Analysis of the spatial characteristics of metabolic abnormalities in newly diagnosed glioma patients

Investigation of metabolite correlates of CEST in the human brain at 7 T

Metabolite-weighted chemical exchange saturation transfer MRI can be used to indirectly image metabolites such as creatine and glutamate. This study aims to further explore the contrast of CEST at 2 ppm in the human brain at 7T and investigate the metabolite correlates of CEST at 2 ppm via correlations with magnetic resonance spectroscopy (MRS). Simulations were performed to establish the optimal acquisition parameters, such as total saturation time (tsat) and B1 root mean squared (B1rms) for CEST at 2 ppm in the human brain. Parameters were validated via in vitro phantom studies at 7T using concentrations, pH and temperature comparable to what is found in the human brain. Finally, 10 healthy volunteers were scanned at 7T for comparison with MRS. Our results show that the optimal parameters to acquire CEST at 2 ppm images are: B1rms = 2.14 μT & tsat = 1500 ms, respectively. Comparison with MRS showed no significant correlation between CEST at 2 ppm and total Creatine measured by MRS (R = 0.19; p-value = 0.273). However, a significant correlation was found between CEST at 2 ppm and Glu (R = 0.39; p-value = 0.033), indicating the broad Glutamate-weighted CEST as the main measurable contributor to CEST at 2 ppm. We identified and confirmed optimal CEST at 2 ppm sequence parameters and validated CEST at 2 ppm measurements in a controlled in vitro environment. Our findings suggest that glutamate is a substantial contributor to the CEST at 2 ppm contrast observed in the human brain, whereas the creatine contribution to CEST at 2 ppm in the brain did not show a measurable contribution.

Preclinical and Clinical Use of Indigenously Developed 99mTc-Diethylenetriaminepentaacetic Acid-Bis-Methionine: l-Type Amino Acid Transporter 1-Targeted Single Photon Emission Computed Tomography Radiotracer for Glioma Management

A new era in tumor classification, diagnosis, and prognostic evaluation has begun as a consequence of recent developments in the molecular and genetic characterization of central nervous system tumors. In this newly emerging era, molecular imaging modalities are essential for preoperative diagnosis, surgical planning, targeted treatment, and post-therapy evaluation of gliomas. The radiotracers are able to identify brain tumors, distinguish between low- and high-grade lesions, confirm a patient's eligibility for theranostics, and assess post-radiation alterations. We previously synthesized and reported the novel l-type amino acid transporter 1 (LAT-1)-targeted amino acid derivative in light of the use of amino acid derivatives in imaging technologies. Further, we have developed a single vial ready to label Tc-lyophilized kit preparations of diethylenetriaminepentaacetic acid-bis-methionine [DTPA-bis(Met)], also referred to as methionine-diethylenetriaminepentaacetic acid-methionine (MDM) and evaluated its imaging potential in numerous clinical studies. This review summarizes our previous publications on 99mTc-DTPA-bis(Met) in different clinical studies such as detection of breast cancer, as a prognostic marker, in detection of recurrent/residual gliomas, for differentiation of recurrent/residual gliomas from radiation necrosis, and for comparison of 99mTc-DTPA-bis(Met) with 11C-L-methionine (11C-MET), with relevant literature on imaging modalities in glioma management.

Preoperative Diagnosis and Molecular Characterization of Gliomas With Liquid Biopsy and Radiogenomics

Gliomas are a heterogenous group of central nervous system tumors with different outcomes and different therapeutic needs. Glioblastoma, the most common subtype in adults, has a very poor prognosis and disabling consequences. The World Health Organization (WHO) classification specifies that the typing and grading of gliomas should include molecular markers. The molecular characterization of gliomas has implications for prognosis, treatment planning, and prediction of treatment response. At present, gliomas are diagnosed via tumor resection or biopsy, which are always invasive and frequently risky methods. In recent years, however, substantial advances have been made in developing different methods for the molecular characterization of tumors through the analysis of products shed in body fluids. Known as liquid biopsies, these analyses can potentially provide diagnostic and prognostic information, guidance on choice of treatment, and real-time information on tumor status. In addition, magnetic resonance imaging (MRI) is another good source of tumor data; radiomics and radiogenomics can link the imaging phenotypes to gene expression patterns and provide insights to tumor biology and underlying molecular signatures. Machine and deep learning and computational techniques can also use quantitative imaging features to non-invasively detect genetic mutations. The key molecular information obtained with liquid biopsies and radiogenomics can be useful not only in the diagnosis of gliomas but can also help predict response to specific treatments and provide guidelines for personalized medicine. In this article, we review the available data on the molecular characterization of gliomas using the non-invasive methods of liquid biopsy and MRI and suggest that these tools could be used in the future for the preoperative diagnosis of gliomas.

Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

NIR Fluorescent Imaging and Photodynamic Therapy with a Novel Theranostic Phospholipid Probe for Triple-Negative Breast Cancer Cells

New exogenous probes are needed for both imaging diagnostics and therapeutics. Here, we introduce a novel nanocomposite near-infrared (NIR) fluorescent imaging probe and test its potency as a photosensitizing agent for photodynamic therapy (PDT) against triple-negative breast cancer cells. The active component in the nanocomposite is a small molecule, pyropheophorbide a-phosphatidylethanolamine-QSY21 (Pyro-PtdEtn-QSY), which is imbedded into lipid nanoparticles for transport in the body. The probe targets abnormal choline metabolism in cancer cells; specifically, the overexpression of phosphatidylcholine-specific phospholipase C (PC-PLC) in breast, prostate, and ovarian cancers. Pyro-PtdEtn-QSY consists of a NIR fluorophore and a quencher, attached to a PtdEtn moiety. It is selectively activated by PC-PLC resulting in enhanced fluorescence in cancer cells compared to normal cells. In our in vitro investigation, four breast cancer cell lines showed higher probe activation levels than noncancerous control cells, immortalized human mammary gland cells, and normal human T cells. Moreover, the ability of this nanocomposite to function as a sensitizer in PDT experiments on MDA-MB-231 cells suggests that the probe is promising as a theranostic agent.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

Magnetic resonance spectroscopy for the study of cns malignancies

Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.

Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review

OBJECTIVE:

The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features.

METHODS:

A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.

RESULTS:

Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.

CONCLUSION:

The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine.

ADVANCES IN KNOWLEDGE:

Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.

Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging

Objectives

This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma.

Methods

Forty histologically proven glioma patients underwent a standard MRI tumour protocol with the addition of IOP sequence. The regions of tumour (solid enhancing, solid non-enhancing, and cystic regions) were delineated using snake model (ITK-SNAP) with reference to structural and diffusion MRI images. The lipid distribution map was constructed based on signal loss ratio (SLR) obtained from the IOP imaging. The mean SLR values of the regions were computed and compared across the different glioma grades.

Results

The solid enhancing region of glioma had the highest SLR for both Grade II and III. The mean SLR of solid non-enhancing region of tumour demonstrated statistically significant difference between the WHO grades (grades II, III & IV) (mean SLR_II = 0.04, mean SLR_III = 0.06, mean SLR_IV = 0.08, & p < .01). A strong positive correlation was seen between WHO grades with mean SLR on lipid map of solid non-enhancing (ρ=0.68, p < .01).

Conclusion

Lipid quantification via lipid map provides useful information on lipid landscape in tumour heterogeneity characterisation of glioma. This technique adds to the surgical diagnostic yield by identifying biopsy targets. It can also be used as an adjunct grading tool for glioma as well as to provide information about lipidomics landscape in glioma development.

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In- and opposed-phase imaging is useful in gliomas characterisation and grading.

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Signal loss ratio in the solid non-enhancing region is a potential imaging marker for discriminating between the WHO grades.

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Lipid quantification via lipid distribution mapping provides useful information on lipid landscape in tumour heterogeneity.

Nonprotecting Group Synthesis of a Phospholipase C Activatable Probe with an Azo-Free Quencher

The near-infrared fluorescent activatable smart probe Pyro-phosphatidylethanolamine (PtdEtn)-QSY was synthesized and observed to selectively fluoresce in the presence of phosphatidylcholine-specific phospholipase C (PC-PLC). PC-PLC is an important biological target as it is known to be upregulated in a variety of cancers, including triple negative breast cancer. Pyro-PtdEtn-QSY features a QSY21 quenching moiety instead of the Black Hole Quencher-3 (BHQ-3) used previously because the latter contains an azo bond, which could lead to biological instability.

MR-guided radiation therapy: transformative technology and its role in the central nervous system

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.

The Potential of Metabolic Imaging

Metabolic imaging is a field of molecular imaging that focuses and targets changes in metabolic pathways for the evaluation of different clinical conditions. Targeting and quantifying metabolic changes noninvasively is a powerful approach to facilitate diagnosis and evaluate therapeutic response. This review addresses only techniques targeting metabolic pathways. Other molecular imaging strategies, such as affinity or receptor imaging or microenvironment-dependent methods are beyond the scope of this review. Here we describe the current state of the art in clinically translatable metabolic imaging modalities. Specifically, we focus on PET and MR spectroscopy, including conventional (1)H- and (13)C-MR spectroscopy at thermal equilibrium and hyperpolarized MRI. In this article, we first provide an overview of metabolic pathways that are altered in many pathologic conditions and the corresponding probes and techniques used to study those alterations. We then describe the application of metabolic imaging to several common diseases, including cancer, neurodegeneration, cardiac ischemia, and infection or inflammation.

Proton MRS imaging in pediatric brain tumors

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors.

Hypercellularity Components of Glioblastoma Identified by High b-Value Diffusion-Weighted Imaging

PURPOSE

Use of conventional magnetic resonance imaging (MRI) for target definition may expose glioblastomas (GB) to inadequate radiation dose coverage of the nonenhanced hypercellular subvolume. This study aimed to develop a technique to identify the hypercellular components of GB by using high b-value diffusion-weighted imaging (DWI) and to investigate its relationship with the prescribed 95% isodose volume (PDV) and progression-free survival (PFS).

METHODS AND MATERIALS

Twenty-one patients with GB underwent chemoradiation therapy post-resection and biopsy. Radiation therapy (RT) treatment planning was based upon conventional MRI. Pre-RT DWIs were acquired in 3 orthogonal directions with b-values of 0, 1000, and 3000 s/mm(2). Hypercellularity volume (HCV) was defined on the high b-value (3000 s/mm(2)) DWI by a threshold method. Nonenhanced signified regions not covered by the Gd-enhanced gross tumor volume (GTV-Gd) on T1-weighted images. The PDV was used to evaluate spatial coverage of the HCV by the dose plan. Association between HCV and PFS or other clinical covariates were assessed using univariate proportional hazards regression models.

RESULTS

HCVs and nonenhanced HCVs varied from 0.58 to 67 cm(3) (median: 9.8 cm(3)) and 0.15 to 60 cm(3) (median: 2.5 cm(3)), respectively. Fourteen patients had incomplete dose coverage of the HCV, 6 of whom had >1 cm(3) HCV missed by the 95% PDV (range: 1.01-25.4 cm(3)). Of the 15 patients who progressed, 5 progressed earlier, within 6 months post-RT, and 10 patients afterward. Pre-RT HCVs within recurrent GTVs-Gd were 78% (range: 65%-89%) for the 5 earliest progressions but lower, 53% (range: 0%-85%), for the later progressions. HCV and nonenhanced HCV were significant negative prognostic indicators for PFS (P<.002 and P<.01, respectively). The hypercellularity subvolume not covered by the 95% PDV was a significant negative predictor for PFS (P<.05).

CONCLUSIONS

High b-value DWI identifies the hypercellular components of GB and could aid in RT target volume definition. Future studies will allow us to investigate the role of high b-value DWI in identifying radiation boost volumes and diagnosing progression.

