Literature DB >> 26163091

Is there a causal relationship between genetic changes and radiomics-based image features? An in vivo preclinical experiment with doxycycline inducible GADD34 tumor cells.

Kranthi Marella Panth1, Ralph T H Leijenaar2, Sara Carvalho2, Natasja G Lieuwes2, Ala Yaromina2, Ludwig Dubois2, Philippe Lambin2.   

Abstract

BACKGROUND AND
PURPOSE: The central hypothesis of "radiomics" is that imaging features reflect tumor phenotype and genotype. Until now only correlative studies have been performed. The main objective of our study is to determine whether a causal relationship exists between genetic changes and image features. The secondary objective is to assess whether the combination with radiotherapy (RT) influences these image features.
MATERIAL AND METHODS: HCT116 doxycycline (dox) inducible GADD34 cells were grown as xenografts in the flanks of NMRI-nu mice. GADD34 overexpression decreases hypoxic fraction. Radiomics analyses were performed on computed tomography images obtained at 40kVp and again at 80kVp for validation, before radiotherapy at a volume of 200mm(3), 4days post RT (10Gy) and 500mm(3). To select reproducible features test-retest experiments were performed at baseline.
RESULTS: Gene induction and/or irradiation translated into significant changes in radiomics features. Post irradiation, 17 features for 40kVp and 9 features for 80kVp differed significantly between dox+ and dox- combined with RT. 8 and 4 of these features remained consistent for 40 and 80kVp, respectively.
CONCLUSION: Radiomics is able to identify early effects of changed gene expression combined with radiation treatment in tumors with similar volumes which are not visible to human eye.
Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Entities:  

Keywords:  CT imaging; Preclinical; Radiogenomics; Radiotherapy

Mesh:

Substances:

Year:  2015        PMID: 26163091     DOI: 10.1016/j.radonc.2015.06.013

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  45 in total

1.  Radiomics: a new application from established techniques.

Authors:  Vishwa Parekh; Michael A Jacobs
Journal:  Expert Rev Precis Med Drug Dev       Date:  2016-03-31

2.  MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma.

Authors:  Lina Zhao; Jie Gong; Yibin Xi; Man Xu; Chen Li; Xiaowei Kang; Yutian Yin; Wei Qin; Hong Yin; Mei Shi
Journal:  Eur Radiol       Date:  2019-08-01       Impact factor: 5.315

3.  Radiomics nomogram outperforms size criteria in discriminating lymph node metastasis in resectable esophageal squamous cell carcinoma.

Authors:  Xianzheng Tan; Zelan Ma; Lifen Yan; Weitao Ye; Zaiyi Liu; Changhong Liang
Journal:  Eur Radiol       Date:  2018-06-19       Impact factor: 5.315

4.  Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma.

Authors:  Wenbing Lv; Qingyu Yuan; Quanshi Wang; Jianhua Ma; Qianjin Feng; Wufan Chen; Arman Rahmim; Lijun Lu
Journal:  Mol Imaging Biol       Date:  2019-10       Impact factor: 3.488

5.  Predicting hypoxia status using a combination of contrast-enhanced computed tomography and [18F]-Fluorodeoxyglucose positron emission tomography radiomics features.

Authors:  Mireia Crispin-Ortuzar; Aditya Apte; Milan Grkovski; Jung Hun Oh; Nancy Y Lee; Heiko Schöder; John L Humm; Joseph O Deasy
Journal:  Radiother Oncol       Date:  2017-12-19       Impact factor: 6.280

Review 6.  Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Authors:  Faiq Shaikh; Benjamin Franc; Erastus Allen; Evis Sala; Omer Awan; Kenneth Hendrata; Safwan Halabi; Sohaib Mohiuddin; Sana Malik; Dexter Hadley; Rasu Shrestha
Journal:  J Am Coll Radiol       Date:  2018-02-01       Impact factor: 5.532

Review 7.  Radiomics: the bridge between medical imaging and personalized medicine.

Authors:  Philippe Lambin; Ralph T H Leijenaar; Timo M Deist; Jurgen Peerlings; Evelyn E C de Jong; Janita van Timmeren; Sebastian Sanduleanu; Ruben T H M Larue; Aniek J G Even; Arthur Jochems; Yvonka van Wijk; Henry Woodruff; Johan van Soest; Tim Lustberg; Erik Roelofs; Wouter van Elmpt; Andre Dekker; Felix M Mottaghy; Joachim E Wildberger; Sean Walsh
Journal:  Nat Rev Clin Oncol       Date:  2017-10-04       Impact factor: 66.675

Review 8.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

9.  A Coclinical Radiogenomic Validation Study: Conserved Magnetic Resonance Radiomic Appearance of Periostin-Expressing Glioblastoma in Patients and Xenograft Models.

Authors:  Pascal O Zinn; Sanjay K Singh; Aikaterini Kotrotsou; Islam Hassan; Ginu Thomas; Markus M Luedi; Ahmed Elakkad; Nabil Elshafeey; Tagwa Idris; Jennifer Mosley; Joy Gumin; Gregory N Fuller; John F de Groot; Veera Baladandayuthapani; Erik P Sulman; Ashok J Kumar; Raymond Sawaya; Frederick F Lang; David Piwnica-Worms; Rivka R Colen
Journal:  Clin Cancer Res       Date:  2018-07-27       Impact factor: 12.531

10.  Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy.

Authors:  Stephen R Bowen; William T C Yuh; Daniel S Hippe; Wei Wu; Savannah C Partridge; Saba Elias; Guang Jia; Zhibin Huang; George A Sandison; Dennis Nelson; Michael V Knopp; Simon S Lo; Paul E Kinahan; Nina A Mayr
Journal:  J Magn Reson Imaging       Date:  2017-10-16       Impact factor: 4.813

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.