Structural and functional effects of metastases in rat brain determined by multimodal MRI

An Effective Approach to Improve the Automatic Segmentation and Classification Accuracy of Brain Metastasis by Combining Multi-phase Delay Enhanced MR Images

The objective of this study is to analyse the diffusion rule of the contrast media in multi-phase delayed enhanced magnetic resonance (MR) T1 images using radiomics and to construct an automatic classification and segmentation model of brain metastases (BM) based on support vector machine (SVM) and Dpn-UNet. A total of 189 BM patients with 1047 metastases were enrolled. Contrast-enhanced MR images were obtained at 1, 3, 5, 10, 18, and 20 min following contrast medium injection. The tumour target volume was delineated, and the radiomics features were extracted and analysed. BM segmentation and classification models in the MR images with different enhancement phases were constructed using Dpn-UNet and SVM, and differences in the BM segmentation and classification models with different enhancement times were compared. (1) The signal intensity for BM decreased with time delay and peaked at 3 min. (2) Among the 144 optimal radiomics features, 22 showed strong correlation with time (highest R-value = 0.82), while 41 showed strong correlation with volume (highest R-value = 0.99). (3) The average dice similarity coefficients of both the training and test sets were the highest at 10 min for the automatic segmentation of BM, reaching 0.92 and 0.82, respectively. (4) The areas under the curve (AUCs) for the classification of BM pathology type applying single-phase MRI was the highest at 10 min, reaching 0.674. The AUC for the classification of BM by applying the six-phase image combination was the highest, reaching 0.9596, and improved by 42.3% compared with that by applying single-phase images at 10 min. The dynamic changes of contrast media diffusion in BM can be reflected by multi-phase delayed enhancement based on radiomics, which can more objectively reflect the pathological types and significantly improve the accuracy of BM segmentation and classification.

Imaging angiogenesis in an intracerebrally induced model of brain macrometastasis using αv β3 -targeted iron oxide microparticles

Brain metastasis is responsible for a large proportion of cancer mortality, and there are currently no effective treatments. Moreover, the impact of treatments, particularly antiangiogenic therapeutics, is difficult to ascertain using current magnetic resonance imaging (MRI) methods. Imaging of the angiogenic vasculature has been successfully carried out in solid tumours using microparticles of iron oxide (MPIO) conjugated to a Arg-Gly-Asp peptide (RGD) targeting integrin αv β3 . The aim of this study was to determine whether RGD-MPIO could be used to identify angiogenic blood vessels in brain metastases in vivo. A mouse model of intracerebrally implanted brain macrometastasis was established through intracerebral injection of 4T1-GFP cells. T2 *-weighted imaging was used to visualise MPIO-induced hypointense voxels in vivo, and Prussian blue staining was used to visualise MPIO and endogenous iron histologically ex vivo. The RGD-MPIO showed target-specific binding in vivo, but the sensitivity of the agent for visualising angiogenic vessels per se was reduced by the presence of endogenous iron-laden macrophages in larger metastases, resulting in pre-existing hypointense areas within the tumour. Further, our data suggest that peptide-targeted MPIO, but not antibody-targeted MPIO, are taken up by perivascular macrophages within the macrometastatic microenvironment, resulting in additional nonspecific contrast. While pre-MPIO imaging will circumvent the issues surrounding pre-existing hypointensities and enable detection of specific contrast, our preliminary findings suggest that the use of antibodies rather than peptides as the targeting ligand may represent a preferable route forward for new angiogenesis-targeted molecular MRI agents.

