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Black, Peter

The diagnosis of idiopathic normal pressure hydrocephalus (iNPH) is still challenging. Alzheimer's disease (AD), along with vascular dementia, the most important differential diagnosis for iNPH, has several potential cerebrospinal fluid (CSF) biomarkers which might help in the selection of patients for shunt treatment. The aim of this study was to compare a battery of CSF biomarkers including well-known AD-related proteins with CSF from patients with suspected iNPH collected from the external lumbar drainage test (ELD). A total of 35 patients with suspected iNPH patients were evaluated with ELD. CSF was collected in the beginning of the test, and the concentrations of total tau, ptau181, Aβ42, NFL, TNF-α, TGFβ1, and VEGF were analysed by ELISA. Twenty-six patients had a positive ELD result—that is, their gait symptoms improved; 9 patients had negative ELD. The levels of all analyzed CSF biomarkers were similar between the groups and none of them predicted the ELD result in these patients. Contrary to expectations lumbar CSF TNF-α concentration was low in iNPH patients.

Gliomas frequently display constitutive activation of the transcription factor STAT3, a protein that is known to be able to mediate neoplastic transformation. STAT3 regulates genes that play a central role in cellular survival, proliferation, self-renewal, and invasion, and a cohort of STAT3 target genes have been found that are commonly coexpressed in human cancers. Thus, these genes likely subserve the transforming ability of constitutively activated STAT3. To determine whether the coordinated expression of STAT3 target genes is present in a subset of human gliomas, and whether this changes the biology of these tumors in patients, gene expression analysis was performed in four distinct human glioma data sets for which patient survival information was available. Coordinate expression of STAT3 targets was significantly associated with poor patient outcome in each data set. Specifically, patients with tumors displaying high expression of STAT3 targets had a shorter median survival time compared to patients whose tumors had low expression of STAT3 targets. These data suggest that constitutively activated STAT3 in gliomas can alter the biology of these tumors, and that development of targeted STAT3 inhibitors would likely be of particular benefit in treatment of this disease.

The non-essential amino acid neurotransmitter glycine (Gly) may serve as a biomarker for brain tumors. Using 36 biopsies from patients with brain tumors [12 glioblastoma multiforme (GBM); 10 low-grade (LG), including 7 schwannoma and 3 pylocytic astrocytoma; 7 meningioma (MN); 7 brain metastases (MT), including 3 adenocarcinoma and 4 breast cancer] and 9 control biopsies from patients undergoing surgery for epilepsy, we tested the hypothesis that the presence of glycine may distinguish among these brain tumor types. Using high-resolution magic angle spinning (HRMAS) 1H magnetic resonance spectroscopy (MRS), we determined a theoretically optimum echo time (TE) of 50 ms for distinguishing Gly signals from overlapping myo-inositol (Myo) signals and tested our methodology in phantom and biopsy specimens. Quantitative analysis revealed higher levels of Gly in tumor biopsies (all combined) relative to controls; Gly levels were significantly elevated in LG, MT and GBM biopsies (P≤0.05). Residual Myo levels were elevated in LG and MT and reduced in MN and GBM (P<0.05 vs. control levels). We observed higher levels of Gly in GBM as compared to LG tumors (P=0.05). Meanwhile, although Gly levels in GBM and MT did not differ significantly from each other, the Gly:Myo ratio did distinguish GBM from MT (P<0.003) and from all other groups, a distinction that has not been adequately made previously. We conclude from these findings that Gly can serve as a biomarker for brain tumors and that the Gly:Myo ratio may be a useful index for brain tumor classification.

BACKGROUND: Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies. OBJECTIVE: This article describes a semiautomatic monitoring approach using longitudinal medical images. We test the method on brain scans of patients with meningioma, which experts have found difficult to monitor because the tumor evolution is very slow and may be obscured by artifacts related to image acquisition. METHODS: We describe a semiautomatic procedure targeted toward identifying difficult-to-detect changes in brain tumor imaging. The tool combines input from a medical expert with state-of-the-art technology. The software is easy to calibrate and, in less than 5 minutes, returns the total volume of tumor change in mm. We test the method on postgadolinium, T1-weighted magnetic resonance images of 10 patients with meningioma and compare our results with experts' findings. We also perform benchmark testing with synthetic data. RESULTS: Our experiments indicated that experts' visual inspections are not sensitive enough to detect subtle growth. Measurements based on experts' manual segmentations were highly accurate but also labor intensive. The accuracy of our approach was comparable to the experts' results. However, our approach required far less user input and generated more consistent measurements. CONCLUSION: The sensitivity of experts' visual inspection is often too low to detect subtle growth of meningiomas from longitudinal scans. Measurements based on experts' segmentation are highly accurate but generally too labor intensive for standard clinical settings. We described an alternative metric that provides accurate and robust measurements of subtle tumor changes while requiring a minimal amount of user input.

