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      Clinical evaluation of respiration-induced attenuation uncertainties in pulmonary 3D PET/CT

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          Abstract

          Background

          In contemporary positron emission tomography (PET)/computed tomography (CT) scanners, PET attenuation correction is performed by means of a CT-based attenuation map. Respiratory motion can however induce offsets between the PET and CT data. Studies have demonstrated that these offsets can cause errors in quantitative PET measures. The purpose of this study is to quantify the effects of respiration-induced CT differences on the attenuation correction of pulmonary 18-fluordeoxyglucose (FDG) 3D PET/CT in a patient population and to investigate contributing factors.

          Methods

          For 32 lung cancer patients, 3D-CT, 4D-PET and 4D-CT data were acquired. The 4D FDG PET data were attenuation corrected (AC) using a free-breathing 3D-CT (3D-AC), the end-inspiration CT (EI-AC), the end-expiration CT (EE-AC) or phase-by-phase (P-AC). After reconstruction and AC, the 4D-PET data were averaged. In the 4D avg data, we measured maximum tumour standardised uptake value (SUV) max in the tumour, SUV mean in a lung volume of interest (VOI) and average SUV (SUV mean) in a muscle VOI. On the 4D-CT, we measured the lung volume differences and CT number changes between inhale and exhale in the lung VOI.

          Results

          Compared to P-AC, we found −2.3% (range −9.7% to 1.2%) lower tumour SUV max in EI-AC and 2.0% (range −0.9% to 9.5%) higher SUV max in EE-AC. No differences in the muscle SUV were found. The use of 3D-AC led to respiration-induced SUV max differences up to 20% compared to the use of P-AC.

          SUV mean differences in the lung VOI between EI-AC and EE-AC correlated to average CT differences in this region ( ρ = 0.83). SUVmax differences in the tumour correlated to the volume changes of the lungs ( ρ = −0.55) and the motion amplitude of the tumour ( ρ = 0.53), both as measured on the 4D-CT.

          Conclusions

          Respiration-induced CT variations in clinical data can in extreme cases lead to SUV effects larger than 10% on PET attenuation correction. These differences were case specific and correlated to differences in CT number in the lungs.

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          Most cited references18

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          From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors.

          The purpose of this article is to review the status and limitations of anatomic tumor response metrics including the World Health Organization (WHO) criteria, the Response Evaluation Criteria in Solid Tumors (RECIST), and RECIST 1.1. This article also reviews qualitative and quantitative approaches to metabolic tumor response assessment with (18)F-FDG PET and proposes a draft framework for PET Response Criteria in Solid Tumors (PERCIST), version 1.0. PubMed searches, including searches for the terms RECIST, positron, WHO, FDG, cancer (including specific types), treatment response, region of interest, and derivative references, were performed. Abstracts and articles judged most relevant to the goals of this report were reviewed with emphasis on limitations and strengths of the anatomic and PET approaches to treatment response assessment. On the basis of these data and the authors' experience, draft criteria were formulated for PET tumor response to treatment. Approximately 3,000 potentially relevant references were screened. Anatomic imaging alone using standard WHO, RECIST, and RECIST 1.1 criteria is widely applied but still has limitations in response assessments. For example, despite effective treatment, changes in tumor size can be minimal in tumors such as lymphomas, sarcoma, hepatomas, mesothelioma, and gastrointestinal stromal tumor. CT tumor density, contrast enhancement, or MRI characteristics appear more informative than size but are not yet routinely applied. RECIST criteria may show progression of tumor more slowly than WHO criteria. RECIST 1.1 criteria (assessing a maximum of 5 tumor foci, vs. 10 in RECIST) result in a higher complete response rate than the original RECIST criteria, at least in lymph nodes. Variability appears greater in assessing progression than in assessing response. Qualitative and quantitative approaches to (18)F-FDG PET response assessment have been applied and require a consistent PET methodology to allow quantitative assessments. Statistically significant changes in tumor standardized uptake value (SUV) occur in careful test-retest studies of high-SUV tumors, with a change of 20% in SUV of a region 1 cm or larger in diameter; however, medically relevant beneficial changes are often associated with a 30% or greater decline. The more extensive the therapy, the greater the decline in SUV with most effective treatments. Important components of the proposed PERCIST criteria include assessing normal reference tissue values in a 3-cm-diameter region of interest in the liver, using a consistent PET protocol, using a fixed small region of interest about 1 cm(3) in volume (1.2-cm diameter) in the most active region of metabolically active tumors to minimize statistical variability, assessing tumor size, treating SUV lean measurements in the 1 (up to 5 optional) most metabolically active tumor focus as a continuous variable, requiring a 30% decline in SUV for "response," and deferring to RECIST 1.1 in cases that do not have (18)F-FDG avidity or are technically unsuitable. Criteria to define progression of tumor-absent new lesions are uncertain but are proposed. Anatomic imaging alone using standard WHO, RECIST, and RECIST 1.1 criteria have limitations, particularly in assessing the activity of newer cancer therapies that stabilize disease, whereas (18)F-FDG PET appears particularly valuable in such cases. The proposed PERCIST 1.0 criteria should serve as a starting point for use in clinical trials and in structured quantitative clinical reporting. Undoubtedly, subsequent revisions and enhancements will be required as validation studies are undertaken in varying diseases and treatments.
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            Positron emission tomography-computed tomography standardized uptake values in clinical practice and assessing response to therapy.

