2024
Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI
Lost J, Ashraf N, Jekel L, von Reppert M, Tillmanns N, Willms K, Merkaj S, Petersen G, Avesta A, Ramakrishnan D, Omuro A, Nabavizadeh A, Bakas S, Bousabarah K, De Lin M, Aneja S, Sabel M, Aboian M. Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI. Neuro-Oncology Advances 2024, vdae157. DOI: 10.1093/noajnl/vdae157.Peer-Reviewed Original ResearchIsocitrate dehydrogenase mutation statusArea under the curveMagnetic resonance imagingMutation statusML modelsMachine learningSemi-automated tumour segmentationsPre-surgical magnetic resonance imagingCare of glioma patientsMachine learning modelsClinical care of glioma patientsIsocitrate dehydrogenase statusAnnotated datasetsFeature extractionPrediction taskMulti-institutional dataModel trainingIDH mutationsPredicting IDH mutationLearning modelsRetrospective studyHeterogeneous datasetsTumor segmentationGlioma patientsBrain tumors
2015
Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma
de la Fuente MI, Young RJ, Rubel J, Rosenblum M, Tisnado J, Briggs S, Arevalo-Perez J, Cross JR, Campos C, Straley K, Zhu D, Dong C, Thomas A, Omuro AA, Nolan CP, Pentsova E, Kaley TJ, Oh JH, Noeske R, Maher E, Choi C, Gutin PH, Holodny AI, Yen K, DeAngelis LM, Mellinghoff IK, Thakur SB. Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma. Neuro-Oncology 2015, 18: 283-290. PMID: 26691210, PMCID: PMC4724186, DOI: 10.1093/neuonc/nov307.Peer-Reviewed Original ResearchConceptsTumor volumeDisease monitoringIsocitrate dehydrogenase (IDH) mutant gliomasProton magnetic resonance spectroscopyConsecutive glioma patientsMR imaging protocolMagnetic resonance spectroscopyCytoreductive therapyTumor levelsLarge tumorsTumor gradeSmall tumorsGlioma patientsGlioma imagingGlioma therapyClinical practiceClinical implicationsRoutine MRTumor cellularityTumor cellsIDH-mutant gliomasGliomasMetabolite RImaging protocolMitotic indexGlutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo
Venneti S, Dunphy MP, Zhang H, Pitter KL, Zanzonico P, Campos C, Carlin SD, La Rocca G, Lyashchenko S, Ploessl K, Rohle D, Omuro AM, Cross JR, Brennan CW, Weber WA, Holland EC, Mellinghoff IK, Kung HF, Lewis JS, Thompson CB. Glutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo. Science Translational Medicine 2015, 7: 274ra17. PMID: 25673762, PMCID: PMC4431550, DOI: 10.1126/scitranslmed.aaa1009.Peer-Reviewed Original ResearchConceptsPositron emission tomographyPermeable blood-brain barrierChemo/radiation therapyHigh tumor/background ratiosClear tumor delineationDecreased tumor burdenHigh background uptakeTumor/background ratiosBlood-brain barrierAltered glucose metabolismHuman glioma patientsVivo positron emission tomographyProgressive diseaseTumor burdenMetabolic evaluationBrain uptakeClinical managementTumor avidityGlioma patientsRadiation therapyGlucose metabolismBackground uptakeEmission tomographyGliomasCancer cells