8598513, DOI: 10.1093/neuonc/noab196.535.
  • NIMG-17. SYSTEMATIC REVIEW OF LITERATURE EVALUATING MACHINE LEARNING ALGORITHMS TO DEVELOP OUTCOME PREDICTION MODELS IN GLIOMA USING MOLECULAR IMAGING WITH AMINO ACID PETShatalov J, Brim W, Subramanian H, Bazaar J, Johnson M, Aboian M. NIMG-17. SYSTEMATIC REVIEW OF LITERATURE EVALUATING MACHINE LEARNING ALGORITHMS TO DEVELOP OUTCOME PREDICTION MODELS IN GLIOMA USING MOLECULAR IMAGING WITH AMINO ACID PET Neuro-Oncology 2021, 23: vi131-vi131. PMCID: PMC8598491, DOI: 10.1093/neuonc/noab196.517.
  • NIMG-38. MEASURING ADHERENCE TO TRIPOD OF ARTIFICIAL INTELLIGENCE PAPERS IN THE GLIOMA SEGMENTATIONTillmanns N, Lum A, Brim W, Subramanian H, Lin M, Bousabarah K, Malhotra A, cui J, Brackett A, Payabvash S, Ikuta I, Johnson M, Turowski B, Aboian M. NIMG-38. MEASURING ADHERENCE TO TRIPOD OF ARTIFICIAL INTELLIGENCE PAPERS IN THE GLIOMA SEGMENTATION Neuro-Oncology 2021, 23: vi137-vi137. PMCID: PMC8598634, DOI: 10.1093/neuonc/noab196.537.
  • NIMG-46. SYSTEMATIC LITERATURE REVIEW OF ARTIFICIAL INTELLIGENCE ALGORITHMS USING PRE-THERAPY MR IMAGING FOR GLIOMA MOLECULAR SUBTYPE CLASSIFICATIONLost J, Verma T, Tillmanns N, Brim W, Subramanian H, Ikuta I, Bronen R, Zucconi W, Lin M, Bousabarah K, Johnson M, Cui J, Malhotra A, Sabel M, Aboian M. NIMG-46. SYSTEMATIC LITERATURE REVIEW OF ARTIFICIAL INTELLIGENCE ALGORITHMS USING PRE-THERAPY MR IMAGING FOR GLIOMA MOLECULAR SUBTYPE CLASSIFICATION Neuro-Oncology 2021, 23: vi139-vi139. DOI: 10.1093/neuonc/noab196.545.
  • NIMG-67. A SYSTEMATIC REVIEW ON THE DEVELOPMENT OF MACHINE LEARNING MODELS FOR DIFFERENTIATING PCNSL FROM GLIOMASPetersen G, Shatalov J, Brim W, Subramanian H, cui J, Johnson M, Malhotra A, Aboian M, Brackett A. NIMG-67. A SYSTEMATIC REVIEW ON THE DEVELOPMENT OF MACHINE LEARNING MODELS FOR DIFFERENTIATING PCNSL FROM GLIOMAS Neuro-Oncology 2021, 23: vi144-vi145. PMCID: PMC8598874, DOI: 10.1093/neuonc/noab196.565.
  • NIMG-71. IDENTIFYING CLINICALLY APPLICABLE MACHINE LEARNING ALGORITHMS FOR GLIOMA SEGMENTATION USING A SYSTEMATIC LITERATURE REVIEWTillmanns N, Lum A, Brim W, Subramanian H, Lin M, Bousabarah K, Malhotra A, cui J, Brackett A, Payabvash S, Ikuta I, Johnson M, Turowski B, Aboian M. NIMG-71. IDENTIFYING CLINICALLY APPLICABLE MACHINE LEARNING ALGORITHMS FOR GLIOMA SEGMENTATION USING A SYSTEMATIC LITERATURE REVIEW Neuro-Oncology 2021, 23: vi145-vi145. PMCID: PMC8598815, DOI: 10.1093/neuonc/noab196.568.
  • Super-resolution PET Brain Imaging using Deep LearningRen S, Liu J, Xie H, Toyonaga T, Mirian N, Chen M, Aboian M, Carson R, Liu C. Super-resolution PET Brain Imaging using Deep Learning 2021, 00: 1-6. DOI: 10.1109/nss/mic44867.2021.9875548.
