Blog
About

7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Point-spread function reconstructed PET images of sub-centimeter lesions are not quantitative

      Read this article at

      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

          Background

          PET image reconstruction methods include modeling of resolution degrading phenomena, often referred to as point-spread function (PSF) reconstruction. The aim of this study was to develop a clinically relevant phantom and characterize the reproducibility and accuracy of high-resolution PSF reconstructed images of small lesions, which is a prerequisite for using PET in the prediction and evaluation of responses to treatment.

          Sets of small homogeneous 18F-spheres (range 3–12 mm diameter, relevant for small lesions and lymph nodes) were suspended and covered by a 11C-silicone, which provided a scattering medium and a varying sphere-to-background ratio. Repeated measurements were made on PET/CT scanners from two vendors using a wide range of reconstruction parameters. Recovery coefficients (RCs) were measured for clinically used volume-of-interest definitions.

          Results

          For non-PSF images, RCs were reproducible and fell monotonically as the sphere diameter decreased, which is the expected behavior. PSF images converged slower and had artifacts: RCs did not fall monotonically as sphere diameters decreased but had a maximum RC for sphere sizes around 8 mm, RCs could be greater than 1, and RCs were less reproducible. To some degree, post-reconstruction filters could suppress PSF artifacts.

          Conclusions

          High-resolution PSF images of small lesions showed artifacts that could lead to serious misinterpretations when used for monitoring treatment response. Thus, it could be safer to use non-PSF reconstruction for quantitative purposes unless PSF reconstruction parameters are optimized for the specific task.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40658-016-0169-9) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references 19

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

          Fully 3-D PET reconstruction with system matrix derived from point source measurements.

          The quality of images reconstructed by statistical iterative methods depends on an accurate model of the relationship between image space and projection space through the system matrix The elements of the system matrix for the clinical Hi-Rez scanner were derived by processing the data measured for a point source at different positions in a portion of the field of view. These measured data included axial compression and azimuthal interleaving of adjacent projections. Measured data were corrected for crystal and geometrical efficiency. Then, a whole system matrix was derived by processing the responses in projection space. Such responses included both geometrical and detection physics components of the system matrix. The response was parameterized to correct for point source location and to smooth for projection noise. The model also accounts for axial compression (span) used on the scanner. The forward projector for iterative reconstruction was constructed using the estimated response parameters. This paper extends our previous work to fully three-dimensional. Experimental data were used to compare images reconstructed by the standard iterative reconstruction software and the one modeling the response function. The results showed that the modeling of the response function improves both spatial resolution and noise properties.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls.

            In this paper, the authors review the field of resolution modeling in positron emission tomography (PET) image reconstruction, also referred to as point-spread-function modeling. The review includes theoretical analysis of the resolution modeling framework as well as an overview of various approaches in the literature. It also discusses potential advantages gained via this approach, as discussed with reference to various metrics and tasks, including lesion detection observer studies. Furthermore, attention is paid to issues arising from this approach including the pervasive problem of edge artifacts, as well as explanation and potential remedies for this phenomenon. Furthermore, the authors emphasize limitations encountered in the context of quantitative PET imaging, wherein increased intervoxel correlations due to resolution modeling can lead to significant loss of precision (reproducibility) for small regions of interest, which can be a considerable pitfall depending on the task of interest.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Monitoring and predicting response to therapy with 18F-FDG PET in colorectal cancer: a systematic review.

              Molecular imaging with (18)F-FDG PET has been proven useful in the management of colorectal cancer. (18)F-FDG PET plays a pivotal role in staging before surgical resection of recurrent colorectal cancer and metastases, in the localization of recurrence in patients with an unexplained rise in serum carcinoembryonic antigen levels, and in the assessment of residual masses after treatment. Currently, there is increasing interest in the role of (18)F-FDG PET beyond staging. The technique appears to have significant potential for the characterization of tumors and for the prediction of prognosis in the context of treatment stratification and early assessment of tumor response to therapy. This systematic review provides an overview of the literature on the value of (18)F-FDG PET for monitoring and predicting the response to therapy in colorectal cancer. The review covers chemotherapy response monitoring in advanced colorectal cancer, monitoring of the effects of local ablative therapies, and preoperative radiotherapy and multimodality treatment response evaluation in primary rectal cancer. Given the added value of (18)F-FDG PET for these indications, implementation in clinical practice and systematic inclusion in therapeutic trials to exploit the potential of (18)F-FDG PET are warranted.
                Bookmark

                Author and article information

                Contributors
                olelajmu@rm.dk
                Lars.Tolbod@aarhus.rm.dk
                soerehse@rm.dk
                tronbogs@rm.dk
                Journal
                EJNMMI Phys
                EJNMMI Phys
                EJNMMI Physics
                Springer International Publishing (Cham )
                2197-7364
                13 January 2017
                13 January 2017
                December 2017
                : 4
                Affiliations
                [1 ]Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Aarhus, Denmark
                [2 ]Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
                Article
                169
                10.1186/s40658-016-0169-9
                5236043
                28091957
                © 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.

                Categories
                Original Research
                Custom metadata
                © The Author(s) 2017

                Comments

                Comment on this article