CEST signal at 2ppm (CEST@2ppm) from Z-spectral fitting correlates with creatine distribution in brain tumor

In general, multiple components such as water direct saturation, magnetization transfer (MT), chemical exchange saturation transfer (CEST) and aliphatic nuclear Overhauser effect (NOE) contribute to the Z-spectrum. The conventional CEST quantification method based on asymmetrical analysis may lead to quantification errors due to the semi-solid MT asymmetry and the aliphatic NOE located on a single side of the Z-spectrum. Fitting individual contributors to the Z-spectrum may improve the quantification of each component. In this study, we aim to characterize the multiple exchangeable components from an intracranial tumor model using a simplified Z-spectral fitting method. In this method, the Z-spectrum acquired at low saturation RF amplitude (50 Hz) was modeled as the summation of five Lorentzian functions that correspond to NOE, MT effect, bulk water, amide proton transfer (APT) effect and a CEST peak located at +2 ppm, called CEST@2ppm. With the pixel-wise fitting, the regional variations of these five components in the brain tumor and the normal brain tissue were quantified and summarized. Increased APT effect, decreased NOE and reduced CEST@2ppm were observed in the brain tumor compared with the normal brain tissue. Additionally, CEST@2ppm decreased with tumor progression. CEST@2ppm was found to correlate with the creatine concentration quantified with proton MRS. Based on the correlation curve, the creatine contribution to CEST@2ppm was quantified. The CEST@2ppm signal could be a novel imaging surrogate for in vivo creatine, the important bioenergetics marker. Given its noninvasive nature, this CEST MRI method may have broad applications in cancer bioenergetics.

Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review

BACKGROUND

Many techniques are proposed for the quantification of tumor heterogeneity as an imaging biomarker for differentiation between tumor types, tumor grading, response monitoring and outcome prediction. However, in clinical practice these methods are barely used. This study evaluates the reported performance of the described methods and identifies barriers to their implementation in clinical practice.

METHODOLOGY

The Ovid, Embase, and Cochrane Central databases were searched up to 20 September 2013. Heterogeneity analysis methods were classified into four categories, i.e., non-spatial methods (NSM), spatial grey level methods (SGLM), fractal analysis (FA) methods, and filters and transforms (F&T). The performance of the different methods was compared.

PRINCIPAL FINDINGS

Of the 7351 potentially relevant publications, 209 were included. Of these studies, 58% reported the use of NSM, 49% SGLM, 10% FA, and 28% F&T. Differentiation between tumor types, tumor grading and/or outcome prediction was the goal in 87% of the studies. Overall, the reported area under the curve (AUC) ranged from 0.5 to 1 (median 0.87). No relation was found between the performance and the quantification methods used, or between the performance and the imaging modality. A negative correlation was found between the tumor-feature ratio and the AUC, which is presumably caused by overfitting in small datasets. Cross-validation was reported in 63% of the classification studies. Retrospective analyses were conducted in 57% of the studies without a clear description.

CONCLUSIONS

In a research setting, heterogeneity quantification methods can differentiate between tumor types, grade tumors, and predict outcome and monitor treatment effects. To translate these methods to clinical practice, more prospective studies are required that use external datasets for validation: these datasets should be made available to the community to facilitate the development of new and improved methods.

Comparison of multiple parameters obtained on 3T pulsed arterial spin-labeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma grading

BACKGROUND AND PURPOSE

Pulsed arterial spin-labeling, DTI, and MR spectroscopy provide useful data for tumor evaluation. We evaluated multiple parameters by using these pulse sequences and the Ki-67 labeling index in newly diagnosed supratentorial gliomas.

MATERIALS AND METHODS

All 32 patients, with grade II (3 each of diffuse astrocytoma, oligodendroglioma, and oligoastrocytoma), grade III (3 anaplastic astrocytomas, 4 anaplastic oligodendrogliomas, and 1 anaplastic oligoastrocytoma), and grade IV (14 glioblastomas and 1 glioblastoma with an oligodendroglioma component) cases underwent pulsed arterial spin-labeling, DTI, and MR spectroscopy studies by using 3T MR imaging. The following variables were used to compare the tumors: relative cerebral blood flow, fractional anisotropy; ADC tumor/normal ratios; and the Cho/Cr, NAA/Cho, NAA/Cr, and lactate/Cr ratios. A logistic regression and receiver operating characteristic analysis were used to assess parameters with a high sensitivity and specificity to identify the threshold values for separate grading. We compared the Ki-67 index with various MR imaging parameters in tumor specimens.

RESULTS

Significant correlations were observed between the Ki-67 index and the mean, maximum, and minimum ADC, Cho/Cr, and lactate/Cr ratios. The receiver operating characteristic analysis showed that the combination of the minimum ADC and Cho/Cr ratios could differentiate low-grade and high-grade gliomas, with a sensitivity and specificity of 87.0% and 88.9%, respectively. The mean and maximum relative cerebral blood flow ratios were used to classify glioblastomas from other-grade astrocytomas, with a sensitivity and specificity of 92.9% and 83.3%, respectively.

CONCLUSIONS

Our findings indicate that pulsed arterial spin-labeling, DTI, and MR spectroscopy are useful for predicting glioma grade. Additionally, the parameters obtained on DTI and MR spectroscopy closely correlated with the proliferative potential of gliomas.

¹H magnetic resonance spectroscopy: a review of the current literature and its potential utility in veterinary oncology

Advanced imaging of veterinary cancer patients has evolved in recent years and modalities once limited to human medicine have now been described for diagnostic purposes in veterinary medicine (positron emission tomography/computed tomography, single-photon emission computed tomography, whole body magnetic resonance imaging). Magnetic resonance spectroscopy (MRS) is a non-invasive and non-ionizing technique that is well described in the human medical literature and is most frequently used to evaluate the metabolic activity of tissues with questionable malignant transformation. Differentiation of neoplastic tissue from surrounding normal tissue is dependent on variations in cellular metabolism. Positive identification of malignancy can be made when neoplastic alterations are occurring at the cellular level prior to gross anatomic changes. This improved, early detection of cancer occurrence (or recurrence) can improve patient survival and direct medical therapy. MRS techniques are largely underutilized in veterinary medicine, with current research predominantly limited to the brain (both evaluation of normal and diseased tissue). Given the clinical utility of MRS in humans, the technique may also be useful in the staging of cancer in veterinary medicine.

Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12–15 months for glioblastomas and 2–5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies, and importantly, for facilitating patient management, sparing patients from weeks or months of toxicity and ineffective treatment. This review will present an overview of epidemiology, molecular pathogenesis and current advances in diagnoses, and management of malignant gliomas.

Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes

BACKGROUND AND PURPOSE

The most powerful adjunct to histopathology for the grading of gliomas seems to be the metabolic imaging using positron emission tomography and magnetic resonance spectroscopy (MRS). The purposes of this study were to examine the feasibility of simultaneous acquisition of both techniques for purposes of tumor grading in a newly launched hybrid magnetic resonance positron emission tomography (MR-PET) and to examine the spatial distributions of metabolic changes in gliomas.

MATERIALS AND METHODS

Twenty-eight consecutive patients with gliomas underwent simultaneous methionine (Met) MR-PET imaging for detection of the most malignant tumor part before surgical sampling. After coregistration and fusion of MR-PET and MRS data, tumor to normal brain (T/N) Met uptake ratios and the corresponding metabolites peaks (choline [Cho], creatine [Cr], and N-acetylaspartate [NAA]) in MRS were recorded. The patients were divided into 4 types on the basis of the relation between the Met uptake area and the increased metabolite ratios: type I, the increased Met uptake area had at least 50% overlap or was completely within the area of increased Cho/NAA ratio; type II, the increased Met uptake site had less than 50% overlap of increased Cho/NAA ratio site; type III, the increased Met uptake region had no spatial relationship with the "hot" lesions in the MRS maps; and type IV, there was no pathologically increased Met uptake. The surgical sampling was performed in the tumor part with the highest Met uptake and, in the absence of increased Met accumulation, in the site with the highest Cho/NAA ratio. All surgical samples were referred to the neuropathology division for histological grading.

RESULTS

A total of 16 low-grade gliomas (World Health Organization grade II) and 12 high-grade gliomas (World Health Organization grade III) were included. Three lesions (10%) of type I were identified. Four lesions (14%) were classified as type II and 6 lesions (21%) were classified as type 3, where the increased Met uptake region had no spatial relationship with the hot lesions in the MRS maps. In 15 of the 28 patients (54%), there was no increased Met accumulation (type 4 lesions). Maps of Cho/NAA and Cr/NAA showed a close spatial relationship in most of the patients. Median T/N Met uptake ratio in the pooled surgically sampled tumor sites was 1.6 (range, 1-3), and median Cho/NAA and Cho/Cr ratios were 2.1 (range, 0.9-5.8) and 1.5 (range, 0.5-8.3), respectively. Spearman rank correlations of the metabolic markers in the low-grade gliomas showed significant correlations between Met uptake and Cr/NAA ratio (ρ = 0.59; P = 0.015) as well as between Cho/NAA and Cr/NAA ratios (ρ = 0.79; P = 0.0002). The normalized tumor creatine was significantly higher in anaplastic tumors compared with the low-grade gliomas (P = 0.001). A tendency for a significant positive correlation was found between normalized tumor creatine and Met uptake in the anaplastic tumors.

CONCLUSIONS

Metabolic mapping before histological sampling is feasible using simultaneous MR-PET imaging. High T/N Met uptake ratio reflecting high expression of amino-acid membrane transporters, which is indicative of proliferating tumor cell populations, does not always spatially correlate with neuronal cell loss and cell membrane proliferation (Cho/NAA) seen in MRS. Increased Cr/NAA is associated with increased methionine uptake in low-grade gliomas, whereas normalized creatine in tumor tends to correlate with methionine accumulation, which indicates a possible coupling of these metabolic indices in anaplastic tumors. Thus, spatial distribution differences in gliomas should be taken into account when planning surgical sampling.

Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging

BACKGROUND

The objective of this study was to examine the predictive value of parameters of 3D (1)H magnetic resonance spectroscopic imaging (MRSI) prior to treatment with radiation/chemotherapy (baseline) and at a postradiation 2-month follow-up (F2mo) in relationship to 6-month progression-free survival (PFS6) and overall survival (OS).

METHODS

Sixty-four patients with newly diagnosed glioblastoma multiforme (GBM) being treated with radiation and concurrent chemotherapy were involved in this study. Evaluated were metabolite indices and metabolite ratios. Logistic linear regression and Cox proportional hazards models were utilized to evaluate PFS6 and OS, respectively. These analyses were adjusted by age and MR scanner field strength (1.5 T or 3 T). Stepwise regression was performed to determine a subset of the most relevant variables.

RESULTS

Associated with shorter PFS6 were a decrease in the ratio of N-acetyl aspartate to choline-containing compounds (NAA/Cho) in the region with a Cho-to-NAA index (CNI) >3 at baseline and an increase of the CNI within elevated CNI regions (>2) at F2mo. Patients with higher normalized lipid and lactate at either time point had significantly worse OS. Patients who had larger volumes with abnormal CNI at F2mo had worse PFS6 and OS.

CONCLUSIONS

Our study found more 3D MRSI parameters that predicted PFS6 and OS for patients with GBM than did anatomic, diffusion, or perfusion imaging, which were previously evaluated in the same population of patients.

Quantitative short echo time 1H MRSI of the peripheral edematous region of human brain tumors in the differentiation between glioblastoma, metastasis, and meningioma

PURPOSE

To assess metabolite levels in peritumoral edematous (PO) and surrounding apparently normal (SAN) brain regions of glioblastoma, metastasis, and meningioma in humans with (1)H-MRSI to find biomarkers that can discriminate between tumors and characterize infiltrative tumor growth.

MATERIALS AND METHODS

Magnetic resonance (MR) spectra (semi-LASER MRSI, 30 msec echo time, 3T) were selected from regions of interest (ROIs) under MRI guidance, and after quality control of MR spectra. Statistical testing between patient groups was performed for mean metabolite ratios of an entire ROI and for the highest value within that ROI.

RESULTS

The highest ratios of the level of choline compounds and the sum of myo-inositol and glycine over N-acetylaspartate and creatine compounds were significantly increased in PO regions of glioblastoma versus that of metastasis and meningioma. In the SAN region of glioblastoma some of these ratios were increased. Differences were less prominent for metabolite levels averaged over entire ROIs.

CONCLUSION

Specific metabolite ratios in PO and SAN regions can be used to discriminate glioblastoma from metastasis and meningioma. An analysis of these ratios averaged over entire ROIs and those with most abnormal values indicates that infiltrative tumor growth in glioblastoma is inhomogeneous and extends into the SAN region.

