Radiomics in glioblastoma: Current status, challenges and potential opportunities

Translational Cancer Research

Volumn 5, Issue 4, 2016, Pages 383-397

  Narang, Shivali ^a   Lehrer, Michael ^a   Yang, Dalu ^a,b   Lee, Joonsang ^a   Rao, Arvind ^a,b  

^a UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^b Rice University   (United States)

Author keywords

Computed tomography (CT); glioblastoma; Magnetic resonance imaging (MRI); Positron emission tomography (PET); Radiomics

Indexed keywords

6 FLUORODOPA F 18; CONTRAST MEDIUM; GADOLINIUM; TRACER;

BIOMICS; CANCER PATIENT; CANCER PROGNOSIS; CANCER STAGING; CLASSIFICATION ALGORITHM; CLINICAL DECISION MAKING; CLINICAL FEATURE; CLINICAL PRACTICE; COMPUTER ASSISTED TOMOGRAPHY; DIAGNOSTIC TEST ACCURACY STUDY; DIFFUSION WEIGHTED IMAGING; EPIGENETICS; EVIDENCE BASED MEDICINE; GLIOBLASTOMA; HISTOGRAM; HUMAN; IMAGE ANALYSIS; MACHINE LEARNING; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; OUTCOME ASSESSMENT; PERSONALIZED MEDICINE; POSITRON EMISSION TOMOGRAPHY; QUALITATIVE DIAGNOSIS; QUANTITATIVE DIAGNOSIS; RADIOBIOLOGY; RADIOGRAPHY; RADIOMICS; REVIEW; SENSITIVITY AND SPECIFICITY; SOLID TUMOR; STANDARDIZATION; STATISTICAL MODEL; TREATMENT RESPONSE; TUMOR GROWTH; TUMOR VOLUME; WORKFLOW;

EID: 84983273906     PISSN: 2218676X     EISSN: 22196803     Source Type: Journal    
DOI: 10.21037/tcr.2016.06.31     Document Type: Review

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