Christopher E. Benton

Low-Grade Gliomas: Six-month Tumor Growth Predicts Patient Outcome Better than Admission Tumor Volume, Relative Cerebral Blood Volume, and Apparent Diffusion Coefficient

PURPOSE To prospectively compare tumor volume, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) and short-term changes of these parameters as predictors of time to malignant transformation and time to death in patients with low-grade gliomas (LGGs). MATERIALS AND METHODS Patients gave written informed consent for this institutional ethics committee-approved study. Patients with histologically proved LGGs underwent conventional, perfusion-weighted, and diffusion-weighted magnetic resonance (MR) imaging at study entry and at 6 months. At both time points, tumor volume, maximum rCBV, and ADC histogram measures were calculated. Patient follow-up consisted of MR imaging every 6 months and clinical examinations. To investigate the association between MR imaging variables and time to progression and time to death, a Cox regression curve was applied at study entry and at 6 months. The models were corrected for age, sex, and histologic findings. RESULTS Thirty-four patients (22 men, 12 women; mean age, 42 years) with histologically proved LGGs (eight oligodendrogliomas, 20 astrocytomas, and six oligoastrocytomas) were followed up clinically and radiologically for a median of 2.6 years (range, 0.4-5.5 years). Tumor growth over the course of 6 months was the best predictor of time to transformation, independent of rCBV, diffusion histogram parameters, age, sex, and histologic findings. When only single-time-point measurements were compared, tumor volume helped predict outcome best and was the only independent predictor of time to death (P < .02). CONCLUSION Six-month tumor growth helps predict outcome in patients with LGG better than parameters derived from perfusion- or diffusion-weighed MR imaging. Tumor growth can readily be calculated from volume measurements on images acquired with standard MR imaging protocols and may well prove most useful among various MR imaging findings in clinical practice.

Relative cerebral blood volume measurements of low-grade gliomas predict patient outcome in a multi-institution setting

BACKGROUND/PURPOSE The prognostic value of defining subcategories of gliomas is still controversial. This study aims to determine the utility of relative cerebral blood volume (rCBV) in predicting clinical response in patients with low-grade glioma at multiple institutions. MATERIALS AND METHODS Sixty-nine patients were studied with dynamic susceptibility contrast-enhanced perfusion MRI at two institutions. The pathologic diagnoses of the low-grade gliomas were 34 astrocytomas, 20 oligodendroglioma, 9 oligoastrocytomas, 1 ganglioglioma and 5 with indeterminate histology. Wilcoxon tests were used to compare patients in different response categories with respect to baseline rCBV. Kaplan-Meier curve and log-rank tests were used to predict the association of rCBV with time to progression. RESULTS At both institutions, patients with an adverse event (progressive disease or death) had a significantly higher baseline rCBV than those without (complete response or stable disease) (p value=0.0138). The odds ratio for detecting an adverse event when using rCBV was 1.87 (95% confidence interval: 1.14-3.08). rCBV was significantly negatively associated with time to progression (p=0.005). The median time to progression among subjects with rCBV>1.75 was 365 days, while there was 95% confidence that the median time to progression was at least 889 days among subjects with rCBV<1.75. CONCLUSION Our study suggests not only that rCBV measurements correlate well with time to progression or death, but also that the findings can be replicated across institutions, which supports the application of rCBV as an adjunct to pathology in predicting glioma biology.

Quantitative Analysis of Whole-Tumor Gd Enhancement Histograms Predicts Malignant Transformation in Low-Grade Gliomas

To quantify subtle gadolinium (Gd) enhancement (signal increase) in whole‐tumor histograms and optimize their ability to predict subsequent malignant transformation in low‐grade gliomas (LGGs).

Inclusion or exclusion of intratumoral vessels in relative cerebral blood volume characterization in low-grade gliomas: does it make a difference?

SUMMARY: We assessed the influence of inclusion (method 1) and exclusion (method 2) of intratumoral vessels when determining maximum relative cerebral blood volume (rCBVmax) in 3 types of low-grade gliomas (LGGs): astrocytomas, oligoastrocytomas, and oligodendrogliomas. Method 1 yielded significantly higher mean rCBVmax than method 2. However, only method 2 demonstrated a significant (P = .026) association between rCBVmax and membership of a differently ranked histologic category. Exclusion of intratumoral vessels appears, therefore, preferable when determining rCBVmax in LGGs.

Quantitative magnetisation transfer imaging in glioma: preliminary results

Quantitative magnetisation transfer imaging (qMTI) is an extension of conventional MT techniques and allows the measurement of parameters that reflect tissue ultrastructure through the properties of macromolecule‐bound protons; these include the bound proton fraction and the relaxation times of free and bound proton pools. It has been used in multiple sclerosis and Alzheimers disease, and has shown changes in some of the parameters, particularly the bound proton fraction. The purpose of this pilot study was to assess whether qMTI could distinguish between gliomas and normal brain tissue, and provide proof of principle for its use in tumour characterisation. Eight subjects [three men, five women; mean age, 44 years; range, 27–66 years; seven World Health Organization (WHO) Grade II, one Grade III] with biopsy‐proven glioma were imaged with a structural MRI protocol that included three‐dimensional qMTI. qMTI parameters were extracted from regions of interest selected from different tumour components visible on conventional MR sequences, normal‐appearing peritumoral tissue and distant normal‐appearing white matter. All patients gave informed consent and the study was approved by the Local Research Ethics Committee. Almost all of the qMTI parameters detected abnormalities in both glioma and the peritumoral region relative to the distant white matter. In particular, the bound proton fraction was reduced significantly from 6.0 percentage units (pu) [standard deviation (SD), 0.5 pu] in normal‐appearing white matter to 1.7 pu (SD = 0.5 pu) in solid tumour and 2.2 pu (SD = 0.5 pu) in peritumoral areas. This work shows that qMTI reveals abnormalities, not only in glioma, but also in the apparently normal tissue surrounding the conventionally defined tumour. Thus, qMTI shows promise for tumour characterisation and for studying tumour boundaries. These preliminary data justify larger studies in a range of different tumour types and grades. Copyright