High-Grade Cerebral Glioma Characterization: Usefulness of MR Spectroscopy and Perfusion Imaging Associated Evaluation

The aim of our study was to evaluate if both spectroscopy and perfusion magnetic resonance (MR) imaging are necessary to differentiate high grade gliomas from low grade tumour, or if only one of these techniques is sufficient. Sixty-five patients with cerebral glioma were retrospectively evaluated. All patients were studied both with spectroscopy and perfusion imaging. In 43 cases histological examination showed a high grade glioma while a low grade glioma was found in 22 patients. For every patient spectroscopic maximum Cho/NAA ratio and lactate presence was established maximum relative CBV value was evaluated by perfusion MR. Both for Cho/NAA and rCBV threshold values were obtained by means of ROC curves. Then diagnostic sensitivity and specificity for high grade gliomas identification was evaluated for spectroscopic data only (Cho/NAA and lactate presence that was considered a high grade glioma marker), for perfusional data only (rCBV) and finally for both spectroscopic and perfusional data together. Sensitivity was significantly highest evaluating both spectroscopic and perfusional data together (89.7%) in comparison with spectroscopy (74.4%) or perfusion (79.4%) alone. Instead specificity was slightly lower with all data (91.7%) in comparison with spectroscopy (95.8%) and perfusion (95.8%) alone. In conclusion, to characterize high grade gliomas it is more useful to evaluate spectroscopic and perfusional data together with respect only one of these techniques alone.

Spatial characteristics of newly diagnosed grade 3 glioma assessed by magnetic resonance metabolic and diffusion tensor imaging

The spatial heterogeneity in magnetic resonance (MR) metabolic and diffusion parameters and their relationship were studied for patients with treatment-naive grade 3 gliomas. MR data were evaluated from 51 patients with newly diagnosed grade 3 gliomas. Anatomic, diffusion, and metabolic imaging data were considered. Variations in metabolite levels, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were evaluated in regions of gadolinium enhancement and T2 hyperintensity as well as regions with abnormal metabolic signatures. Contrast enhancement was present in only 21 of the 51 patients. When present, the enhancing component of the lesion had higher choline-to-N-acetylaspartate index (CNI), higher choline, lower N-acetylaspartate, similar creatine, similar ADC and FA, and higher lactate/lipid than the nonenhancing lesion. Regions with CNI ≥ 4 had higher choline, lower N-acetylaspartate, higher lactate/lipid, higher ADC, and lower FA than normal-appearing white matter and regions with intermediate CNI values. For lesions that exhibited gadolinium enhancement, the metabolite levels and diffusion parameters in the region of enhancement were consistent with it corresponding to the most abnormal portion of the tumor. For nonenhancing lesions, areas with CNI ≥ 4 were the most abnormal in metabolic and diffusion parameters. This suggests that the region with the highest CNI might provide a good target for biopsies for nonenhancing lesions to obtain a representative histologic diagnosis of its degree of malignancy. Metabolic and diffusion parameter levels may be of interest not only for directing tissue sampling but also for defining the targets for focal therapy and assessing response to therapy.

In vivo detection of phospholipase C by enzyme-activated near-infrared probes

In this article, the characterization of the first near-infrared (NIR) phospholipase-activated molecular beacon is reported, and its utility for in vivo cancer imaging is demonstrated. The probe consists of three elements: a phospholipid (PL) backbone to which the NIR fluorophore, pyropheophorbide a (Pyro), and the NIR Black Hole Quencher 3 (BHQ) were conjugated. Because of the close proximity of BHQ to Pyro, the Pyro-PtdEtn-BHQ probe is self-quenched until enzyme hydrolysis releases the fluorophore. The Pyro-PtdEtn-BHQ probe is highly specific to one isoform of phospholipase C, phosphatidylcholine-specific phospholipase C (PC-PLC), responsible for catabolizing phosphatidylcholine directly to phosphocholine. Incubation of Pyro-PtdEtn-BHQ in vitro with PC-PLC demonstrated a 150-fold increase in fluorescence that could be inhibited by the specific PC-PLC inhibitor tricyclodecan-9-yl xanthogenate (D609) with an IC(50) of 34 ± 8 μM. Since elevations in phosphocholine have been consistently observed by magnetic resonance spectroscopy in a wide array of cancer cells and solid tumors, we assessed the utility of Pyro-PtdEtn-BHQ as a probe for targeted tumor imaging. Injection of Pyro-PtdEtn-BHQ into mice bearing DU145 human prostate tumor xenografts followed by in vivo NIR imaging resulted in a 4-fold increase in tumor radiance over background and a 2 fold increase in the tumor/muscle ratio. Tumor fluorescence enhancement was inhibited with the administration of D609. The ability to image PC-PLC activity in vivo provides a unique and sensitive method of monitoring one of the critical phospholipase signaling pathways activated in cancer, as well as the phospholipase activities that are altered in response to cancer treatment.

Heterogeneity in malignant gliomas: a magnetic resonance analysis of spatial distribution of metabolite changes and regional blood volume

First-pass contrast-enhanced dynamic perfusion imaging provides information about the regional cerebral blood volume (rCBV), an increase of which indicates neovascularization. MR spectroscopic imaging informs about metabolite changes in brain tumors, with elevated choline (Cho) values revealing cell proliferation and density, and the glial metabolite creatine (Cr) representing high-energy storage. This study investigates metabolite changes within the tumor voxel of maximal rCBV value (rCBVmax). Anatomically coregistered parameter maps of rCBV, Cho and Cr were evaluated in 36 patients with primary or recurrent WHO grade III or IV gliomas. Apart from Cho and Cr values within the voxel of rCBVmax (Choperf, Crperf), the maximal Cho and Cr values of the tumor tissue were recorded (Chomax, Crmax). The correlation between these parameters was analyzed with Spearman’s rho test while a binomial test was performed to check whether Chomax = Choperf and Crmax = Crperf. We found that, in 29 of the 36 patients, neither Cho nor Cr had their maxima in the voxel of rCBVmax (Choperf, Crperf < Chomax, Crmax, P < 0.001). However, Choperf was highly correlated with Chomax (r = 0.76, P < 0.001) and Crperf with Crmax (r = 0.47, P < 0.001). Further Choperf correlated with Crperf (r = 0.55, P < 0.001). Neither of the spectroscopic parameters (Chomax, Crmax, Choperf, Crperf,) correlated with rCBVmax. In conclusion, in WHO grade III and IV gliomas the voxel with maximal rCBV often differs from the voxel with the maximal Cho and Cr, indicating the spatial divergence between neovascularization and tumor cell proliferation, cell density and glial processes. However, tCho and tCr changes within the area of neovascularization are positively correlated with the maximal increase within the tumor tissue. These results demonstrate aspects of regional tumor heterogeneity as characterized by different MR modalities that, apart from histopathological grading might be crucial for neurosurgical biopsy as well as for antiangiogenetic and future molecular therapies.

