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Linear Accelerator-Based Stereotactic Radiosurgery for Cranial Intraparenchymal Metastasis of a Malignant Peripheral Nerve Sheath Tumor: Case Report and Review of the Literature.
Fenlon JB, Khattab MH, Ferguson DC, Luo G, Keedy VL, Chambless LB, Kirschner AN
(2019) World Neurosurg 123: 123-127
MeSH Terms: Adult, Brain Neoplasms, Humans, Magnetic Resonance Imaging, Male, Nerve Sheath Neoplasms, Neurofibrosarcoma, Particle Accelerators, Positron-Emission Tomography, Radiosurgery
Show Abstract · Added April 2, 2019
BACKGROUND - Malignant peripheral nerve sheath tumors (MPNSTs) are rare, aggressive soft tissue sarcomas. MPNST intracranial metastasis is exceedingly rare with only 22 documented cases in the literature and, to our knowledge, only 1 case with intraparenchymal brain metastasis. Most have been managed surgically; however, 2 documented cases were treated with Gamma Knife radiosurgery. Excluding this case report, there are no other documented cases of linear accelerator-based stereotactic radiosurgery (SRS) to treat MPNST brain metastasis.
CASE DESCRIPTION - A 41-year-old man with MPNST of the lung initially underwent tumor resection. He developed multiple systemic metastases that were managed with directed radiation therapy. A parietal brain metastasis was treated with linear accelerator-based SRS. Following SRS therapy, the patient was treated with a tropomyosin receptor kinase inhibitor. Complete resolution of brain metastasis was seen on brain magnetic resonance imaging 5 months after treatment with SRS. At 11 months after SRS, there was no evidence of recurrence or progression of the intraparenchymal disease. The patient continued to have stable extracranial disease on his ninth cycle of systemic treatment.
CONCLUSIONS - This report provides important insights into efficacy of linear accelerator-based SRS to treat MPNST brain metastases.
Copyright © 2018 Elsevier Inc. All rights reserved.
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Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer.
Hormuth DA, Weis JA, Barnes SL, Miga MI, Quaranta V, Yankeelov TE
(2018) Int J Radiat Oncol Biol Phys 100: 1270-1279
MeSH Terms: Animals, Brain Neoplasms, Cell Death, Cell Proliferation, Contrast Media, Cranial Irradiation, Diffusion Magnetic Resonance Imaging, Disease Models, Animal, Female, Glioma, Magnetic Resonance Imaging, Models, Biological, Radiation Dosage, Rats, Rats, Wistar, Treatment Outcome, Tumor Burden
Show Abstract · Added July 23, 2018
PURPOSE - To develop and investigate a set of biophysical models based on a mechanically coupled reaction-diffusion model of the spatiotemporal evolution of tumor growth after radiation therapy.
METHODS AND MATERIALS - Post-radiation therapy response is modeled using a cell death model (M), a reduced proliferation rate model (M), and cell death and reduced proliferation model (M). To evaluate each model, rats (n = 12) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging (MRI) and contrast-enhanced MRI at 7 time points over 2 weeks. Rats received either 20 or 40 Gy between the third and fourth imaging time point. Diffusion-weighted MRI was used to estimate tumor cell number within enhancing regions in contrast-enhanced MRI data. Each model was fit to the spatiotemporal evolution of tumor cell number from time point 1 to time point 5 to estimate model parameters. The estimated model parameters were then used to predict tumor growth at the final 2 imaging time points. The model prediction was evaluated by calculating the error in tumor volume estimates, average surface distance, and voxel-based cell number.
RESULTS - For both the rats treated with either 20 or 40 Gy, significantly lower error in tumor volume, average surface distance, and voxel-based cell number was observed for the M and M models compared with the M model. The M model fit, however, had significantly lower sum squared error compared with the M and M models.
CONCLUSIONS - The results of this study indicate that for both doses, the M and M models result in accurate predictions of tumor growth, whereas the M model poorly describes response to radiation therapy.
Copyright © 2017 Elsevier Inc. All rights reserved.
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17 MeSH Terms
Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological Details.
Hormuth DA, Eldridge SL, Weis JA, Miga MI, Yankeelov TE
(2018) Methods Mol Biol 1711: 225-241
MeSH Terms: Algorithms, Animals, Brain, Brain Neoplasms, Computer Simulation, Female, Glioma, Magnetic Resonance Imaging, Models, Biological, Rats, Wistar, Software
Show Abstract · Added July 23, 2018
Biophysical models designed to predict the growth and response of tumors to treatment have the potential to become a valuable tool for clinicians in care of cancer patients. Specifically, individualized tumor forecasts could be used to predict response or resistance early in the course of treatment, thereby providing an opportunity for treatment selection or adaption. This chapter discusses an experimental and modeling framework in which noninvasive imaging data is used to initialize and parameterize a subject-specific model of tumor growth. This modeling approach is applied to an analysis of murine models of glioma growth.
