Volumetric analysis of functional diffusion maps is a predictive imaging biomarker for cytotoxic and anti-angiogenic treatments in malignant gliomas.

Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee, WI, USA.
Journal of Neuro-Oncology (Impact Factor: 2.79). 03/2011; 102(1):95-103. DOI: 10.1007/s11060-010-0293-7
Source: PubMed

ABSTRACT Anti-angiogenic agents targeting brain tumor neovasculature may increase progression-free survival in patients with recurrent malignant gliomas. However, when these patients do recur it is not always apparent as an increase in enhancing tumor volume on MRI, which has been the standard of practice for following patients with brain tumors. Therefore alternative methods are needed to evaluate patients treated with these novel therapies. Furthermore, a method that can also provide useful information for the evaluation of conventional therapies would provide an important advantage for general applicability. Diffusion-weighted magnetic resonance imaging (DWI) has the potential to serve as a valuable biomarker for these purposes. In the current study, we explore the prognostic ability of functional diffusion maps (fDMs), which examine voxel-wise changes in the apparent diffusion coefficient (ADC) over time, applied to regions of fluid-attenuated inversion recovery (FLAIR) abnormalities in patients with malignant glioma, treated with either anti-angiogenic or cytotoxic therapies. Results indicate that the rate of change in fDMs is an early predictor of tumor progression, time to progression and overall survival for both treatments, suggesting the application of fDMs in FLAIR abnormal regions may be a significant advance in brain tumor biomarker technology.

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    ABSTRACT: RATIONALE AND OBJECTIVES To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms. MATERIALS AND METHODS Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration–approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared. RESULTS For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT. CONCLUSIONS Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.
    Academic Radiology 08/2014; 21(10). DOI:10.1016/j.acra.2014.05.016 · 2.08 Impact Factor
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    ABSTRACT: To evaluate metrics that describe changes in apparent diffusion coefficient (ADC) and to examine their association with clinical outcome for patients with newly diagnosed GBM who were participating in a Phase II clinical trial of treatment with radiation (RT), temozolomide, erlatonib and bevacizumab. Thirty six patients were imaged after surgery but prior to therapy and at regular follow-up time points. The following ADC metrics were evaluated: (1) histogram percentiles within the T2-hyperintense lesion (T2L) at serial follow-ups; (2) parameters obtained by fitting a two-mixture normal distribution to the histogram within the contrast-enhancing lesion (CEL) at baseline; (3) parameters obtained using both traditional and graded functional diffusion maps within the CEL and T2L. Cox Proportional Hazards models were employed to assess the association of the ADC parameters with overall survival (OS) and progression-free survival (PFS). A lower ADC percentile value within the T2L at early follow-up time points was associated with worse outcome. Of particular interest is that, even when adjusting for clinical prognostic factors, the ADC10% within the T2L at 2 months was strongly associated with OS (p < 0.001) and PFS (p < 0.007). fDM metrics showed an association with OS and PFS within the CEL when considered by univariate analysis, but not in the T2L. Our study emphasizes the value of ADC metrics obtained from the T2L at the post-RT time point as non-invasive biomarkers for assessing residual tumor in patients with newly diagnosed GBM being treated with combination therapy that includes the anti-angiogenic agent bevacizumab.
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    ABSTRACT: Gliomas comprise 80% of primary brain neoplasms, with glioblastoma multiforme being the most commonly diagnosed glioma. The annual incidence is 5.26 per 100,000, or 17,000 newly diagnosed cases per year in the United States. The incidence increases with age, peaking between the 6th and 8th decades. Gliomas are more common among Caucasians and occur more often in men. They can be associated with certain rare hereditary syndromes including Cowden, Turcot, Li-Fraumeni, neurofibromatosis type 1 and type 2, tuberous sclerosis, and familial schwannomatosis. Known risk factors include a history of ionizing radiation, family history of glioma, and certain genetic susceptibility variants that are weakly associated with glioma. Preventative measures have not been shown to decrease the risk of later development. In addition, screening tests are unwarranted since early diagnosis and treatment have not been shown to improve outcome.
    Seminars in Oncology 08/2014; 41(4):478-495. DOI:10.1053/j.seminoncol.2014.06.006 · 3.94 Impact Factor

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Benjamin Ellingson