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Impact of PET - CT motion correction in minimizing the gross tumor volume in non-small cell lung cancer

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      Abstract

      Objective(s):

      To investigate the impact of respiratory motion on localization, and quantification of lung lesions for the Gross Tumor Volume utilizing a fully automated Auto3Dreg program and dynamic NURBS-based cardiac-torso digitized phantom (NCAT).

      Methods:

      Respiratory motion may result in more than 30% underestimation of the SUV values of lung, liver and kidney tumor lesions. The motion correction technique adopted in this study was an image-based motion correction approach using, a voxel-intensity-based and a multi-resolution multi-optimization (MRMO) algorithm. The NCAT phantom was used to generate CT attenuation maps and activity distribution volumes for the lung regions. All the generated frames were co-registered to a reference frame using a time efficient scheme. Quantitative assessment including Region of Interest (ROI), image fidelity and image correlation techniques, as well as semi-quantitative line profile analysis and qualitatively overlaying non-motion and motion corrected image frames were performed.

      Results:

      The largest motion was observed in the Z-direction. The greatest translation was for the frame 3, end inspiration, and the smallest for the frame 5 which was closet frame to the reference frame at 67% expiration. Visual assessment of the lesion sizes, 20-60mm at 3 different locations, apex, mid and base of lung showed noticeable improvement for all the foci and their locations. The maximum improvements for the image fidelity were from 0.395 to 0.930 within the lesion volume of interest. The greatest improvement in activity concentration underestimation was 7.7% below the true activity for the 20 mm lesion in comparison to 34.4% below, prior to correction. The discrepancies in activity underestimation were reduced with increasing the lesion sizes. Overlaying activity distribution on the attenuation map showed improved localization of the PET metabolic information to the anatomical CT images.

      Conclusion:

      The respiratory motion correction for the lung lesions has led to an improvement in the lesion size, localization and activity quantification with a potential application in reducing the size of the PET GTV for radiotherapy treatment planning applications and hence improving the accuracy of the regime in treatment of lung cancer.

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      Most cited references 37

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      Stereotaxic display of brain lesions.

      Traditionally lesion location has been reported using standard templates, text based descriptions or representative raw slices from the patient's CT or MRI scan. Each of these methods has drawbacks for the display of neuroanatomical data. One solution is to display MRI scans in the same stereotaxic space popular with researchers working in functional neuroimaging. Presenting brains in this format is useful as the slices correspond to the standard anatomical atlases used by neuroimagers. In addition, lesion position and volume are directly comparable across patients. This article describes freely available software for presenting stereotaxically aligned patient scans. This article focuses on MRI scans, but many of these tools are also applicable to other modalities (e.g. CT, PET and SPECT). We suggest that this technique of presenting lesions in terms of images normalized to standard stereotaxic space should become the standard for neuropsychological studies.
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        Partial-volume effect in PET tumor imaging.

        PET has the invaluable advantage of being intrinsically quantitative, enabling accurate measurements of tracer concentrations in vivo. In PET tumor imaging, indices characterizing tumor uptake, such as standardized uptake values, are becoming increasingly important, especially in the context of monitoring the response to therapy. However, when tracer uptake in small tumors is measured, large biases can be introduced by the partial-volume effect (PVE). The purposes of this article are to explain what PVE is and to describe its consequences in PET tumor imaging. The parameters on which PVE depends are reviewed. Actions that can be taken to reduce the errors attributable to PVE are described. Various PVE correction schemes are presented, and their applicability to PET tumor imaging is discussed.
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          Cancer statistics, 2002.

          Every year the American Cancer Society estimates the number of new cancer cases and deaths expected in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival, using National Cancer Institute (NCI) incidence and National Center for Health Statistics (NCHS) mortality data. Incidence and death rates are age adjusted to the 1970 US standard population. It is estimated that 1,284,900 new cases of cancer will be diagnosed and 555,500 people will die from cancer in the United States in the year 2002. From 1992 to 1998, cancer death rates declined in males and females, while cancer incidence rates decreased among males and increased slightly among females. Most notably, African-American men showed the largest decline for both incidence and mortality. Nevertheless, African Americans still carry the highest burden of cancer with later-stage cancer diagnosis and poorer survival compared with whites. Despite the continued decline in cancer death rates, the total number of recorded cancer deaths in the United States continues to increase slightly due to the aging and expanding population.
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            Author and article information

            Affiliations
            [1 ]Department of Nuclear Medicine, Farwaniya Hospital, Kuwait
            [2 ]Nuclear Medicine Physics, Queen Alexandra Hospital, Portsmouth, UK
            [3 ]Clinical Physics, Barts Health - NHS Trust, UK
            [4 ]Faculty of Health Science, University of Sydney, Sydney, Australia
            [5 ]The Harley Street Clinic, London, UK
            Author notes
            * Corresponding author: Dr Michael A Masoomi, Department of Nuclear Medicine, Farwaniya Hospital, MOH, PO Box 18373, Kuwait 81004, Email: masoomim@ 123456sky.com
            Journal
            Asia Ocean J Nucl Med Biol
            Asia Ocean J Nucl Med Biol
            AOJNMB
            Asia Oceania Journal of Nuclear Medicine and Biology
            Asia Oceania Journal of Nuclear Medicine & Biology (Iran )
            2322-5718
            2322-5726
            Autumn 2013
            : 1
            : 2
            : 35-46
            27408848 4927049 AOJNMB-1-35
            Copyright: © mums.ac.ir

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Original Article

            correction, pet-ct, lung cancer, ncat

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