Multi-faceted computational assessment of risk and progression in oligodendroglioma implicates NOTCH and PI3K pathways

Oligodendrogliomas are diffusely infiltrative gliomas defined by IDH-mutation and co-deletion of 1p/19q. They have highly variable clinical courses, with survivals ranging from 6 months to over 20 years, but little is known regarding the pathways involved with their progression or optimal markers for stratifying risk. We utilized machine-learning approaches with genomic data from The Cancer Genome Atlas to objectively identify molecular factors associated with clinical outcomes of oligodendroglioma and extended these findings to study signaling pathways implicated in oncogenesis and clinical endpoints associated with glioma progression. Our multi-faceted computational approach uncovered key genetic alterations associated with disease progression and shorter survival in oligodendroglioma and specifically identified Notch pathway inactivation and PI3K pathway activation as the most strongly associated with MRI and pathology findings of advanced disease and poor clinical outcome. Our findings that Notch pathway inactivation and PI3K pathway activation are associated with advanced disease and survival risk will pave the way for clinically relevant markers of disease progression and therapeutic targets to improve clinical outcomes. Furthermore, our approach demonstrates the strength of machine learning and computational methods for identifying genetic events critical to disease progression in the era of big data and precision medicine.

Is there added value in obtaining cervical spine MRI in the assessment of nontraumatic angiographically negative subarachnoid hemorrhage? A retrospective study and meta-analysis of the literature

OBJECTIVE Diagnostic algorithms for nontraumatic angiographically negative subarachnoid hemorrhage (AN-SAH) vary, and the optimal method remains subject to debate. This study assessed the added value of cervical spine MRI in identifying a cause for nontraumatic AN-SAH. METHODS Consecutive patients 18 years of age or older who presented with nontraumatic SAH between February 1, 2009, and October 31, 2014, with negative cerebrovascular catheter angiography and subsequent cervical MRI were studied. Patients with intraparenchymal, subdural, or epidural hemorrhage; recent trauma; or known vascular malformations were excluded. All cervical MR images were reviewed by two blinded neuroradiologists. The diagnostic yield of cervical MRI was calculated. A literature review was conducted to identify studies reporting the diagnostic yield of cervical MRI in patients with AN-SAH. The weighted pooled estimate of diagnostic yield of cervical MRI was calculated. RESULTS For all 240 patients (mean age 53 years, 48% male), catheter angiography was performed within 4 days after admission (median 12 hours, interquartile range [IQR] 10 hours). Cervical MRI was performed within 19 days of admission (median 24 hours, IQR 10 hours). In a single patient, cervical MRI identified a source for SAH (cervical vascular malformation). Meta-analysis of 7 studies comprising 538 patients with AN-SAH produced a pooled estimate of 1.3% (95% confidence interval 0.5%-2.5%) for diagnostic yield of cervical MRI. No statistically significant between-study heterogeneity or publication bias was identified. CONCLUSIONS Cervical MRI following AN-SAH, in the absence of findings to suggest spinal etiology, has a very low diagnostic yield and is not routinely necessary.

Semi-Automated Volumetric and Morphological Assessment of Glioblastoma Resection with Fluorescence-Guided Surgery

PURPOSE

Glioblastoma (GBM) neurosurgical resection relies on contrast-enhanced MRI-based neuronavigation. However, it is well-known that infiltrating tumor extends beyond contrast enhancement. Fluorescence-guided surgery (FGS) using 5-aminolevulinic acid (5-ALA) was evaluated to improve extent of resection (EOR) of GBMs. Preoperative morphological tumor metrics were also assessed.

PROCEDURES

Thirty patients from a phase II trial evaluating 5-ALA FGS in newly diagnosed GBM were assessed. Tumors were segmented preoperatively to assess morphological features as well as postoperatively to evaluate EOR and residual tumor volume (RTV).

RESULTS

Median EOR and RTV were 94.3 % and 0.821 cm(3), respectively. Preoperative surface area to volume ratio and RTV were significantly associated with overall survival, even when controlling for the known survival confounders.

CONCLUSIONS

This study supports claims that 5-ALA FGS is helpful at decreasing tumor burden and prolonging survival in GBM. Moreover, morphological indices are shown to impact both resection and patient survival.

Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma

BACKGROUND AND PURPOSE

Lower grade gliomas (LGGs), lesions of WHO grades II and III, comprise 10-15% of primary brain tumors. In this first-of-a-kind study, we aim to carry out a radioproteomic characterization of LGGs using proteomics data from the TCGA and imaging data from the TCIA cohorts, to obtain an association between tumor MRI characteristics and protein measurements. The availability of linked imaging and molecular data permits the assessment of relationships between tumor genomic/proteomic measurements with phenotypic features.

MATERIALS AND METHODS

Multiple-response regression of the image-derived, radiologist scored features with reverse-phase protein array (RPPA) expression levels generated correlation coefficients for each combination of image-feature and protein or phospho-protein in the RPPA dataset. Significantly-associated proteins for VASARI features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis was used to determine which feature groups were most strongly correlated with pathway activity and cellular functions.