  • OTHR-11. Comprehensive Analysis of Driver Mutation Profile in a Cohort of Lung Cancer Patients Using Targeted Gene Panel Analysis with Focus on Brain Metastatic DiseaseKazarian M, Cui J, Tocino I, Mahajan A, Aboian M. OTHR-11. Comprehensive Analysis of Driver Mutation Profile in a Cohort of Lung Cancer Patients Using Targeted Gene Panel Analysis with Focus on Brain Metastatic Disease Neuro-Oncology Advances 2021, 3: iii16-iii16. PMCID: PMC8351181, DOI: 10.1093/noajnl/vdab071.066.
  • OTHR-12. The development of machine learning algorithms for the differentiation of glioma and brain metastases – a systematic reviewBrim W, Jekel L, Petersen G, Subramanian H, Zeevi T, Payabvash S, Bousabarah K, Lin M, Cui J, Brackett A, Mahajan A, Johnson M, Mahajan A, Aboian M. OTHR-12. The development of machine learning algorithms for the differentiation of glioma and brain metastases – a systematic review Neuro-Oncology Advances 2021, 3: iii17-iii17. PMCID: PMC8351249, DOI: 10.1093/noajnl/vdab071.067.
  • OTHR-06. PACS Lesion Tracking Tool provides real time automatic information on brain tumor metastasis growth curves and RECIST criteriaJang B, Lin M, Owens R, Bousabarah K, Mahajan A, Fadel S, Ikuta I, Tocino I, Aboian M. OTHR-06. PACS Lesion Tracking Tool provides real time automatic information on brain tumor metastasis growth curves and RECIST criteria Neuro-Oncology Advances 2021, 3: iii15-iii15. DOI: 10.1093/noajnl/vdab071.061.
  • OTHR-15. Assessment of TRIPOD adherence in articles developing machine learning models for differentiation of glioma from brain metastasisJekel L, Brim W, Petersen G, Subramanian H, Zeevi T, Payabvash S, Bousabarah K, Lin M, Cui J, Brackett A, Johnson M, Malhotra A, Aboian M. OTHR-15. Assessment of TRIPOD adherence in articles developing machine learning models for differentiation of glioma from brain metastasis Neuro-Oncology Advances 2021, 3: iii17-iii18. PMCID: PMC8351195, DOI: 10.1093/noajnl/vdab071.070.
  • LGG-09. CORRELATING GENETIC SIGNATURE OF PILOMYXOID ASTROCYTOMAS AND PILOCYTIC ASTROCYTOMAS WITH QUALITATIVE AND QUANTITATIVE MR IMAGING CHARACTERISTICSFadel S, Omay Z, Darbinyan A, Bronen R, Fulbright R, Mahajan A, Aboian M. LGG-09. CORRELATING GENETIC SIGNATURE OF PILOMYXOID ASTROCYTOMAS AND PILOCYTIC ASTROCYTOMAS WITH QUALITATIVE AND QUANTITATIVE MR IMAGING CHARACTERISTICS Neuro-Oncology 2020, 22: iii367-iii368. PMCID: PMC7715503, DOI: 10.1093/neuonc/noaa222.392.
  • LGG-53. PNOC001 (NCT01734512): A PHASE II STUDY OF EVEROLIMUS FOR RECURRENT OR PROGRESSIVE PEDIATRIC LOW-GRADE GLIOMAS (pLGG)Mueller S, Aboian M, Nazemi K, Gauvain K, Yoon J, Minturn J, Leary S, AbdelBaki M, Goldman S, Elster J, Resnick A, Molinaro A, Phillips J, Prados M, Haas-Kogan D. LGG-53. PNOC001 (NCT01734512): A PHASE II STUDY OF EVEROLIMUS FOR RECURRENT OR PROGRESSIVE PEDIATRIC LOW-GRADE GLIOMAS (pLGG) Neuro-Oncology 2020, 22: iii376-iii376. PMCID: PMC7715067, DOI: 10.1093/neuonc/noaa222.431.
  • DDRE-12. PNOC001 (NCT01734512): A PHASE II STUDY OF EVEROLIMUS FOR RECURRENT OR PROGRESSIVE PEDIATRIC LOW-GRADE GLIOMAS (pLGG)Mueller S, Aboian M, Nazemi K, Gauvain K, Yoon J, Minturn J, Leary S, AbdelBaki M, Goldman S, Elster J, Resnick A, Molinaro A, Phillips J, Prados M, Haas-Kogan D. DDRE-12. PNOC001 (NCT01734512): A PHASE II STUDY OF EVEROLIMUS FOR RECURRENT OR PROGRESSIVE PEDIATRIC LOW-GRADE GLIOMAS (pLGG) Neuro-Oncology 2020, 22: ii63-ii64. PMCID: PMC7651691, DOI: 10.1093/neuonc/noaa215.257.