Low grade tumors are associated with a high risk of seizures. Prolonged use of antiepileptic drugs (AEDs) is associated with morbidity. Determining which patients can safely discontinue AEDs perioperatively is difficult. We examined patients with low grade supratentorial brain tumors to determine characteristics of patients who underwent AED withdrawal. A retrospective chart review was performed in patients who underwent resection between 1/1/2004 and 12/31/2005 at a single center. Data were collected regarding the use of postoperative AEDs, occurrence of postoperative seizures, and patient/tumor characteristics. We examined 169 patients with a median follow-up of 3.1 years. AEDs were withdrawn or never started in 111 patients; post-withdrawal seizures occurred in 11 (9.9%). The rate was similar between meningiomas and primary brain tumors. No independent risk factors for post-withdrawal seizures were found. Of 58 patients whose AEDs were not withdrawn, postoperative seizures occurred in 28 (48%). Predictors of AED continuation included existence of preoperative seizures, temporal tumor location, tumor recurrence, incomplete resection, and male sex. The decision to continue AEDs was predictive for postoperative seizures even after controlling for known risk factors. Although clinicians are able to identify patients at high risk for postoperative seizures, treatment with AEDs is ineffective in many patients.

Objective: To quantify size and localization differences between tumors presenting with seizures vs nonseizure neurological symptoms. Design: Retrospective imaging survey. We performed magnetic resonance imaging–based morphometric analysis and nonparametric mapping in patients with brain tumors. Setting: University-affiliated teaching hospital. Patients or Other Participants: One hundred twenty-four patients with newly diagnosed supratentorial glial tumors. Main Outcome Measures: Volumetric and mapping methods were used to evaluate differences in size and location of the tumors in patients who presented with seizures as compared with patients who presented with other symptoms. Results: In high-grade gliomas, tumors presenting with seizures were smaller than tumors presenting with other neurological symptoms, whereas in low-grade gliomas, tumors presenting with seizures were larger. Tumor location maps revealed that in high-grade gliomas, deep-seated tumors in the pericallosal regions were more likely to present with nonseizure neurological symptoms. In low-grade gliomas, tumors of the temporal lobe as well as the insular region were more likely to present with seizures. Conclusions: The influence of size and location of the tumors on their propensity to cause seizures varies with the grade of the tumor. In high-grade gliomas, rapidly growing tumors, particularly those situated in deeper structures, present with non–seizure-related symptoms. In low-grade gliomas, lesions in the temporal lobe or the insula grow large without other symptoms and eventually cause seizures. Quantitative image analysis allows for the mapping of regions in each group that are more or less susceptible to seizures. Seizures are encountered in a majority of patients with primary brain tumors and are a major cause of morbidity in these patients.1,2 Thirty percent to 50% of patients experience a seizure by the time their tumors are diagnosed, and an additional 6% to 45% of patients who do not initially present with seizures eventually develop them.3- 5 Characteristics of brain tumors and their mechanism in causing seizures in patients are incompletely understood.4,6 Low-grade, well-differentiated gliomas,1,6- 9 cortically located tumors,3,10- 14 and location in the temporal/frontal and motor/sensory cortices6,8,15- 17 are more frequently associated with seizures. Although there is a high incidence of seizures in these patients, treatment strategies remain poorly defined. Prophylactic anticonvulsant therapy, shown to be ineffective in preventing seizures in patients with brain tumors in multiple large-scale studies,12,18- 20 is not recommended by the American Academy of Neurology.5 Nonetheless, prophylaxis remains a widespread practice21 because of difficulty in determining which patients are at greatest risk for seizures. Determination of morphometric factors influencing seizures would help in identifying patients at greatest risk for early, targeted treatment and prevent potentially toxic, unnecessary treatment in patients at minimal risk. Although studies examining brain tumors in relationship to epilepsy have localized tumors to a particular lobe,10 few studies have performed quantitative volumetric or spatial mapping analysis of tumors in relation to their epileptogenic potential. Regions within a particular lobe are likely to exhibit different epileptogenic potential to tumor invasion and tumors frequently affect multiple contiguous lobes.6 Modern imaging techniques allow for analysis of lesions over a large group of subjects through registration and mapping techniques. In this study, we used these techniques to examine the size and location of primary supratentorial glial brain tumors and characterized their propensity to cause seizures at presentation.

