1H-MRSI pattern perturbation in a mouse glioma: the effects of acute hyperglycemia and moderate hypothermia

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks

BACKGROUND

Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation.

METHODS

This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation.

RESULTS

The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method.

CONCLUSIONS

The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.

Short TE downfield magnetic resonance spectroscopy in a mouse model of brain glioma

PURPOSE

Enhanced cell proliferation in tumors can be associated with altered metabolic profiles and dramatic microenvironmental changes. Downfield magnetic resonance spectroscopy (MRS) has received increasing attention due to its ability to report on labile resonances of molecules not easily detected in upfield ¹ H MRS. Image-selected-in-vivo-spectroscopy-relaxation enhanced MRS (iRE-MRS) was recently introduced for acquiring short echo-time (TE) spectra. Here, iRE-MRS was used to investigate in-vivo downfield spectra in glioma-bearing mice.

METHODS

Experiments were performed in vivo in an immunocompetent glioma mouse model at 9.4 T using a cryogenic coil. iRE-MRS spectra were acquired in N = 6 glioma-bearing mice (voxel size = 2.2³  mm³ ) and N = 6 control mice. Spectra were modeled by a sum of Lorentzian peaks simulating known downfield resonances, and differences between controls and tumors were quantified using relative peak areas.

RESULTS

Short TE tumor spectra exhibited large qualitative differences compared to control spectra. Most peaks appeared modulated, with strong attenuation of NAA (∼7.82, 7.86 ppm) and changes in relative peak areas between 6.75 and 8.49 ppm. Peak areas tended to be smaller for DF_6.83 , DF_7.60 , DF_8.18 and NAA; and larger for DF_7.95 and DF_8.24 . Differences were also detected in signals resonating above 8.5 ppm, assumed to arise from NAD+.

CONCLUSIONS

In-vivo downfield ¹ H iRE-MRS of mouse glioma revealed differences between controls and tumor bearing mice, including in metabolites which are not easily detectable in the more commonly investigated upfield spectrum. These findings motivate future downfield MRS investigations exploring pH and exchange contributions to these differences.

Immune System-Related Changes in Preclinical GL261 Glioblastoma under TMZ Treatment: Explaining MRSI-Based Nosological Imaging Findings with RT-PCR Analyses

Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Previous work suggests that magnetic resonance spectroscopic imaging (MRSI) could act as a biomarker of efficient immune system attack onto GB, presenting oscillatory changes. Glioma-associated microglia/macrophages (GAMs) constitute the most abundant non-tumour cell type within the GB and can be polarised into anti-tumour (M1) or pro-tumour (M2) phenotypes. One of the mechanisms to mediate immunosuppression in brain tumours is the interaction between programmed cell death-1 ligand 1 (PD-L1) and programmed cell death-1 receptor (PD-1). We evaluated the subpopulations of GAMs in responding and control GB tumours to correlate PD-L1 expression to GAM polarisation in order to explain/validate MRSI-detected findings. Mice were evaluated by MRI/MRSI to assess the extent of response to treatment and with qPCR for GAMs M1 and M2 polarisation analyses. M1/M2 ratios and PD-L1 expression were higher in treated compared to control tumours. Furthermore, PD-L1 expression was positively correlated with the M1/M2 ratio. The oscillatory change in the GAMs prevailing population could be one of the key causes for the differential MRSI-detected pattern, allowing this to act as immune system activity biomarker in future work.

Successful Partnerships: Exploring the Potential of Immunogenic Signals Triggered by TMZ, CX-4945, and Combined Treatment in GL261 Glioblastoma Cells

BACKGROUND

The relevance of the cancer immune cycle in therapy response implies that successful treatment may trigger the exposure or the release of immunogenic signals. Previous results with the preclinical GL261 glioblastoma (GB) showed that combination treatment of temozolomide (TMZ) + CX-4945 (protein kinase CK2 inhibitor) outperformed single treatments, provided an immune-friendly schedule was followed. Our purpose was to study possible immunogenic signals released in vitro by GB cells.

METHODS

GL261 GB cells were treated with TMZ and CX-4945 at different concentrations (25 µM-4 mM) and time frames (12-72 h). Cell viability was measured with Trypan Blue and propidium iodide. Calreticulin exposure was assessed with immunofluorescence, and ATP release was measured with bioluminescence.

RESULTS

TMZ showed cytostatic rather than cytotoxic effects, while CX-4945 showed remarkable cytotoxic effects already at low concentrations. Calreticulin exposure after 24 h was detected with TMZ treatment, as well as TMZ/CX-4945 low concentration combined treatment. ATP release was significantly higher with CX-4945, especially at high concentrations, as well as with TMZ/CX-4945.

