Radiomics and visual analysis for predicting success of transplantation of heterotopic glioblastoma in mice with MRI

Nandu H, Wen PY, Huang RY (2018) Imaging in neuro-oncology. Ther Adv Neurol Disord 11:1–19. https://doi.org/10.1177/1756286418759865

Article  Google Scholar 

Verburg N, de Witt Hamer PC (2021) State-of-the-art imaging for glioma surgery. Neurosurg Rev 44:1331–1343. https://doi.org/10.1007/s10143-020-01337-9

Article  PubMed  Google Scholar 

Thorsen F, Ersland L, Nordli H, Enger PO, Huszthy PC, Lundervold A, Standnes T, Bjerkvig R, Lund-Johansen M (2003) Imaging of experimental rat gliomas using a clinical MR scanner. J Neurooncol 63:225–323. https://doi.org/10.1023/a:1024241905888

Article  PubMed  Google Scholar 

Herrmann KH, Pfeiffer N, Krumbein I, Herrmann L, Reichenbach JR (2014) MRI compatible small animal monitoring and trigger system for whole body scanners. Z Med Phys 24:55–64. https://doi.org/10.1016/j.zemedi.2013.07.005

Article  PubMed  Google Scholar 

Driehuys B, Nouls J, Badea A, Bucholz E, Ghaghada K, Petiet A, Hedlund LW (2008) Small animal imaging with magnetic resonance microscopy. ILAR J 49:35–53. https://doi.org/10.1093/ilar.49.1.35

Article  CAS  PubMed  Google Scholar 

Richmond A, Su Y (2008) Mouse xenograft models vs GEM models for human cancer therapeutics. Dis Model Mech 1:78–82. https://doi.org/10.1242/dmm.000976

Article  PubMed  PubMed Central  Google Scholar 

Seymour L, Bogaerts J, Perrone A, Ford R, Schwartz LH, Mandrekar S, Lin NU, Litière S, Dancey J, Chen A, Hodi FS, Therasse P, Hoekstra OS, Shankar LK, Wolchok JD, Ballinger M, Caramella C, de Vries EGE, RECIST working group, (2017) iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol 18:143–152. https://doi.org/10.1016/S1470-2045(17)30074-8

Article  Google Scholar 

Altman DA, Atkinson DS Jr, Brat DJ (2007) Best cases from the AFIP: glioblastoma multiforme. Radiographics 27:883–888. https://doi.org/10.1148/rg.273065138

Article  PubMed  Google Scholar 

Herrmann KH, Schmidt S, Kretz A, Haenold R, Krumbein I, Metzler M, Gaser C, Witte OW, Reichenbach JR (2012) Possibilities and limitations for high resolution small animal MRI on a clinical whole-body 3T scanner. Magn Reson Mater Phy 25:233–244. https://doi.org/10.1007/s10334-011-0284-5

Article  Google Scholar 

Rizzo S, Botta F, Raimondi S, Origgi D, Fanciullo C, Morganti AG, Bellomi M (2018) Radiomics: the facts and the challenges of image analysis. Eur Radiol Exp 2(1):36. https://doi.org/10.1186/s41747-018-0068-z

Article  PubMed  PubMed Central  Google Scholar 

Zhang Y, Chen C, Tian Z, Feng R, Cheng Y, Xu J (2019) The Diagnostic Value of MRI-Based Texture Analysis in Discrimination of Tumors Located in Posterior Fossa: A Preliminary Study. Front Neurosci 13:1113. https://doi.org/10.3389/fnins.2019.01113

Article  PubMed  PubMed Central  Google Scholar 

Ion-Mărgineanu A, Van Cauter S, Sima DM, Maes F, Sunaert S, Himmelreich U, Van Huffel S (2017) Classifying glioblastoma multiforme follow-up progressive vs. responsive forms using multiparametric MRI features. Front Neurosci 10:615. https://doi.org/10.3389/fnins.2016.00615

Article  PubMed  PubMed Central  Google Scholar 

Jalil O, Afaq A, Ganeshan B, Patel UB, Boone D, Endozo R, Groves A, Sizer B, Arulampalam T (2017) Magnetic resonance based texture parameters as potential imaging biomarkers for predicting long-term survival in locally advanced rectal cancer treated by chemoradiotherapy. Colorectal Dis 19:349–362. https://doi.org/10.1111/codi.13496

Article  CAS  PubMed  Google Scholar 

Kim JH, Ko ES, Lim Y, Lee KS, Han BK, Ko EY, Hahn SY, Nam SJ (2017) Breast cancer heterogeneity: MR imaging texture analysis and survival outcomes. Radiology 282:665–675. https://doi.org/10.1148/radiol.2016160261

Article  PubMed  Google Scholar 

Chaddad A, Daniel P, Desrosiers C, Toews M, Abdulkarim B (2019) Novel radiomic features based on joint intensity matrixes for predicting glioblastoma patient survival time. IEEE J Biomed Health Inform 23:795–804. https://doi.org/10.1109/JBHI.2018.2825027