Inhibition of Anti-Inflammatory Macrophage Phenotype Reduces Tumour Growth in Mouse Models of Brain Metastasis

Breast cancer brain metastasis is a significant clinical problem and carries a poor prognosis. Although it is well-established that macrophages are a primary component of the brain metastasis microenvironment, the role of blood-derived macrophages (BDM) and brain-resident microglia in the progression of brain metastases remains uncertain. The aim of this study, therefore, was to determine the role, specifically, of pro- and anti-inflammatory BDM and microglial phenotypes on metastasis progression. Initial in vitro studies demonstrated decreased migration of EO771 metastatic breast cancer cells in the presence of pro-inflammatory, but not anti-inflammatory, stimulated RAW 264.7 macrophages. In vivo, suppression of the anti-inflammatory BDM phenotype, specifically, via myeloid knock out of Krüppel-like Factor 4 (KLF4) significantly reduced EO771 tumour growth in the brains of C57BL/6 mice. Further, pharmacological inhibition of the anti-inflammatory BDM and/or microglial phenotypes, via either Colony Stimulating Factor 1 Receptor (CSF-1R) or STAT6 pathways, significantly decreased tumour burden in two different syngeneic mouse models of breast cancer brain metastasis. These findings suggest that switching BDM and microglia towards a more pro-inflammatory phenotype may be an effective therapeutic strategy in brain metastasis.

The Role of the Immune Response in Brain Metastases: Novel Imaging Biomarkers for Immunotherapy

Brain metastases are a major clinical problem, and immunotherapy offers a novel treatment paradigm with the potential to synergize with existing focal therapies like surgery and radiosurgery or even replace them in future. The brain is a unique microenvironment structurally and immunologically. The immune response is likely to be crucial to the adaptation of systemic immune modulating agents against this disease. Imaging is frequently employed in the clinical diagnosis and management of brain metastasis, so it is logical that brain imaging techniques are investigated as a source of biomarkers of the immune response in these tumors. Current imaging techniques in clinical use include structural MRI (post-contrast T1W sequences, T2, and FLAIR), physiological sequences (perfusion- and diffusion-weighted imaging), and molecular imaging (MR spectroscopy and PET). These are reviewed for their application to predicting and measuring the response to immunotherapy in brain metastases.

Current landscape and future perspectives in preclinical MR and PET imaging of brain metastasis

Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imaging (MRI) and positron emission tomography (PET) represent important resources to assess tumor progression and treatment responses. In preclinical research, anatomical MRI and to some extent functional MRI have frequently been used to assess tumor progression. In contrast, PET has only to a limited extent been used in animal BM research. A considerable culprit is that results from most preclinical studies have shown little impact on the implementation of new treatment strategies in the clinic. This emphasizes the need for the development of robust, high-quality preclinical imaging strategies with potential for clinical translation. This review focuses on advanced preclinical MRI and PET imaging methods for BM, describing their applications in the context of what has been done in the clinic. The strengths and shortcomings of each technology are presented, and recommendations for future directions in the development of the individual imaging modalities are suggested. Finally, we highlight recent developments in quantitative MRI and PET, the use of radiomics and multimodal imaging, and the need for a standardization of imaging technologies and protocols between preclinical centers.

STAT3-Mediated Astrocyte Reactivity Associated with Brain Metastasis Contributes to Neurovascular Dysfunction

Astrocytes are thought to play a pivotal role in coupling neural activity and cerebral blood flow. However, it has been shown that astrocytes undergo morphologic changes in response to brain metastasis, switching to a reactive phenotype, which has the potential to significantly compromise cerebrovascular function and contribute to the neurological sequelae associated with brain metastasis. Given that STAT3 is a key regulator of astrocyte reactivity, we aimed here to determine the impact of STAT3-mediated astrocyte reactivity on neurovascular function in brain metastasis. Rat models of brain metastasis and ciliary neurotrophic factor were used to induce astrocyte reactivity. Multimodal imaging, electrophysiology, and IHC were performed to determine the relationship between reactive astrocytes and changes in the cerebrovascular response to electrical and physiological stimuli. Subsequently, the STAT3 pathway in astrocytes was inhibited with WP1066 to determine the role of STAT3-mediated astrocyte reactivity, specifically, in brain metastasis. Astrocyte reactivity associated with brain metastases impaired cerebrovascular responses to stimuli at both the cellular and functional level and disrupted astrocyte-endothelial interactions in both animal models and human brain metastasis samples. Inhibition of STAT3-mediated astrocyte reactivity in rats with brain metastases restored cerebrovascular function, as shown by in vivo imaging, and limited cerebrovascular changes associated with tumor growth. Together these findings suggest that inhibiting STAT3-mediated astrocyte reactivity may confer significant improvements in neurological outcome for patients with brain metastases and could potentially be tested in other brain tumors. SIGNIFICANCE: These findings demonstrate that selectively targeting STAT3-mediated astrocyte reactivity ameliorates the cerebrovascular dysfunction associated with brain metastasis, providing a potential therapeutic avenue for improved patient outcome.