RESULTS

The multiple-response regression approach identified multiple proteins associated with each VASARI imaging feature. VASARI features were found to be correlated with expression of IL8, PTEN, PI3K/Akt, Neuregulin, ERK/MAPK, p70S6K and EGF signaling pathways.

CONCLUSION

Radioproteomics analysis might enable an insight into the phenotypic consequences of molecular aberrations in LGGs.

Yield of computed tomography of the cervical spine in cases of simple assault

BACKGROUND

Computed tomography (CT) of the cervical spine (C-spine) is routinely ordered for low-impact, non-penetrating or "simple" assault at our institution and others. Common clinical decision tools for C-spine imaging in the setting of trauma include the National Emergency X-Radiography Utilization Study (NEXUS) and the Canadian Cervical Spine Rule for Radiography (CCR). While NEXUS and CCR have served to decrease the amount of unnecessary imaging of the C-spine, overutilization of CT is still of concern.

METHODS

A retrospective, cross-sectional study was performed of the electronic medical record (EMR) database at an urban, Level I Trauma Center over a 6-month period for patients receiving a C-spine CT. The primary outcome of interest was prevalence of cervical spine fracture. Secondary outcomes of interest included appropriateness of C-spine imaging after retrospective application of NEXUS and CCR. The hypothesis was that fracture rates within this patient population would be extremely low.

RESULTS

No C-spine fractures were identified in the 460 patients who met inclusion criteria. Approximately 29% of patients did not warrant imaging by CCR, and 25% by NEXUS. Of note, approximately 44% of patients were indeterminate for whether imaging was warranted by CCR, with the most common reason being lack of assessment for active neck rotation.

CONCLUSIONS

Cervical spine CT is overutilized in the setting of simple assault, despite established clinical decision rules. With no fractures identified regardless of other factors, the likelihood that a CT of the cervical spine will identify clinically significant findings in the setting of "simple" assault is extremely low, approaching zero. At minimum, adherence to CCR and NEXUS within this patient population would serve to reduce both imaging costs and population radiation dose exposure.

Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma

Due to glioblastoma's infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter. Maps depicting choline to N-Acetylaspartate (Cho/NAA) ratios were registered to contrast-enhanced T1-weighted RT planning MRI for each patient. Volumes depicting metabolic abnormalities (1.5-, 1.75-, and 2.0-fold increases in Cho/NAA ratios) were compared with conventional target volumes and contrast-enhancing tumor at recurrence. sMRI-modified RT plans were generated to evaluate target volume coverage and organ-at-risk dose constraints. Conventional clinical target volumes and Cho/NAA abnormalities identified significantly different regions of microscopic infiltration with substantial Cho/NAA abnormalities falling outside of the conventional 60 Gy isodose line (41.1, 22.2, and 12.7 cm³, respectively). Clinical target volumes using Cho/NAA thresholds exhibited significantly higher coverage of contrast enhancement at recurrence on average (92.4%, 90.5%, and 88.6%, respectively) than conventional plans (82.5%). sMRI-based plans targeting tumor infiltration met planning objectives in all cases with no significant change in target coverage. In 2 cases, the sMRI-modified plan exhibited better coverage of contrast-enhancing tumor at recurrence than the original plan. Integration of the high-resolution, whole-brain sMRI into RT planning is feasible, resulting in RT target volumes that can effectively target tumor infiltration while adhering to conventional constraints.

Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma

Background

Glioblastoma (GBM) tumors exhibit strong phenotypic differences that can be quantified using magnetic resonance imaging (MRI), but the underlying biological drivers of these imaging phenotypes remain largely unknown. An Imaging-Genomics analysis was performed to reveal the mechanistic associations between MRI derived quantitative volumetric tumor phenotype features and molecular pathways.

Methods

One hundred fourty one patients with presurgery MRI and survival data were included in our analysis. Volumetric features were defined, including the necrotic core (NE), contrast-enhancement (CE), abnormal tumor volume assessed by post-contrast T1w (tumor bulk or TB), tumor-associated edema based on T2-FLAIR (ED), and total tumor volume (TV), as well as ratios of these tumor components. Based on gene expression where available (n = 91), pathway associations were assessed using a preranked gene set enrichment analysis. These results were put into context of molecular subtypes in GBM and prognostication.

Results

Volumetric features were significantly associated with diverse sets of biological processes (FDR < 0.05). While NE and TB were enriched for immune response pathways and apoptosis, CE was associated with signal transduction and protein folding processes. ED was mainly enriched for homeostasis and cell cycling pathways. ED was also the strongest predictor of molecular GBM subtypes (AUC = 0.61). CE was the strongest predictor of overall survival (C-index = 0.6; Noether test, p = 4x10⁻⁴).

Conclusion

GBM volumetric features extracted from MRI are significantly enriched for information about the biological state of a tumor that impacts patient outcomes. Clinical decision-support systems could exploit this information to develop personalized treatment strategies on the basis of noninvasive imaging.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2659-5) contains supplementary material, which is available to authorized users.