            The use of standardized uptake values (SUVs) is now common place in clinical 2-deoxy-2-[(18)F] fluoro-D-glucose (FDG) position emission tomography-computed tomography oncology imaging and has a specific role in assessing patient response to cancer therapy. Ideally, the use of SUVs removes variability introduced by differences in patient size and the amount of injected FDG. However, in practice there are several sources of bias and variance that are introduced in the measurement of FDG uptake in tumors and also in the conversion of the image count data to SUVs. In this article the overall imaging process is reviewed and estimates of the magnitude of errors, where known, are given. Recommendations are provided for best practices in improving SUV accuracy. Copyright © 2010 Elsevier Inc. All rights reserved.
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              Attenuation correction for a combined 3D PET/CT scanner.

              In this work we demonstrate the proof of principle of CT-based attenuation correction of 3D positron emission tomography (PET) data by using scans of bone and soft tissue equivalent phantoms and scans of humans. This method of attenuation correction is intended for use in a single scanner that combines volume-imaging (3D) PET with x-ray computed tomography (CT) for the purpose of providing accurately registered anatomical localization of structures seen in the PET image. The goal of this work is to determine if we can perform attenuation correction of the PET emission data using accurately aligned CT attenuation information. We discuss possible methods of calculating the PET attenuation map at 511 keV based on CT transmission information acquired from 40 keV through 140 keV. Data were acquired on separate CT and PET scanners and were aligned using standard image registration procedures. Results are presented on three of the attenuation calculation methods: segmentation, scaling, and our proposed hybrid segmentation/scaling method. The results are compared with those using the standard 3D PET attenuation correction method as a gold standard. We demonstrate the efficacy of our proposed hybrid method for converting the CT attenuation map from an effective CT photon energy of 70 keV to the PET photon energy of 511 keV. We conclude that using CT information is a feasible way to obtain attenuation correction factors for 3D PET.
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                Author and article information

                Contributors
                m.kruis@nki.nl
                j.vd.kamer@nki.nl
                w.vogel@nki.nl
                j.belderbos@nki.nl
                j.sonke@nki.nl
                m.v.herk@nki.nl
                Journal
                EJNMMI Phys
                EJNMMI Phys
                EJNMMI Physics
                Springer International Publishing (Cham )
                2197-7364
                24 February 2015
                24 February 2015
                December 2015
                : 2
                : 4
                Affiliations
                [ ]Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
                [ ]Department of Nuclear Medicine, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
                Article
                107
                10.1186/s40658-014-0107-7
                4545225
                7857266b-0ec3-4193-811c-126d42781a2f
                © Kruis et al.; licensee Springer. 2015

                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 use, distribution, and reproduction in any medium, provided the original work is properly credited.

                History
                : 16 September 2014
                : 30 December 2014
                Categories
                Original Research
                Custom metadata
                © The Author(s) 2015

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