  • MLTI-18. PRECISION IMAGING OF METASTATIC AND PRIMARY BRAIN TUMORS AFTER RADIATION WITH 18F-FDOPA PET-MRI IS FEASIBLE AND COST EFFECTAboian M, Ravanfar V, Bahroos E, Tong E, Taylor J, Oberheim Bush N, Seo Y, Cha S, Pampaloni M. MLTI-18. PRECISION IMAGING OF METASTATIC AND PRIMARY BRAIN TUMORS AFTER RADIATION WITH 18F-FDOPA PET-MRI IS FEASIBLE AND COST EFFECT Neuro-Oncology Advances 2019, 1: i18-i18. PMCID: PMC7213305, DOI: 10.1093/noajnl/vdz014.077.
  • DIPG-15. PNOC-003: CLINICAL IMPACT OF A PRECISION MEDICINE STRATEGY FOR CHILDREN WITH DIFFUSE INTRINSIC PONTINE GLIOMAMueller S, Kline C, Kilburn L, Liang W, Jain P, Gupta N, Panditharatna E, Nazemi K, Magge S, Crawford J, Banerjee A, Packer R, Roos A, Zhang B, Zhu Y, Aboian M, Tamrazi B, Philips J, Solomon D, Molinaro A, Kuhn J, Byron S, Nazarian J, Resnick A, Berens M, Prados M. DIPG-15. PNOC-003: CLINICAL IMPACT OF A PRECISION MEDICINE STRATEGY FOR CHILDREN WITH DIFFUSE INTRINSIC PONTINE GLIOMA Neuro-Oncology 2019, 21: ii71-ii71. PMCID: PMC6477269, DOI: 10.1093/neuonc/noz036.036.
  • THER-26. PHARMACOKINETIC AND UPDATED OUTCOME DATA FROM PNOC-002: A SAFETY STUDY OF VEMURAFENIB, AN ORAL INHIBITOR OF BRAFV600E, IN CHILDREN WITH RECURRENT/REFRACTORY BRAFV600E MUTANT BRAIN TUMORSNicolaides T, Margol A, Gajjar A, Goldman S, Gauvain K, Kilburn L, Nazemi K, Minturn J, Leary S, Whipple N, Gururangan S, Crawford J, Long-Boyle J, Wang H, Ivaturi V, Aboian M, Molinaro A, Mueller S, Prados M. THER-26. PHARMACOKINETIC AND UPDATED OUTCOME DATA FROM PNOC-002: A SAFETY STUDY OF VEMURAFENIB, AN ORAL INHIBITOR OF BRAFV600E, IN CHILDREN WITH RECURRENT/REFRACTORY BRAFV600E MUTANT BRAIN TUMORS Neuro-Oncology 2019, 21: ii119-ii119. PMCID: PMC6477532, DOI: 10.1093/neuonc/noz036.231.
  • Brainstem Toxicity in Pediatric Patients Receiving Posterior Fossa Photon RadiationDevine C, Liu K, Ioakeim-Ioannidou M, Susko M, Poussaint T, Huisman T, Aboian M, Brown D, Zaslowe-Dude C, Rao A, Orlina L, Rawal B, Mueller S, Marcus K, Terezakis S, Braunstein S, Haas-Kogan D. Brainstem Toxicity in Pediatric Patients Receiving Posterior Fossa Photon Radiation International Journal Of Radiation Oncology • Biology • Physics 2018, 102: s51-s52. DOI: 10.1016/j.ijrobp.2018.06.153.
  • DIPG-32. CLINICALLY RELEVANT AND MINIMALLY INVASIVE TUMOR SURVEILLANCE IN PEDIATRIC GLIOMAS USING LIQUID BIOMEPanditharatna E, Kilburn L, Aboian M, Kambhampati M, Gordish-Dressman H, Magge S, Gupta N, Myseros J, Hwang E, Crawford J, Warren K, Resnick A, Packer R, Prados M, Mueller S, Nazarian J. DIPG-32. CLINICALLY RELEVANT AND MINIMALLY INVASIVE TUMOR SURVEILLANCE IN PEDIATRIC GLIOMAS USING LIQUID BIOME Neuro-Oncology 2018, 20: i55-i55. PMCID: PMC6012100, DOI: 10.1093/neuonc/noy059.125.