Assessing the Effects of Software Platforms on Volumetric Segmentation of Glioblastoma

Background

Radiological assessments of biologically relevant regions in glioblastoma have been associated with genotypic characteristics, implying a potential role in personalized medicine. Here, we assess the reproducibility and association with survival of two volumetric segmentation platforms and explore how methodology could impact subsequent interpretation and analysis.

Methods

Post-contrast T1- and T2-weighted FLAIR MR images of 67 TCGA patients were segmented into five distinct compartments (necrosis, contrast-enhancement, FLAIR, post contrast abnormal, and total abnormal tumor volumes) by two quantitative image segmentation platforms - 3D Slicer and a method based on Velocity AI and FSL. We investigated the internal consistency of each platform by correlation statistics, association with survival, and concordance with consensus neuroradiologist ratings using ordinal logistic regression.

Results

We found high correlations between the two platforms for FLAIR, post contrast abnormal, and total abnormal tumor volumes (spearman’s r(67) = 0.952, 0.959, and 0.969 respectively). Only modest agreement was observed for necrosis and contrast-enhancement volumes (r(67) = 0.693 and 0.773 respectively), likely arising from differences in manual and automated segmentation methods of these regions by 3D Slicer and Velocity AI/FSL, respectively. Survival analysis based on AUC revealed significant predictive power of both platforms for the following volumes: contrast-enhancement, post contrast abnormal, and total abnormal tumor volumes. Finally, ordinal logistic regression demonstrated correspondence to manual ratings for several features.

Conclusion

Tumor volume measurements from both volumetric platforms produced highly concordant and reproducible estimates across platforms for general features. As automated or semi-automated volumetric measurements replace manual linear or area measurements, it will become increasingly important to keep in mind that measurement differences between segmentation platforms for more detailed features could influence downstream survival or radio genomic analyses.

A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma

The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, the heterogeneous and infiltrative nature of gliomas make it difficult to identify the optimal region for biopsy with conventional magnetic resonance imaging (MRI). This is particularly true for low-grade gliomas, which are often nonenhancing tumors. To improve the management of patients with such tumors, neuro-oncology requires an imaging modality that can specifically identify a tumor's most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution, whole-brain 3-dimensional sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histological analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically stained tissue specimens. As a proof of concept, we describe the combination of these 2 techniques in a small cohort of patients with grade 3 glioma. With this work, we aim to present a systematic pipeline to stimulate histopathological image validation of advanced MRI techniques, such as sMRI.

Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients

BACKGROUND

The standard of care for glioblastoma (GBM) is maximal safe resection followed by radiation therapy with chemotherapy. Currently, contrast-enhanced MRI is used to define primary treatment volumes for surgery and radiation therapy. However, enhancement does not identify the tumor entirely, resulting in limited local control. Proton spectroscopic MRI (sMRI), a method reporting endogenous metabolism, may better define the tumor margin. Here, we develop a whole-brain sMRI pipeline and validate sMRI metrics with quantitative measures of tumor infiltration.

METHODS

Whole-brain sMRI metabolite maps were coregistered with surgical planning MRI and imported into a neuronavigation system to guide tissue sampling in GBM patients receiving 5-aminolevulinic acid fluorescence-guided surgery. Samples were collected from regions with metabolic abnormalities in a biopsy-like fashion before bulk resection. Tissue fluorescence was measured ex vivo using a hand-held spectrometer. Tissue samples were immunostained for Sox2 and analyzed to quantify the density of staining cells using a novel digital pathology image analysis tool. Correlations among sMRI markers, Sox2 density, and ex vivo fluorescence were evaluated.

RESULTS

Spectroscopic MRI biomarkers exhibit significant correlations with Sox2-positive cell density and ex vivo fluorescence. The choline to N-acetylaspartate ratio showed significant associations with each quantitative marker (Pearson's ρ = 0.82, P < .001 and ρ = 0.36, P < .0001, respectively). Clinically, sMRI metabolic abnormalities predated contrast enhancement at sites of tumor recurrence and exhibited an inverse relationship with progression-free survival.

CONCLUSIONS

As it identifies tumor infiltration and regions at high risk for recurrence, sMRI could complement conventional MRI to improve local control in GBM patients.

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

Introduction

MR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM).

Methods

Seventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status.

Results

Our results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature.

Conclusion

MRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine.

Electronic supplementary material

The online version of this article (doi:10.1007/s00234-015-1576-7) contains supplementary material, which is available to authorized users.

Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival

BACKGROUND

Despite an aggressive therapeutic approach, the prognosis for most patients with glioblastoma (GBM) remains poor. The aim of this study was to determine the significance of preoperative MRI variables, both quantitative and qualitative, with regard to overall and progression-free survival in GBM.

METHODS

We retrospectively identified 94 untreated GBM patients from the Cancer Imaging Archive who had pretreatment MRI and corresponding patient outcomes and clinical information in The Cancer Genome Atlas. Qualitative imaging assessments were based on the Visually Accessible Rembrandt Images feature-set criteria. Volumetric parameters were obtained of the specific tumor components: contrast enhancement, necrosis, and edema/invasion. Cox regression was used to assess prognostic and survival significance of each image.

