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Amine-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine- and pH-sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine-weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine-weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine-weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited., (© 2022 John Wiley & Sons Ltd.)

Acidity within the extracellular milieu is a hallmark of cancer. There is a current need for fast, high spatial resolution pH imaging techniques for clinical evaluation of cancers, including gliomas. Chemical exchange saturation transfer (CEST) MRI targeting fast-exchanging amine protons can be used to obtain high-resolution pH-weighted images, but conventional CEST acquisition strategies are slow. There is also a need for more accurate MR simulations to better understand the effects of amine CEST pulse sequence parameters on pH-weighted image contrast. In the current study we present a simulation of amine CEST contrast specific for a newly developed CEST echoplanar imaging (EPI) pulse sequence. The accuracy of the simulations was validated by comparing the exchange rates and Z-spectrum under a variety of conditions using physical phantoms of glutamine with different pH values. The effects of saturation pulse shapes, pulse durations, pulse train lengths, repetition times, and relaxation rates of bulk water and exchangeable amine protons on the CEST signal were explored for normal-appearing white matter (NAWM), glioma, and cerebrospinal fluid. Last, 18 patients with WHO II-IV gliomas were evaluated. Results showed that the Z-spectrum was highly dependent on saturation pulse shape, repetition time, saturation amplitude, magnetic field strength, and T 2 within bulk water; however, the Z-spectrum was only minimally influenced by saturation pulse duration and the specific relaxation rates of amine protons. Results suggest that a Gaussian saturation pulse train consisting of 3 × 100 ms pulses using the minimum allowable repetition time is optimal for achieving over 90% available contrast across all tissues. Results also demonstrate that high saturation pulse amplitude and scanner field strength (>3 T) are necessary for adequate endogenous pH-weighted amine CEST contrast. pH-weighted amine CEST contrast increased with increasing tumor grade, with glioblastoma showing significantly higher contrast compared with WHO II or III gliomas., (Copyright © 2016 John Wiley & Sons, Ltd.)

Since the overall glioma mass and its subcomponents-enhancing region (malignant part of the tumor), non-enhancing (less aggressive tumor cells), necrotic core (dead cells), and edema (water deposition)-are complex and irregular structures, non-Euclidean geometric measures such as fractal dimension (FD or "fractality") and lacunarity are needed to quantify their structural complexity. Fractality measures the extent of structural irregularity, while lacunarity measures the spatial distribution or gaps. The complex geometric patterns of the glioma subcomponents may be closely associated with the grade and molecular landscape. Therefore, we measured FD and lacunarity in the glioma subcomponents and developed machine learning models to discriminate between tumor grades and isocitrate dehydrogenase (IDH) gene status. 3D fractal dimension (FD3D) and lacunarity (Lac3D) were measured for the enhancing, non-enhancing plus necrotic core, and edema-subcomponents using preoperative structural-MRI obtained from the The Cancer Genome Atlas (TCGA) and University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) glioma cohorts. The FD3D and Lac3D measures of the tumor-subcomponents were then compared across glioma grades (HGGs: high-grade gliomas vs. LGGs: low-grade gliomas) and IDH status (mutant vs. wild type). Using these measures, machine learning platforms discriminative of glioma grade and IDH status were developed. Kaplan-Meier survival analysis was used to assess the prognostic significance of FD3D and Lac3D measurements. HGG exhibited significantly higher fractality and lower lacunarity in the enhancing subcomponent, along with lower fractality in the non-enhancing subcomponent compared to LGG. This suggests that a highly irregular and complex geometry in the enhancing-subcomponent is a characteristic feature of HGGs. A comparison of FD3D and Lac3D between IDH-wild type and IDH-mutant gliomas revealed that mutant gliomas had ~2.5-fold lower FD3D in the enhancing-subcomponent and higher FD3D with lower Lac3D in the non-enhancing subcomponent, indicating a less complex and smooth enhancing subcomponent, and a more continuous non-enhancing subcomponent as features of IDH-mutant gliomas. Supervised ML models using FD3D from both the enhancing and non-enhancing subcomponents together demonstrated high-sensitivity in discriminating glioma grades (~97.9%) and IDH status (~94.4%). A combined fractal estimation of the enhancing and non-enhancing subcomponents using MR images could serve as a non-invasive, precise, and quantitative measure for discriminating glioma grade and IDH status. The combination of 2-hydroxyglutarate-magnetic resonance spectroscopy (2HG-MRS) with FD3D and Lac3D quantification may be established as a robust imaging signature for glioma subtyping., (© 2024 John Wiley & Sons Ltd.)