CONCLUSIONS

combined treatment may produce the simultaneous release of two potent immunogenic signals, which can explain the outperformance over single treatments in vivo. A word of caution may be raised since in vitro conditions are not able to mimic pharmacokinetics observed in vivo fully.

Anti-PD-1 Immunotherapy in Preclinical GL261 Glioblastoma: Influence of Therapeutic Parameters and Non-Invasive Response Biomarker Assessment with MRSI-Based Approaches

Glioblastomas (GBs) are malignant brain tumours with poor prognosis even after aggressive therapy. Programmed cell death-1 (PD-1) immune checkpoint blockade is a promising strategy in many types of cancer, but its therapeutic effects in GB remain low and associated with immune infiltration. Previous work suggests that oscillations of magnetic resonance spectroscopic imaging (MRSI)-based response pattern with chemotherapy could act as a biomarker of efficient immune system attack onto GBs. The presence of such oscillations with other monotherapies such as anti-PD-1 would reinforce its monitoring potential. Here, we confirm that the oscillatory behaviour of the response biomarker is also detected in mice treated with anti PD-1 immunotherapy both in combination with temozolomide and as monotherapy. This indicates that the spectral pattern changes observed during therapy response are shared by different therapeutic strategies, provided the host immune system is elicited and able to productively attack tumour cells. Moreover, the participation of the immune system in response is also supported by the rate of cured animals observed with different therapeutic strategies (in the range of 50–100% depending on the treatment), which also held long-term immune memory against tumour cells re-challenge. Taken together, our findings open the way for a translational use of the MRSI-based biomarker in patient-tailored GB therapy, including immunotherapy, for which reliable non-invasive biomarkers are still missing.

Anti-tumour immune response in GL261 glioblastoma generated by Temozolomide Immune-Enhancing Metronomic Schedule monitored with MRSI-based nosological images

Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Improvements in both therapeutic and follow-up strategies are urgently needed. In previous work we described an oscillatory pattern of response to Temozolomide (TMZ) using a standard administration protocol, detected through MRSI-based machine learning approaches. In the present work, we have introduced the Immune-Enhancing Metronomic Schedule (IMS) with an every 6-d TMZ administration at 60 mg/kg and investigated the consistence of such oscillatory behaviour. A total of n = 17 GL261 GB tumour-bearing C57BL/6j mice were studied with MRI/MRSI every 2 d, and the oscillatory behaviour (6.2 ± 1.5 d period from the TMZ administration day) was confirmed during response. Furthermore, IMS-TMZ produced significant improvement in mice survival (22.5 ± 3.0 d for controls vs 135.8 ± 78.2 for TMZ-treated), outperforming standard TMZ treatment. Histopathological correlation was investigated in selected tumour samples (n = 6) analyzing control and responding fields. Significant differences were found for CD3+ cells (lymphocytes, 3.3 ± 2.5 vs 4.8 ± 2.9, respectively) and Iba-1 immunostained area (microglia/macrophages, 16.8% ± 9.7% and 21.9% ± 11.4%, respectively). Unexpectedly, during IMS-TMZ treatment, tumours from some mice (n = 6) fully regressed and remained undetectable without further treatment for 1 mo. These animals were considered "cured" and a GL261 re-challenge experiment performed, with no tumour reappearance in five out of six cases. Heterogeneous therapy response outcomes were detected in tumour-bearing mice, and a selected group was investigated (n = 3 non-responders, n = 6 relapsing tumours, n = 3 controls). PD-L1 content was found ca. 3-fold increased in the relapsing group when comparing with control and non-responding groups, suggesting that increased lymphocyte inhibition could be associated to IMS-TMZ failure. Overall, data suggest that host immune response has a relevant role in therapy response/escape in GL261 tumours under IMS-TMZ therapy. This is associated to changes in the metabolomics pattern, oscillating every 6 d, in agreement with immune cycle length, which is being sampled by MRSI-derived nosological images.