RESULTS

Univariable Cox regression analysis demonstrated 10 imaging features and 2 clinical variables to be significantly associated with overall survival. Multivariable Cox regression analysis showed that tumor-enhancing volume (P = .03) and eloquent brain involvement (P < .001) were independent prognostic indicators of overall survival. In the multivariable Cox analysis of the volumetric features, the edema/invasion volume of more than 85 000 mm(3) and the proportion of enhancing tumor were significantly correlated with higher mortality (Ps = .004 and .003, respectively).

CONCLUSIONS

Preoperative MRI parameters have a significant prognostic role in predicting survival in patients with GBM, thus making them useful for patient stratification and endpoint biomarkers in clinical trials.

Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor

PURPOSE

To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers.

MATERIALS AND METHODS

An institutional review board waiver was obtained for this HIPAA-compliant retrospective study. Forty-five patients with GBM underwent baseline imaging with contrast material-enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging. Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests.

RESULTS

Worsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBVNER), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBVNER and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBVNER marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBVNER as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBVNER, age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49-1.79 years).

CONCLUSION

Patients with high rCBVNER and NER crossing the midline and those with high rCBVNER and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBVNER provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.

Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients

PURPOSE

The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type.

METHODS

The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis.

RESULTS

The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001).

CONCLUSION

A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM.

Imaging genomic mapping of an invasive MRI phenotype predicts patient outcome and metabolic dysfunction: a TCGA glioma phenotype research group project

Background

Invasion of tumor cells into adjacent brain parenchyma is a major cause of treatment failure in glioblastoma. Furthermore, invasive tumors are shown to have a different genomic composition and metabolic abnormalities that allow for a more aggressive GBM phenotype and resistance to therapy. We thus seek to identify those genomic abnormalities associated with a highly aggressive and invasive GBM imaging-phenotype.

Methods

We retrospectively identified 104 treatment-naïve glioblastoma patients from The Cancer Genome Atlas (TCGA) whom had gene expression profiles and corresponding MR imaging available in The Cancer Imaging Archive (TCIA). The standardized VASARI feature-set criteria were used for the qualitative visual assessments of invasion. Patients were assigned to classes based on the presence (Class A) or absence (Class B) of statistically significant invasion parameters to create an invasive imaging signature; imaging genomic analysis was subsequently performed using GenePattern Comparative Marker Selection module (Broad Institute).

Results

Our results show that patients with a combination of deep white matter tracts and ependymal invasion (Class A) on imaging had a significant decrease in overall survival as compared to patients with absence of such invasive imaging features (Class B) (8.7 versus 18.6 months, p < 0.001). Mitochondrial dysfunction was the top canonical pathway associated with Class A gene expression signature. The MYC oncogene was predicted to be the top activation regulator in Class A.

Conclusion

We demonstrate that MRI biomarker signatures can identify distinct GBM phenotypes associated with highly significant survival differences and specific molecular pathways. This study identifies mitochondrial dysfunction as the top canonical pathway in a very aggressive GBM phenotype. Thus, imaging-genomic analyses may prove invaluable in detecting novel targetable genomic pathways.

MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set

PURPOSE

To conduct a comprehensive analysis of radiologist-made assessments of glioblastoma (GBM) tumor size and composition by using a community-developed controlled terminology of magnetic resonance (MR) imaging visual features as they relate to genetic alterations, gene expression class, and patient survival.

MATERIALS AND METHODS

Because all study patients had been previously deidentified by the Cancer Genome Atlas (TCGA), a publicly available data set that contains no linkage to patient identifiers and that is HIPAA compliant, no institutional review board approval was required. Presurgical MR images of 75 patients with GBM with genetic data in the TCGA portal were rated by three neuroradiologists for size, location, and tumor morphology by using a standardized feature set. Interrater agreements were analyzed by using the Krippendorff α statistic and intraclass correlation coefficient. Associations between survival, tumor size, and morphology were determined by using multivariate Cox regression models; associations between imaging features and genomics were studied by using the Fisher exact test.

RESULTS

Interrater analysis showed significant agreement in terms of contrast material enhancement, nonenhancement, necrosis, edema, and size variables. Contrast-enhanced tumor volume and longest axis length of tumor were strongly associated with poor survival (respectively, hazard ratio: 8.84, P = .0253, and hazard ratio: 1.02, P = .00973), even after adjusting for Karnofsky performance score (P = .0208). Proneural class GBM had significantly lower levels of contrast enhancement (P = .02) than other subtypes, while mesenchymal GBM showed lower levels of nonenhanced tumor (P < .01).

CONCLUSION

This analysis demonstrates a method for consistent image feature annotation capable of reproducibly characterizing brain tumors; this study shows that radiologists' estimations of macroscopic imaging features can be combined with genetic alterations and gene expression subtypes to provide deeper insight to the underlying biologic properties of GBM subsets.