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE-MRI data acquisition. Quantitative DCE-MRI analysis was performed for computing various parameters such as wash-out slope (Slope-2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (V p ), and volume transfer constant (K trans ). An approach based on data-clustering algorithm, morphological operations, and quantitative DCE-MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data-clustering algorithms were evaluated on two types of quantitative maps: (a) Slope-2, and (b) a new proposed combination of rCBV and Slope-2 maps. Fluid-attenuated inversion recovery-MRI hyperintense lesions were also automatically segmented using deep learning-based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE-MRI parameters were obtained in the segmented tumor. t-test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k-means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high-grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95 th percentile values) of all parameters in the tumor region showed a statistically significant difference (p < 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low-grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and V p maps show better visualization of tumor regions., (© 2024 John Wiley & Sons Ltd.)

Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low‐concentration biomolecules with water‐exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer‐weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies. [ABSTRACT FROM AUTHOR]

The effect of a human vascular endothelial growth factor antibody on the vasculature of human tumor grown in rat brain was studied. Using dynamic contrast‐enhanced magnetic resonance imaging, the effects of intravenous bevacizumab (Avastin; 10 mg/kg) were examined before and at postadministration times of 1, 2, 4, 8, 12 and 24 h (N = 26; 4–5 per time point) in a rat model of orthotopic, U251 glioblastoma (GBM). The commonly estimated vascular parameters for an MR contrast agent were: (i) plasma distribution volume (vp), (ii) forward volumetric transfer constant (Ktrans) and (iii) reverse transfer constant (kep). In addition, extracellular distribution volume (VD) was estimated in the tumor (VD‐tumor), tumor edge (VD‐edge) and the mostly normal tumor periphery (VD‐peri), along with tumor blood flow (TBF), peri‐tumoral hydraulic conductivity (K) and interstitial flow (Flux) and tumor interstitial fluid pressure (TIFP). Studied as % changes from baseline, the 2‐h post‐treatment time point began showing significant decreases in vp, VD‐tumor, VD‐edge and VD‐peri, as well as K, with these changes persisting at 4 and 8 h in vp, K, VD‐tumor, −edge and ‐peri (t‐tests; p < 0.05–0.01). Decreases in Ktrans were observed at the 2‐ and 4‐h time points (p < 0.05), while interstitial volume fraction (ve; = Ktrans/kep) showed a significant decrease only at the 2‐h time point (p < 0.05). Sustained decreases in Flux were observed from 2 to 24 h (p < 0.01) while TBF and TIFP showed delayed responses, increases in the former at 12 and 24 h and a decrease in the latter only at 12 h. These imaging biomarkers of tumor vascular kinetics describe the short‐term temporal changes in physical spaces and fluid flows in a model of GBM after Avastin administration. [ABSTRACT FROM AUTHOR]

The physiological mechanism induced by the isocitrate dehydrogenase 1 (IDH1) mutation, associated with better treatment response in gliomas, remains unknown. The aim of this preclinical study was to characterize the IDH1 mutation through in vivo multiparametric MRI and MRS. Multiparametric MRI, including the measurement of blood flow, vascularity, oxygenation, permeability, and in vivo MRS, was performed on a 4.7 T animal MRI system in rat brains grafted with human‐derived glioblastoma U87 cell lines expressing or not the IDH1 mutation by the CRISPR/Cas9 method, and secondarily characterized with additional ex vivo HR‐MAS and histological analyses. In univariate analyses, compared with IDH1−, IDH1+ tumors exhibited higher vascular density (p < 0.01) and better perfusion (p = 0.02 for cerebral blood flow), but lower vessel permeability (p < 0.01 for time to peak (TTP), p = 0.04 for contrast enhancement) and decreased T1 map values (p = 0.02). Using linear discriminant analysis, vascular density and TTP values were found to be independent MRI parameters for characterizing the IDH1 mutation (p < 0.01). In vivo MRS and ex vivo HR‐MAS analysis showed lower metabolites of tumor aggressiveness for IDH1+ tumors (p < 0.01). Overall, the IDH1 mutation exhibited a higher vascularity on MRI, a lower permeability, and a less aggressive metabolic profile. These MRI features may prove helpful to better pinpoint the physiological mechanisms induced by this mutation. [ABSTRACT FROM AUTHOR]