Embedding MRI information into MRSI data source extraction improves brain tumour delineation in animal models

Glioblastoma is the most frequent malignant intra-cranial tumour. Magnetic resonance imaging is the modality of choice in diagnosis, aggressiveness assessment, and follow-up. However, there are examples where it lacks diagnostic accuracy. Magnetic resonance spectroscopy enables the identification of molecules present in the tissue, providing a precise metabolomic signature. Previous research shows that combining imaging and spectroscopy information results in more accurate outcomes and superior diagnostic value. This study proposes a method to combine them, which builds upon a previous methodology whose main objective is to guide the extraction of sources. To this aim, prior knowledge about class-specific information is integrated into the methodology by setting the metric of a latent variable space where Non-negative Matrix Factorisation is performed. The former methodology, which only used spectroscopy and involved combining spectra from different subjects, was adapted to use selected areas of interest that arise from segmenting the T2-weighted image. Results showed that embedding imaging information into the source extraction (the proposed semi-supervised analysis) improved the quality of the tumour delineation, as compared to those obtained without this information (unsupervised analysis). Both approaches were applied to pre-clinical data, involving thirteen brain tumour-bearing mice, and tested against histopathological data. On results of twenty-eight images, the proposed Semi-Supervised Source Extraction (SSSE) method greatly outperformed the unsupervised one, as well as an alternative semi-supervised approach from the literature, with differences being statistically significant. SSSE has proven successful in the delineation of the tumour, while bringing benefits such as 1) not constricting the metabolomic-based prediction to the image-segmented area, 2) ability to deal with signal-to-noise issues, 3) opportunity to answer specific questions by allowing researchers/radiologists define areas of interest that guide the source extraction, 4) creation of an intra-subject model and avoiding contamination from inter-subject overlaps, and 5) extraction of meaningful, good-quality sources that adds interpretability, conferring validation and better understanding of each case.

Assessment of prenatal cerebral and cardiac metabolic changes in a rabbit model of fetal growth restriction based on 13C-labelled substrate infusions and ex vivo multinuclear HRMAS

BACKGROUND

We have used a previously reported rabbit model of fetal growth restriction (FGR), reproducing perinatal neurodevelopmental and cardiovascular impairments, to investigate the main relative changes in cerebral and cardiac metabolism of term FGR fetuses during nutrient infusion.

METHODS

FGR was induced in 9 pregnant New Zealand rabbits at 25 days of gestation: one horn used as FGR, by partial ligation of uteroplacental vessels, and the contralateral as control (appropriate for gestation age, AGA). At 30 days of gestation, fasted mothers under anesthesia were infused i.v. with 1-13C-glucose (4 mothers), 2-13C-acetate (3 mothers), or not infused (2 mothers). Fetal brain and heart samples were quickly harvested and frozen down. Brain cortex and heart apex regions from 30 fetuses were studied ex vivo by HRMAS at 4°C, acquiring multinuclear 1D and 2D spectra. The data were processed, quantified by peak deconvolution or integration, and normalized to sample weight.

RESULTS

Most of the total 13C-labeling reaching the fetal brains/hearts (80-90%) was incorporated to alanine and lactate (cytosol), and to the glutamine-glutamate pool (mitochondria). Acetate-derived lactate (Lac C2C3) had a slower turnover in FGR brains (~ -20%). In FGR hearts, mitochondrial turnover of acetate-derived glutamine (Gln C4) was slower (-23%) and there was a stronger accumulation of phospholipid breakdown products (glycerophosphoethanolamine and glycerophosphocholine, +50%), resembling the profile of non-infused control hearts.

CONCLUSIONS

Our results indicate specific functional changes in cerebral and cardiac metabolism of FGR fetuses under nutrient infusion, suggesting glial impairment and restricted mitochondrial metabolism concomitant with slower cell membrane turnover in cardiomyocytes, respectively. These prenatal metabolic changes underlie neurodevelopmental and cardiovascular problems observed in this FGR model and in clinical patients, paving the way for future studies aimed at evaluating metabolic function postnatally and in response to stress and/or treatment.

1H Spectroscopic Imaging of the Rodent Brain

Proton MR spectroscopic imaging (MRSI) can provide a variety of "molecular images" from animal models of human disease, which are useful for different research purposes. This chapter describes a protocol for in vivo acquisition and analysis of MRSI data from the rodent brain.

