Faculty Bibliography

BACKGROUND AND PURPOSE: Integration of imaging and genomic data is critical for a better understanding of gliomas, particularly considering the increasing focus on the use of imaging biomarkers for patient survival and treatment response. The purpose of this study was to correlate CBV and PS measured by using PCT with the genes regulating angiogenesis in GBM. MATERIALS AND METHODS: Eighteen patients with WHO grade IV gliomas underwent pretreatment PCT and measurement of CBV and PS values from enhancing tumor. Tumor specimens were analyzed by TCGA by using Human Gene Expression Microarrays and were interrogated for correlation between CBV and PS estimates across the genome. We used the GO biologic process pathways for angiogenesis regulation to select genes of interest. RESULTS: We observed expression levels for 92 angiogenesis-associated genes (332 probes), 19 of which had significant correlation with PS and 9 of which had significant correlation with CBV (P < .05). Proangiogenic genes such as TNFRSF1A (PS = 0.53, P = .024), HIF1A (PS = 0.62, P = .0065), KDR (CBV = 0.60, P = .0084; PS = 0.59, P = .0097), TIE1 (CBV = 0.54, P = .022; PS = 0.49, P = .039), and TIE2/TEK (CBV = 0.58, P = .012) showed a significant positive correlation; whereas antiangiogenic genes such as VASH2 (PS = -0.72, P = .00011) showed a significant inverse correlation. CONCLUSIONS: Our findings are provocative, with some of the proangiogenic genes showing a positive correlation and some of the antiangiogenic genes showing an inverse correlation with tumor perfusion parameters, suggesting a molecular basis for these imaging biomarkers; however, this should be confirmed in a larger patient population.

We have tested the predictive value of apparent diffusion coefficient (ADC) histogram analysis in stratifying progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients with recurrent glioblastoma multiforme (GBM) from the multi-center BRAIN study. Available MRI's from patients enrolled in the BRAIN study (n = 97) were examined by generating ADC histograms from areas of enhancing tumor on T1 weighted post-contrast images fitted to a two normal distribution mixture curve. ADC classifiers including the mean ADC from the lower curve (ADC-L) and the mean lower curve proportion (LCP) were tested for their ability to stratify PFS and OS by using Cox proportional hazard ratios and the Kaplan-Meier method with log-rank test. Mean ADC-L was 1,209 x 10(-6)mm(2)/s +/- 224 (SD), and mean LCP was 0.71 +/- 0.23 (SD). Low ADC-L was associated with worse outcome. The hazard ratios for 6-month PFS, overall PFS, and OS in patients with less versus greater than mean ADC-L were 3.1 (95 % confidence interval: 1.6, 6.1; P = 0.001), 2.3 (95 % CI: 1.3, 4.0; P = 0.002), and 2.4 (95 % CI: 1.4, 4.2; P = 0.002), respectively. In patients with ADC-L <1,209 and LCP >0.71 versus ADC-L >1,209 and LCP <0.71, there was a 2.28-fold reduction in the median time to progression, and a 1.42-fold decrease in the median OS. The predictive value of ADC histogram analysis, in which low ADC-L was associated with poor outcome, was confirmed in bevacizumab-treated patients with recurrent GBM in a post hoc analysis from the multi-center (BRAIN) study.

Acute calcific longus colli tendinitis (LCT) has been reported as an unusual cause of acute-onset neck pain, dysphagia, and headache.(1-5) As described in most of the published reports, LCT traditionally manifests on computed tomography (CT) imaging as paramidline calcium hydroxyapatite crystal deposits anterior to the C1 and C2 vertebral bodies. However, recent studies have brought attention to the disease existing at the C4-C5 and C5-C6 levels.(6,7) Acute LCT is considered relatively benign, typically resolving on its own within several weeks.

Distinguishing tumor progression from radiation necrosis after treatment in patients with brain tumors presents a clinical dilemma. A well-characterized, orthotopic rodent model of radiation-induced brain necrosis including a tumor is not currently available The objective of the study was to create focal radiation necrosis in rat brain bearing human glioblastoma (GBM) using stereotactic radiosurgery and confirm it by immuno-histological analysis. Nude rats implanted with primary GBM cells were irradiated using a stereotactic setup (n = 3) or received no radiation (n = 3). Ten weeks after the implantation, growth of the tumor was confirmed by magnetic resonance imaging (MRI). For each animal, MRI and contrast-enhanced CT images were obtained and fused using registration software. The tumor was identified and delineated using the fused CT/MR images. A treatment plan was generated using a 4 mm radiosurgery cone such that one portion of the tumor receives 100% dose of 60 Gy sufficient to cause necrosis, whereas the tumor edge at depth receives only 50% or less dose, allowing for regrowth of the tumor. The brains were collected 10 weeks after irradiation and immuno-histological analysis was performed. Hematoxylin and eosin staining showed central liquefaction necrosis in the high dose region consistent with necrosis and viable tumor in the peripheral low dose region. Ki-67 staining showed highly proliferative tumor cells surrounding the necrotic parts of the tumor. Luxol fast blue and lectin staining showed demyelination and vascular injury in brain tissue consistent with radiation necrosis. We have developed a novel model of radiation necrosis in rats bearing glioma.