Multimodality assessment of brain tumors and tumor recurrence

Neuroimaging plays a significant role in the diagnosis of intracranial tumors, especially brain gliomas, and must consist of an assessment of location and extent of the tumor and of its biologic activity. Therefore, morphologic imaging modalities and functional, metabolic, or molecular imaging modalities should be combined for primary diagnosis and for following the course and evaluating therapeutic effects. MRI is the gold standard for providing detailed morphologic information and can supply some additional insights into metabolism (MR spectroscopy) and perfusion (perfusion-weighted imaging) but still has limitations in identifying tumor grade, invasive growth into neighboring tissue, and treatment-induced changes, as well as recurrences. These insights can be obtained by various PET modalities, including imaging of glucose metabolism, amino acid uptake, nucleoside uptake, and hypoxia. Diagnostic accuracy can benefit from coregistration of PET results and MRI, combining the high-resolution morphologic images with the biologic information. These procedures are optimized by the newly developed combination of PET and MRI modalities, permitting the simultaneous assessment of morphologic, functional, metabolic, and molecular information on the human brain.

Metabolic tumor imaging using magnetic resonance spectroscopy

The adaptability and the genomic plasticity of cancer cells, and the interaction between the tumor microenvironment and co-opted stromal cells, coupled with the ability of cancer cells to colonize distant organs, contribute to the frequent intractability of cancer. It is becoming increasingly evident that personalized molecular targeting is necessary for the successful treatment of this multifaceted and complex disease. Noninvasive imaging modalities such as magnetic resonance (MR), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) are filling several important niches in this era of targeted molecular medicine, in applications that span from bench to bedside. In this review we focus on noninvasive magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) and their roles in future personalized medicine in cancer. Diagnosis, the identification of the most effective treatment, monitoring treatment delivery, and response to treatment are some of the broad areas into which MRS techniques can be integrated to improve treatment outcomes. The development of novel probes for molecular imaging--in combination with a slew of functional imaging capabilities--makes MRS techniques, especially in combination with other imaging modalities, valuable in cancer drug discovery and basic cancer research.

Distinguishing recurrent high-grade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging

RATIONALE AND OBJECTIVES

The accurate delineation of tumor recurrence and its differentiation from radiation injury in the follow-up of adjuvantly treated high-grade gliomas presents a significant problem in neuro-oncology. The aim of this study was to investigate whether hemodynamic parameters derived from dynamic contrast-enhanced (DCE) T1-weighted magnetic resonance imaging (MRI) can be used to distinguish recurrent gliomas from radiation necrosis.

MATERIALS AND METHODS

Eighteen patients who were being treated for glial neoplasms underwent prospectively conventional and DCE-MRI using a 3T scanner. The pharmacokinetic modelling was based on a two-compartment model that allows for the calculation of K(trans) (transfer constant between intra- and extravascular, extracellular space), v(e) (extravascular, extracellular space), k(ep) (transfer constant from the extracellular, extravascular space into the plasma), and iAUC (initial area under the signal intensity-time curve). Regions of interest (ROIs) were drawn around the entire recurrence-suspected contrast-enhanced region. A definitive diagnosis was established at subsequent surgical resection or clinicoradiologic follow-up. The hemodynamic parameters in the contralateral normal white matter, the radiation injury sites, and the tumor recurrent lesions were compared using nonparametric tests.

RESULTS

The K(trans), v(e), k(ep), and iAUC values in the normal white matter were significantly different than those in the radiation necrosis and recurrent gliomas (0.01, <P < .0001). The only significantly different hemodynamic parameter between the recurrent tumor lesions and the radiation-induced necrotic sites were K(trans) and iAUC, which were significantly higher in the recurrent glioma group than in the radiation necrosis group (P ≤ .0184). A K(trans) cutoff value higher than 0.19 showed 100% sensitivity and 83% specificity for detecting the recurrent gliomas, whereas an iAUC cutoff value higher than 15.35 had 71% sensitivity and 71% specificity. The v(e) and k(ep) values in recurrent tumors were not significantly higher than those in radiation-induced necrotic lesions.

CONCLUSIONS

These findings suggest that DCE-MRI may be used to distinguish between recurrent gliomas and radiation injury and thus, assist in follow-up patient management strategy.

Brainstem metabolites in multiple system atrophy of cerebellar type: 3.0-T magnetic resonance spectroscopy study

BACKGROUND

The aim of this study was to find biomarkers of disease severity in multiple system atrophy of cerebellar type by imaging disease specific regions using proton magnetic resonance spectroscopy on a 3.0 T system.

METHODS

We performed proton magnetic resonance spectroscopy separately in the pons and medulla on 12 multiple system atrophy of cerebellar type patients and 12 age and gender matched control subjects. The metabolite concentrations were estimated from single-voxel proton magnetic resonance spectra measured by point resolved spectroscopy, which were then correlated with clinical severity using Part I, II, and IV of the unified multiple system atrophy rating scale.