Metronomic treatment in immunocompetent preclinical GL261 glioblastoma: effects of cyclophosphamide and temozolomide

Glioblastoma (GBM) causes poor survival in patients even when applying aggressive treatment. Temozolomide (TMZ) is the standard chemotherapeutic choice for GBM treatment, but resistance always ensues. In previous years, efforts have focused on new therapeutic regimens with conventional drugs to activate immune responses that may enhance tumor regression and prevent regrowth, for example the "metronomic" approaches. In metronomic scheduling studies, cyclophosphamide (CPA) in GL261 GBM growing subcutaneously in C57BL/6 mice was shown not only to activate antitumor CD8⁺ T-cell response, but also to induce long-term specific T-cell tumor memory. Accordingly, we have evaluated whether metronomic CPA or TMZ administration could increase survival in orthotopic GL261 in C57BL/6 mice, an immunocompetent model. Longitudinal in vivo studies with CPA (140 mg/kg) or TMZ (range 140-240 mg/kg) metronomic administration (every 6 days) were performed in tumor-bearing mice. Tumor evolution was monitored at 7 T with MRI (T₂ -weighted, diffusion-weighted imaging) and MRSI-based nosological images of response to therapy. Obtained results demonstrated that both treatments resulted in increased survival (38.6 ± 21.0 days, n = 30) compared with control (19.4 ± 2.4 days, n = 18). Best results were obtained with 140 mg/kg TMZ (treated, 44.9 ± 29.0 days, n = 12, versus control, 19.3 ± 2.3 days, n = 12), achieving a longer survival rate than previous group work using three cycles of TMZ therapy at 60 mg/kg (33.9 ± 11.7 days, n = 38). Additional interesting findings were, first, clear edema appearance during chemotherapeutic treatment, second, the ability to apply the semi-supervised source analysis previously developed in our group for non-invasive TMZ therapy response monitoring to detect CPA-induced response, and third, the necropsy findings in mice cured from GBM after high TMZ cumulative dosage (980-1400 mg/kg), which demonstrated lymphoma incidence. In summary, every 6 day administration schedule of TMZ or CPA improves survival in orthotopic GL261 GBM with respect to controls or non-metronomic therapy, in partial agreement with previous work on subcutaneous GL261.

Applications of high-resolution magic angle spinning MRS in biomedical studies I-cell line and animal models

High-resolution magic angle spinning (HRMAS) MRS allows for direct measurements of non-liquid tissue and cell specimens to present valuable insights into the cellular metabolisms of physiological and pathological processes. HRMAS produces high-resolution spectra comparable to those obtained from solutions of specimen extracts but without complex metabolite extraction processes, and preserves the tissue cellular structure in a form suitable for pathological examinations following spectroscopic analysis. The technique has been applied in a wide variety of biomedical and biochemical studies and become one of the major platforms of metabolomic studies. By quantifying single metabolites, metabolite ratios, or metabolic profiles in their entirety, HRMAS presents promising possibilities for diagnosis and prediction of clinical outcomes for various diseases, as well as deciphering of metabolic changes resulting from drug therapies or xenobiotic interactions. In this review, we evaluate HRMAS MRS results on animal models and cell lines reported in the literature, and present the diverse applications of the method for the understanding of pathological processes and the effectiveness of therapies, development of disease animal models, and new progress in HRMAS methodology.

Metabolomics of Therapy Response in Preclinical Glioblastoma: A Multi-Slice MRSI-Based Volumetric Analysis for Noninvasive Assessment of Temozolomide Treatment

Glioblastoma (GBM) is the most common aggressive primary brain tumor in adults, with a short survival time even after aggressive therapy. Non-invasive surrogate biomarkers of therapy response may be relevant for improving patient survival. Previous work produced such biomarkers in preclinical GBM using semi-supervised source extraction and single-slice Magnetic Resonance Spectroscopic Imaging (MRSI). Nevertheless, GBMs are heterogeneous and single-slice studies could prevent obtaining relevant information. The purpose of this work was to evaluate whether a multi-slice MRSI approach, acquiring consecutive grids across the tumor, is feasible for preclinical models and may produce additional insight into therapy response. Nosological images were analyzed pixel-by-pixel and a relative responding volume, the Tumor Responding Index (TRI), was defined to quantify response. Heterogeneous response levels were observed and treated animals were ascribed to three arbitrary predefined groups: high response (HR, n = 2), TRI = 68.2 ± 2.8%, intermediate response (IR, n = 6), TRI = 41.1 ± 4.2% and low response (LR, n = 2), TRI = 13.4 ± 14.3%, producing therapy response categorization which had not been fully registered in single-slice studies. Results agreed with the multi-slice approach being feasible and producing an inverse correlation between TRI and Ki67 immunostaining. Additionally, ca. 7-day oscillations of TRI were observed, suggesting that host immune system activation in response to treatment could contribute to the responding patterns detected.