Improving Delineation of True Tumor Volume With Multimodal MRI in a Rat Model of Brain Metastasis

PURPOSE

Brain metastases are almost universally lethal with short median survival times. Despite this, they are often potentially curable, with therapy failing only because of local relapse. One key reason relapse occurs is because treatment planning did not delineate metastasis margins sufficiently or accurately, allowing residual tumor to regrow. The aim of this study was to determine the extent to which multimodal magnetic resonance imaging (MRI), with a simple and automated analysis pipeline, could improve upon current clinical practice of single-modality, independent-observer tumor delineation.

METHODS AND MATERIALS

We used a single rat model of brain metastasis (ENU1564 breast carcinoma cells in BD-IX rats), with and without radiation therapy. Multimodal MRI data were acquired using sequences either in current clinical use or in clinical trial and included postgadolinium T1-weighted images and maps of blood flow, blood volume, T1 and T2 relaxation times, and apparent diffusion coefficient.

RESULTS

In all cases, independent observers underestimated the true size of metastases from single-modality gadolinium-enhanced MRI (85 ± 36 μL vs 131 ± 40 μL histologic measurement), although multimodal MRI more accurately delineated tumor volume (132 ± 41 μL). Multimodal MRI offered increased sensitivity compared with independent observer for detecting metastasis (0.82 vs 0.61, respectively), with only a slight decrease in specificity (0.86 vs 0.98). Blood flow maps conferred the greatest improvements in margin detection for late-stage metastases after radiation therapy. Gadolinium-enhanced T1-weighted images conferred the greatest increase in accuracy of detection for smaller metastases.

CONCLUSIONS

These findings suggest that multimodal MRI of brain metastases could significantly improve the visualization of brain metastasis margins, beyond current clinical practice, with the potential to decrease relapse rates and increase patient survival. This finding now needs validation in additional tumor models or clinical cohorts.

Does the application of diffusion weighted imaging improve the prediction of survival in patients with resected brain metastases? A retrospective multicenter study

BACKGROUND

Brain metastases are common in clinical practice. Many clinical scales exist for predicting survival and hence deciding on best treatment but none are individualised and none use quantitative imaging parameters. A multicenter study was carried out to evaluate the prognostic utility of a simple diffusion weighted MRI parameter, tumor apparent diffusion coefficient (ADC).

METHODS

A retrospective analysis of imaging and clinical data was performed on a cohort of 223 adult patients over a ten-year period 2002-2012 pooled from three institutions. All patients underwent surgical resection with histologically confirmed brain metastases and received adjuvant whole brain radiotherapy and/or chemotherapy. Survival was modelled using standard clinical variables and statistically compared with and without the addition of tumor ADC.

RESULTS

The median overall survival was 9.6 months (95% CI 7.5-11.7) for this cohort. Greater age (p = 0.002), worse performance status (p < 0.0001) and uncontrolled extracranial disease (p < 0.0001) were all significantly associated with shorter survival in univariate analysis. Adjuvant whole brain radiotherapy (p = 0.007) and higher tumor ADC (p < 0.001) were associated with prolonged survival. Combining values of tumor ADC with conventional clinical scoring systems such as the Graded Prognostic Assessment (GPA) score significantly improved the modelling of survival (e.g. concordance increased from 0.5956 to 0.6277 with Akaike's Information Criterion reduced from 1335 to 1324).