Using proton MRSI to predict response to vorinostat treatment in recurrent GBM

3055

Background: A major impediment to the development of new therapies for glioblastoma (GBM) is a lack of biomarkers indicating response. Epigenetic modifications are now recognized as a frequent occurrence in the early phases of tumorigenesis, playing a central role in tumor development. Epigenetic alterations differ significantly from genetic modifications in that they may be reversed by ‘‘epigenetic drugs’’ such as histone deacetylase inhibitors (HDACis). As a promising new modality for cancer therapy, the first generation of HDACi is currently being tested in phase I/II clinical trials. Methods: GBM alterations from therapy with HDACis, such as vorinostat (SAHA), include tumor redifferentiation/cytostasis rather than tumor size reduction limits the utility of traditional imaging methods such as MRI. Magnetic resonance spectroscopic imaging (MRSI) quantitates various metabolite levels in tumor and normal brain, allowing characterization of metabolic processes in live tissue. Results: In our preclinical model, MRS detected metabolic response to SAHA after only 3 days of treatment: reduced alanine and lactate and elevated myo-inositol, N-acetyl aspartate and creatine; each returning toward normal brain levels. This led to our clinical study of MRSI to evaluate the metabolic response of recurrent GBMs to SAHA + temozolomide. After only 7 days of SAHA treatment, MRSI can distinguish metabolic responders (normalization/restoration of tumor metabolites towards normal brain-like metabolism) from non-responders (no significant change in tumor metabolites). Our initial cohort (n=6) consists of 3 responders and 3 non-responders with highly significant differences in their change in metabolite levels (p < 0.001). Conclusions: Our results provide exciting insights into the mechanisms by which HDACi exerts its effect on GBMs. Tumor cells have increased biosynthetic needs requiring reprogramming of cellular metabolism. This creates increased energy demands, making tumor cells even more vulnerable to interventions targeting their metabolism. HDACi may induce redifferentiation in tumors by targeting tumor metabolism. Thus, MRSI provides a novel modality to predict response to HDACi-containing combination therapy in GBM.

Abstract LB-159: Using proton MRSI to predict response of Vorinostat treatment in recurrent GBM

A major impediment to the development of new therapies for glioblastoma is a lack of biomarkers indicating response. The current standard for assessing tumor progression relies on changes in size of the enhancing components of the tumor on standard MRI. While this was adequate when patients were treated with radiation alone, the addition of temozolomide has significantly increased the incidence of “pseudoprogression” while use of anti-angiogenic agents (e.g. cediranib) has increased the incidence of “pseudoresponse” complicating the interpretation of standard imaging. Tissue biopsy following treatment can assess tumor viability but this is invasive and impractical. Also, many newer agents do not produce a traditional tumor “response”. Epigenetic modifications are now recognized as a frequent development in the early phases of tumorigenesis, playing a central role in tumor development. Epigenetic alterations differ significantly from genetic modifications in that they may be readily revertible by ‘‘epigenetic drugs’’ such as inhibitors of histone deacetylases (HDAC). HDACs As a promising new modality for cancer therapy the first generation of HDAC inhibitors (HDACi) are currently being tested in phase I/II clinical trials. Glioblastomas benefit from therapy with HDACi, such as vorinostat, or SAHA, demonstrating tumor redifferentiation/cytostasis rather than tumor size reduction. This limits the utility of traditional imaging methods such as MRI. Magnetic resonance spectroscopic imaging (MRSI) quantitates amino acids and other metabolic substances in tumor and normal brain, allowing characterization of metabolic processes in live tissue. Our preclinical MRSI results show that after only three days of treatment with SAHA, elevated alanine and lactate levels and reduced myo-inositol (MI), N-acetyl aspartate (NAA), and creatine levels in gliomas return toward normal brain levels. In our patient study of SAHA and temozolomide in recurrent GBMs, MRSI showed normalization (or restoration) of glioblastoma metabolism toward normal brain tissue-like metabolism following only 7 days of SAHA treatment in 50% of enrolled patients (metabolic responders). In contrast, MRSI showed no changes at day 7 in the other 50% of enrolled GBM patients (non-metabolic responders, p &lt; 0.001). These results provide an exciting insight of the mechanisms by which HDACi exert their effect on glioblastomas. The increased biosynthetic needs of tumor cells demand a reprogramming of cellular metabolism. This creates increased energy demands and makes tumor cells more vulnerable to interventions targeting their metabolism. The mechanism by which HDACi induces redifferentiation/cytostasis in tumors may be by targeting tumor metabolism. The changes, as measured by MRSI, may serve as novel early predictors of response to HDACi-containing combination therapy in glioblastomas.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-159. doi:1538-7445.AM2012-LB-159

Alterations in cortical thickness and white matter integrity in mild cognitive impairment measured by whole-brain cortical thickness mapping and diffusion tensor imaging

BACKGROUND AND PURPOSE

Mild cognitive impairment (MCI) is a risk factor for Alzheimer disease and can be difficult to diagnose because of the subtlety of symptoms. This study attempted to examine gray matter (GM) and white matter (WM) changes with cortical thickness analysis and diffusion tensor imaging (DTI) in patients with MCI and demographically matched comparison subjects to test these measurements as possible imaging markers for diagnosis.