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Space Invaders: Brain Tumor Exploitation of the Stem Cell Niche.
Sinnaeve J, Mobley BC, Ihrie RA
(2018) Am J Pathol 188: 29-38
MeSH Terms: Animals, Brain Neoplasms, Humans, Neural Stem Cells, Neurogenesis, Stem Cell Niche
Show Abstract · Added April 10, 2019
Increasing evidence indicates that the adult neurogenic niche of the ventricular-subventricular zone (V-SVZ), beyond serving as a potential site of origin, affects the outcome of malignant brain cancers. Glioma contact with this niche predicts worse prognosis, suggesting a supportive role for the V-SVZ environment in tumor initiation or progression. In this review, we describe unique components of the V-SVZ that may permit or promote tumor growth within the region. Cell-cell interactions, soluble factors, and extracellular matrix composition are discussed, and the role of the niche in future therapies is explored. The purpose of this review is to highlight niche intrinsic factors that may promote or support malignant cell growth and maintenance, and point out how we might leverage these features to improve patient outcome.
Copyright © 2018 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
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Measurement of APT using a combined CERT-AREX approach with varying duty cycles.
Zu Z, Li H, Xu J, Zhang XY, Zaiss M, Li K, Does MD, Gore JC, Gochberg DF
(2017) Magn Reson Imaging 42: 22-31
MeSH Terms: Amides, Animals, Brain, Brain Neoplasms, Disease Models, Animal, Glioblastoma, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Phantoms, Imaging, Protons, Rats, Rats, Sprague-Dawley
Show Abstract · Added March 14, 2018
The goal is to develop an imaging method where contrast reflects amide-water magnetization exchange, with minimal signal contributions from other sources. Conventional chemical exchange saturation transfer (CEST) imaging of amides (often called amide proton transfer, or APT, and quantified by the metric MTR) is confounded by several factors unrelated to amides, such as aliphatic protons, water relaxation, and macromolecular magnetization transfer. In this work, we examined the effects of combining our previous chemical exchange rotation (CERT) approach with the non-linear AREX method while using different duty cycles (DC) for the label and reference scans. The dependencies of this approach, named AREX, on tissue parameters, including T, T, semi-solid component concentration (f), relayed nuclear Overhauser enhancement (rNOE), and nearby amines, were studied through numerical simulations and control sample experiments at 9.4T and 1μT irradiation. Simulations and experiments show that AREX is sensitive to amide-water exchange effects, but is relatively insensitive to T, T, f, nearby amine, and distant aliphatic protons, while the conventional metric MTR as well as several other APT imaging methods, are significantly affected by at least some of these confounding factors.
Copyright © 2017 Elsevier Inc. All rights reserved.
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12 MeSH Terms
Mutant IDH1 and seizures in patients with glioma.
Chen H, Judkins J, Thomas C, Wu M, Khoury L, Benjamin CG, Pacione D, Golfinos JG, Kumthekar P, Ghamsari F, Chen L, Lein P, Chetkovich DM, Snuderl M, Horbinski C
(2017) Neurology 88: 1805-1813
MeSH Terms: Action Potentials, Animals, Brain Neoplasms, Cells, Cultured, Cerebral Cortex, Chromosome Deletion, Chromosomes, Human, Pair 1, Female, Glioma, Glutarates, Humans, Isocitrate Dehydrogenase, Male, Middle Aged, Mutation, Neoplasm Grading, Neurons, Rats, Sprague-Dawley, Retrospective Studies, Seizures
Show Abstract · Added April 2, 2019
OBJECTIVE - Because the d-2-hydroxyglutarate (D2HG) product of mutant isocitrate dehydrogenase 1 (IDH1) is released by tumor cells into the microenvironment and is structurally similar to the excitatory neurotransmitter glutamate, we sought to determine whether IDH1 increases the risk of seizures in patients with glioma, and whether D2HG increases the electrical activity of neurons.
METHODS - Three WHO grade II-IV glioma cohorts from separate institutions (total N = 712) were retrospectively assessed for the presence of preoperative seizures and tumor location, WHO grade, 1p/19q codeletion, and IDH1 status. Rat cortical neurons were grown on microelectrode arrays, and their electrical activity was measured before and after treatment with exogenous D2HG, in the presence or absence of the selective NMDA antagonist, AP5.
