Literature DB >> 28900832

Spatial discrimination of glioblastoma and treatment effect with histologically-validated perfusion and diffusion magnetic resonance imaging metrics.

Melissa A Prah1, Mona M Al-Gizawiy1, Wade M Mueller2, Elizabeth J Cochran3, Raymond G Hoffmann4, Jennifer M Connelly5, Kathleen M Schmainda6,7.   

Abstract

The goal of this study is to spatially discriminate tumor from treatment effect (TE), within the contrast-enhancing lesion, for brain tumor patients at all stages of treatment. To this end, the diagnostic accuracy of MRI-derived diffusion and perfusion parameters to distinguish pure TE from pure glioblastoma (GBM) was determined utilizing spatially-correlated biopsy samples. From July 2010 through June 2015, brain tumor patients who underwent pre-operative DWI and DSC-MRI and stereotactic image-guided biopsy were considered for inclusion in this IRB-approved study. MRI-derived parameter maps included apparent diffusion coefficient (ADC), normalized cerebral blood flow (nCBF), normalized and standardized relative cerebral blood volume (nRCBV, sRCBV), peak signal-height (PSR) and percent signal-recovery (PSR). These were co-registered to the Stealth MRI and median values extracted from the spatially-matched biopsy regions. A ROC analysis accounting for multiple subject samples was performed, and the optimal threshold for distinguishing TE from GBM determined for each parameter. Histopathologic diagnosis of pure TE (n = 10) or pure GBM (n = 34) was confirmed in tissue samples from 15 consecutive subjects with analyzable data. Perfusion thresholds of sRCBV (3575; SN/SP% = 79.4/90.0), nRCBV (1.13; SN/SP% = 82.1/90.0), and nCBF (1.05; SN/SP% = 79.4/80.0) distinguished TE from GBM (P < 0.05), whereas ADC, PSR, and PH could not (P > 0.05). The thresholds for CBF and CBV can be applied to lesions with any admixture of tumor or treatment effect, enabling the identification of true tumor burden within enhancing lesions. This approach overcomes current limitations of averaging values from both tumor and TE for quantitative assessments.

Entities:  

Keywords:  ADC; Glioblastoma; MRI; Radiation necrosis; Treatment effect; rCBV

Mesh:

Substances:

Year:  2017        PMID: 28900832      PMCID: PMC5756123          DOI: 10.1007/s11060-017-2617-3

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  32 in total

1.  Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging.

Authors:  Hee Ho Chu; Seung Hong Choi; Inseon Ryoo; Soo Chin Kim; Jeong A Yeom; Hwaseon Shin; Seung Chai Jung; A Leum Lee; Tae Jin Yoon; Tae Min Kim; Se-Hoon Lee; Chul-Kee Park; Ji-Hoon Kim; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim
Journal:  Radiology       Date:  2013-10-28       Impact factor: 11.105

Review 2.  The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Authors:  David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison
Journal:  Acta Neuropathol       Date:  2016-05-09       Impact factor: 17.088

3.  Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR Imaging.

Authors:  Ramon F Barajas; Joanna J Phillips; Rupa Parvataneni; Annette Molinaro; Emma Essock-Burns; Gabriela Bourne; Andrew T Parsa; Manish K Aghi; Michael W McDermott; Mitchel S Berger; Soonmee Cha; Susan M Chang; Sarah J Nelson
Journal:  Neuro Oncol       Date:  2012-06-18       Impact factor: 12.300

4.  Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma.

Authors:  M A Prah; S M Stufflebeam; E S Paulson; J Kalpathy-Cramer; E R Gerstner; T T Batchelor; D P Barboriak; B R Rosen; K M Schmainda
Journal:  AJNR Am J Neuroradiol       Date:  2015-06-11       Impact factor: 3.825

5.  Standardization of relative cerebral blood volume (rCBV) image maps for ease of both inter- and intrapatient comparisons.

Authors:  Devyani Bedekar; Todd Jensen; Kathleen M Schmainda
Journal:  Magn Reson Med       Date:  2010-09       Impact factor: 4.668

6.  Intraaxial brain masses: MR imaging-based diagnostic strategy--initial experience.

Authors:  Riyadh N Al-Okaili; Jaroslaw Krejza; John H Woo; Ronald L Wolf; Donald M O'Rourke; Kevin D Judy; Harish Poptani; Elias R Melhem
Journal:  Radiology       Date:  2007-05       Impact factor: 11.105

7.  Pseudoprogression of glioblastoma after chemo- and radiation therapy: diagnosis by using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging with ferumoxytol versus gadoteridol and correlation with survival.

Authors:  Seymur Gahramanov; Leslie L Muldoon; Csanad G Varallyay; Xin Li; Dale F Kraemer; Rongwei Fu; Bronwyn E Hamilton; William D Rooney; Edward A Neuwelt
Journal:  Radiology       Date:  2012-11-30       Impact factor: 11.105

Review 8.  FSL.