MATERIALS AND METHODS

Subjects with amnestic MCI (n = 10; age, 72.2 +/- 7.1 years) and normal cognition (n = 10; age, 70.1 +/- 7.7 years) underwent DTI and T1-weighted MR imaging at 3T. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), and cortical thickness were measured and compared between the MCI and control groups. We evaluated the diagnostic accuracy of 2 methods, either in combination or separately, using binary logistic regression and nonparametric statistical analyses for sensitivity, specificity, and accuracy.

RESULTS

Decreased FA and increased ADC in WM regions of the frontal and temporal lobes and corpus callosum (CC) were observed in patients with MCI. Cortical thickness was decreased in GM regions of the frontal, temporal, and parietal lobes in patients with MCI. Changes in WM and cortical thickness seemed to be more pronounced in the left hemisphere compared with the right hemisphere. Furthermore, the combination of cortical thickness and DTI measurements in the left temporal areas improved the accuracy of differentiating MCI patients from control subjects compared with either measure alone.

CONCLUSIONS

DTI and cortical thickness analyses may both serve as imaging markers to differentiate MCI from normal aging. Combined use of these 2 methods may improve the accuracy of MCI diagnosis.

Diffusion Tensor and Functional Magnetic Resonance Imaging of Diffuse Axonal Injury and Resulting Language Impairment

Diffuse axonal injury (DAI) is a common aftermath of brain trauma. The diagnosis of DAI is often difficult using conventional magnetic resonance imaging (MRI). We report a diffusion tensor imaging (DTI) study of a patient who sustained DAI presenting with language impairment. Fractional anisotropy (FA) and DTI tractography revealed a reduction of white matter integrity in the left frontal and medial temporal areas. White matter damage identified by DTI was correlated with the patient's language impairment as assessed by functional MRI (fMRI) and a neuropsychological exam. The findings demonstrate the utility of DTI for identifying white matter changes secondary to traumatic brain injury (TBI).

Magnetic resonance imaging with lateralized arterial spin labeling

We report the development of a new MRI technique which allows spins from right-sided arteries to be labeled separately from spins from left-sided arteries. This method uses two spatially-selective adiabatic inversion pulses to alternate the labeling of the right carotid and vertebral artery separate from the left carotid and vertebral artery. Normal volunteers were scanned on a clinical 1.5 T system and the resultant brain images correlated with the T2 anatomic images. Arterial anatomy was depicted using the new sequence and corresponded to the labeling scheme employed by the sequence. It was demonstrated that spatially selective inversion pulses permit the encoding of the spins within specific vascular origins and the observation of their run-off territory.

Complications of gamma knife surgery for Parkinson disease

BACKGROUND

Many medical centers throughout the world offer radiosurgery with the gamma knife (GK) for pallidotomy and thalamotomy as a safe and effective alternative to radiofrequency ablative surgery and deep brain stimulation for Parkinson disease (PD). The reported incidence of significant complications varies considerably, and the long-term complication rate remains unknown.

DESIGN

We describe 8 patients seen during an 8-month period referred for complications of GK surgery for PD.

RESULTS

Of the 8 patients, 1 died as a result of complications, including dysphagia and aspiration pneumonia. Other complications included hemiplegia, homonymous visual field deficit, hand weakness, dysarthria, hypophonia, aphasia, arm and face numbness, and pseudobulbar laughter. In all patients, lesions were significantly off target.

CONCLUSIONS

The 8 patients with PD seen in referral at our center for complications of GK surgery highlight a spectrum of potential problems associated with this procedure. These include lesion accuracy and size and the delayed development of neurological complications secondary to radiation necrosis. Gamma knife surgery may have a higher complication rate than has been previously appreciated due to delayed onset and underreporting. We believe that the risk-benefit ratio of the GK will require further scrutiny when considering pallidotomy or thalamotomy in patients with PD. Physicians using this technique should carefully follow up patients postoperatively for delayed complications, and fully inform patients of these potential risks.

Diffusion-weighted MR imaging of the normal human spinal cord in vivo

BACKGROUND AND PURPOSE

Diffusion-weighted imaging is a robust technique for evaluation of a variety of neurologic diseases affecting the brain, and might also have applications in the spinal cord. The purpose of this study was to determine the feasibility of obtaining in vivo diffusion-weighted images of the human spinal cord, to calculate normal apparent diffusion coefficient (ADC) values, and to assess cord anisotropy.

METHODS

Fifteen healthy volunteers were imaged using a multi-shot, navigator-corrected, spin-echo, echo-planar pulse sequence. Axial images of the cervical spinal cord were obtained with diffusion gradients applied along three orthogonal axes (6 b values each), and ADC values were calculated for white and gray matter.

RESULTS

With the diffusion gradients perpendicular to the orientation of the white matter tracts, spinal cord white matter was hyperintense to central gray matter at all b values. This was also the case at low b values with the diffusion gradients parallel to the white matter tracts; however, at higher b values, the relative signal intensity of gray and white matter reversed. With the diffusion gradients perpendicular to spinal cord, mean ADC values ranged from 0.40 to 0.57 x 10(-3) mm2/s for white and gray matter. With the diffusion gradients parallel to the white matter tracts, calculated ADC values were significantly higher. There was a statistically significant difference between the ADCs of white versus gray matter with all three gradient directions. Strong diffusional anisotropy was observed in spinal cord white matter.