RESULTS - Preoperative seizures were observed in 18%-34% of IDH1 wild-type (IDH1) patients and in 59%-74% of IDH1 patients ( < 0.001). Multivariable analysis, including WHO grade, 1p/19q codeletion, and temporal lobe location, showed that IDH1 was an independent correlate with seizures (odds ratio 2.5, 95% confidence interval 1.6-3.9, < 0.001). Exogenous D2HG increased the firing rate of cultured rat cortical neurons 4- to 6-fold, but was completely blocked by AP5.
CONCLUSIONS - The D2HG product of IDH1 may increase neuronal activity by mimicking the activity of glutamate on the NMDA receptor, and IDH1 gliomas are more likely to cause seizures in patients. This has rapid translational implications for the personalized management of tumor-associated epilepsy, as targeted IDH1 inhibitors may improve antiepileptic therapy in patients with IDH1 gliomas.
© 2017 American Academy of Neurology.
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A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict glioma growth.
Hormuth DA, Weis JA, Barnes SL, Miga MI, Rericha EC, Quaranta V, Yankeelov TE
(2017) J R Soc Interface 14:
MeSH Terms: Animals, Brain Neoplasms, Female, Glioma, Magnetic Resonance Imaging, Models, Biological, Neoplasms, Experimental, Rats, Rats, Wistar
Show Abstract · Added May 5, 2017
While gliomas have been extensively modelled with a reaction-diffusion (RD) type equation it is most likely an oversimplification. In this study, three mathematical models of glioma growth are developed and systematically investigated to establish a framework for accurate prediction of changes in tumour volume as well as intra-tumoural heterogeneity. Tumour cell movement was described by coupling movement to tissue stress, leading to a mechanically coupled (MC) RD model. Intra-tumour heterogeneity was described by including a voxel-specific carrying capacity (CC) to the RD model. The MC and CC models were also combined in a third model. To evaluate these models, rats ( = 14) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging over 10 days to estimate tumour cellularity. Model parameters were estimated from the first three imaging time points and then used to predict tumour growth at the remaining time points which were then directly compared to experimental data. The results in this work demonstrate that mechanical-biological effects are a necessary component of brain tissue tumour modelling efforts. The results are suggestive that a variable tissue carrying capacity is a needed model component to capture tumour heterogeneity. Lastly, the results advocate the need for additional effort towards capturing tumour-to-tissue infiltration.
© 2017 The Author(s).
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9 MeSH Terms
Spin-lock imaging of exogenous exchange-based contrast agents to assess tissue pH.
Zu Z, Li H, Jiang X, Gore JC
(2018) Magn Reson Med 79: 298-305
MeSH Terms: Animals, Brain, Brain Neoplasms, Contrast Media, Glioblastoma, Hydrogen-Ion Concentration, Iohexol, Magnetic Resonance Imaging, Mannitol, Models, Theoretical, Phantoms, Imaging, Rats
Show Abstract · Added April 6, 2017
PURPOSE - Some X-ray contrast agents contain exchangeable protons that give rise to exchange-based effects on MRI, including chemical exchange saturation transfer (CEST). However, CEST has poor specificity to explicit exchange parameters. Spin-lock sequences at high field are also sensitive to chemical exchange. Here, we evaluate whether spin-locking techniques can detect the contrast agent iohexol in vivo after intravenous administration, and their potential for measuring changes in tissue pH.
METHODS - Two metrics of contrast based on R , the spin lattice relaxation rate in the rotating frame, were derived from the behavior of R at different locking fields. Solutions containing iohexol at different concentrations and pH were used to evaluate the ability of the two metrics to quantify exchange effects. Images were also acquired from rat brains bearing tumors before and after intravenous injections of iohexol to evaluate the potential of spin-lock techniques for detecting the agent and pH variations.
RESULTS - The two metrics were found to depend separately on either agent concentration or pH. Spin-lock imaging may therefore provide specific quantification of iohexol concentration and the iohexol-water exchange rate, which reports on pH.
CONCLUSIONS - Spin-lock techniques may be used to assess the dynamics of intravenous contrast agents and detect extracellular acidification. Magn Reson Med 79:298-305, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
© 2017 International Society for Magnetic Resonance in Medicine.
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CEST imaging of fast exchanging amine pools with corrections for competing effects at 9.4 T.