CONCLUSIONS

Combining advanced MRI readings such as tumor ADC with clinical scoring systems is a potentially simple method for improving and individualising the estimation of survival in patients having surgery for brain metastases.

Discrimination Between Solitary Brain Metastasis and Glioblastoma Multiforme by Using ADC-Based Texture Analysis: A Comparison of Two Different ROI Placements

RATIONALE AND OBJECTIVES

To explore the value of texture analysis based on the apparent diffusion coefficient (ADC) value and the effect of region of interest (ROI) placements in distinguishing glioblastoma multiforme (GBM) from solitary brain metastasis (sMET).

MATERIALS AND METHODS

Sixty-two patients with pathologically confirmed GBM (n = 36) and sMET (n = 26) were retrospectively included. All patients underwent diffusion-weighted imaging with b values of 0 and 1000 s/mm², and the ADC maps were generated automatically. ROIs were placed on the largest whole single-slice tumor (ROI1) and the enhanced solid portion (ROI2) of the ADC maps, respectively. The texture feature metrics of the histogram and gray-level co-occurrence matrix were then extracted by using in-house software. The parameters of the texture analysis were compared between GBM and sMET, using the Mann-Whitney U test. A receiver operating characteristic (ROC) curve analysis was performed to determine the best parameters for distinguishing between GBM from sMET.

RESULTS

Homogeneity and the inverse difference moment (IDM) of GBM were significantly higher than those of sMET in both ROIs (ROI1, p = 0.014 for homogeneity and p = 0.048 for IDM; ROI2, p< 0.001 for homogeneity and p = 0.029 for IDM). According to the ROC curve analysis, the area under the ROC curve (AUC) of homogeneity in ROI1 (AUC, 0.682, sensitivity, 72.2%, specificity, 61.5%) was significantly lower than that of ROI2 (AUC, 0.886, sensitivity, 83.3%, specificity, 76.9%; p= 0.012), whereas the IDM showed no statistical significance between two ROIs (p> 0.05).

CONCLUSION

The ADC-based texture analysis can help differentiate GBM from sMET, and the ROI on the solid portion would be recommended to calculate the ADC-based texture metrics.

Development of Therapeutic Anti-JAGGED1 Antibodies for Cancer Therapy

The role of Notch signaling and its ligand JAGGED1 (JAG1) in tumor biology has been firmly established, making them appealing therapeutic targets for cancer treatment. Here, we report the development and characterization of human/rat-specific JAG1-neutralizing mAbs. Epitope mapping identified their binding to the Notch receptor interaction site within the JAG1 Delta/Serrate/Lag2 domain, where E228D substitution prevented effective binding to the murine Jag1 ortholog. These antibodies were able to specifically inhibit JAG1-Notch binding in vitro, downregulate Notch signaling in cancer cells, and block the heterotypic JAG1-mediated Notch signaling between endothelial and vascular smooth muscle cells. Functionally, in vitro treatment impaired three-dimensional growth of breast cancer cell spheroids, in association with a reduction in cancer stem cell number. In vivo testing showed variable effects on human xenograft growth when only tumor-expressed JAG1 was targeted (mouse models) but a more robust effect when stromal-expressed Jag1 was also targeted (rat MDA-MB-231 xenograft model). Importantly, treatment of established triple receptor-negative breast cancer brain metastasis in rats showed a significant reduction in neoplastic growth. MRI imaging demonstrated that this was associated with a substantial improvement in blood-brain barrier function and tumor perfusion. Lastly, JAG1-targeting antibody treatment did not cause any detectable toxicity, further supporting its clinical potential for cancer therapy.