Although combined spin‐ and gradient‐echo (SAGE) dynamic susceptibility‐contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T1‐shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo‐planar imaging (EPI) sequence with simultaneous multi‐slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi‐band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR2*(t) and ΔR2(t) curves were derived to calculate dynamic signal‐to‐noise ratio (dSNR), ΔR2*‐ and ΔR2‐based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal‐appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal‐appearing gray matter were not statistically significant between the two protocols. ΔR2*‐ and ΔR2‐rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most common primary brain tumor. It is highly malignant and has a correspondingly poor prognosis. Diagnosis and monitoring are mainly accomplished with MRI, but remain challenging in some cases. Therefore, complementary methods for tumor detection and characterization would be beneficial. Using magnetic resonance elastography (MRE), we performed a longitudinal study of the biomechanical properties of intracranially implanted GBM in mice and compared the results to histopathology. The biomechanical parameters of viscoelastic modulus, shear wave speed and phase angle were significantly lower in tumors compared with healthy brain tissue and decreased over time with tumor progression. Moreover, some MRE parameters revealed sub‐regions at later tumor stages, which were not easily detectable on anatomical MRI images. Comparison with histopathology showed that softer tumor regions contained necrosis and patches of viable tumor cells. In contrast, areas of densely packed tumor cells and blood vessels identified with histology coincided with higher values of viscoelastic modulus and shear wave speed. Interestingly, the phase angle was independent from these anatomical variations. In summary, MRE depicted longitudinal and morphological changes in GBM and may prove valuable for tumor characterization in patients. [ABSTRACT FROM AUTHOR]

Abnormally high levels of the ‘oncometabolite’ 2‐hydroxyglutarate (2‐HG) occur in many grade II and III gliomas, and correlate with mutations in the genes of isocitrate dehydrogenase (IDH) isoforms. In vivo measurement of 2‐HG in patients, using magnetic resonance spectroscopy (MRS), has largely been carried out at 3 T, yet signal overlap continues to pose a challenge for 2‐HG detection. To combat this, several groups have proposed MRS methods at ultra‐high field ( ≥7 T) where theoretical increases in signal‐to‐noise ratio and spectral resolution could improve 2‐HG detection. Long echo time (long‐TE) semi‐localization by adiabatic selective refocusing (semi‐LASER) (TE = 110 ms) is a promising method for improved 2‐HG detection in vivo at either 3 or 7 T owing to the use of broad‐band adiabatic localization. Using previously published semi‐LASER methods at 3 and 7 T, this study directly compares the detectability of 2‐HG in phantoms and in vivo across nine patients. Cramér–Rao lower bounds (CRLBs) of 2‐HG fitting were found to be significantly lower at 7 T (6 ± 2%) relative to 3 T (15 ± 7%) (p = 0.0019), yet were larger at 7 T in an IDH wild‐type patient. Although no increase in SNR was detected at 7 T (77 ± 26) relative to 3 T (77 ± 30), the detection of 2‐HG was greatly enhanced through an improved spectral profile and increased resolution at 7 T. 7 T had a large effect on pairwise fitting correlations between γ‐aminobutyric acid (GABA) and 2‐HG (p = 0.004), and resulted in smaller coefficients. The increased sensitivity for 2‐HG detection using long‐TE acquisition at 7 T may allow for more rapid estimation of 2‐HG (within a few spectral averages) together with other associated metabolic markers in glioma. [ABSTRACT FROM AUTHOR]