CONCLUSION

Small field-of-view diffusion-weighted images of the human spinal cord can be acquired in vivo with reasonable scan times. Diffusion within spinal cord white matter is highly anisotropic.

MR diffusion imaging of the cervical spine

Although diffusion-weighted imaging (DWI) of the brain has gained widespread clinical acceptance, DWI of the spine and spinal cord is less well known. This article briefly reviews some of the principles and concepts of diffusion imaging, including technical considerations with regard to in vivo DWI of the spine and spinal cord, and summarizes the research and clinical experience to date. With further development and refinement, DWI eventually may provide useful and important insight into a variety of diseases of the spine and spinal cord.

MR characteristics of muslin-induced optic neuropathy: report of two cases and review of the literature

Muslin-induced optic neuropathy is a rarely reported but important cause of delayed visual loss after repair of intracranial aneurysms. Most of the previously reported cases were published before the introduction of MR imaging. We describe the clinical features and MR appearance of two cases of delayed visual loss due to "muslinoma," and compare them with the 21 cases reported in the literature.

Mucopolysaccharidosis III (Sanfilippo syndrome) type B: cranial imaging in two cases

We present the imaging findings in two patients with mucopolysaccharidosis III (Sanfilippo syndrome) type B, both with arachnoid cysts. We postulate that the deposition of glycosaminoglycans in the meninges may impair CSF flow and explain the development of arachnoid cysts also noted in patients with other forms of mucopolysaccharidoses.

Isolated straight sinus and deep cerebral venous thrombosis: successful treatment with local infusion of urokinase. Case report

A 23-year-old woman presented with headache and progressive lethargy. The diagnosis of isolated thrombosis of the straight sinus and of the deep cerebral venous system was established using cranial computerized tomography, magnetic resonance imaging, phase-contrast magnetic resonance venography, and cerebral angiography. Because of the rapid deterioration in the patient's clinical condition, the authors used direct transcatheter infusion of urokinase into the straight sinus. This treatment resulted in a successful outcome.

Magnetization transfer imaging of the pituitary: further insights into the nature of the posterior "bright spot"

PURPOSE

After more than a decade of investigation, the chemical nature of the posterior pituitary "bright spot" remains elusive. Speculations into the source of this high signal have included relaxation of water by phospholipid vesicles, vasopressin, paramagnetic substances, and membrane-associated proteins. We hypothesized that if the T1 shortening observed in this structure were caused by water/macromolecular interactions, this interaction could be modulated by the use of magnetization transfer (MT) saturation.

METHOD

Twenty-five normal subjects were recruited over a 2 month period who were identified on routine T1 sagittal head images to have pituitary bright spots with cross-sectional area of > 2 mm2. Thin section (4 mm), T1-weighted (SE 450/20) sagittal MR images were obtained both with and without the use of an MT suppression pulse (1,000 Hz offset, 200 Hz bandwidth, peak amplitude 7.3 microT). Region-of-interest measurements were made of the posterior pituitary lobe, anterior pituitary lobe, genu of corpus callosum, and pons, with MT ratios (MTRs) calculated for each structure.

RESULTS

Relatively low (and similar) MTRs were observed in both parts of the pituitary gland: anterior lobe, 12.3%; posterior lobe 10.8%. Paired t test analysis demonstrated no statistically significant difference between the MTRs of the anterior and posterior pituitary lobes (p = 0.23). Considerable suppression of signal was noted in the genu (MTR = 25.0%) and pons (MTR = 21.9%). The MTRs of both portions of the pituitary differed significantly from those of the genu and pons (p < 0.00001).

CONCLUSION

The high signal of the posterior pituitary gland suppresses only slightly on MT images, having a behavior similar to that in the anterior lobe but significantly different from the rest of the brain. These findings suggest that direct water/macromolecule, water/membrane, or water/phospholipid interactions are not likely to be responsible for the appearance of the bright spot. The experimental results are more consistent with water interacting with a paramagnetic substance or low molecular weight molecule (e.g., vasopressin, neurophysins).

Optimization of parameters for the detection of cerebral aneurysms: CT angiography of a model

PURPOSE

To optimize parameters with computed tomographic angiography for the detection of cerebral aneurysms.

MATERIALS AND METHODS

Model aneurysms were placed randomly at various branch points and scanned multiple times with spiral technique. The final analysis included 63 branch points and 22 aneurysms. Each spiral scan used a different parameter combination. Collimation ranged from 1.5 to 4.0 mm and pitch ranged from 1:1 to 1.5:1. Images were constructed with shaded surface display (SSD) and maximum intensity projection (MIP) algorithms and were interpreted by three readers for the presence or absence of aneurysm.