Dynamic urinary proteomic analysis in a Walker 256 intracerebral tumor model

BACKGROUND

Patients with primary and metastatic brain cancer have an extremely poor prognosis, mostly due to the late diagnosis of disease. Urine, which lacks homeostatic mechanisms, is an ideal biomarker source that accumulates early and highly sensitive changes to provide information about the early stage of disease.

METHODS

A rat model mimicking the local tumor growth process in the brain was established with intracerebral Walker 256 (W256) cell injection. Urine samples were collected on days 3, 5, and 8 after injection, and then analyzed by liquid chromatography coupled with tandem mass spectrometry.

RESULTS

In the intracerebral W256 model, no obvious clinical manifestations or abnormal magnetic resonance imaging (MRI) signals were found on days 3 or 5; at these time points, 9 proteins were changed significantly in the urine of all eight tumor rats. On day 8, when tumors were detected by MRI, 25 differential proteins were identified, including 10 that have been reported to be closely related to brain metastasis or primary tumors. The differential urinary proteome was compared with those from the subcutaneous W256 model and the intracerebral C6 model. Few differential proteins overlapped, and specific differential protein patterns were observed among the three models.

CONCLUSIONS

These findings demonstrate that early changes in the urine proteome can be detected in the intracerebral W256 model. The urinary proteome can reflect the difference when tumor cells with different growth characteristics are inoculated into the brain and when identical tumor cells are inoculated into different areas, specifically, the subcutis and the brain.

Tumor pH and Protein Concentration Contribute to the Signal of Amide Proton Transfer Magnetic Resonance Imaging

Abnormal pH is a common feature of malignant tumors and has been associated clinically with suboptimal outcomes. Amide proton transfer magnetic resonance imaging (APT MRI) holds promise as a means to noninvasively measure tumor pH, yet multiple factors collectively make quantification of tumor pH from APT MRI data challenging. The purpose of this study was to improve our understanding of the biophysical sources of altered APT MRI signals in tumors. Combining in vivo APT MRI measurements with ex vivo histological measurements of protein concentration in a rat model of brain metastasis, we determined that the proportion of APT MRI signal originating from changes in protein concentration was approximately 66%, with the remaining 34% originating from changes in tumor pH. In a mouse model of hypopharyngeal squamous cell carcinoma (FaDu), APT MRI showed that a reduction in tumor hypoxia was associated with a shift in tumor pH. The results of this study extend our understanding of APT MRI data and may enable the use of APT MRI to infer the pH of individual patients' tumors as either a biomarker for therapy stratification or as a measure of therapeutic response in clinical settings. SIGNIFICANCE: These findings advance our understanding of amide proton transfer magnetic resonance imaging (APT MRI) of tumors and may improve the interpretation of APT MRI in clinical settings.

13C Pyruvate Transport Across the Blood-Brain Barrier in Preclinical Hyperpolarised MRI

Hyperpolarised MRI with Dynamic Nuclear Polarisation overcomes the fundamental thermodynamic limitations of conventional magnetic resonance, and is translating to human studies with several early-phase clinical trials in progress including early reports that demonstrate the utility of the technique to observe lactate production in human brain cancer patients. Owing to the fundamental coupling of metabolism and tissue function, metabolic neuroimaging with hyperpolarised [1-13C]pyruvate has the potential to be revolutionary in numerous neurological disorders (e.g. brain tumour, ischemic stroke, and multiple sclerosis). Through the use of [1-13C]pyruvate and ethyl-[1-13C]pyruvate in naïve brain, a rodent model of metastasis to the brain, or porcine brain subjected to mannitol osmotic shock, we show that pyruvate transport across the blood-brain barrier of anaesthetised animals is rate-limiting. We show through use of a well-characterised rat model of brain metastasis that the appearance of hyperpolarized [1-13C]lactate production corresponds to the point of blood-brain barrier breakdown in the disease. With the more lipophilic ethyl-[1-13C]pyruvate, we observe pyruvate production endogenously throughout the entire brain and lactate production only in the region of disease. In the in vivo porcine brain we show that mannitol shock permeabilises the blood-brain barrier sufficiently for a dramatic 90-fold increase in pyruvate transport and conversion to lactate in the brain, which is otherwise not resolvable. This suggests that earlier reports of whole-brain metabolism in anaesthetised animals may be confounded by partial volume effects and not informative enough for translational studies. Issues relating to pyruvate transport and partial volume effects must therefore be considered in pre-clinical studies investigating neuro-metabolism in anaesthetised animals, and we additionally note that these same techniques may provide a distinct biomarker of blood-brain barrier permeability in future studies.