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

There is an expanding research interest in high-grade gliomas because of their significant population burden and poor survival despite the extensive standard multimodal treatment. One of the obstacles is the lack of individualized monitoring of tumor characteristics and treatment response before, during and after treatment. We have developed a two-stage semi-automatic method to co-register MRI scans at different time points before and after surgical and adjuvant treatment of high-grade gliomas. This two-stage co-registration includes a linear co-registration of the semi-automatically derived mask of the preoperative contrast-enhancing area or postoperative resection cavity, brain contour and ventricles between different time points. The resulting transformation matrix was then applied in a non-linear manner to co-register conventional contrast-enhanced T1-weighted images. Targeted registration errors were calculated and compared with linear and non-linear co-registered images. Targeted registration errors were smaller for the semi-automatic non-linear co-registration compared with both the non-linear and linear co-registered images. This was further visualized using a three-dimensional structural similarity method. The semi-automatic non-linear co-registration allowed for optimal correction of the variable brain shift at different time points as evaluated by the minimal targeted registration error. This proposed method allows for the accurate evaluation of the treatment response, essential for the growing research area of brain tumor imaging and treatment response evaluation in large sets of patients. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Solid tumors have an acidic extracellular pH (pHe) but near neutral intracellular pH (pHi). Because acidic pHe milieu is conducive to tumor growth and builds resistance to therapy, simultaneous mapping of pHe inside and outside the tumor (i.e., intratumoral-peritumoral pHe gradient) fulfills an important need in cancer imaging. We used Biosensor Imaging of Redundant Deviation in Shifts (BIRDS), which utilizes shifts of non-exchangeable protons from macrocyclic chelates (e.g., 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrakis(methylene phosphonate) or DOTP8−) complexed with paramagnetic thulium (Tm3+) ion, to generate in vivo pHe maps in rat brains bearing 9L and RG2 tumors. Upon TmDOTP5− infusion, MRI identified the tumor boundary by enhanced water transverse relaxation and BIRDS allowed imaging of intratumoral-peritumoral pHe gradients. The pHe measured by BIRDS was compared with pHi measured with 31P-MRS. In normal tissue, pHe was similar to pHi, but inside the tumor pHe was lower than pHi. While the intratumoral pHe was acidic for both tumor types, peritumoral pHe varied with tumor type. The intratumoral-peritumoral pHe gradient was much larger for 9L than RG2 tumors because in RG2 tumors acidic pHe was found in distal peritumoral regions. The increased presence of Ki-67 positive cells beyond the RG2 tumor border suggested that RG2 was more invasive than the 9L tumor. These results indicate that extensive acidic pHe beyond the tumor boundary correlates with tumor cell invasion. In summary, BIRDS has sensitivity to map the in vivo intratumoral-peritumoral pHe gradient, thereby creating preclinical applications in monitoring cancer therapeutic responses (e.g., with pHe-altering drugs). Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection ofMR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra frombrain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future. [ABSTRACT FROM AUTHOR]

Conventional MRI for brain tumor diagnosis employs T2-weighted and contrast-enhanced T1-weighted sequences. Non-enhanced T1-weighted images provide improved anatomical details for precise tumor location, but reduced tumor-to-background contrast as elevated T1 and proton density (PD) values in tumor tissue affect the signal inversely. Radiofrequency (RF) coil inhomogeneities may further mask tumor and edema outlines. To overcome this problem, the aims of this work were to employ quantitative MRI techniques to create purely T1-weighted synthetic anatomies which can be expected to yield improved tissue and tumor-to-background contrasts, to compare the quality of conventional and synthetic anatomies, and to investigate optical contrast and visibility of brain tumors and edema in synthetic anatomies. Conventional magnetization-prepared rapid acquisition of gradient echoes (MP-RAGE) anatomies and maps of T1, PD and RF coil profiles were acquired in comparable and clinically feasible times. Three synthetic MP-RAGE anatomies (PD T1 weighting both with and without RF bias; pure T1 weighting) were calculated for healthy subjects and 32 patients with brain tumors. In healthy subjects, the PD T1-weighted synthetic anatomies with RF bias precisely matched the conventional anatomies, yielding high signal-to-noise (SNR) and contrast-to-noise (CNR) ratios. Pure T1 weighting yielded lower SNR, but high CNR, because of increased optical contrasts. In patients with brain tumors, synthetic anatomies with pure T1 weighting yielded significant increases in optical contrast and improved visibility of tumor and edema in comparison with anatomies reflecting conventional T1 contrasts. In summary, the optimized purely T1-weighted synthetic anatomy with an isotropic resolution of 1 mm, as proposed in this work, considerably enhances optical contrast and visibility of brain tumors and edema. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

2-Hydroxyglutarate (2HG) is produced in gliomas with mutations of isocitrate dehydrogenase (IDH) 1 and 2. The 1H resonances of the J-coupled spins of 2HG are extensively overlapped with signals from other metabolites. Here, we report a comparative study at 3 T of the utility of the point-resolved spectroscopy sequence with a standard short TE (35 ms) and a long TE (97 ms), which had been theoretically designed for the detection of the 2HG 2.25-ppm resonance. The performance of the methods is evaluated using data from phantoms, seven healthy volunteers and 22 subjects with IDH-mutated gliomas. The results indicate that TE = 97 ms provides higher detectability of 2HG than TE = 35 ms, and that this improved capability is gained when data are analyzed with basis spectra that include the effects of the volume localizing radiofrequency and gradient pulses. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by 13 C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1- 13 C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr 13 C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the 13 C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. 31 P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole 1 H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits., (© 2019 John Wiley & Sons, Ltd.)

