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J Neurooncol. 2018 Jan;136(1):13-21. doi: 10.1007/s11060-017-2617-3. Epub 2017 Sep 12.

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

Author information

1
Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA.
2
Department of Neurosurgery, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA.
3
Department of Pathology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA.
4
Department of Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA.
5
Department of Neurology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA.
6
Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA. kathleen@mcw.edu.
7
Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA. kathleen@mcw.edu.

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.

KEYWORDS:

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

PMID:
28900832
PMCID:
PMC5756123
[Available on 2019-01-01]
DOI:
10.1007/s11060-017-2617-3

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