T-Cell Densities in Brain Metastases Are Associated with Patient Survival Times and Diffusion Tensor MRI Changes

Brain metastases are common and are usually detected by MRI. Diffusion tensor imaging (DTI) is a derivative MRI technique that can detect disruption of white matter tracts in the brain. We have matched preoperative DTI with image-guided sampling of the brain-tumor interface in 26 patients during resection of a brain metastasis and assessed mean diffusivity and fractional anisotropy (FA). The tissue samples were analyzed for vascularity, inflammatory cell infiltration, growth pattern, and tumor expression of proteins associated with growth or local invasion such as Ki67, S100A4, and MMP2, 9, and 13. A lower FA in the peritumoral region indicated more white matter tract disruption and independently predicted longer overall survival times (HR for death = 0.21; 95% confidence interval, 0.06-0.82; P = 0.024). Of all the biological markers studied, only increased density of CD3⁺ lymphocytes in the same region correlated with decreased FA (Mann-Whitney U, P = 0.037) as well as confounding completely the effect of FA on multivariate survival analyses. We conclude that the T-cell response to brain metastases is not a surrogate of local tumor invasion, primary cancer type, or aggressive phenotype and is associated with patient survival time regardless of these biological factors. Furthermore, it can be assayed by DTI, potentially offering a quick, noninvasive, clinically available method to detect an active immune microenvironment and, in principle, to measure susceptibility to immunotherapy.Significance: These findings show that white matter tract integrity is degraded in areas where T-cell infiltration is highest, providing a noninvasive method to identify immunologically active microenvironments in secondary brain tumors. Cancer Res; 78(3); 610-6. ©2017 AACR.

Quantitative and textural analysis of magnetization transfer and diffusion images in the early detection of brain metastases

PURPOSE

The sensitivity of the magnetization transfer ratio (MTR) and apparent diffusion coefficient (ADC) for early detection of brain metastases was investigated in mice and humans.

METHODS

Mice underwent MRI twice weekly for up to 31 d following intracardiac injection of the brain-homing breast cancer cell line MDA-MB231-BR. Patients with small cell lung cancer underwent quarterly MRI for 1 year. MTR and ADC were measured in regions of metastasis and matched contralateral tissue at the final time point and in registered regions at earlier time points. Texture analysis and linear discriminant analysis were performed to detect metastasis-containing slices.

RESULTS

Compared with contralateral tissue, mouse metastases had significantly lower MTR and higher ADC at the final time point. Some lesions were visible at earlier time points on the MTR and ADC maps: 24% of these were not visible on corresponding T2 -weighted images. Texture analysis using the MTR maps showed 100% specificity and 98% sensitivity for metastasis at the final time point, with 77% sensitivity 2-4 d earlier and 46% 5-8 d earlier. Only 2 of 16 patients developed metastases, and their penultimate scans were normal.

