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Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions
Feature stability and standardization remain challenges that impede the clinical implementation of radiomics. This study investigates the potential of spectral reconstructions from photon-counting computed tomography (PCCT) regarding organ-specific radiomics feature stability. Abdominal portal-venou...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665022/ https://www.ncbi.nlm.nih.gov/pubmed/36379992 http://dx.doi.org/10.1038/s41598-022-22877-8 |
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author | Tharmaseelan, Hishan Rotkopf, Lukas T. Ayx, Isabelle Hertel, Alexander Nörenberg, Dominik Schoenberg, Stefan O. Froelich, Matthias F. |
author_facet | Tharmaseelan, Hishan Rotkopf, Lukas T. Ayx, Isabelle Hertel, Alexander Nörenberg, Dominik Schoenberg, Stefan O. Froelich, Matthias F. |
author_sort | Tharmaseelan, Hishan |
collection | PubMed |
description | Feature stability and standardization remain challenges that impede the clinical implementation of radiomics. This study investigates the potential of spectral reconstructions from photon-counting computed tomography (PCCT) regarding organ-specific radiomics feature stability. Abdominal portal-venous phase PCCT scans of 10 patients in virtual monoenergetic (VM) (keV 40–120 in steps of 10), polyenergetic, virtual non-contrast (VNC), and iodine maps were acquired. Two 2D and 3D segmentations measuring 1 and 2 cm in diameter of the liver, lung, spleen, psoas muscle, subcutaneous fat, and air were obtained for spectral reconstructions. Radiomics features were extracted with pyradiomics. The calculation of feature-specific intraclass correlation coefficients (ICC) was performed by comparing all segmentation approaches and organs. Feature-wise and organ-wise correlations were evaluated. Segmentation-resegmentation stability was evaluated by concordance correlation coefficient (CCC). Compared to non-VM, VM-reconstruction features tended to be more stable. For VM reconstructions, 3D 2 cm segmentation showed the highest average ICC with 0.63. Based on a criterion of ≥ 3 stable organs and an ICC of ≥ 0.75, 12—mainly non-first-order features—are shown to be stable between the VM reconstructions. In a segmentation-resegmentation analysis in 3D 2 cm, three features were identified as stable based on a CCC of > 0.6 in ≥ 3 organs in ≥ 6 VM reconstructions. Certain radiomics features vary between monoenergetic reconstructions and depend on the ROI size. Feature stability was also shown to differ between different organs. Yet, glcm_JointEntropy, gldm_GrayLevelNonUniformity, and firstorder_Entropy could be identified as features that could be interpreted as energy-independent and segmentation-resegmentation stable in this PCCT collective. PCCT may support radiomics feature standardization and comparability between sites. |
format | Online Article Text |
id | pubmed-9665022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96650222022-11-16 Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions Tharmaseelan, Hishan Rotkopf, Lukas T. Ayx, Isabelle Hertel, Alexander Nörenberg, Dominik Schoenberg, Stefan O. Froelich, Matthias F. Sci Rep Article Feature stability and standardization remain challenges that impede the clinical implementation of radiomics. This study investigates the potential of spectral reconstructions from photon-counting computed tomography (PCCT) regarding organ-specific radiomics feature stability. Abdominal portal-venous phase PCCT scans of 10 patients in virtual monoenergetic (VM) (keV 40–120 in steps of 10), polyenergetic, virtual non-contrast (VNC), and iodine maps were acquired. Two 2D and 3D segmentations measuring 1 and 2 cm in diameter of the liver, lung, spleen, psoas muscle, subcutaneous fat, and air were obtained for spectral reconstructions. Radiomics features were extracted with pyradiomics. The calculation of feature-specific intraclass correlation coefficients (ICC) was performed by comparing all segmentation approaches and organs. Feature-wise and organ-wise correlations were evaluated. Segmentation-resegmentation stability was evaluated by concordance correlation coefficient (CCC). Compared to non-VM, VM-reconstruction features tended to be more stable. For VM reconstructions, 3D 2 cm segmentation showed the highest average ICC with 0.63. Based on a criterion of ≥ 3 stable organs and an ICC of ≥ 0.75, 12—mainly non-first-order features—are shown to be stable between the VM reconstructions. In a segmentation-resegmentation analysis in 3D 2 cm, three features were identified as stable based on a CCC of > 0.6 in ≥ 3 organs in ≥ 6 VM reconstructions. Certain radiomics features vary between monoenergetic reconstructions and depend on the ROI size. Feature stability was also shown to differ between different organs. Yet, glcm_JointEntropy, gldm_GrayLevelNonUniformity, and firstorder_Entropy could be identified as features that could be interpreted as energy-independent and segmentation-resegmentation stable in this PCCT collective. PCCT may support radiomics feature standardization and comparability between sites. Nature Publishing Group UK 2022-11-15 /pmc/articles/PMC9665022/ /pubmed/36379992 http://dx.doi.org/10.1038/s41598-022-22877-8 Text en © The Author(s) 2022 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 | Article Tharmaseelan, Hishan Rotkopf, Lukas T. Ayx, Isabelle Hertel, Alexander Nörenberg, Dominik Schoenberg, Stefan O. Froelich, Matthias F. Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title | Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title_full | Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title_fullStr | Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title_full_unstemmed | Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title_short | Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions |
title_sort | evaluation of radiomics feature stability in abdominal monoenergetic photon counting ct reconstructions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665022/ https://www.ncbi.nlm.nih.gov/pubmed/36379992 http://dx.doi.org/10.1038/s41598-022-22877-8 |
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