Targeting Protein Kinase CK2: Evaluating CX-4945 Potential for GL261 Glioblastoma Therapy in Immunocompetent Mice

Glioblastoma (GBM) causes poor survival in patients even with aggressive treatment. Temozolomide (TMZ) is the standard chemotherapeutic choice for GBM treatment but resistance always ensues. Protein kinase CK2 (CK2) contributes to tumour development and proliferation in cancer, and it is overexpressed in human GBM. Accordingly, targeting CK2 in GBM may benefit patients. Our goal has been to evaluate whether CK2 inhibitors (iCK2s) could increase survival in an immunocompetent preclinical GBM model. Cultured GL261 cells were treated with different iCK2s including CX-4945, and target effects evaluated in vitro. CX-4945 was found to decrease CK2 activity and Akt(S129) phosphorylation in GL261 cells. Longitudinal in vivo studies with CX-4945 alone or in combination with TMZ were performed in tumour-bearing mice. Increase in survival (p < 0.05) was found with combined CX-4945 and TMZ metronomic treatment (54.7 ± 11.9 days, n = 6) when compared to individual metronomic treatments (CX-4945: 24.5 ± 2.0 and TMZ: 38.7 ± 2.7, n = 6) and controls (22.5 ± 1.2, n = 6). Despite this, CX-4945 did not improve mice outcome when administered on every/alternate days, either alone or in combination with 3-cycle TMZ. The highest survival rate was obtained with the metronomic combined TMZ+CX-4945 every 6 days, pointing to the participation of the immune system or other ancillary mechanism in therapy response.

Development of a transplantable glioma tumour model from genetically engineered mice: MRI/MRS/MRSI characterisation

The initial aim of this study was to generate a transplantable glial tumour model of low-intermediate grade by disaggregation of a spontaneous tumour mass from genetically engineered models (GEM). This should result in an increased tumour incidence in comparison to GEM animals. An anaplastic oligoastrocytoma (OA) tumour of World Health Organization (WHO) grade III was obtained from a female GEM mouse with the S100β-v-erbB/inK4a-Arf (+/-) genotype maintained in the C57BL/6 background. The tumour tissue was disaggregated; tumour cells from it were grown in aggregates and stereotactically injected into C57BL/6 mice. Tumour development was followed using Magnetic Resonance Imaging (MRI), while changes in the metabolomics pattern of the masses were evaluated by Magnetic Resonance Spectroscopy/Spectroscopic Imaging (MRS/MRSI). Final tumour grade was evaluated by histopathological analysis. The total number of tumours generated from GEM cells from disaggregated tumour (CDT) was 67 with up to 100 % penetrance, as compared to 16 % in the local GEM model, with an average survival time of 66 ± 55 days, up to 4.3-fold significantly higher than the standard GL261 glioblastoma (GBM) tumour model. Tumours produced by transplantation of cells freshly obtained from disaggregated GEM tumour were diagnosed as WHO grade III anaplastic oligodendroglioma (ODG) and OA, while tumours produced from a previously frozen sample were diagnosed as WHO grade IV GBM. We successfully grew CDT and generated tumours from a grade III GEM glial tumour. Freezing and cell culture protocols produced progression to grade IV GBM, which makes the developed transplantable model qualify as potential secondary GBM model in mice.

MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis

Characterization of glioblastoma (GB) response to treatment is a key factor for improving patients' survival and prognosis. MRI and magnetic resonance spectroscopic imaging (MRSI) provide morphologic and metabolic profiles of GB but usually fail to produce unequivocal biomarkers of response. The purpose of this work is to provide proof of concept of the ability of a semi-supervised signal source extraction methodology to produce images with robust recognition of response to temozolomide (TMZ) in a preclinical GB model. A total of 38 female C57BL/6 mice were used in this study. The semi-supervised methodology extracted the required sources from a training set consisting of MRSI grids from eight GL261 GBs treated with TMZ, and six control untreated GBs. Three different sources (normal brain parenchyma, actively proliferating GB and GB responding to treatment) were extracted and used for calculating nosologic maps representing the spatial response to treatment. These results were validated with an independent test set (7 control and 17 treated cases) and correlated with histopathology. Major differences between the responder and non-responder sources were mainly related to the resonances of mobile lipids (MLs) and polyunsaturated fatty acids in MLs (0.9, 1.3 and 2.8 ppm). Responding tumors showed significantly lower mitotic (3.3 ± 2.9 versus 14.1 ± 4.2 mitoses/field) and proliferation rates (29.8 ± 10.3 versus 57.8 ± 5.4%) than control untreated cases. The methodology described in this work is able to produce nosological images of response to TMZ in GL261 preclinical GBs and suitably correlates with the histopathological analysis of tumors. A similar strategy could be devised for monitoring response to treatment in patients. Copyright © 2016 John Wiley & Sons, Ltd.