Article  PubMed  Google Scholar 

Lisson CS, Lisson CG, Flosdorf K, Mayer-Steinacker R, Schultheiss M, von Baer A, Barth TFE, Beer AJ, Baumhauer M, Meier R, Beer M, Schmidt SA (2018) Diagnostic value of MRI-based 3D texture analysis for tissue characterisation and discrimination of low-grade chondrosarcoma from enchondroma: a pilot study. Eur Radiol 28:468–477. https://doi.org/10.1007/s00330-017-5014-6

Article  PubMed  Google Scholar 

Giannini V, Mazzetti S, Bertotto I, Chiarenza C, Cauda S, Delmastro E, Bracco C, Di Dia A, Leone F, Medico E, Pisacane A, Ribero D, Stasi M, Regge D (2019) Predicting locally advanced rectal cancer response to neoadjuvant therapy with F-FDG PET and MRI radiomics features. Eur J Nucl Med Mol Imaging 46:878–888. https://doi.org/10.1007/s00259-018-4250-6

Article  CAS  PubMed  Google Scholar 

Bigner DD, Bigner SH, Pontén J, Westermark B, Mahaley MS, Ruoslahti E, Herschman H, Eng LF, Wikstrand CJ (1981) Heterogeneity of genotypic and phenotypic characteristics of fifteen permanent cell lines derived from human gliomas. J Neuropathol Exp Neurol 40:201–229. https://doi.org/10.1097/00005072-198105000-00001

Article  CAS  PubMed  Google Scholar 

VASARI project - https://wiki.cancerimagingarchive.net. Read relevant article. Accessed on 09/06/2016

Inderbitzin D, Stoupis C, Sidler D, Gass M, Candinas D (2007) Abdominal magnetic resonance imaging in small rodents using a clinical 1.5 T MR scanner. Methods 43:46–53. https://doi.org/10.1016/j.ymeth.2007.03.010

Article  CAS  PubMed  Google Scholar 

Strzelecki M, Szczypinski P, Materka A, Klepaczko A (2013) A software tool for automatic classification and segmentation of 2D/3D medical images. Physics Res 702:137–140. https://doi.org/10.1016/j.nima.2012.09.006

Article  CAS  Google Scholar 

Szczypinski P, Strzelecki M, Materka A, Klepaczko A (2009) MaZda-A software package for image texture analysis. Comput Methods Programs Biomed 94:66–76. https://doi.org/10.1016/j.cmpb.2008.08.005

Article  PubMed  Google Scholar 

Mayerhoefer ME, Materka A, Langs G, Häggström I, Szczypiński P, Gibbs P, Cook G (2020) Introduction to Radiomics. J Nucl Med 61:488–495. https://doi.org/10.2967/jnumed.118.222893

Article  CAS  PubMed  PubMed Central  Google Scholar 

Materka A (2004) Texture analysis methodologies for magnetic resonance imaging. Dialogues Clin Neurosci 6:243–250. https://doi.org/10.2967/jnumed.118.222893

Article  CAS  PubMed  PubMed Central  Google Scholar 

R. Core Team (2020) R: A language and environment for statistical computing. http://www.r-project.org/

Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674. https://doi.org/10.1016/j.cell.2011.02.013

Article  CAS  PubMed  Google Scholar 

Deoni SCL (2017) From Image Formation to Image Contrast: Understanding Contrast Mechanisms, Acquisition Strategies, and Artifacts. In: Atlas SW (ed) Magnetic Resonance Imaging of the Brain and Spine, 5th edn. Wolters Kluver, Philadelphia, pp 22–58

Google Scholar 

Haddad AF, Young JS, Amara D, Berger MS, Raleigh DR, Aghi MK, Butowski NA (2021) Mouse models of glioblastoma for the evaluation of novel therapeutic strategies. Neurooncol Adv 26:vdab100. https://doi.org/10.1093/noajnl/vdab100

Jacobs VL, Valdes PA, Hickey WF, De Leo JA (2011) Current review of in vivo GBM rodent models: emphasis on the CNS-1 tumour model. ASN Neuro 3:171–181. https://doi.org/10.1042/AN20110014

Article  CAS  Google Scholar 

Radaelli E, Ceruti R, Patton V, Russo M, Degrassi A, Croci V, Caprera F, Stortini G, Scanziani E, Pesenti E, Alzani R (2009) Immunohistopathological and neuroimaging characterization of murine orthotopic xenograft models of glioblastoma multiforme recapitulating the most salient features of human disease. Histol Histopathol 24:879–89. https://doi.org/10.14670/HH-24.879

Article  CAS  PubMed  Google Scholar 

de Vries NA, Beijnen JH, van Tellingen O (2009) High-grade glioma mouse models and their applicability for preclinical testing. Cancer Treat Rev 35:714–723. https://doi.org/10.1016/j.ctrv.2009.08.011

Article  CAS  PubMed  Google Scholar 

Telles B, D’Amore F, Jayaraman MV, Boxerman JL, Law M, Shiroishi MS, Lerner A (2017) Adult brain tumors. In: Atlas SW (ed) Magnetic Resonance Imaging of the Brain and Spine, 5th edn. Wolters Kluver, Philadelphia, pp 303–429

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