CONCLUSIONS

Some brain metastases may be detected earlier on MTR than conventional T2 ; however, the small gain is unlikely to justify "predictive" MRI. Magn Reson Med 77:1987-1995, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Use of diffusion-weighted MRI to modify radiosurgery planning in brain metastases may reduce local recurrence

Stereotactic radiosurgery (SRS) is an effective and well tolerated treatment for selected brain metastases; however, local recurrence still occurs. We investigated the use of diffusion weighted MRI (DWI) as an adjunct for SRS treatment planning in brain metastases. Seventeen consecutive patients undergoing complete surgical resection of a solitary brain metastasis underwent image analysis retrospectively. SRS treatment plans were generated based on standard 3D post-contrast T1-weighted sequences at 1.5T and then separately using apparent diffusion coefficient (ADC) maps in a blinded fashion. Control scans immediately post operation confirmed complete tumour resection. Treatment plans were compared to one another and with volume of local recurrence at progression quantitatively and qualitatively by calculating the conformity index (CI), the overlapping volume as a proportion of the total combined volume, where 1 = identical plans and 0 = no conformation whatsoever. Gross tumour volumes (GTVs) using ADC and post-contrast T1-weighted sequences were quantitatively the same (related samples Wilcoxon signed rank test = -0.45, p = 0.653) but showed differing conformations (CI 0.53, p < 0.001). The diffusion treatment volume (DTV) obtained by combining the two target volumes was significantly greater than the treatment volume based on post contrast T1-weighted MRI alone, both quantitatively (median 13.65 vs. 9.52 cm3, related samples Wilcoxon signed rank test p < 0.001) and qualitatively (CI 0.74, p = 0.001). This DTV covered a greater volume of subsequent tumour recurrence than the standard plan (median 3.53 cm3 vs. 3.84 cm3, p = 0.002). ADC maps may be a useful tool in addition to the standard post-contrast T1-weighted sequence used for SRS planning.

Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms

The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym , APT*, MTRRex , AREX and CESTR* with and without T1 /T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1 /T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents.

Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice

Over 20% of cancer patients will develop brain metastases. Prognosis is currently extremely poor, largely owing to late-stage diagnosis. We hypothesized that biofluid metabolomics could detect tumours at the micrometastatic stage, prior to the current clinical gold-standard of blood-brain barrier breakdown. Metastatic mammary carcinoma cells (4T1-GFP) were injected into BALB/c mice via intracerebral, intracardiac or intravenous routes to induce differing cerebral and systemic tumour burdens. B16F10 melanoma and MDA231BR-GFP human breast carcinoma cells were used for additional modelling. Urine metabolite composition was analysed by 1H NMR spectroscopy. Statistical pattern recognition and modelling was applied to identify differences or commonalities indicative of brain metastasis burden. Significant metabolic profile separations were found between control cohorts and animals with tumour burdens at all time-points for the intracerebral 4T1-GFP time-course. Models became stronger, with higher sensitivity and specificity, as the time-course progressed indicating a more severe tumour burden. Sensitivity and specificity for predicting a blinded testing set were 0.89 and 0.82, respectively, at day 5, both rising to 1.00 at day 35. Significant separations were also found between control and all 4T1-GFP injected mice irrespective of route. Likewise, significant separations were observed in B16F10 and MDA231BR-GFP cell line models. Metabolites underpinning each separation were identified. These findings demonstrate that brain metastases can be diagnosed in an animal model based on urinary metabolomics from micrometastatic stages. Furthermore, it is possible to separate differing systemic and CNS tumour burdens, suggesting a metabolite fingerprint specific to brain metastasis. This method has strong potential for clinical translation.

SCF (Fbxl17) ubiquitylation of Sufu regulates Hedgehog signaling and medulloblastoma development