Zhang XY, Wang F, Li H, Xu J, Gochberg DF, Gore JC, Zu Z
(2017) NMR Biomed 30:
MeSH Terms: Algorithms, Amines, Animals, Artifacts, Biomarkers, Tumor, Brain Neoplasms, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Molecular Imaging, Proton Magnetic Resonance Spectroscopy, Rats, Reproducibility of Results, Sensitivity and Specificity
Show Abstract · Added March 13, 2017
Chemical exchange saturation transfer (CEST) imaging of fast exchanging amine protons at 3 ppm offset from the water resonant frequency is of practical interest, but quantification of fast exchanging pools by CEST is challenging. To effectively saturate fast exchanging protons, high irradiation powers need to be applied, but these may cause significant direct water saturation as well as non-specific semi-solid magnetization transfer (MT) effects, and thus decrease the specificity of the measured signal. In addition, the CEST signal may depend on the water longitudinal relaxation time (T ), which likely varies between tissues and with pathology, further reducing specificity. Previously, an analysis of the asymmetry of saturation effects (MTR ) has been commonly used to quantify fast exchanging amine CEST signals. However, our results show that MTR is greatly affected by the above factors, as well as asymmetric MT and nuclear Overhauser enhancement (NOE) effects. Here, we instead applied a relatively more specific inverse analysis method, named AREX (apparent exchange-dependent relaxation), that has previously been applied only to slow and intermediate exchanging solutes. Numerical simulations and controlled phantom experiments show that, although MTR depends on T and semi-solid content, AREX acquired in steady state does not, which suggests that AREX is more specific than MTR . By combining with a fitting approach instead of using the asymmetric analysis to obtain reference signals, AREX can also avoid contaminations from asymmetric MT and NOE effects. Animal experiments show that these two quantification methods produce differing contrasts between tumors and contralateral normal tissues in rat brain tumor models, suggesting that conventional MTR applied in vivo may be influenced by variations in T , semi-solid content, or NOE effect. Thus, the use of MTR may lead to misinterpretation, while AREX with corrections for competing effects likely enhances the specificity and accuracy of quantification to fast exchanging pools.
Copyright © 2017 John Wiley & Sons, Ltd.
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14 MeSH Terms
Accuracy in the quantification of chemical exchange saturation transfer (CEST) and relayed nuclear Overhauser enhancement (rNOE) saturation transfer effects.
Zhang XY, Wang F, Li H, Xu J, Gochberg DF, Gore JC, Zu Z
(2017) NMR Biomed 30:
MeSH Terms: Algorithms, Amines, Animals, Artifacts, Biomarkers, Tumor, Brain Neoplasms, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Molecular Imaging, Proton Magnetic Resonance Spectroscopy, Rats, Reproducibility of Results, Sensitivity and Specificity
Show Abstract · Added March 13, 2017
Accurate quantification of chemical exchange saturation transfer (CEST) effects, including dipole-dipole mediated relayed nuclear Overhauser enhancement (rNOE) saturation transfer, is important for applications and studies of molecular concentration and transfer rate (and thereby pH or temperature). Although several quantification methods, such as Lorentzian difference (LD) analysis, multiple-pool Lorentzian fits, and the three-point method, have been extensively used in several preclinical and clinical applications, the accuracy of these methods has not been evaluated. Here we simulated multiple-pool Z spectra containing the pools that contribute to the main CEST and rNOE saturation transfer signals in the brain, numerically fit them using the different methods, and then compared their derived CEST metrics with the known solute concentrations and exchange rates. Our results show that the LD analysis overestimates contributions from amide proton transfer (APT) and intermediate exchanging amine protons; the three-point method significantly underestimates both APT and rNOE saturation transfer at -3.5 ppm (NOE(-3.5)). The multiple-pool Lorentzian fit is more accurate than the other two methods, but only at lower irradiation powers (≤1 μT at 9.4 T) within the range of our simulations. At higher irradiation powers, this method is also inaccurate because of the presence of a fast exchanging CEST signal that has a non-Lorentzian lineshape. Quantitative parameters derived from in vivo images of rodent brain tumor obtained using an irradiation power of 1 μT were also compared. Our results demonstrate that all three quantification methods show similar contrasts between tumor and contralateral normal tissue for both APT and the NOE(-3.5). However, the quantified values of the three methods are significantly different. Our work provides insight into the fitting accuracy obtainable in a complex tissue model and provides guidelines for evaluating other newly developed quantification methods.
Copyright © 2017 John Wiley & Sons, Ltd.
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14 MeSH Terms