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      A review of substitute CT generation for MRI-only radiation therapy

      review-article
      1 , 2 , , 3 , 4
      Radiation Oncology (London, England)
      BioMed Central

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          Abstract

          Radiotherapy based on magnetic resonance imaging as the sole modality (MRI-only RT) is an area of growing scientific interest due to the increasing use of MRI for both target and normal tissue delineation and the development of MR based delivery systems. One major issue in MRI-only RT is the assignment of electron densities (ED) to MRI scans for dose calculation and a similar need for attenuation correction can be found for hybrid PET/MR systems. The ED assigned MRI scan is here named a substitute CT (sCT). In this review, we report on a collection of typical performance values for a number of main approaches encountered in the literature for sCT generation as compared to CT. A literature search in the Scopus database resulted in 254 papers which were included in this investigation. A final number of 50 contributions which fulfilled all inclusion criteria were categorized according to applied method, MRI sequence/contrast involved, number of subjects included and anatomical site investigated. The latter included brain, torso, prostate and phantoms. The contributions geometric and/or dosimetric performance metrics were also noted. The majority of studies are carried out on the brain for 5–10 patients with PET/MR applications in mind using a voxel based method. T1 weighted images are most commonly applied. The overall dosimetric agreement is in the order of 0.3–2.5%. A strict gamma criterion of 1% and 1mm has a range of passing rates from 68 to 94% while less strict criteria show pass rates > 98%. The mean absolute error (MAE) is between 80 and 200 HU for the brain and around 40 HU for the prostate. The Dice score for bone is between 0.5 and 0.95. The specificity and sensitivity is reported in the upper 80s% for both quantities and correctly classified voxels average around 84%. The review shows that a variety of promising approaches exist that seem clinical acceptable even with standard clinical MRI sequences. A consistent reference frame for method benchmarking is probably necessary to move the field further towards a widespread clinical implementation.

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          Most cited references64

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          A technique for the quantitative evaluation of dose distributions.

          The commissioning of a three-dimensional treatment planning system requires comparisons of measured and calculated dose distributions. Techniques have been developed to facilitate quantitative comparisons, including superimposed isodoses, dose-difference, and distance-to-agreement (DTA) distributions. The criterion for acceptable calculation performance is generally defined as a tolerance of the dose and DTA in regions of low and high dose gradients, respectively. The dose difference and DTA distributions complement each other in their useful regions. A composite distribution has recently been developed that presents the dose difference in regions that fail both dose-difference and DTA comparison criteria. Although the composite distribution identifies locations where the calculation fails the preselected criteria, no numerical quality measure is provided for display or analysis. A technique is developed to unify dose distribution comparisons using the acceptance criteria. The measure of acceptability is the multidimensional distance between the measurement and calculation points in both the dose and the physical distance, scaled as a fraction of the acceptance criteria. In a space composed of dose and spatial coordinates, the acceptance criteria form an ellipsoid surface, the major axis scales of which are determined by individual acceptance criteria and the center of which is located at the measurement point in question. When the calculated dose distribution surface passes through the ellipsoid, the calculation passes the acceptance test for the measurement point. The minimum radial distance between the measurement point and the calculation points (expressed as a surface in the dose-distance space) is termed the gamma index. Regions where gamma > 1 correspond to locations where the calculation does not meet the acceptance criteria. The determination of gamma throughout the measured dose distribution provides a presentation that quantitatively indicates the calculation accuracy. Examples of a 6 MV beam penumbra are used to illustrate the gamma index.
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            MRI-based attenuation correction for PET/MRI using ultrashort echo time sequences.

