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      EFFECT OF RADIATION DOSE LEVEL ON ACCURACY AND PRECISION OF MANUAL SIZE MEASUREMENTS IN CHEST TOMOSYNTHESIS EVALUATED USING SIMULATED PULMONARY NODULES

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          Abstract

          The aim of the present study was to investigate the dependency of the accuracy and precision of nodule diameter measurements on the radiation dose level in chest tomosynthesis. Artificial ellipsoid-shaped nodules with known dimensions were inserted in clinical chest tomosynthesis images. Noise was added to the images in order to simulate radiation dose levels corresponding to effective doses for a standard-sized patient of 0.06 and 0.04 mSv. These levels were compared with the original dose level, corresponding to an effective dose of 0.12 mSv for a standard-sized patient. Four thoracic radiologists measured the longest diameter of the nodules. The study was restricted to nodules located in high-dose areas of the tomosynthesis projection radiographs. A significant decrease of the measurement accuracy and intraobserver variability was seen for the lowest dose level for a subset of the observers. No significant effect of dose level on the interobserver variability was found. The number of non-measurable small nodules (≤5 mm) was higher for the two lowest dose levels compared with the original dose level. In conclusion, for pulmonary nodules at positions in the lung corresponding to locations in high-dose areas of the projection radiographs, using a radiation dose level resulting in an effective dose of 0.06 mSv to a standard-sized patient may be possible in chest tomosynthesis without affecting the accuracy and precision of nodule diameter measurements to any large extent. However, an increasing number of non-measurable small nodules (≤5 mm) with decreasing radiation dose may raise some concerns regarding an applied general dose reduction for chest tomosynthesis examinations in the clinical praxis.

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          Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society.

          Lung nodules are detected very commonly on computed tomographic (CT) scans of the chest, and the ability to detect very small nodules improves with each new generation of CT scanner. In reported studies, up to 51% of smokers aged 50 years or older have pulmonary nodules on CT scans. However, the existing guidelines for follow-up and management of noncalcified nodules detected on nonscreening CT scans were developed before widespread use of multi-detector row CT and still indicate that every indeterminate nodule should be followed with serial CT for a minimum of 2 years. This policy, which requires large numbers of studies to be performed at considerable expense and with substantial radiation exposure for the affected population, has not proved to be beneficial or cost-effective. During the past 5 years, new information regarding prevalence, biologic characteristics, and growth rates of small lung cancers has become available; thus, the authors believe that the time-honored requirement to follow every small indeterminate nodule with serial CT should be revised. In this statement, which has been approved by the Fleischner Society, the pertinent data are reviewed, the authors' conclusions are summarized, and new guidelines are proposed for follow-up and management of small pulmonary nodules detected on CT scans.
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            Survey: interpolation methods in medical image processing.

            Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sinc; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic B-spline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1 x 1 up to 8 x 8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced and fundamental properties of interpolators are derived. Successful methods should be direct current (DC)-constant and interpolators rather than DC-inconstant or approximators. Each method's parameters are tuned with respect to those properties. This results in three novel kernels, which are introduced in this paper and proven to be within the best choices for medical image interpolation: the 6 x 6 Blackman-Harris windowed sinc interpolator, and the C2-continuous cubic kernels with N = 6 and N = 8 supporting points. For quantitative error evaluations, a set of 50 direct digital X rays was used. They have been selected arbitrarily from clinical routine. In general, large kernel sizes were found to be superior to small interpolation masks. Except for truncated sinc interpolators, all kernels with N = 6 or larger sizes perform significantly better than N = 2 or N = 3 point methods (p < 0.005). However, the differences within the group of large-sized kernels were not significant. Summarizing the results, the cubic 6 x 6 interpolator with continuous second derivatives, as defined in (24), can be recommended for most common interpolation tasks. It appears to be the fastest six-point kernel to implement computationally. It provides eminent local and Fourier properties, is easy to implement, and has only small errors. The same characteristics apply to B-spline interpolation, but the 6 x 6 cubic avoids the intrinsic border effects produced by the B-spline technique. However, the goal of this study was not to determine an overall best method, but to present a comprehensive catalogue of methods in a uniform terminology, to define general properties and requirements of local techniques, and to enable the reader to select that method which is optimal for his specific application in medical imaging.
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              Digital x-ray tomosynthesis: current state of the art and clinical potential.

              Digital x-ray tomosynthesis is a technique for producing slice images using conventional x-ray systems. It is a refinement of conventional geometric tomography, which has been known since the 1930s. In conventional geometric tomography, the x-ray tube and image receptor move in synchrony on opposite sides of the patient to produce a plane of structures in sharp focus at the plane containing the fulcrum of the motion; all other structures above and below the fulcrum plane are blurred and thus less visible in the resulting image. Tomosynthesis improves upon conventional geometric tomography in that it allows an arbitrary number of in-focus planes to be generated retrospectively from a sequence of projection radiographs that are acquired during a single motion of the x-ray tube. By shifting and adding these projection radiographs, specific planes may be reconstructed. This topical review describes the various reconstruction algorithms used to produce tomosynthesis images, as well as approaches used to minimize the residual blur from out-of-plane structures. Historical background and mathematical details are given for the various approaches described. Approaches for optimizing the tomosynthesis image are given. Applications of tomosynthesis to various clinical tasks, including angiography, chest imaging, mammography, dental imaging and orthopaedic imaging, are also described.
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                Author and article information

                Journal
                Radiat Prot Dosimetry
                Radiat Prot Dosimetry
                rpd
                rpd
                Radiation Protection Dosimetry
                Oxford University Press
                0144-8420
                1742-3406
                June 2016
                07 June 2016
                07 June 2016
                : 169
                : 1-4
                : 188-198
                Affiliations
                [1 ]Department of Radiation Physics, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg , SE-413 45 Gothenburg, Sweden
                [2 ]Department of Radiology, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg , SE-413 45 Gothenburg, Sweden
                [3 ]Department of Radiology, Sahlgrenska University Hospital , SE-413 45 Gothenburg, Sweden
                [4 ]Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital , SE-413 45 Gothenburg, Sweden
                Author notes
                Article
                ncw041
                10.1093/rpd/ncw041
                4911967
                26994093
                645ae2ae-7d4c-4d75-aa62-fe100d552c7d
                © The Author 2016. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Funding
                Funded by: Swedish Research Council
                Award ID: 2011/488
                Award ID: 2013/3477
                Funded by: Swedish Radiation Safety Authority
                Award ID: 2014/2641
                Funded by: Swedish Federal Government
                Award ID: ALFGBG-428961
                Funded by: Region Västra Götaland
                Award ID: VGFOUREG-483951
                Categories
                Paper

                Chemical & Environmental safety
                Chemical & Environmental safety

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