Dynamic contrast enhanced T(1)-weighted MRI using the contrast agent gadopentetate dimeglumine (Gd-DTPA) was performed on 10 patients with glioblastoma. Nested models with as many as three parameters were used to estimate plasma volume or plasma volume and forward vascular transfer constant (K(trans)) and the reverse vascular transfer constant (k(ep)). These constituted models 1, 2, and 3, respectively. Model 1 predominated in normal nonleaky brain tissue, showing little or no leakage of contrast agent. Model 3 predominated in regions associated with aggressive portions of the tumor, and model 2 bordered model 3 regions, showing leakage at reduced rates. In the patient sample, v(p) was about four times that of white matter in the enhancing part of the tumor. K(trans) varied by a factor of 10 between the model 2 (1.9 <--> 10(-3) min(-1)) and model 3 regions (1.9 <--> 10(-2) min(-1)). The mean calculated interstitial space (model 3) was 5.5%. In model 3 regions, excellent curve fits were obtained to summarize concentration-time data (mean R(2) = 0.99). We conclude that the three parameters of the standard model are sufficient to fit dynamic contrast enhanced T(1) data in glioblastoma under the conditions of the experiment.

Malignant gliomas are often very heterogeneous tumors with complex vasculature, frequently exhibiting angiogenesis and increased vascular permeability. In vivo measurement of the tumor vessel permeability can serve as a potential imaging biomarker to assess tumor grade and aggressiveness. It can also be used to study the response of tumors to various therapies, especially antiangiogenic therapy. Central to the concept of permeability is a thorough knowledge of the BBB and its role in brain tumors and angiogenesis. Much work has been done in the past to understand the structural/molecular composition of the BBB and the role it plays in various pathologic processes, including brain tumors. Various imaging techniques have also been used to evaluate BBB leakiness in brain tumors because higher tumor vascular leakiness is known to be associated with higher grade and malignant potential of the tumor and hence poor patient prognosis. These imaging techniques range from routine postcontrast T1-weighted images to measurement of vascular permeability using various quantitative or semiquantitative indices based on multicompartment pharmacokinetic models. The purpose of this article is to discuss BBB anatomy; various clinically available imaging techniques to evaluate tumor vascular leakiness (perfusion imaging), including their advantages and limitations; as well as a brief discussion of the clinical utility of measuring vascular permeability in brain tumors. We will also discuss the various permeability-related indices along with the pharmacokinetic models to simplify the "nomenclature soup."

BACKGROUND: This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. METHODS: Nineteen patients with histologically confirmed treatment naive glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. RESULTS: Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. CONCLUSIONS: The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity).

INTRODUCTION: Meningiomas are typically slow-growing lesions that, depending on the location, can be relatively benign. Knowing their exact rate of growth can be helpful in determining whether surgery is necessary. METHODS: In this study we retrospectively reviewed the meningioma practices of the two senior authors (JR, MR). Our goal was to measure meningioma growth using a variety of methods (linear using diameters, and volumetric using the computer-aided perimeter and cross-sectional diameter methods) to compare rates of growth among the methods. Of 295 meningioma patients seen over an 8-year period, we identified a cohort of 31 patients with at least 30 months of follow-up. Volumes were calculated using medical imaging software with T1 post-contrast magnetic resonance imaging. Doubling times and growth rates were calculated. RESULTS: Of the 31 patients, 26 (84%) were shown to have growing meningiomas. The perimeter methodology measured higher growth rates than the diameter method for both doubling times as well as percentage annual growth (p<0.01). The mean doubling time was 13.4 years (range, 2.1-72.8 years) and 17.9 years (range, 4-92.3 years) comparing perimeter and diameter methods, respectively. The mean percentage of annual growth was 15.2% (range, 1.8-61.7%) and 5.6% (range, 0.7-12.2%), comparing perimeter and diameter methods, respectively. Linear growth was calculated at 0.7 mm/year. CONCLUSION: Overall, we found that computer-aided perimeter methods showed a more accurate picture of tumor progression than traditional methods, which generally underestimated growth.