RESULTS

The receiver operating characteristic (ROC) curve area for 1.5-mm collimation was greater than those of 3- or 4-mm collimation (P < .01 and P < .001, respectively). There was no statistically significant difference in the ROC curve areas between 3- and 4-mm collimation (P = .37). There was no statistically significant decrease in ROC curve area when increasing pitch from 1:1 to 1.5:1 for any value of collimation (P = .96). For all parameter combinations the ROC curve areas for SSD images was greater than that of MIP images (P < .0001).

CONCLUSION

For cerebral aneurysm detection, narrow collimation is superior to wider collimation. Mild increases in pitch do not substantially degrade diagnostic accuracy. SSD offers improved diagnostic accuracy over MIP display in this model.

Breath-holding capability of adults. Implications for spiral computed tomography, fast-acquisition magnetic resonance imaging, and angiography

PURPOSE

The breath-holding capabilities of various groups of individuals were evaluated to develop protocols so that patients undergoing spiral computed tomography (CT), digital angiography, and breath-hold magnetic resonance imaging (MRI) can be studied successfully.

METHODS

Twenty-five outpatients and 25 inpatients (all adults) were studied before undergoing body CT. Each subject was asked to hold his or her breath for as long as possible. Then each patient was asked to perform as many repetitive 12-second breath holds as possible. These data were correlated with demographic and historical information.

RESULTS

The maximum breath-hold time for inpatients and those outpatients who were heavy smokers or had chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF) was 18 to 32 seconds (95% confidence interval) with a mean of 25 seconds. For all other outpatients, breath-hold time was 38 to 56 seconds (mean = 45 seconds). The 95% confidence interval for the number of 12-second breath holds for these two groups was 4 to 6 breath holds (mean = 4.9) and 6 to 7 breath holds (mean = 6.6), respectively. One inpatient could not hold his breath at all and three others were only able to hold their breath once for short periods. The sex and age of the patient had no significant effect on breath-holding performance.

CONCLUSIONS

Breath-holding protocols must account for the diminished capabilities of most inpatients, and outpatients who are heavy smokers or have COPD or CHF. Most outpatients who are not heavy smokers or without COPD or CHF can achieve a single breath hold of 38 seconds, or up to six 12-second breath holds.

Methods used for liver computed tomography scanning in community radiology practice

RATIONALE AND OBJECTIVES

A survey conducted in 1987 of mostly academic radiologists revealed that 8 of 22 (36%) respondents used bolus enhanced dynamic technique when performing computed tomography (CT) of the liver. In the current study, the authors performed a new survey of private practice radiologists that was over four times larger and had more comprehensive questions.

METHODS

An 18-item questionnaire was sent to 260 members of the American College of Radiology. The answers from 98 usable responses were tallied and analyzed.

RESULTS

Forty-six percent of the radiologists polled use bolus enhanced dynamic CT. Thirty-three percent still use ionic contrast, and a significantly lower iodine dose was used when nonionic contrast was chosen.

CONCLUSIONS

There is general agreement in the imaging literature that dynamic enhanced scanning is the method of choice for detecting liver masses with CT. The authors speculate that cost and convenience considerations strongly influence such decisions, because less than 50% of radiologists we polled use this somewhat more expensive and time-consuming technique.

Dose-dependent responses to macrophage-targeted glucocerebrosidase in a child with Gaucher disease

Long-term studies of a child with Gaucher disease indicated that the response to treatment with macrophage-targeted glucocerebrosidase (glucosylceramidase) is dose dependent, and that the hematologic response precedes the skeletal response.

Incidence, determinants and significance of fixed retrograde conduction in the region of the atrioventricular node. Evidence for retrograde atrioventricular nodal bypass tracts

Of 104 consecutive patients studied in our laboratory with His bundle electrograms, atrial and ventricular pacing and the atrial and ventricular extrastimulus techniques, 18 patients in whom the existence and utilization of ventriculoatrial (V-A) bypass tracts were excluded demonstrated evidence for fixed and rapid retrograde conduction in the region of the atrioventricular node (A-V) as suggested by the following: (1) short (36 +/- 2 msec [mean +/- standard error of mean]) and constant retrograde H2-A2 intervals during retrograde refractory period studies; (2) significantly (P less than 0.025) better V-A than A-V conduction; (3) significantly (P less than 0.025) shorter retrograde functional refractory period of the V-A conducting system than of the A-V conduction system; and (4) the retrograde effective refractory period of the A=V nodal region was not attainable in any of the 18 patients. Fourteen of the 18 patients (77 percent) had a history of palpitations and 10 (51 percent) had documented paroxysmal supraventricular tachycardia; in 13 (72 percent) single echoes or sustained reentrant supraventricular tachycardia, or both, could be induced during atrial pacing or atrial premature stimulation studies, or both. During tachycardia all these 13 patients had a short (37 +/- 2.4 msec) and constant conduction time in the retrograde limb (H-Ae interval) of the reentrant circuit that was identical to the H2-A2 interval. In conclusion, fixed and rapid retrograde conduction in the region of the A-V node (1) is seen in approximately 17 percent of patients, (2) is associated with a large incidence of reentrant paroxysmal supraventricular tachycardia, and (3) suggests the presence of A-V nodal bypass tracts (intranodal or extranodal functioning in retrograde manner).