Heteronuclear Micro-Helmholtz Coil Facilitates µm-Range Spatial and Sub-Hz Spectral Resolution NMR of nL-Volume Samples on Customisable Microfluidic Chips

We present a completely revised generation of a modular micro-NMR detector, featuring an active sample volume of ∼ 100 nL, and an improvement of 87% in probe efficiency. The detector is capable of rapidly screening different samples using exchangeable, application-specific, MEMS-fabricated, microfluidic sample containers. In contrast to our previous design, the sample holder chips can be simply sealed with adhesive tape, with excellent adhesion due to the smooth surfaces surrounding the fluidic ports, and so withstand pressures of ∼2.5 bar, while simultaneously enabling high spectral resolution up to 0.62 Hz for H2O, due to its optimised geometry. We have additionally reworked the coil design and fabrication processes, replacing liquid photoresists by dry film stock, whose final thickness does not depend on accurate volume dispensing or precise levelling during curing. We further introduced mechanical alignment structures to avoid time-intensive optical alignment of the chip stacks during assembly, while we exchanged the laser-cut, PMMA spacers by diced glass spacers, which are not susceptible to melting during cutting. Doing so led to an overall simplification of the entire fabrication chain, while simultaneously increasing the yield, due to an improved uniformity of thickness of the individual layers, and in addition, due to more accurate vertical positioning of the wirebonded coils, now delimited by a post base plateau. We demonstrate the capability of the design by acquiring a 1H spectrum of ∼ 11 nmol sucrose dissolved in D2O, where we achieved a linewidth of 1.25 Hz for the TSP reference peak. Chemical shift imaging experiments were further recorded from voxel volumes of only ∼ 1.5 nL, which corresponded to amounts of just 1.5 nmol per voxel for a 1 M concentration. To extend the micro-detector to other nuclei of interest, we have implemented a trap circuit, enabling heteronuclear spectroscopy, demonstrated by two 1H/13C 2D HSQC experiments.

In Vivo Detection of Perinatal Brain Metabolite Changes in a Rabbit Model of Intrauterine Growth Restriction (IUGR)

Background

Intrauterine growth restriction (IUGR) is a risk factor for abnormal neurodevelopment. We studied a rabbit model of IUGR by magnetic resonance imaging (MRI) and spectroscopy (MRS), to assess in vivo brain structural and metabolic consequences, and identify potential metabolic biomarkers for clinical translation.

Methods

IUGR was induced in 3 pregnant rabbits at gestational day 25, by 40–50% uteroplacental vessel ligation in one horn; the contralateral horn was used as control. Fetuses were delivered at day 30 and weighted. A total of 6 controls and 5 IUGR pups underwent T2-w MRI and localized proton MRS within the first 8 hours of life, at 7T. Changes in brain tissue volumes and respective contributions to each MRS voxel were estimated by semi-automated registration of MRI images with a digital atlas of the rabbit brain. MRS data were used for: (i) absolute metabolite quantifications, using linear fitting; (ii) local temperature estimations, based on the water chemical shift; and (iii) classification, using spectral pattern analysis.

Results

Lower birth weight was associated with (i) smaller brain sizes, (ii) slightly lower brain temperatures, and (iii) differential metabolite profile changes in specific regions of the brain parenchyma. Specifically, we found estimated lower levels of aspartate and N-acetylaspartate (NAA) in the cerebral cortex and hippocampus (suggesting neuronal impairment), and higher glycine levels in the striatum (possible marker of brain injury). Our results also suggest that the metabolic changes in cortical regions are more prevalent than those detected in hippocampus and striatum.

Conclusions

IUGR was associated with brain metabolic changes in vivo, which correlate well with the neurostructural changes and neurodevelopment problems described in IUGR. Metabolic parameters could constitute non invasive biomarkers for the diagnosis and abnormal neurodevelopment of perinatal origin.

Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma

Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.

Effect of acute hyperglycemia on moderately hypothermic GL261 mouse glioma monitored by T1-weighted DCE MRI

OBJECTIVE

We sought to evaluate the effects of acute hyperglycemia induced by intraperitoneal injection of glucose (2.7 g/kg) on vascular delivery to GL261 mouse gliomas kept at moderate hypothermia (~30 °C).

MATERIALS AND METHODS

Seven GL261 glioma-bearing mice were studied by T1-weighted DCE MRI before and after an injection of glucose (n = 4) or saline (n = 3). Maximum relative contrast enhancement (RCE) and initial area under the enhancement curve (IAUC) were determined in each pixel.