The present studies investigated the expression of the two PDGF genes (c-sis/PDGF-2 and PDGF-1) and the PDGF-receptor b gene (PDGF-R) in 34 primary human astrocytomas. Northern blot analysis demonstrated the coexpression of the c-sis/PDGF-2 protooncogene and the PDGF-R gene in all astrocytomas examined. The majority of the tumors also expressed the PDGF-1 gene. There was no correlation between the expression of the two PDGF genes. Nonmalignant human brain tissue expressed the PDGF-R and PDGF-1 genes but not the c-sis/PDGF-2 protooncogene. In situ hybridization of astrocytoma tissue localized the expression of the c-sis and PDGF-R mRNA's in tumor cells. Capillary endothelial cells also expressed c-sis mRNA. In contrast, nonmalignant human brain tissue expressed only PDGF-R mRNA but not c-sis/PDGF-2 mRNA. The coexpression of a potent mitogenic growth factor protooncogene (c-sis) and its receptor gene in astrocytoma tumor cells suggests the presence of an autocrine mechanism that may contribute to the development and maintenance of astrocytomas. The expression of c-sis mRNA in tumor cells but not in nonmalignant brain cells may serve as an additional diagnostic criterion for the detection of astrocytomas in small tissue specimen using in situ hybridization for the detection of c-sis mRNA and/or immunostaining for the recognition of its protein product.

Meningiomas account for approximately 30% of all primary central nervous system tumors and are found in half of neurofibromatosis type 2 patients often causing significant morbidity. Although most meningiomas are benign, 10% are classified as atypical or anaplastic, displaying aggressive clinical behavior. Biallelic inactivation of the neurofibromatosis 2 (NF2) tumor suppressor is associated with meningioma formation in all NF2 patients and 60% of sporadic meningiomas. Deletion of the p16INK4a/p14ARF locus is found in both benign and malignant meningiomas, while mutation of the p53 tumor suppressor gene is uncommon. Previously, we inactivated Nf2 in homozygous conditional knockout mice by adenoviral Cre delivery and showed that Nf2 loss in arachnoid cells is rate-limiting for meningioma formation. Here, we report that additional nullizygosity for p16Ink4a increases the frequency of meningioma and meningothelial proliferation in these mice without modifying the tumor grade. In addition, by using magnetic resonance imaging (MRI) to screen a large cohort of mutant mice, we were able to detect meningothelial proliferation and meningioma development opening the way to future studies in which therapeutic interventions can be tested as preclinical assessment of their potential clinical application.

Our purpose was to develop temperature sensitive MR sequences and image-processing techniques to asses their potential of monitoring interstitial laser therapy (ILT) in brain tumors (n = 3) and liver tumors (n = 7). ILT lasted 2 to 26 minutes, while images from T1-weighted Fast-Spin-Echo (FSE)- or Spoiled Gradient-Recalled (SPGR) sequences were acquired within 5 - 13 seconds.

Pixel subtraction and visualization of T1-weighted images or optical flow computation was done within less than 110 msec. Alternating, phase-mapping of real- and imaginary components of SPGR sequences was performed within 220 msec.

Pixel subtraction of T1-weighted images identified thermal changes in liver and brain tumors but could not evaluate the temperature values as chemical-shift based imaging, which was however, more affected by susceptibility effects and motion. Optical flow computation displayed the predicted course of thermal changes and revealed that the rate of heat deposition can be anisotropic, which may be related to heterogeneous tumor structure and/or vascularization.