RESULTS

Proton magnetic resonance spectroscopy showed that myo-inositol concentrations in both the pons and medulla were significantly higher in multiple system atrophy of cerebellar type patients compared to those of the control subjects (P < 0.05). By contrast, total N-acetylaspartate (the sum of N-acetylaspartate and N-acetylaspartylglutamate) and total choline compounds concentrations in both the pons and medulla were significantly lower in multiple system atrophy of cerebellar type patients compared to control subjects (P < 0.05). Creatine concentration in the pons was significantly higher in multiple system atrophy of cerebellar type patients compared to the control subjects (P < 0.05). Furthermore, a significant correlation was found between the myo-inositol/creatine ratio in the pons and clinical severity, defined by the sum score of unified multiple system atrophy rating scale (I+II+IV) (r = 0.76, P < 0.01).

CONCLUSION

Proton magnetic resonance spectroscopy, in conjunction with a 3.0 T system, can be feasible to detect part of pathological changes in the brainstem, such as gliosis and neuronal cell loss, and the metabolites can be used as biomarkers of clinical severity in multiple system atrophy of cerebellar type patients.

Multimodal mass spectrometric imaging of small molecules reveals distinct spatio-molecular signatures in differentially metastatic breast tumor models

Phosphocholine (PC) and total choline (tCho) are increased in malignant breast tumors. In this study, we combined magnetic resonance spectroscopic imaging (MRSI), mass spectrometry (MS) imaging, and pathologic assessment of corresponding tumor sections to investigate the localization of choline metabolites and cations in viable versus necrotic tumor regions in the nonmetastatic MCF-7 and the highly metastatic MDA-MB-231 breast cancer xenograft models. In vivo three-dimensional MRSI showed that high tCho levels, consisting of free choline (Cho), PC, and glycerophosphocholine (GPC), displayed a heterogeneous spatial distribution in the tumor. MS imaging performed on tumor sections detected the spatial distributions of individual PC, Cho, and GPC, as well as sodium (Na+) and potassium (K+), among many others. PC and Cho intensity were increased in viable compared with necrotic regions of MDA-MB-231 tumors, but relatively homogeneously distributed in MCF-7 tumors. Such behavior may be related to the role of PC and PC-related enzymes, such as choline kinase, choline transporters, and others, in malignant tumor growth. Na+ and K+ colocalized in the necrotic tumor areas of MDA-MB-231 tumors, whereas in MCF-7 tumors, Na+ was detected in necrotic and K+ in viable tumor regions. This may be attributed to differential Na+/K+ pump functions and K+ channel expressions. Principal component analysis of the MS imaging data clearly identified different tumor microenvironmental regions by their distinct molecular signatures. This molecular information allowed us to differentiate between distinct tumor regions and tumor types, which may, in the future, prove clinically useful in the pathologic assessment of breast cancers.

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T

PURPOSE

The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques.

METHODS

The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods.

RESULTS

The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36-2.47-fold loss in spatial resolution due to the differences in their point spread functions.

CONCLUSION

The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA.

Functional and metabolic magnetic resonance imaging and positron emission tomography for tumor volume definition in high-grade gliomas

Although the addition of concurrent and adjuvant temozolomide (TMZ) to standard-dose radiation (60 Gy) improves survival, the pattern of failure continues to be local. Conventional contrast enhanced T1-weighted and T2-weighted magnetic resonance imaging (MRI) used for radiation planning reflect anatomic rather than molecular or functional, properties of the tumor. Functional and metabolic MRI and positron emission tomography are able to detect metabolic and functional abnormalities beyond the tumor volume seen on conventional MRI, assess early response to treatment, and delineate the regions of high risks for failure in high-grade gliomas. This article focuses on the potential of these functional and metabolic imaging techniques to refine our clinical target volumes.

Neuroimaging in neuro-oncology

Neuroimaging of brain tumors has evolved from a strictly morphology-based discipline to one that encompasses function, physiology, and anatomy. This review outlines the current imaging standard for patients with brain tumor and summarizes the latest advances in physiology-based imaging methods that complement traditional brain tumor imaging protocols. Emphasis is on the strength and limitations of the current imaging standards and on an overview of several advanced imaging methods including diffusion-weighted magnetic resonance imaging (MRI), perfusion MRI, and proton magnetic resonance spectroscopic (MRS) imaging. Basic physical principles behind each imaging method are briefly presented, along with a more in-depth discussion of clinical application and potential pitfalls of each technique.

Nosologic imaging of the brain: segmentation and classification using MRI and MRSI

A new technique is presented to create nosologic images of the brain based on magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI). A nosologic image summarizes the presence of different tissues and lesions in a single image by color coding each voxel or pixel according to the histopathological class it is assigned to. The proposed technique applies advanced methods from image processing as well as pattern recognition to segment and classify brain tumors. First, a registered brain atlas and a subject-specific abnormal tissue prior, obtained from MRSI data, are used for the segmentation. Next, the detected abnormal tissue is classified based on supervised pattern recognition methods. Class probabilities are also calculated for the segmented abnormal region. Compared to previous approaches, the new framework is more flexible and able to better exploit spatial information leading to improved nosologic images. The combined scheme offers a new way to produce high-resolution nosologic images, representing tumor heterogeneity and class probabilities, which may help clinicians in decision making.

Role of advanced MR imaging modalities in diagnosing cerebral gliomas

The objective of this study was to evaluate the potential role of newly developed, advanced magnetic resonance (MR) imaging techniques (spectroscopy, diffusion and perfusion imaging) in diagnosing brain gliomas, with special reference to histological typing and grading, treatment planning and posttreatment follow-up. Conventional MR imaging enables the detection and localisation of neoplastic lesions, as well as providing, in typical cases, some indication about their nature. However, it has limited sensitivity and specificity in evaluating histological type and grade, delineating margins and differentiating oedema, tumour and treatment side-effects. These limitations can be overcome by supplementing the morphological data obtained with conventional MR imaging with the metabolic, structural and perfusional information provided by new MR techniques that are increasingly becoming an integral part of routine MR studies. Incorporation of such new MR techniques can lead to more comprehensive and precise diagnoses that can better assist surgeons in determining prognosis and planning treatment strategies. In addition, the recent development of new, more effective, treatments for cerebral glioma strongly relies on morphofunctional MR imaging with its ability to provide a biological interpretation of these characteristically heterogeneous tumours.

