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      Relationship between radiation dose and microbleed formation in patients with malignant glioma

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          Abstract

          Background

          Cranial irradiation is associated with long-term cognitive changes. Cerebral microbleeds (CMBs) have been identified on susceptibility-weighted MRI (SWI) in patients who have received prior cranial radiation, and serve as radiographic markers for microvascular injury thought to contribute to late cognitive decline. The relationship between CMB formation and radiation dose has not previously been quantified.

          Methods

          SWI was performed on 13 patients with stable WHO grade III-IV gliomas between 2 and 4 years after chemoradiotherapy to 60 Gy. The median age at the time of treatment was 41 years (range 25 – 74 years). CMBs were identified as discrete foci of susceptibility on SWI that did not correspond to vessels. CMB density for low (<30 Gy), median (30–45 Gy), and high (>45 Gy) dose regions was computed.

          Results

          Twelve of 13 patients exhibited CMBs. The number of CMBs was significantly higher for late (>3 years from treatment) compared to early (<3 years) timepoints (early median 6 CMBs; late median 27 CMBs; p = 0.001), and there were proportionally more CMBs at lower doses for late scans ( p = 0.006). 88% of all CMBs were observed in regions receiving at least 30 Gy, but the CMB density within medium and high dose regions was not significantly different ( p = 0.33 and p = 0.9, respectively, for early and late time points).

          Conclusions

          CMBs predominantly form in regions receiving at least 30 Gy, but form in lower dose regions with longer follow-up. We do not observe a clear dose–response relationship at doses above 30 Gy. These findings provide important information to assess the risk of late microvascular sequelae from cranial irradiation.

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          Most cited references33

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          Radiation plus Procarbazine, CCNU, and Vincristine in Low-Grade Glioma.

          Grade 2 gliomas occur most commonly in young adults and cause progressive neurologic deterioration and premature death. Early results of this trial showed that treatment with procarbazine, lomustine (also called CCNU), and vincristine after radiation therapy at the time of initial diagnosis resulted in longer progression-free survival, but not overall survival, than radiation therapy alone. We now report the long-term results.
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            Susceptibility weighted imaging (SWI).

            Susceptibility differences between tissues can be utilized as a new type of contrast in MRI that is different from spin density, T1-, or T2-weighted imaging. Signals from substances with different magnetic susceptibilities compared to their neighboring tissue will become out of phase with these tissues at sufficiently long echo times (TEs). Thus, phase imaging offers a means of enhancing contrast in MRI. Specifically, the phase images themselves can provide excellent contrast between gray matter (GM) and white matter (WM), iron-laden tissues, venous blood vessels, and other tissues with susceptibilities that are different from the background tissue. Also, for the first time, projection phase images are shown to demonstrate tissue (vessel) continuity. In this work, the best approach for combining magnitude and phase images is discussed. The phase images are high-pass-filtered and then transformed to a special phase mask that varies in amplitude between zero and unity. This mask is multiplied a few times into the original magnitude image to create enhanced contrast between tissues with different susceptibilities. For this reason, this method is referred to as susceptibility-weighted imaging (SWI). Mathematical arguments are presented to determine the number of phase mask multiplications that should take place. Examples are given for enhancing GM/WM contrast and water/fat contrast, identifying brain iron, and visualizing veins in the brain. Copyright 2004 Wiley-Liss, Inc.
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              Imaging iron stores in the brain using magnetic resonance imaging.

              For the last century, there has been great physiological interest in brain iron and its role in brain function and disease. It is well known that iron accumulates in the brain for people with Huntington's disease, Parkinson's disease, Alzheimer's disease, multiple sclerosis, chronic hemorrhage, cerebral infarction, anemia, thalassemia, hemochromatosis, Hallervorden-Spatz, Down syndrome, AIDS and in the eye for people with macular degeneration. Measuring the amount of nonheme iron in the body may well lead to not only a better understanding of the disease progression but an ability to predict outcome. As there are many forms of iron in the brain, separating them and quantifying each type have been a major challenge. In this review, we present our understanding of attempts to measure brain iron and the potential of doing so with magnetic resonance imaging. Specifically, we examine the response of the magnetic resonance visible iron in tissue that produces signal changes in both magnitude and phase images. These images seem to correlate with brain iron content, perhaps ferritin specifically, but still have not been successfully exploited to accurately and precisely quantify brain iron. For future quantitative studies of iron content we propose four methods: correlating R2' and phase to iron content; applying a special filter to the phase to obtain a susceptibility map; using complex analysis to extract the product of susceptibility and volume content of the susceptibility source; and using early and late echo information to separately predict susceptibility and volume content.
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                Author and article information

                Contributors
                Michael.Wahl@ucsf.edu
                Mekhail.Anwar@ucsf.edu
                Christopher.Hess@ucsf.edu
                Susan.Chang@ucsf.edu
                (415) 502-0646 , Janine.Lupo@ucsf.edu
                Journal
                Radiat Oncol
                Radiat Oncol
                Radiation Oncology (London, England)
                BioMed Central (London )
                1748-717X
                10 August 2017
                10 August 2017
                2017
                : 12
                : 126
                Affiliations
                [1 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Radiation Oncology, , University of California, ; San Francisco, CA USA
                [2 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Radiology and Biomedical Imaging, , University of California, ; San Francisco, CA USA
                [3 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Neurology, , University of California, ; San Francisco, CA USA
                [4 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Neurological Surgery, , University of California, ; San Francisco, CA USA
                Article
                861
                10.1186/s13014-017-0861-5
                5553662
                28797254
                632ae901-c66f-41c7-a2c0-59cd6ce9e25d
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 9 January 2017
                : 1 August 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R01 CA127612
                Award ID: P01 CA118816
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Oncology & Radiotherapy
                glioma,microbleeds,radiation therapy,susceptibility-weighted imaging,treatment effects

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