72 research outputs found

    Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

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    Abstract Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images

    Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

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    Objectives: At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community. Methods: Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media. Results: Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%). Conclusion: Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed. Key Points: • We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.• Perfusion MRI is recommended for diagnosis and follow-up of glioma.• Use of advanced imaging could be promoted with increased education activities.• Most response assessment is currently performed qualitatively.• Reporting templates are not widely used, and could facilitate standardisation

    New aspects in the pathogenesis, prevention, and treatment of hyponatremic encephalopathy in children

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    Hyponatremia is the most common electrolyte abnormality encountered in children. In the past decade, new advances have been made in understanding the pathogenesis of hyponatremic encephalopathy and in its prevention and treatment. Recent data have determined that hyponatremia is a more serious condition than previously believed. It is a major comorbidity factor for a variety of illnesses, and subtle neurological findings are common. It has now become apparent that the majority of hospital-acquired hyponatremia in children is iatrogenic and due in large part to the administration of hypotonic fluids to patients with elevated arginine vasopressin levels. Recent prospective studies have demonstrated that administration of 0.9% sodium chloride in maintenance fluids can prevent the development of hyponatremia. Risk factors, such as hypoxia and central nervous system (CNS) involvement, have been identified for the development of hyponatremic encephalopathy, which can lead to neurologic injury at mildly hyponatremic values. It has also become apparent that both children and adult patients are dying from symptomatic hyponatremia due to inadequate therapy. We have proposed the use of intermittent intravenous bolus therapy with 3% sodium chloride, 2 cc/kg with a maximum of 100 cc, to rapidly reverse CNS symptoms and at the same time avoid the possibility of overcorrection of hyponatremia. In this review, we discuss how to recognize patients at risk for inadvertent overcorrection of hyponatremia and what measures should taken to prevent this, including the judicious use of 1-desamino-8d-arginine vasopressin (dDAVP)

