Literature DB >> 28981352

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

Daniel Chow1, Peter Chang2, Brent D Weinberg3, Daniela A Bota4, Jack Grinband5, Christopher G Filippi6.   

Abstract

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.

Entities:  

Keywords:  glioblastoma; machine learning; radiogenomics

Mesh:

Year:  2017        PMID: 28981352     DOI: 10.2214/AJR.17.18754

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  22 in total

1.  Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype.

Authors:  Zhenyu Tang; Yuyun Xu; Zhicheng Jiao; Junfeng Lu; Lei Jin; Abudumijiti Aibaidula; Jinsong Wu; Qian Wang; Han Zhang; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2019-10-10

2.  Aging-related tumor associated fibroblasts changes could worsen the prognosis of GBM patients.

Authors:  Hongwang Song; Xiaojun Fu; Chenxing Wu; Shouwei Li
Journal:  Cancer Cell Int       Date:  2020-10-08       Impact factor: 5.722

3.  Dissecting and rebuilding the glioblastoma microenvironment with engineered materials.

Authors:  Kayla J Wolf; Joseph Chen; Jason Coombes; Manish K Aghi; Sanjay Kumar
Journal:  Nat Rev Mater       Date:  2019-08-16       Impact factor: 66.308

4.  Integrated MRI-Immune-Genomic Features Enclose a Risk Stratification Model in Patients Affected by Glioblastoma.

Authors:  Giulia Mazzaschi; Alessandro Olivari; Antonio Pavarani; Costanza Anna Maria Lagrasta; Caterina Frati; Denise Madeddu; Bruno Lorusso; Silvia Dallasta; Chiara Tommasi; Antonino Musolino; Marcello Tiseo; Maria Michiara; Federico Quaini; Pellegrino Crafa
Journal:  Cancers (Basel)       Date:  2022-07-01       Impact factor: 6.575

Review 5.  Standard clinical approaches and emerging modalities for glioblastoma imaging.

Authors:  Joshua D Bernstock; Sam E Gary; Neil Klinger; Pablo A Valdes; Walid Ibn Essayed; Hannah E Olsen; Gustavo Chagoya; Galal Elsayed; Daisuke Yamashita; Patrick Schuss; Florian A Gessler; Pier Paolo Peruzzi; Asim K Bag; Gregory K Friedman
Journal:  Neurooncol Adv       Date:  2022-05-26

6.  Correlations between metabolic texture features, genetic heterogeneity, and mutation burden in patients with lung cancer.

Authors:  Seung Hwan Moon; Jinho Kim; Je-Gun Joung; Hongui Cha; Woong-Yang Park; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park; Joon Young Choi; Kyung-Han Lee; Byung-Tae Kim; Se-Hoon Lee
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-08-25       Impact factor: 9.236

7.  Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients.

Authors:  Zhenyu Tang; Yuyun Xu; Lei Jin; Abudumijiti Aibaidula; Junfeng Lu; Zhicheng Jiao; Jinsong Wu; Han Zhang; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2020-01-06       Impact factor: 10.048

8.  Identification of magnetic resonance imaging features for the prediction of molecular profiles of newly diagnosed glioblastoma.

Authors:  Sung Soo Ahn; Chansik An; Yae Won Park; Kyunghwa Han; Jong Hee Chang; Se Hoon Kim; Seung-Koo Lee; Soonmee Cha
Journal:  J Neurooncol       Date:  2021-06-30       Impact factor: 4.130

9.  Analysis of peritumoral hyperintensity on pre-operative T2-weighted MR images in glioblastoma: Additive prognostic value of Minkowski functionals.

Authors:  Yangsean Choi; Kook Jin Ahn; Yoonho Nam; Jinhee Jang; Na-Young Shin; Hyun Seok Choi; So-Lyung Jung; Bum-Soo Kim
Journal:  PLoS One       Date:  2019-05-31       Impact factor: 3.240

Review 10.  Extracellular Vesicles Involvement in the Modulation of the Glioblastoma Environment.

Authors:  Fausta Ciccocioppo; Paola Lanuti; Marco Marchisio; Sebastiano Miscia
Journal:  J Oncol       Date:  2020-01-28       Impact factor: 4.375

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