62
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose

          Standardized uptake values (SUV) are commonly used for quantification of whole-body [ 18F]fluoro-2-deoxy- D-glucose (FDG) positron emission tomography (PET) studies. Changes in SUV following therapy, however, only provide a proper measure of response in case of homogeneous FDG uptake in the tumour. The purpose of this study was therefore to implement and characterize a method that enables quantification of heterogeneity in tumour FDG uptake.

          Methods

          Cumulative SUV-volume histograms (CSH), describing % of total tumour volume above % threshold of maximum SUV (SUV max), were calculated. The area under a CSH curve (AUC) is a quantitative index of tumour uptake heterogeneity, with lower AUC corresponding to higher degrees of heterogeneity. Simulations of homogeneous and heterogeneous responses were performed to assess the value of AUC-CSH for measuring uptake and/or response heterogeneity. In addition, partial volume correction and image denoising was applied prior to calculating AUC-CSH. Finally, the method was applied to a number of human FDG scans.

          Results

          Partial volume correction and noise reduction improved CSH curves. Both simulations and clinical examples showed that AUC-CSH values corresponded with level of tumour heterogeneity and/or heterogeneity in response. In contrast, this correspondence was not seen with SUV max alone. The results indicate that the main advantage of AUC-CSH above other measures, such as 1/COV (coefficient of variation), is the possibility to measure or normalize AUC-CSH in different ways.

          Conclusion

          AUC-CSH might be used as a quantitative index of heterogeneity in tracer uptake. In response monitoring studies it can be used to address heterogeneity in response.

          Related collections

          Most cited references24

          • Record: found
          • Abstract: found
          • Article: not found

          Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study.

          Semiquantitative standard uptake values (SUVs) are used for tumor diagnosis and response monitoring. However, the accuracy of the SUV and the accuracy of relative change during treatment are not well documented. Therefore, an experimental and simulation study was performed to determine the effects of noise, image resolution, and region-of-interest (ROI) definition on the accuracy of SUVs. Experiments and simulations are based on thorax phantoms with tumors of 10-, 15-, 20-, and 30-mm diameter and background ratios (TBRs) of 2, 4, and 8. For the simulation study, sinograms were generated by forward projection of the phantoms. For each phantom, 50 sinograms were generated at 3 noise levels. All sinograms were reconstructed using ordered-subset expectation maximization (OSEM) with 2 iterations and 16 subsets, with or without a 6-mm gaussian filter. For each tumor, the maximum pixel value and the average of a 50%, a 70%, and an adaptive isocontour threshold ROI were derived as well as with an ROI of 15 x 15 mm. The accuracy of SUVs was assessed using the average of 50 ROI values. Treatment response was simulated by varying the tumor size or the TBR. For all situations, a strong correlation was found between maximum and isocontour-based ROI values resulting in similar dependencies on image resolution and noise of all studied SUV measures. A strong variation with tumor size of > or =50% was found for all SUV values. For nonsmoothed data with high noise levels this variation was primarily due to noise, whereas for smoothed data with low noise levels partial-volume effects were most important. In general, SUVs showed under- and overestimations of > or =50% and depended on all parameters studied. However, SUV ratios, used for response monitoring, were only slightly dependent of ROI definition but were still affected by noise and resolution. The poor accuracy of the SUV under various conditions may hamper its use for diagnosis, especially in multicenter trials. SUV ratios used to measure response to treatment, however, are less dependent on noise, image resolution, and ROI definition. Therefore, the SUV might be more suitable for response-monitoring purposes.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Exploring feature-based approaches in PET images for predicting cancer treatment outcomes.

            Accumulating evidence suggests that characteristics of pre-treatment FDG-PET could be used as prognostic factors to predict outcomes in different cancer sites. Current risk analyses are limited to visual assessment or direct uptake value measurements. We are investigating intensity-volume histogram metrics and shape and texture features extracted from PET images to predict patient's response to treatment. These approaches were demonstrated using datasets from cervix and head and neck cancers, where AUC of 0.76 and 1.0 were achieved, respectively. The preliminary results suggest that the proposed approaches could potentially provide better tools and discriminant power for utilizing functional imaging in clinical prognosis.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-Small cell lung cancer.

              PET with (18)F-FDG ((18)F-FDG PET) is increasingly used in the definition of target volumes for radiotherapy, especially in patients with non-small cell lung cancer (NSCLC). In this context, the delineation of tumor contours is crucial and is currently done by different methods. This investigation compared the gross tumor volumes (GTVs) resulting from 4 methods used for this purpose in a set of clinical cases. Data on the primary tumors of 25 patients with NSCLC were analyzed. They had (18)F-FDG PET during initial tumor staging. Thereafter, additional PET of the thorax in treatment position was done, followed by planning CT. CT and PET images were coregistered, and the data were then transferred to the treatment planning system (PS). Sets of 4 GTVs were generated for each case by 4 methods: visually (GTV(vis)), applying a threshold of 40% of the maximum standardized uptake value (SUV(max); GTV(40)), and using an isocontour of SUV = 2.5 around the tumor (GTV(2.5)). By phantom measurements we determined an algorithm, which rendered the best fit comparing PET with CT volumes using tumor and background intensities at the PS. Using this method as the fourth approach, GTV(bg) was defined. A subset of the tumors was clearly delimitable by CT. Here, a GTV(CT) was determined. We found substantial differences between the 4 methods of up to 41% of the GTV(vis). The differences correlated with SUV(max), tumor homogeneity, and lesion size. The volumes increased significantly from GTV(40) (mean 53.6 mL) < GTV(bg) (94.7 mL) < GTV(vis) (157.7 mL) and GTV(2.5) (164.6 mL). In inhomogeneous lesions, GTV(40) led to visually inadequate tumor coverage in 3 of 8 patients, whereas GTV(bg) led to intermediate, more satisfactory volumes. In contrast to all other GTVs, GTV(40) did not correlate with the GTV(CT). The different techniques of tumor contour definition by (18)F-FDG PET in radiotherapy planning lead to substantially different volumes, especially in patients with inhomogeneous tumors. Here, the GTV(40) does not appear to be suitable for target volume delineation. More complex methods, such as system-specific contrast-oriented algorithms for contour definition, should be further evaluated with special respect to patient data.
                Bookmark

                Author and article information

                Contributors
                +31-0-204441729 , +31-0-204443090 , f.vvelden@vumc.nl
                Journal
                Eur J Nucl Med Mol Imaging
                European Journal of Nuclear Medicine and Molecular Imaging
                Springer-Verlag (Berlin/Heidelberg )
                1619-7070
                1619-7089
                27 May 2011
                27 May 2011
                September 2011
                : 38
                : 9
                : 1636-1647
                Affiliations
                [1 ]Department of Nuclear Medicine & PET Research, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
                [2 ]Department of Pulmonary Diseases, VU University Medical Center, Amsterdam, The Netherlands
                Article
                1845
                10.1007/s00259-011-1845-6
                3151405
                21617975
                52eb0413-0b83-4c5c-988b-e14501bc296a
                © The Author(s) 2011
                History
                : 21 January 2011
                : 9 May 2011
                Categories
                Original Article
                Custom metadata
                © Springer-Verlag 2011

                Radiology & Imaging
                intensity-volume histograms (ivh),intratumoural heterogeneity,standardized uptake value (suv),cumulative suv-volume histogram (csh),positron emission tomography (pet)

                Comments

                Comment on this article