    Diffusion Weighted Image Denoising using overcomplete Local PCA

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    Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to the presence of noise from the measurement process that complicates and biases the estimation of quantitative diffusion parameters. In this paper, a new denoising methodology is proposed that takes into consideration the multicomponent nature of multi-directional DWI datasets such as those employed in diffusion imaging. This new filter reduces random noise in multicomponent DWI by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with state-of-the-art methods using synthetic and real clinical MR images, showing improved performance in terms of denoising quality and estimation of diffusion parameters.This work has been supported by the Spanish grant TIN2011-26727 from Ministerio de Ciencia e Innovacion. This work has been also partially supported by the French grant "HR-DTI" ANR-10-LABX-57 funded by the TRAIL from the French Agence Nationale de la Recherche within the context of the Investments for the Future program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Manjón Herrera, JV.; Coupé, P.; Concha, L.; Buades, A.; Collins, L.; Robles Viejo, M. (2013). Diffusion Weighted Image Denoising using overcomplete Local PCA. PLoS ONE. 8(9):1-12. https://doi.org/10.1371/journal.pone.0073021S11289Sundgren, P. C., Dong, Q., Gómez-Hassan, D., Mukherji, S. K., Maly, P., & Welsh, R. (2004). Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology, 46(5), 339-350. doi:10.1007/s00234-003-1114-xJohansen-Berg, H., & Behrens, T. E. (2006). Just pretty pictures? What diffusion tractography can add in clinical neuroscience. Current Opinion in Neurology, 19(4), 379-385. doi:10.1097/01.wco.0000236618.82086.01Jones DK, Basser PJ (2004) Squashing peanuts and smashing pumpkins: how noise distorts diffusion-weighted MR data. Magnetic Resonance in Medicine 52, 979–993.Chen, B., & Hsu, E. W. (2005). Noise removal in magnetic resonance diffusion tensor imaging. Magnetic Resonance in Medicine, 54(2), 393-401. doi:10.1002/mrm.20582Aja-Fernandez, S., Niethammer, M., Kubicki, M., Shenton, M. E., & Westin, C.-F. (2008). Restoration of DWI Data Using a Rician LMMSE Estimator. IEEE Transactions on Medical Imaging, 27(10), 1389-1403. doi:10.1109/tmi.2008.920609Basu S, Fletcher T, Whitaker R (2006) Rician noise removal in diffusion tensor MRI. MICCAI2006: 9,117–25.Hamarneh, G., & Hradsky, J. (2007). Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images. IEEE Transactions on Image Processing, 16(10), 2463-2475. doi:10.1109/tip.2007.904964Xu, Q., Anderson, A. W., Gore, J. C., & Ding, Z. (2010). Efficient anisotropic filtering of diffusion tensor images. Magnetic Resonance Imaging, 28(2), 200-211. doi:10.1016/j.mri.2009.10.001Parker, G. J. M., Schnabel, J. A., Symms, M. R., Werring, D. J., & Barker, G. J. (2000). Nonlinear smoothing for reduction of systematic and random errors in diffusion tensor imaging. Journal of Magnetic Resonance Imaging, 11(6), 702-710. doi:10.1002/1522-2586(200006)11:63.0.co;2-aWeickert J, Brox T (2002) Diffusion and regularization of vector and matrix valued images. Saarland Department of Mathematics, Saarland University. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.195Wang, Z., Vemuri, B. C., Chen, Y., & Mareci, T. H. (2004). A Constrained Variational Principle for Direct Estimation and Smoothing of the Diffusion Tensor Field From Complex DWI. IEEE Transactions on Medical Imaging, 23(8), 930-939. doi:10.1109/tmi.2004.831218Reisert, M., & Kiselev, V. G. (2011). Fiber Continuity: An Anisotropic Prior for ODF Estimation. IEEE Transactions on Medical Imaging, 30(6), 1274-1283. doi:10.1109/tmi.2011.2112769Fillard, P., Pennec, X., Arsigny, V., & Ayache, N. (2007). Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics. IEEE Transactions on Medical Imaging, 26(11), 1472-1482. doi:10.1109/tmi.2007.899173Poon PK, Wei-Ren Ng, Sridharan V (2009) Image Denoising with Singular Value Decompositon and Principal Component Analysis. http://www.u.arizona.edu/~ppoon/ImageDenoisingWithSVD.pdfZhang, L., Dong, W., Zhang, D., & Shi, G. (2010). Two-stage image denoising by principal component analysis with local pixel grouping. Pattern Recognition, 43(4), 1531-1549. doi:10.1016/j.patcog.2009.09.023Deledalle C, Salmon J, Dalalyan A (2011) Image denoising with patch based PCA: local versus global. BMVC2011.Manjón JV, Thacker N, Lull JJ, Garcia-Martí G, Martí-Bonmatí L, et al.. (2009) Multicomponent MR Image Denoising. International Journal of Biomedical imaging, Article ID 756897.Bao, L., Robini, M., Liu, W., & Zhu, Y. (2013). Structure-adaptive sparse denoising for diffusion-tensor MRI. Medical Image Analysis, 17(4), 442-457. doi:10.1016/j.media.2013.01.006Strang G (1976) Linear Algebra and Its Applications Academic. New York,19802.Jolliffe IT (1986) Principal component analysis (Vol. 487). New York: Springer-Verlag.Manjón, J. V., Coupé, P., Buades, A., Louis Collins, D., & Robles, M. (2012). New methods for MRI denoising based on sparseness and self-similarity. Medical Image Analysis, 16(1), 18-27. doi:10.1016/j.media.2011.04.003Coifman R, Donoho DL (1995) Translation Invariant Denoising, Wavelets and Statistics. Anestis Antoniadis, ed. Springer Verlag Lecture Notes.Nowak, R. D. (1999). Wavelet-based Rician noise removal for magnetic resonance imaging. IEEE Transactions on Image Processing, 8(10), 1408-1419. doi:10.1109/83.791966Koay CG, Basser PJ (2006) Analytically exact correction scheme for signal extraction from noisy magnitude MR signals. J Magn Reson, 179,317–322.Coupé, P., Manjón, J. V., Gedamu, E., Arnold, D., Robles, M., & Collins, D. L. (2010). Robust Rician noise estimation for MR images. Medical Image Analysis, 14(4), 483-493. doi:10.1016/j.media.2010.03.001Close, T. G., Tournier, J.-D., Calamante, F., Johnston, L. A., Mareels, I., & Connelly, A. (2009). A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms. NeuroImage, 47(4), 1288-1300. doi:10.1016/j.neuroimage.2009.03.077Coupe, P., Yger, P., Prima, S., Hellier, P., Kervrann, C., & Barillot, C. (2008). An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images. IEEE Transactions on Medical Imaging, 27(4), 425-441. doi:10.1109/tmi.2007.906087Manjón, J. V., Coupé, P., Martí-Bonmatí, L., Collins, D. L., & Robles, M. (2009). Adaptive non-local means denoising of MR images with spatially varying noise levels. Journal of Magnetic Resonance Imaging, 31(1), 192-203. doi:10.1002/jmri.22003Coupé P, Hellier P, Prima S, Kervrann C, Barillot C (2008) 3D Wavelet Subbands Mixing for Image Denoising. International Journal of Biomedical Imaging. Article ID 590183.Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., … Matthews, P. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23, S208-S219. doi:10.1016/j.neuroimage.2004.07.051Basser, P. J., Mattiello, J., & Lebihan, D. (1994). Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo. Journal of Magnetic Resonance, Series B, 103(3), 247-254. doi:10.1006/jmrb.1994.103

    Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape

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    The wide variety of treatment options that exist for glioblastoma, including surgery, ionizing radiation, anti-neoplastic chemotherapies, anti-angiogenic therapies, and active or passive immunotherapies, all may alter aspects of vascular permeability within the tumor and/or normal parenchyma. These alterations manifest as changes in the degree of contrast enhancement or T2-weighted signal hyperintensity on standard anatomic MRI scans, posing a potential challenge for accurate radiographic response assessment for identifying anti-tumor effects. The current review highlights the challenges that remain in differentiating true disease progression from changes due to radiation therapy, including pseudoprogression and radionecrosis, as well as immune or inflammatory changes that may occur as either an undesired result of cytotoxic therapy or as a desired consequence of immunotherapies

    Relationship Between [18F]FDOPA PET Uptake, Apparent Diffusion Coefficient (ADC), and Proliferation Rate in Recurrent Malignant Gliomas

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    Purpose: Diffusion magnetic resonance imaging (MRI) and 6-[18F]fluoro-l-dopa ([18F]FDOPA) positron emission tomography (PET) are used to interrogate malignant tumor microenvironment. It remains unclear whether there is a relationship between [18F]FDOPA uptake, diffusion MRI estimates of apparent diffusion coefficient (ADC), and mitotic activity in the context of recurrent malignant gliomas, where the tumor may be confounded by the effects of therapy. The purpose of the current study is to determine whether there is a correlation between these imaging techniques and mitotic activity in malignant gliomas.Procedures: We retrospectively examined 29 patients with recurrent malignant gliomas who underwent structural MRI, diffusion MRI, and [18F]FDOPA PET prior to surgical resection. Qualitative associations were noted, and quantitative voxel-wise and median measurement correlations between [18F]FDOPA PET, ADC, and mitotic index were performed.Results: Areas of high [18F]FDOPA uptake exhibited low ADC and areas of hyperintensity T2/fluid-attenuated inversion recovery (FLAIR) with low [18F]FDOPA uptake exhibited high ADC. There was a significant inverse voxel-wise correlation between [18F]FDOPA and ADC for all patients. Median [18F]FDOPA uptake and median ADC also showed a significant inverse correlation. Median [18F]FDOPA uptake was positively correlated, and median ADC was inversely correlated with mitotic index from resected tumor tissue.Conclusions: A significant association may exist between [18F]FDOPA uptake, diffusion MRI, and mitotic activity in recurrent malignant gliomas

    Characterization of Functional and Structural Integrity in Experimental Focal Epilepsy: Reduced Network Efficiency Coincides with White Matter Changes

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    BACKGROUND: Although focal epilepsies are increasingly recognized to affect multiple and remote neural systems, the underlying spatiotemporal pattern and the relationships between recurrent spontaneous seizures, global functional connectivity, and structural integrity remain largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we utilized serial resting-state functional MRI, graph-theoretical analysis of complex brain networks and diffusion tensor imaging to characterize the evolution of global network topology, functional connectivity and structural changes in the interictal brain in relation to focal epilepsy in a rat model. Epileptic networks exhibited a more regular functional topology than controls, indicated by a significant increase in shortest path length and clustering coefficient. Interhemispheric functional connectivity in epileptic brains decreased, while intrahemispheric functional connectivity increased. Widespread reductions of fractional anisotropy were found in white matter regions not restricted to the vicinity of the epileptic focus, including the corpus callosum. CONCLUSIONS/SIGNIFICANCE: Our longitudinal study on the pathogenesis of network dynamics in epileptic brains reveals that, despite the locality of the epileptogenic area, epileptic brains differ in their global network topology, connectivity and structural integrity from healthy brains
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