RESULTS

The mean tumor parameter values showed no significant changes after injecting either saline (RCE -5.9 ± 5.0 %; IAUC -3.7 ± 3.6 %) or glucose (RCE -1.6 ± 9.0 %; IAUC +0.6 ± 6.4 %). Pixel-by-pixel analysis revealed small post-injection changes in RCE and IAUC between the glucose and saline groups, all within 13 % range of their baseline values.

CONCLUSION

Perturbing the metabolism of GL261 tumors kept at moderate hypothermia with hyperglycemia did not induce significant changes in the permeability/perfusion of these tumors. This is relevant for future studies with this model since regional differences in glucose accumulation could thus reflect basal heterogeneities in vasculature and/or metabolism of GL261 tumors.

Minimization of spectral pattern changes during HRMAS experiments at 37 degrees celsius by prior focused microwave irradiation

OBJECT

High-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy provides detailed metabolomic information from intact tissue. However, long acquisition times and high rotation speed may lead to timedependent spectral pattern changes, which may affect proper interpretation of results. We report a strategy to minimize those changes, even at physiological recording temperature.

MATERIALS AND METHODS

Glioblastoma(Gbm) tumours were induced in 12 mice by stereotactic injection of GL261 cells. Animals were sacrificed and tumours were removed and stored in liquid N2. Half of the samples were exposed to focused microwave (FMW) irradiation prior to HRMAS while the other half was not. Time-course experiments (374 min at 37°C, 9.4T, 3,000 Hz spinning rate) were carried out to monitor spectral pattern changes. Differences were assessed with Unianova test while post-HRMAS histopathology analysis was performed to assess tissue integrity.

RESULTS

Significant changes (up to 1.7 fold) were observed in samples without FMW irradiation in several spectral regions e.g. mobile lipids/lactate (0.90-1.30 ppm), acetate (1.90 ppm), N-acetyl aspartate (2.00 ppm), and Choline-containing compounds (3.19-3.25 ppm). No significant changes in the spectral pattern of FMW-irradiated samples were recorded.

CONCLUSION

We describe here a successful strategy to minimize spectral pattern changes in mouse Gbm samples using a FMW irradiation system.

Dimethyl sulfoxide (DMSO) as a potential contrast agent for brain tumors

Dimethyl sulfoxide (DMSO) is commonly used in preclinical studies of animal models of high-grade glioma as a solvent for chemotherapeutic agents. A strong DMSO signal was detected by single-voxel MRS in the brain of three C57BL/6 control mice during a pilot study of DMSO tolerance after intragastric administration. This led us to investigate the accumulation and wash-out kinetics of DMSO in both normal brain parenchyma (n=3 control mice) by single-voxel MRS, and in 12 GL261 glioblastomas (GBMs) by single-voxel MRS (n=3) and MRSI (n=9). DMSO accumulated differently in each tissue type, reaching its highest concentration in tumors: 6.18 ± 0.85 µmol/g water, 1.5-fold higher than in control mouse brain (p<0.05). A faster wash-out was detected in normal brain parenchyma with respect to GBM tissue: half-lives of 2.06 ± 0.58 and 4.57 ± 1.15 h, respectively. MRSI maps of time-course DMSO changes revealed clear hotspots of differential spatial accumulation in GL261 tumors. Additional MRSI studies with four mice bearing oligodendrogliomas (ODs) revealed similar results as in GBM tumors. The lack of T(1) contrast enhancement post-gadolinium (gadopentetate dimeglumine, Gd-DTPA) in control mouse brain and mice with ODs suggested that DMSO was fully able to cross the intact blood-brain barrier in both normal brain parenchyma and in low-grade tumors. Our results indicate a potential role for DMSO as a contrast agent for brain tumor detection, even in those tumors 'invisible' to standard gadolinium-enhanced MRI, and possibly for monitoring heterogeneities associated with progression or with therapeutic response.

Convex non-negative matrix factorization for brain tumor delimitation from MRSI data

Background

Pattern Recognition techniques can provide invaluable insights in the field of neuro-oncology. This is because the clinical analysis of brain tumors requires the use of non-invasive methods that generate complex data in electronic format. Magnetic Resonance (MR), in the modalities of spectroscopy (MRS) and spectroscopic imaging (MRSI), has been widely applied to this purpose. The heterogeneity of the tissue in the brain volumes analyzed by MR remains a challenge in terms of pathological area delimitation.