Authors:  Mark Jenkinson; Christian F Beckmann; Timothy E J Behrens; Mark W Woolrich; Stephen M Smith
Journal:  Neuroimage       Date:  2011-09-16       Impact factor: 6.556

9.  Spiral Perfusion Imaging With Consecutive Echoes (SPICE™) for the Simultaneous Mapping of DSC- and DCE-MRI Parameters in Brain Tumor Patients: Theory and Initial Feasibility.

Authors:  Eric S Paulson; Douglas E Prah; Kathleen M Schmainda
Journal:  Tomography       Date:  2016-12

Review 10.  The diagnosis and treatment of pseudoprogression, radiation necrosis and brain tumor recurrence.

Authors:  Kashif Parvez; Aatif Parvez; Gelareh Zadeh
Journal:  Int J Mol Sci       Date:  2014-07-03       Impact factor: 5.923

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  16 in total

1.  Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project.

Authors:  K M Schmainda; M A Prah; S D Rand; Y Liu; B Logan; M Muzi; S D Rane; X Da; Y-F Yen; J Kalpathy-Cramer; T L Chenevert; B Hoff; B Ross; Y Cao; M P Aryal; B Erickson; P Korfiatis; T Dondlinger; L Bell; L Hu; P E Kinahan; C C Quarles
Journal:  AJNR Am J Neuroradiol       Date:  2018-05-24       Impact factor: 3.825

2.  Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies.

Authors:  J M Hoxworth; J M Eschbacher; A C Gonzales; K W Singleton; G D Leon; K A Smith; A M Stokes; Y Zhou; G L Mazza; A B Porter; M M Mrugala; R S Zimmerman; B R Bendok; D P Patra; C Krishna; J L Boxerman; L C Baxter; K R Swanson; C C Quarles; K M Schmainda; L S Hu
Journal:  AJNR Am J Neuroradiol       Date:  2020-03-12       Impact factor: 3.825

3.  Moving Toward a Consensus DSC-MRI Protocol: Validation of a Low-Flip Angle Single-Dose Option as a Reference Standard for Brain Tumors.

Authors:  K M Schmainda; M A Prah; L S Hu; C C Quarles; N Semmineh; S D Rand; J M Connelly; B Anderies; Y Zhou; Y Liu; B Logan; A Stokes; G Baird; J L Boxerman
Journal:  AJNR Am J Neuroradiol       Date:  2019-03-28       Impact factor: 3.825

4.  Imaging-Based Algorithm for the Local Grading of Glioma.

Authors:  E D H Gates; J S Lin; J S Weinberg; S S Prabhu; J Hamilton; J D Hazle; G N Fuller; V Baladandayuthapani; D T Fuentes; D Schellingerhout
Journal:  AJNR Am J Neuroradiol       Date:  2020-02-06       Impact factor: 3.825

5.  Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics.

Authors:  Ahmed Abdel Khalek Abdel Razek; Lamiaa El-Serougy; Mohamed Abdelsalam; Gada Gaballa; Mona Talaat
Journal:  Neuroradiology       Date:  2017-12-07       Impact factor: 2.804

6.  Guiding the first biopsy in glioma patients using estimated Ki-67 maps derived from MRI: conventional versus advanced imaging.

Authors:  Evan D H Gates; Jonathan S Lin; Jeffrey S Weinberg; Jackson Hamilton; Sujit S Prabhu; John D Hazle; Gregory N Fuller; Veera Baladandayuthapani; David Fuentes; Dawid Schellingerhout
Journal:  Neuro Oncol       Date:  2019-03-18       Impact factor: 12.300

7.  DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery.

Authors:  F Kuo; N N Ng; S Nagpal; E L Pollom; S Soltys; M Hayden-Gephart; G Li; D E Born; M Iv
Journal:  AJNR Am J Neuroradiol       Date:  2022-04-28       Impact factor: 4.966

Review 8.  Imaging of intratumoral heterogeneity in high-grade glioma.

Authors:  Leland S Hu; Andrea Hawkins-Daarud; Lujia Wang; Jing Li; Kristin R Swanson
Journal:  Cancer Lett       Date:  2020-02-27       Impact factor: 8.679

9.  Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas.

Authors:  Jerrold L Boxerman; Chad C Quarles; Leland S Hu; Bradley J Erickson; Elizabeth R Gerstner; Marion Smits; Timothy J Kaufmann; Daniel P Barboriak; Raymond H Huang; Wolfgang Wick; Michael Weller; Evanthia Galanis; Jayashree Kalpathy-Cramer; Lalitha Shankar; Paula Jacobs; Caroline Chung; Martin J van den Bent; Susan Chang; W K Al Yung; Timothy F Cloughesy; Patrick Y Wen; Mark R Gilbert; Bruce R Rosen; Benjamin M Ellingson; Kathleen M Schmainda
Journal:  Neuro Oncol       Date:  2020-09-29       Impact factor: 12.300

10.  Optimization of Acquisition and Analysis Methods for Clinical Dynamic Susceptibility Contrast MRI Using a Population-Based Digital Reference Object.

Authors:  N B Semmineh; L C Bell; A M Stokes; L S Hu; J L Boxerman; C C Quarles
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-11       Impact factor: 3.825

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