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Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging
BACKGROUND: Early cancer detection is crucial for patients’ survival. The image quality in (111)In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-base...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238363/ https://www.ncbi.nlm.nih.gov/pubmed/37266738 http://dx.doi.org/10.1186/s40658-023-00557-4 |
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author | Wikberg, Emma van Essen, Martijn Rydén, Tobias Svensson, Johanna Gjertsson, Peter Bernhardt, Peter |
author_facet | Wikberg, Emma van Essen, Martijn Rydén, Tobias Svensson, Johanna Gjertsson, Peter Bernhardt, Peter |
author_sort | Wikberg, Emma |
collection | PubMed |
description | BACKGROUND: Early cancer detection is crucial for patients’ survival. The image quality in (111)In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction. METHODS: Thirty-seven SPECT/CT examinations with (111)In-octreotide were randomly selected. The inclusion criterion was no liver lesions at the time of examination and for the following 3 years. SPECT images of spheres representing lesions were simulated using MC. The raw data of the spheres were added to the raw data of the established healthy patients in 26 of the examinations, and the remaining 11 examinations were not modified. The images were reconstructed using conventional OSEM reconstruction with attenuation correction and post filtering (fAC OSEM) and MC-based OSEM reconstruction without and with post filtering (MC OSEM and fMC OSEM, respectively). The images were visually and blindly evaluated by a nuclear medicine specialist. The criteria evaluated were liver lesion yes or no, including coordinates if yes, with confidence level 1–3. The percentage of detected lesions and accuracy (percentage of correctly classified cases), as well as tumor-to-normal tissue concentration (TNC) ratios and signal-to-noise ratios (SNRs), were evaluated. RESULTS: The detection rates were 30.8% for fAC OSEM, 42.3% for fMC OSEM, and 50.0% for MC OSEM. The accuracies were 45.9% for fAC OSEM, 45.9% for fMC OSEM, and 54.1% for MC OSEM. The number of false positives was higher for fMC and MC OSEM. The observer’s confidence level was higher in filtered images than in unfiltered images. TNC ratios were significantly higher, statistically, with MC OSEM and fMC OSEM than with AC OSEM, but SNRs were similar due to higher noise with MC OSEM. CONCLUSION: One in two lesions were found using MC OSEM versus one in three using conventional reconstruction. TNC ratios were significantly improved, statistically, using MC-based reconstruction, but the noise levels increased and consequently the confidence level of the observer decreased. For further improvements, image noise needs to be suppressed. |
format | Online Article Text |
id | pubmed-10238363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-102383632023-06-04 Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging Wikberg, Emma van Essen, Martijn Rydén, Tobias Svensson, Johanna Gjertsson, Peter Bernhardt, Peter EJNMMI Phys Original Research BACKGROUND: Early cancer detection is crucial for patients’ survival. The image quality in (111)In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction. METHODS: Thirty-seven SPECT/CT examinations with (111)In-octreotide were randomly selected. The inclusion criterion was no liver lesions at the time of examination and for the following 3 years. SPECT images of spheres representing lesions were simulated using MC. The raw data of the spheres were added to the raw data of the established healthy patients in 26 of the examinations, and the remaining 11 examinations were not modified. The images were reconstructed using conventional OSEM reconstruction with attenuation correction and post filtering (fAC OSEM) and MC-based OSEM reconstruction without and with post filtering (MC OSEM and fMC OSEM, respectively). The images were visually and blindly evaluated by a nuclear medicine specialist. The criteria evaluated were liver lesion yes or no, including coordinates if yes, with confidence level 1–3. The percentage of detected lesions and accuracy (percentage of correctly classified cases), as well as tumor-to-normal tissue concentration (TNC) ratios and signal-to-noise ratios (SNRs), were evaluated. RESULTS: The detection rates were 30.8% for fAC OSEM, 42.3% for fMC OSEM, and 50.0% for MC OSEM. The accuracies were 45.9% for fAC OSEM, 45.9% for fMC OSEM, and 54.1% for MC OSEM. The number of false positives was higher for fMC and MC OSEM. The observer’s confidence level was higher in filtered images than in unfiltered images. TNC ratios were significantly higher, statistically, with MC OSEM and fMC OSEM than with AC OSEM, but SNRs were similar due to higher noise with MC OSEM. CONCLUSION: One in two lesions were found using MC OSEM versus one in three using conventional reconstruction. TNC ratios were significantly improved, statistically, using MC-based reconstruction, but the noise levels increased and consequently the confidence level of the observer decreased. For further improvements, image noise needs to be suppressed. Springer International Publishing 2023-06-02 /pmc/articles/PMC10238363/ /pubmed/37266738 http://dx.doi.org/10.1186/s40658-023-00557-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Research Wikberg, Emma van Essen, Martijn Rydén, Tobias Svensson, Johanna Gjertsson, Peter Bernhardt, Peter Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title | Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title_full | Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title_fullStr | Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title_full_unstemmed | Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title_short | Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)In-octreotide SPECT imaging |
title_sort | evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in (111)in-octreotide spect imaging |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238363/ https://www.ncbi.nlm.nih.gov/pubmed/37266738 http://dx.doi.org/10.1186/s40658-023-00557-4 |
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