Skp1-Cul1-F-box protein (SCF) ubiquitin ligases direct cell survival decisions by controlling protein ubiquitylation and degradation. Sufu (Suppressor of fused) is a central regulator of Hh (Hedgehog) signaling and acts as a tumor suppressor by maintaining the Gli (Glioma-associated oncogene homolog) transcription factors inactive. Although Sufu has a pivotal role in Hh signaling, the players involved in controlling Sufu levels and their role in tumor growth are unknown. Here, we show that Fbxl17 (F-box and leucine-rich repeat protein 17) targets Sufu for proteolysis in the nucleus. The ubiquitylation of Sufu, mediated by Fbxl17, allows the release of Gli1 from Sufu for proper Hh signal transduction. Depletion of Fbxl17 leads to defective Hh signaling associated with an impaired cancer cell proliferation and medulloblastoma tumor growth. Furthermore, we identify a mutation in Sufu, occurring in medulloblastoma of patients with Gorlin syndrome, which increases Sufu turnover through Fbxl17-mediated polyubiquitylation and leads to a sustained Hh signaling activation. In summary, our findings reveal Fbxl17 as a novel regulator of Hh pathway and highlight the perturbation of the Fbxl17-Sufu axis in the pathogenesis of medulloblastoma.

Contributions and complexities from the use of in vivo animal models to improve understanding of human neuroimaging signals

Many of the major advances in our understanding of how functional brain imaging signals relate to neuronal activity over the previous two decades have arisen from physiological research studies involving experimental animal models. This approach has been successful partly because it provides opportunities to measure both the hemodynamic changes that underpin many human functional brain imaging techniques and the neuronal activity about which we wish to make inferences. Although research into the coupling of neuronal and hemodynamic responses using animal models has provided a general validation of the correspondence of neuroimaging signals to specific types of neuronal activity, it is also highlighting the key complexities and uncertainties in estimating neural signals from hemodynamic markers. This review will detail how research in animal models is contributing to our rapidly evolving understanding of what human neuroimaging techniques tell us about neuronal activity. It will highlight emerging issues in the interpretation of neuroimaging data that arise from in vivo research studies, for example spatial and temporal constraints to neuroimaging signal interpretation, or the effects of disease and modulatory neurotransmitters upon neurovascular coupling. We will also give critical consideration to the limitations and possible complexities of translating data acquired in the typical animals models used in this area to the arena of human fMRI. These include the commonplace use of anesthesia in animal research studies and the fact that many neuropsychological questions that are being actively explored in humans have limited homologs within current animal models for neuroimaging research. Finally we will highlighting approaches, both in experimental animals models (e.g. imaging in conscious, behaving animals) and human studies (e.g. combined fMRI-EEG), that mitigate against these challenges.

Diffusion-weighted MRI characteristics of the cerebral metastasis to brain boundary predicts patient outcomes

Background

Diffusion-weighted MRI (DWI) has been used in neurosurgical practice mainly to distinguish cerebral metastases from abscess and glioma. There is evidence from other solid organ cancers and metastases that DWI may be used as a biomarker of prognosis and treatment response. We therefore investigated DWI characteristics of cerebral metastases and their peritumoral region recorded pre-operatively and related these to patient outcomes.

Methods

Retrospective analysis of 76 cases operated upon at a single institution with DWI performed pre-operatively at 1.5T. Maps of apparent diffusion coefficient (ADC) were generated using standard protocols. Readings were taken from the tumor, peritumoral region and across the brain-tumor interface. Patient outcomes were overall survival and time to local recurrence.

Results

A minimum ADC greater than 919.4 × 10^-6 mm²/s within a metastasis predicted longer overall survival regardless of adjuvant therapies. This was not simply due to differences between the types of primary cancer because the effect was observed even in a subgroup of 36 patients with the same primary, non-small cell lung cancer. The change in diffusion across the tumor border and into peritumoral brain was measured by the “ADC transition coefficient” or ATC and this was more strongly predictive than ADC readings alone. Metastases with a sharp change in diffusion across their border (ATC >0.279) showed shorter overall survival compared to those with a more diffuse edge. The ATC was the only imaging measurement which independently predicted overall survival in multivariate analysis (hazard ratio 0.54, 95% CI 0.3 – 0.97, p = 0.04).

Conclusions

DWI demonstrates changes in the tumor, across the tumor edge and in the peritumoral region which may not be visible on conventional MRI and this may be useful in predicting patient outcomes for operated cerebral metastases.