MRI and MRS techniques are being applied to the characterisation of various aspects of the tumour microenvironment and to the assessment of tumour response to therapy. For example, kinetic parameters describing tumour blood vessel flow and permeability can be derived from dynamic contrast-enhanced MRI data and have been correlated with a positive tumour response to antivascular therapies. The ongoing development and validation of noninvasive, high-resolution anatomical/molecular MR techniques will equip us with the means to detect specific tumour biomarkers early on, and then to monitor the efficacy of cancer treatments efficiently and reliably, all within a clinically relevant time frame. Reliable tumour microenvironment imaging biomarkers will provide obvious advantages by enabling tumour-specific treatment tailoring and potentially improving patient outcome. However, for routine clinical application across many disease types, such imaging biomarkers must be quantitative, robust, reproducible, sufficiently sensitive and cost-effective. These characteristics are all difficult to achieve in practice, but image biomarker development and validation have been greatly facilitated by an increasing number of pertinent preclinical in vivo cancer models. Emphasis must now be placed on discovering whether the preclinical results translate into an improvement in patient care and, therefore, overall survival. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T1-weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T2 lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Early imaging or blood biomarkers of tumor response is needed to customize anti-tumor therapy on an individual basis. This study evaluates the sensitivity and relevance of five potential MRI biomarkers. Sixty nude rats were implanted with human glioma cells (U-87 MG) and randomized into three groups: one group received an anti-angiogenic treatment (Sorafenib), a second a cytotoxic drug [1,3-bis(2-chloroethyl)-1-nitrosourea, BCNU (Carmustine)] and a third no treatment. The tumor volume, apparent diffusion coefficient (ADC) of water, blood volume fraction (BVf), microvessel diameter (vessel size index, VSI) and vessel wall integrity (contrast enhancement, CE) were monitored before and during treatment. Sorafenib reduced tumor CE as early as 1 day after treatment onset. By 4 days after treatment onset, tumor BVf was reduced and tumor VSI was increased. By 14 days after treatment onset, ADC was increased and the tumor growth rate was reduced. With BCNU, ADC was increased and the tumor growth rate was reduced 14 days after treatment onset. Thus, the estimated MRI parameters were sensitive to treatment at different times after treatment onset and in a treatment-dependent manner. This study suggests that multiparametric MR monitoring could allow the assessment of new anti-tumor drugs and the optimization of combined therapies. Copyright © 2010 John Wiley & Sons, Ltd. Multiparametric MRI reveals that both tumor microvasculature and cellularity are altered by anti-angiogenic and cytotoxic therapy. Multiparametric MRI thus has strong potential for the evaluation of the effect of new drugs on brain tumors. In addition, multiparametric MRI could contribute towards an understanding of the mechanisms of action of anti-angiogenic therapies and the optimization of therapeutic combinations. [ABSTRACT FROM AUTHOR]

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three‐dimensional echo planar spectroscopic imaging (3D‐EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo‐radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow‐up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N‐acetylaspartate (Cho/NAA) were computed and co‐registered with post‐contrast T1‐weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D‐EPSI in differentiating TP from PsP with high sensitivity and specificity. Significantly higher Cho/NAA was observed from contrast enhancing (CER), immediate peritumor (IPR), and distal peritumor (DPR) regions in patients with true progression (TP) compared with pseudoprogression (PsP).Significantly elevated Cho/Cr from CER was observed in TP compared with PsP.Inclusion of Cho/Cr from CER and Cho/NAA from CER, IPR, and DPR using logistic regression provided the best classification model, with a high accuracy (AUC = 0.93) along with a sensitivity of 94% and specificity of 87% in distinguishing TP from PsP. [ABSTRACT FROM AUTHOR]