Imaging Genetic Heterogeneity in Glioblastoma and Other Glial Tumors: Review of Current Methods and Future Directions

被引：52

作者：

Chow, Daniel ^{[1
]}

Chang, Peter ^{[2
]}

Weinberg, Brent D. ^{[3
]}

Bota, Daniela A. ^{[4
]}

Grinband, Jack ^{[5
]}

Filippi, Christopher G. ^{[6
]}

机构：

[1] Univ Calif Irvine, Irvine Med Ctr, Dept Radiol, Douglas Hosp, Rte 140,Rm 0115, Orange, CA 92868 USA

[2] Univ Calif San Francisco, Dept Radiol, San Francisco, CA USA

[3] Emory Univ, Sch Med, Dept Radiol, Emory Univ Hosp, Atlanta, GA 30322 USA

[4] Univ Calif Irvine, Irvine Med Ctr, Dept Neurooncol, Orange, CA 92668 USA

[5] Columbia Univ, Coll Phys & Surg, Dept Radiol, New York, NY USA

[6] North Shore Univ Hosp, Dept Radiol, Manhasset, NY USA

来源：

AMERICAN JOURNAL OF ROENTGENOLOGY | 2018年 / 210卷 / 01期

基金：

美国国家卫生研究院;

关键词：

glioblastoma; machine learning; radiogenomics; MGMT PROMOTER METHYLATION; ADJUVANT TEMOZOLOMIDE; CLASSIFICATION MODELS; AMPLIFICATION STATUS; ASTROCYTIC TUMORS; MOLECULAR MARKERS; MUTATIONAL STATUS; IDH MUTATION; DIFFUSION; SURVIVAL;

D O I：

10.2214/AJR.17.18754

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

OBJECTIVE. The purpose of this review is to summarize advances in the molecular analysis of gliomas, the role genetics plays in MRI features, and how machine-learning approaches can be used to survey the tumoral environment. CONCLUSION. The genetic profile of gliomas influences the course of treatment and clinical outcomes. Though biopsy is the reference standard for determining tumor genetics, it can suffer diagnostic delays due to surgical planning and pathologic assessment. Radiogenomics may allow rapid, low-risk characterization of genetic heterogeneity.

引用

页码：30 / 38

页数：9

共 72 条

[1] Magnetic resonance imaging characteristics predict epidermal growth factor receptor amplification status in glioblastoma [J].

Aghi, M ;

Gaviani, P ;

Henson, JW ;

Batchelor, TT ;

Louis, DN ;

Barker, FG .

CLINICAL CANCER RESEARCH, 2005, 11 (24) :8600-8605

[2] Biomarker-driven diagnosis of diffuse gliomas [J].

Appin, Christina L. ;

Brat, Daniel J. .

MOLECULAR ASPECTS OF MEDICINE, 2015, 45 :87-96

[3]

Auffinger Brenda, 2012, F1000 Med Rep, V4, P18

[4] Genetics of Glioblastoma: A Window into Its Imaging and Histopathologic Variability [J].

Belden, Clifford J. ;

Valdes, Pablo A. ;

Ran, Cong ;

Pastel, David A. ;

Harris, Brent T. ;

Fadul, Camilo E. ;

Israel, Mark A. ;

Paulsen, Keith ;

Roberts, David W. .

RADIOGRAPHICS, 2011, 31 (06) :1717-1740

[5] Prognostic Molecular and Imaging Biomarkers in Primary Glioblastoma [J].

Bosnyak, Edit ;

Michelhaugh, Sharon K. ;

Klinger, Neil V. ;

Kamson, David O. ;

Barger, Geoffrey R. ;

Mittal, Sandeep ;

Juhasz, Csaba .

CLINICAL NUCLEAR MEDICINE, 2017, 42 (05) :341-347

[6]

Boyle, 2015, IMAGE PROCESSING ANA

[7] Diagnostic, prognostic and predictive relevance of molecular markers in gliomas [J].

Brandner, S. ;

von Deimling, A. .

NEUROPATHOLOGY AND APPLIED NEUROBIOLOGY, 2015, 41 (06) :694-720

[8] ATRX mRNA expression combined with IDH1/2 mutational status and Ki-67 expression refines the molecular classification of astrocytic tumors: evidence from the whole transcriptome sequencing of 169 samples [J].

Cai, Jinquan ;

Yang, Pei ;

Zhang, Chuanbao ;

Zhang, Wei ;

Liu, Yanwei ;

Bao, Zhaoshi ;

Liu, Xing ;

Du, Wenzhong ;

Wang, Hongjun ;

Jiang, Tao ;

Jiang, Chuanlu .

ONCOTARGET, 2014, 5 (09) :2551-2561

[9] Relationship between Tumor Enhancement, Edema, IDH1 Mutational Status, MGMT Promoter Methylation, and Survival in Glioblastoma [J].

Carrillo, J. A. ;

Lai, A. ;

Nghiemphu, P. L. ;

Kim, H. J. ;

Phillips, H. S. ;

Kharbanda, S. ;

Moftakhar, P. ;

Lalaezari, S. ;

Yong, W. ;

Ellingson, B. M. ;

Cloughesy, T. F. ;

Pope, W. B. .

AMERICAN JOURNAL OF NEURORADIOLOGY, 2012, 33 (07) :1349-1355

[10] Texture analysis of medical images [J].

Castellano, G ;

Bonilha, L ;

Li, LM ;

Cendes, F .

CLINICAL RADIOLOGY, 2004, 59 (12) :1061-1069

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