            One of the challenges in PET/MRI is the derivation of an attenuation map to correct the PET image for attenuation. Different methods have been suggested for deriving the attenuation map from an MR image. Because the low signal intensity of cortical bone on images acquired with conventional MRI sequences makes it difficult to detect this tissue type, these methods rely on some sort of anatomic precondition to predict the attenuation map, raising the question of whether these methods will be usable in the clinic when patients may exhibit anatomic abnormalities. We propose the use of the transverse relaxation rate, derived from images acquired with an ultrashort echo time sequence to classify the voxels into 1 of 3 tissue classes (bone, soft tissue, or air), without making any assumptions on patient anatomy. Each voxel is assigned a linear attenuation coefficient corresponding to its tissue class. A reference CT scan is used to determine the voxel-by-voxel accuracy of the proposed method. The overall accuracy of the MRI-based attenuation correction is evaluated using a method that takes into account the nonlocal effects of attenuation correction. As a proof of concept, the head of a pig was used as a phantom for imaging. The new method yielded a correct tissue classification in 90% of the voxels. Five human brain PET/CT and MRI datasets were also processed, yielding slightly worse voxel-by-voxel performance, compared to a CT-derived attenuation map. The PET datasets were reconstructed using the segmented MRI attenuation map derived with the new method, and the resulting images were compared with segmented CT-based attenuation correction. An average error of around 5% was found in the brain. The feasibility of using the transverse relaxation rate map derived from ultrashort echo time MR images for the estimation of the attenuation map was shown on phantom and clinical brain data. The results indicate that the new method, compared with CT-based attenuation correction, yields clinically acceptable errors. The proposed method does not make any assumptions about patient anatomy and could therefore also be used in cases in which anatomic abnormalities are present.
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              Similarity coefficients for molecular markers in studies of genetic relationships between individuals for haploid, diploid, and polyploid species.

              Determining true genetic dissimilarity between individuals is an important and decisive point for clustering and analysing diversity within and among populations, because different dissimilarity indices may yield conflicting outcomes. We show that there are no acceptable universal approaches to assessing the dissimilarity between individuals with molecular markers. Different measures are relevant to dominant and codominant DNA markers depending on the ploidy of organisms. The Dice coefficient is the suitable measure for haploids with codominant markers and it can be applied directly to (0,1)-vectors representing banding profiles of individuals. None of the common measures, Dice, Jaccard, simple mismatch coefficient (or the squared Euclidean distance), is appropriate for diploids with codominant markers. By transforming multiallelic banding patterns at each locus into the corresponding homozygous or heterozygous states, a new measure of dissimilarity within locus was developed and expanded to assess dissimilarity between multilocus states of two individuals by averaging across all codominant loci tested. There is no rigorous well-founded solution in the case of dominant markers. The simple mismatch coefficient is the most suitable measure of dissimilarity between banding patterns of closely related haploid forms. For distantly related haploid individuals, the Jaccard dissimilarity is recommended. In general, no suitable method for measuring genetic dissimilarity between diploids with dominant markers can be proposed. Banding patterns of diploids with dominant markers and polyploids with codominant markers represent individuals' phenotypes rather than genotypes. All dissimilarity measures proposed and developed herein are metrics.
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                Author and article information

                Contributors
                +45 3868 3170 , jens.edmund@regionh.dk
                Journal
                Radiat Oncol
                Radiat Oncol
                Radiation Oncology (London, England)
                BioMed Central (London )
                1748-717X
                26 January 2017
                26 January 2017
                2017
                : 12
                : 28
                Affiliations
                [1 ]Radiotherapy Research Unit, Department of Oncology, Herlev & Gentofte Hospital, Copenhagen University, Herlev, Denmark
                [2 ]ISNI 0000 0001 0674 042X, GRID grid.5254.6, Niels Bohr Institute, , Copenhagen University, ; Copenhagen, Denmark
                [3 ]ISNI 0000 0001 1034 3451, GRID grid.12650.30, Department of Radiation Sciences, , Umeå University, ; Umeå, SE-901 87 Sweden
                [4 ]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Medical Radiation Physics, Department of Immunology, , Genetics and Pathology, Uppsala University, ; Uppsala, Sweden
                Article
                747
                10.1186/s13014-016-0747-y
                5270229
                28126030
                9d18408f-b8c7-464a-9ccf-0cb6a9be4143
                © 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
                : 14 September 2016
                : 21 December 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007210, Varian Medical Systems;
                Categories
                Review
                Custom metadata
                © The Author(s) 2017

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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