TY - JOUR
T1 - Radiogenomics of lower-grade glioma
T2 - algorithmically-assessed tumor shape is associated with tumor genomic subtypes and patient outcomes in a multi-institutional study with The Cancer Genome Atlas data
AU - Mazurowski, Maciej A.
AU - Clark, Kal
AU - Czarnek, Nicholas M.
AU - Shamsesfandabadi, Parisa
AU - Peters, Katherine B.
AU - Saha, Ashirbani
N1 - Funding Information:
Dr. Katherine B. Peters received research funding from the following companies: Agios, AMGEN, BioMimetix, Eisai, Genentech, Merck, VBL. Dr. Katherine B. Peters is on the Advisory Board of the following companies:Agios, Novocure. Other authors have nothing relevant to disclose.
Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Recent studies identified distinct genomic subtypes of lower-grade gliomas that could potentially be used to guide patient treatment. This study aims to determine whether there is an association between genomics of lower-grade glioma tumors and patient outcomes using algorithmic measurements of tumor shape in magnetic resonance imaging (MRI). We analyzed preoperative imaging and genomic subtype data from 110 patients with lower-grade gliomas (WHO grade II and III) from The Cancer Genome Atlas. Computer algorithms were applied to analyze the imaging data and provided five quantitative measurements of tumor shape in two and three dimensions. Genomic data for the analyzed cohort of patients consisted of previously identified genomic clusters based on IDH mutation and 1p/19q co-deletion, DNA methylation, gene expression, DNA copy number, and microRNA expression. Patient outcomes were quantified by overall survival. We found that there is a strong association between angular standard deviation (ASD), which measures irregularity of the tumor boundary, and the IDH-1p/19q subtype (p < 0.0017), RNASeq cluster (p < 0.0002), DNA copy number cluster (p < 0.001), and the cluster of clusters (p < 0.0002). The RNASeq cluster was also associated with bounding ellipsoid volume ratio (p < 0.0005). Tumors in the IDH wild type cluster and R2 RNASeq cluster which are associated with much poorer outcomes generally had higher ASD reflecting more irregular shape. ASD also showed association with patient overall survival (p = 0.006). Shape features in MRI were strongly associated with genomic subtypes and patient outcomes in lower-grade glioma.
AB - Recent studies identified distinct genomic subtypes of lower-grade gliomas that could potentially be used to guide patient treatment. This study aims to determine whether there is an association between genomics of lower-grade glioma tumors and patient outcomes using algorithmic measurements of tumor shape in magnetic resonance imaging (MRI). We analyzed preoperative imaging and genomic subtype data from 110 patients with lower-grade gliomas (WHO grade II and III) from The Cancer Genome Atlas. Computer algorithms were applied to analyze the imaging data and provided five quantitative measurements of tumor shape in two and three dimensions. Genomic data for the analyzed cohort of patients consisted of previously identified genomic clusters based on IDH mutation and 1p/19q co-deletion, DNA methylation, gene expression, DNA copy number, and microRNA expression. Patient outcomes were quantified by overall survival. We found that there is a strong association between angular standard deviation (ASD), which measures irregularity of the tumor boundary, and the IDH-1p/19q subtype (p < 0.0017), RNASeq cluster (p < 0.0002), DNA copy number cluster (p < 0.001), and the cluster of clusters (p < 0.0002). The RNASeq cluster was also associated with bounding ellipsoid volume ratio (p < 0.0005). Tumors in the IDH wild type cluster and R2 RNASeq cluster which are associated with much poorer outcomes generally had higher ASD reflecting more irregular shape. ASD also showed association with patient overall survival (p = 0.006). Shape features in MRI were strongly associated with genomic subtypes and patient outcomes in lower-grade glioma.
KW - Brain MRI
KW - Lower-grade gliomas
KW - Radiogenomics
KW - Tumor genomic subtype
KW - Tumor shape feature
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U2 - 10.1007/s11060-017-2420-1
DO - 10.1007/s11060-017-2420-1
M3 - Article
C2 - 28470431
AN - SCOPUS:85019010156
SN - 0167-594X
VL - 133
SP - 27
EP - 35
JO - Journal of Neuro-Oncology
JF - Journal of Neuro-Oncology
IS - 1
ER -