Methodology/Principal Findings

A pre-clinical study was carried out using seven brain tumor-bearing mice. Imaging and spectroscopy information was acquired from the brain tissue. A methodology is proposed to extract tissue type-specific sources from these signals by applying Convex Non-negative Matrix Factorization (Convex-NMF). Its suitability for the delimitation of pathological brain area from MRSI is experimentally confirmed by comparing the images obtained with its application to selected target regions, and to the gold standard of registered histopathology data. The former showed good accuracy for the solid tumor region (proliferation index (PI)>30%). The latter yielded (i) high sensitivity and specificity in most cases, (ii) acquisition conditions for safe thresholds in tumor and non-tumor regions (PI>30% for solid tumoral region; ≤5% for non-tumor), and (iii) fairly good results when borderline pixels were considered.

Conclusions/Significance

The unsupervised nature of Convex-NMF, which does not use prior information regarding the tumor area for its delimitation, places this approach one step ahead of classical label-requiring supervised methods for discrimination between tissue types, minimizing the negative effect of using mislabeled voxels. Convex-NMF also relaxes the non-negativity constraints on the observed data, which allows for a natural representation of the MRSI signal. This should help radiologists to accurately tackle one of the main sources of uncertainty in the clinical management of brain tumors, which is the difficulty of appropriately delimiting the pathological area.

Improving the classification of brain tumors in mice with perturbation enhanced (PE)-MRSI

Classifiers based on statistical pattern recognition analysis of MRSI data are becoming important tools for the non-invasive diagnosis of human brain tumors. Here we investigate the potential interest of perturbation-enhanced MRSI (PE-MRSI), in this case acute hyperglycemia, for improving the discrimination between mouse brain MRS patterns of glioblastoma multiforme (GBM), oligodendroglioma (ODG), and non-tumor brain parenchyma (NT). Six GBM-bearing mice and three ODG-bearing mice were scanned at 7 Tesla by PRESS-MRSI with 12 and 136 ms echo-time, during euglycemia (Eug) and also during induced acute hyperglycemia (Hyp), generating altogether four datasets per animal (echo time + glycemic condition): 12Eug, 136Eug, 12Hyp, and 136Hyp. For classifier development all spectral vectors (spv) selected from the MRSI matrix were unit length normalized (UL2) and used either as a training set (76 GBM spv, four mice; 70 ODG spv, two mice; 54 NT spv) or as an independent testing set (61 GBM spv, two mice; 31 ODG, one mouse; 23 NT spv). All Fisher's LDA classifiers obtained were evaluated as far as their descriptive performance-correctly classified cases of the training set (bootstrapping)-and predictive accuracy-balanced error rate of independent testing set classification. MRSI-based classifiers at 12Hyp were consistently more efficient in separating GBM, ODG, and NT regions, with overall accuracies always >80% and up to 95-96%; remaining classifiers were within the 48-85% range. This was also confirmed by user-independent selection of training and testing sets, using leave-one-out (LOO). This highlights the potential interest of perturbation-enhanced MRSI protocols for improving the non-invasive characterization of preclinical brain tumors.

SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

BACKGROUND

SpectraClassifier (SC) is a Java solution for designing and implementing Magnetic Resonance Spectroscopy (MRS)-based classifiers. The main goal of SC is to allow users with minimum background knowledge of multivariate statistics to perform a fully automated pattern recognition analysis. SC incorporates feature selection (greedy stepwise approach, either forward or backward), and feature extraction (PCA). Fisher Linear Discriminant Analysis is the method of choice for classification. Classifier evaluation is performed through various methods: display of the confusion matrix of the training and testing datasets; K-fold cross-validation, leave-one-out and bootstrapping as well as Receiver Operating Characteristic (ROC) curves.

RESULTS

SC is composed of the following modules: Classifier design, Data exploration, Data visualisation, Classifier evaluation, Reports, and Classifier history. It is able to read low resolution in-vivo MRS (single-voxel and multi-voxel) and high resolution tissue MRS (HRMAS), processed with existing tools (jMRUI, INTERPRET, 3DiCSI or TopSpin). In addition, to facilitate exchanging data between applications, a standard format capable of storing all the information needed for a dataset was developed. Each functionality of SC has been specifically validated with real data with the purpose of bug-testing and methods validation. Data from the INTERPRET project was used.

CONCLUSIONS

SC is a user-friendly software designed to fulfil the needs of potential users in the MRS community. It accepts all kinds of pre-processed MRS data types and classifies them semi-automatically, allowing spectroscopists to concentrate on interpretation of results with the use of its visualisation tools.