  • NIMG-71. DIFFUSION CHARACTERISTICS OF PEDIATRIC DIFFUSE MIDLINE GLIOMAS WITH HISTONE H3 K27M MUTATION USING APPARENT DIFFUSION COEFFICIENT HISTOGRAM ANALYSISAboian M, Solomon D, Kline-Nunnally C, Vardapetyan A, Tong E, Li Y, Felton E, Braunstein S, Mueller S, Cha S. NIMG-71. DIFFUSION CHARACTERISTICS OF PEDIATRIC DIFFUSE MIDLINE GLIOMAS WITH HISTONE H3 K27M MUTATION USING APPARENT DIFFUSION COEFFICIENT HISTOGRAM ANALYSIS Neuro-Oncology 2017, 19: vi158-vi158. PMCID: PMC5692475, DOI: 10.1093/neuonc/nox168.643.
  • PDCT-19. A SAFETY STUDY OF VEMURAFENIB, AN ORAL INHIBITOR OF BRAFV600E, IN CHILDREN WITH RECURRENT/REFRACTORY BRAFV600E MUTANT BRAIN TUMORS: PNOC-002Nicolaides T, Nazemi K, Crawford J, Kilburn L, Minturn J, Gajjar A, Gauvain K, Leary S, Dhall G, Aboian M, Robinson G, Molinaro A, Mueller S, Prados M. PDCT-19. A SAFETY STUDY OF VEMURAFENIB, AN ORAL INHIBITOR OF BRAFV600E, IN CHILDREN WITH RECURRENT/REFRACTORY BRAFV600E MUTANT BRAIN TUMORS: PNOC-002 Neuro-Oncology 2017, 19: vi188-vi188. PMCID: PMC5692489, DOI: 10.1093/neuonc/nox168.761.
  • MEDU-40. DETECTION OF NON-ENHANCING RECURRENT MEDULLOBLASTOMA ON DIFFUSION WEIGHTED IMAGINGAboian M, Kline C, Li Y, Solomon D, Banerjee A, Braunstein S, Mueller S, Dillon W, Cha S. MEDU-40. DETECTION OF NON-ENHANCING RECURRENT MEDULLOBLASTOMA ON DIFFUSION WEIGHTED IMAGING Neuro-Oncology 2017, 19: iv46-iv46. PMCID: PMC5475162, DOI: 10.1093/neuonc/nox083.190.
  • TB-02UPFRONT, REAL-TIME TUMOR AND GERMLINE SEQUENCING OF PEDIATRIC BRAIN TUMOR PATIENTS: THE UCSF EXPERIENCEKline C, Solomon D, Perry A, Bastian B, Joseph N, Phillips J, Tihan T, Yeh I, Van Ziffle J, Grenert J, Bollen A, Mueller S, Banerjee A, Gupta N, Raffel C, Braunstein S, Cha S, Aboian M, Samuel D, Torkildson J, Campomanes A, Nicolaides T. TB-02UPFRONT, REAL-TIME TUMOR AND GERMLINE SEQUENCING OF PEDIATRIC BRAIN TUMOR PATIENTS: THE UCSF EXPERIENCE Neuro-Oncology 2016, 18: iii169.2-iii169. PMCID: PMC4903852, DOI: 10.1093/neuonc/now084.02.
  • HG-92IMAGING CHARACTERISTICS OF PEDIATRIC DIFFUSE MIDLINE GLIOMAS BASED ON THE PRESENCE OF A POOR PROGNOSTIC MARKER HISTONE H3 K27M MUTATIONAboian M, Solomon D, Felton E, Mueller S, Cha S. HG-92IMAGING CHARACTERISTICS OF PEDIATRIC DIFFUSE MIDLINE GLIOMAS BASED ON THE PRESENCE OF A POOR PROGNOSTIC MARKER HISTONE H3 K27M MUTATION Neuro-Oncology 2016, 18: iii69-iii69. PMCID: PMC4903465, DOI: 10.1093/neuonc/now073.88.
  • PropofolAboian M, Johnson J, Ginat D. Propofol 2015, 347-349. DOI: 10.1007/978-3-319-12715-6_50.

Clinical Trials