Magnetic resonance spectroscopy of the brain: review of metabolites and clinical applications

Magnetic resonance imaging (MRI) provides anatomic images and morphometric characterization of disease, whereas magnetic resonance spectroscopy (MRS) provides metabolite/biochemical information about tissues non-invasively in vivo. MRS has been used clinically for more than two decades. The major applications of this advanced MRI tool are in the investigation of neurological and neurosurgical disorders. MRS has also been used in the evaluation of the prostate gland and muscle tissue, but these applications will not be addressed in this review. The aim of this review is to attempt to introduce the technique, review the metabolites and literature, as well as briefly describe our clinical experience.

Myo-inositol: a marker of reactive astrogliosis in glial tumors?

In a prospective study, two-dimensional (1)H-MRS with TE of 30 ms was performed before surgery in 56 patients with glial brain tumors. Concentrations of myo-inositol (MI), trimethylamine (TMA) and creatine/phosphocreatine (tCr) were evaluated for the whole tumor and scaled to the normal-appearing contralateral brain tissue. To assign changes in MI to specific tissue pathology, the normalized peak and mean concentrations of MI were correlated with TMA and tCr concentrations. TMA is accepted as a marker of proliferating tumor tissue, and tCr might be a marker of reactive astrogliosis. The mean and peak concentrations of MI and tCr correlated positively (r = 0.7), but not the concentrations of MI and TMA. The absolute concentration of MI was significantly increased in all tumor tissues (5.55 +/- 2.92 mM; mean +/- SD) compared with the normal-appearing white matter (4.33 +/- 1.22 mM, p = 0.005), with the highest concentrations for gliomatoses (n = 10) and grade II oligoastrocytomas (n = 3). Significant differences (P = 0.004) between low- and high-grade astrocytomas were found for TMA (1.67 +/- 0.32 mM and 2.65 +/- 0.86 mM, respectively), but not for MI (5.92 +/- 1.98 mM and 5.49 +/- 3.27 mM, respectively). As increased MI and tCr concentrations were found in gliomatosis and other cerebral diseases associated with marked astrogliosis, this process may also be responsible for the observed changes in MI in other glial tumors.

3D 1H MRSI of brain tumors at 3.0 Tesla using an eight-channel phased-array head coil

PURPOSE

To implement proton magnetic resonance spectroscopic imaging (1H MRSI) at 3 Tesla (3T) using an eight-channel phased-array head coil in a population of brain-tumor patients.

MATERIALS AND METHODS

A total of 49 MRI/MRSI examinations were performed on seven volunteers and 34 patients on a 3T GE Signa EXCITE scanner using body coil excitation and reception with an eight-channel phased-array head coil. 1H MRSI was acquired using point-resolved spectroscopy (PRESS) volume selection and three-dimensional (3D) phase encoding using a 144-msec echo time (TE).

RESULTS

The mean choline to N-acetyl aspartate ratio (Cho/NAA) was similar within regions of normal-appearing white matter (NAWM) in volunteers (0.5 +/- 0.04) and patients (0.6 +/- 0.1, P = 0.15). This ratio was significantly higher in regions of T2-hyperintensity lesion (T2L) relative to NAWM for patients (1.4 +/- 0.7, P = 0.001). The differences between metabolite intensities in lesions and NAWM were similar, but there was an increase in SNR of 1.95 when an eight-channel head coil was used at 3T vs. previous results at 1.5T.

CONCLUSION

The realized increase in SNR means that clinically relevant data can be obtained in five to 10 minutes at 3T and used to predict the spatial extent of tumor in a manner similar to that previously used to acquire 1.5T data in 17 minutes.

Analysis of metabolic indices in regions of abnormal perfusion in patients with high-grade glioma

BACKGROUND AND PURPOSE

MR spectroscopic imaging (MRSI) and dynamic susceptibility-contrast MR imaging (DSC-MR imaging) are functional in vivo techniques for assessing tumor metabolism and vasculature characteristics. Because tumor hypoxia is influenced by tortuous, degraded, swollen, and angiogenic tumor vasculature, regions of abnormal perfusion parameters should coexist with changes in lactate and creatine metabolite levels.

MATERIALS AND METHODS

DSC-MR imaging and lactate-edited MRSI were performed on 38 treatment-naive patients with high-grade gliomas (17 grade III, 21 grade IV) before surgical diagnosis. Regions of abnormal perfusion were determined from peak height and percent recovery maps for each voxel within the spectroscopic imaging volume. Choline, creatine, and lactate levels within voxels experiencing only abnormal peak height (aPH), only abnormal recovery (aRec), and both abnormal peak height and recovery (aPH+aRec) were determined and compared to the surrounding T2 hyperintensity (T2h) and normal-appearing white matter.

RESULTS

There were decreasing trends in volume from aPH to aRec to aPH+aRec regions for both grade III and grade IV gliomas. Grade IV gliomas exhibited significantly elevated choline in all abnormal perfusion regions, with reduced creatine and increased lactate in the aRec region relative to the surrounding T2h. Grade III gliomas showed trends toward increased creatine within the aPH region and reduced levels within the aRec region.

CONCLUSION

Depressed creatine and elevated lactate levels confirmed the lack of oxygenation within regions of compromised vascular integrity. Identification of regions with leaky or dense vasculature and metabolic markers of hypoxia and cellular proliferation could be useful in determining the more aggressive part of the tumor for targeting, monitoring, and assessing effects of treatment.

Monovoxel 1H Magnetic Resonance Spectroscopy in the Progression of Gliomas

AIM

Can monovoxel magnetic resonance spectroscopy (MRS) reliably follow tumour progression in low-grade glioma?

MATERIALS AND METHODS

21 patients with low-grade glioma underwent at least 3 MRS.

RESULTS

For progression from a grade II to grade III tumour, a sensitivity of 57.1% and specificity of 60% were observed, with a positive predictive value (PPV) of 48.8% and a negative predictive value (NPV) of 54.5%. For progression under treatment, we obtained a sensitivity of 57.1% by N-acetylaspartate (NAA)/choline (Cho) and myoinositol/creatine (Cr) and a specificity of 100% by Cho/Cr and lipids, with a PPV of 80% and a NPV of 63.6%.

CONCLUSION

We found that NAA/Cho is the best marker of tumour progression before therapy, with a sensitivity of 53.9%. For the therapeutic response, sensitivity was only 28.2%.