Literature DB >> 29988289

Assessment of concurrent stereotactic radiosurgery and bevacizumab treatment of recurrent malignant gliomas using multi-modality MRI imaging and radiomics analysis.

Chunhao Wang1, Wenzheng Sun1, John Kirkpatrick1, Zheng Chang1, Fang-Fang Yin1.   

Abstract

PURPOSE: To assess the response and predict the overall survival (OS) of recurrent malignant gliomas (MG) patients treated with concurrent BVZ/SRS using multi-modality MRI imaging and radiomics analysis.Methods and materials: SRS was delivered in a single fraction (18/24Gy) or 25Gy in 5 fractions. BVZ was administered immediately before SRS and 2 weeks after. MRI scans were performed before SRS, 1 week and 2 months after SRS. The MR protocol included 2 anatomical (T1w and T2w) and 2 functional (dynamic contrast-enhanced DCE-MRI and diffusion weighted DW-MRI) modalities. Functional biomarkers including apparent diffusion coefficient (ADC), micro-vascular transfer constant Ktrans, brain blood flow FB, and blood volume VB were analyzed. Radiomics analysis was performed to extract imaging features from anatomical MRI images and functional biomarker maps. Wicoxon signed rank tests were performed to evaluate treatment-induced changes, and Mann-Whitney U tests were performed to compare the differences of treatment-induced changes between different patient groups. Selected biomarkers and radiomics features were used to predict the OS after treatment using Support Vector Regression (SVR) with leave-one-out cross validation (LOOCV).
RESULTS: Twelve patients with recurrent MG were studied. The median OS was 13.8 months post SRS. DCE results showed that Ktrans (p=0.035) and VB (p=0.035) showed significant decrease 2 months after SRS, and FB showed significant decrease as early as 1 week (p=0.017) after SRS. No functional parameters reflected statistically significant treatment response 1 week after SRS. A total of 888 radiomics features were extracted. 31/126 features demonstrated significant changes 1 week/2 months after SRS, respectively. 9 features' changes were significantly different between WHO Grade III vs IV patient groups, and 6 features' changes were found to be linearly correlated with OS. Using 5 selected features, 9 patients' survival time could be accurately predicted (Mean absolute error = 1.47 months, RMSE = 2.10 months).
CONCLUSION: The results of this work demonstrate the potential of combined radiomics analysis and functional MR imaging in quantitatively identifying early treatment response of concurrent SRS/BVZ.

Entities:  

Keywords:  DCE-MRI; DW-MRI; SRS; radiomics, treatment assessment; recurrent glioma

Year:  2018        PMID: 29988289      PMCID: PMC6018043     

Source DB:  PubMed          Journal:  J Radiosurg SBRT


  37 in total

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Authors:  Weijie Chen; Maryellen L Giger; Hui Li; Ulrich Bick; Gillian M Newstead
Journal:  Magn Reson Med       Date:  2007-09       Impact factor: 4.668

2.  Quantification of cerebral blood flow, cerebral blood volume, and blood-brain-barrier leakage with DCE-MRI.

Authors:  Steven Sourbron; Michael Ingrisch; Axel Siefert; Maximilian Reiser; Karin Herrmann
Journal:  Magn Reson Med       Date:  2009-07       Impact factor: 4.668

Review 3.  Dynamic contrast-enhanced magnetic resonance imaging as an imaging biomarker.

Authors:  Nola Hylton
Journal:  J Clin Oncol       Date:  2006-07-10       Impact factor: 44.544

Review 4.  Lessons from phase III clinical trials on anti-VEGF therapy for cancer.

Authors:  Rakesh K Jain; Dan G Duda; Jeffrey W Clark; Jay S Loeffler
Journal:  Nat Clin Pract Oncol       Date:  2006-01

5.  Heterogeneity in DCE-MRI parametric maps: a biomarker for treatment response?

Authors:  L Alic; M van Vliet; C F van Dijke; A M M Eggermont; J F Veenland; W J Niessen
Journal:  Phys Med Biol       Date:  2011-02-18       Impact factor: 3.609

6.  Water diffusion in the different microenvironments of breast cancer.

Authors:  Yael Paran; Peter Bendel; Raanan Margalit; Hadassa Degani
Journal:  NMR Biomed       Date:  2004-06       Impact factor: 4.044

7.  FDA drug approval summary: bevacizumab (Avastin) plus Carboplatin and Paclitaxel as first-line treatment of advanced/metastatic recurrent nonsquamous non-small cell lung cancer.

Authors:  Martin H Cohen; Joe Gootenberg; Patricia Keegan; Richard Pazdur
Journal:  Oncologist       Date:  2007-06

Review 8.  Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols.

Authors:  P S Tofts; G Brix; D L Buckley; J L Evelhoch; E Henderson; M V Knopp; H B Larsson; T Y Lee; N A Mayr; G J Parker; R E Port; J Taylor; R M Weisskoff
Journal:  J Magn Reson Imaging       Date:  1999-09       Impact factor: 4.813

Review 9.  DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents.

Authors:  J P B O'Connor; A Jackson; G J M Parker; G C Jayson
Journal:  Br J Cancer       Date:  2007-01-09       Impact factor: 7.640

10.  DCE-MRI for Pre-Treatment Prediction and Post-Treatment Assessment of Treatment Response in Sites of Squamous Cell Carcinoma in the Head and Neck.

Authors:  Ann D King; Steven Kwok Keung Chow; Kwok-Hung Yu; Frankie Kwok Fai Mo; David K W Yeung; Jing Yuan; Benjamin King Hong Law; Kunwar S Bhatia; Alexander C Vlantis; Anil T Ahuja
Journal:  PLoS One       Date:  2015-12-10       Impact factor: 3.240

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  5 in total

1.  Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).

Authors:  Yushi Chang; Kyle Lafata; William Paul Segars; Fang-Fang Yin; Lei Ren
Journal:  Phys Med Biol       Date:  2020-03-19       Impact factor: 3.609

2.  Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma.

Authors:  E George; E Flagg; K Chang; H X Bai; H J Aerts; M Vallières; D A Reardon; R Y Huang
Journal:  AJNR Am J Neuroradiol       Date:  2022-04-28       Impact factor: 3.825

3.  Application of radiomics feature captured from MRI for prediction of recurrence for glioma patients.

Authors:  Canyu Liu; Yujiao Li; Xiang Xia; Jiazhou Wang; Chaosu Hu
Journal:  J Cancer       Date:  2022-01-04       Impact factor: 4.207

4.  Prediction of transient tumor enlargement using MRI tumor texture after radiosurgery on vestibular schwannoma.

Authors:  Patrick P J H Langenhuizen; Sander H P Sebregts; Svetlana Zinger; Sieger Leenstra; Jeroen B Verheul; Peter H N de With
Journal:  Med Phys       Date:  2020-02-18       Impact factor: 4.071

5.  An investigation of machine learning methods in delta-radiomics feature analysis.

Authors:  Yushi Chang; Kyle Lafata; Wenzheng Sun; Chunhao Wang; Zheng Chang; John P Kirkpatrick; Fang-Fang Yin
Journal:  PLoS One       Date:  2019-12-13       Impact factor: 3.240

  5 in total

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