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Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients
Iterative reconstructions (IR) might alter radiomic features extraction. We aim to evaluate the influence of Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on CT radiomic features. Patients who underwent unenhanced abdominal CT (Revolution Evo, GE Healthcare, USA) were retrospectively enro...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8229560/ https://www.ncbi.nlm.nih.gov/pubmed/34072633 http://dx.doi.org/10.3390/diagnostics11061000 |
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author | Caruso, Damiano Zerunian, Marta Pucciarelli, Francesco Bracci, Benedetta Polici, Michela D’Arrigo, Benedetta Polidori, Tiziano Guido, Gisella Barbato, Luca Polverari, Daniele Benvenga, Antonella Iannicelli, Elsa Laghi, Andrea |
author_facet | Caruso, Damiano Zerunian, Marta Pucciarelli, Francesco Bracci, Benedetta Polici, Michela D’Arrigo, Benedetta Polidori, Tiziano Guido, Gisella Barbato, Luca Polverari, Daniele Benvenga, Antonella Iannicelli, Elsa Laghi, Andrea |
author_sort | Caruso, Damiano |
collection | PubMed |
description | Iterative reconstructions (IR) might alter radiomic features extraction. We aim to evaluate the influence of Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on CT radiomic features. Patients who underwent unenhanced abdominal CT (Revolution Evo, GE Healthcare, USA) were retrospectively enrolled. Raw data of filtered-back projection (FBP) were reconstructed with 10 levels of ASIR-V (10–100%). CT texture analysis (CTTA) of liver, kidney, spleen and paravertebral muscle for all datasets was performed. Six radiomic features (mean intensity, standard deviation (SD), entropy, mean of positive pixel (MPP), skewness, kurtosis) were extracted and compared between FBP and all ASIR-V levels, with and without altering the spatial scale filter (SSF). CTTA of all organs revealed significant differences between FBP and all ASIR-V reconstructions for mean intensity, SD, entropy and MPP (all p < 0.0001), while no significant differences were observed for skewness and kurtosis between FBP and all ASIR-V reconstructions (all p > 0.05). A per-filter analysis was also performed comparing FBP with all ASIR-V reconstructions for all six SSF separately (SSF0-SSF6). Results showed significant differences between FBP and all ASIR-V reconstruction levels for mean intensity, SD, and MPP (all filters p < 0.0315). Skewness and kurtosis showed no differences for all comparisons performed (all p > 0.05). The application of incremental ASIR-V levels affects CTTA across various filters. Skewness and kurtosis are not affected by IR and may be reliable quantitative parameters for radiomic analysis. |
format | Online Article Text |
id | pubmed-8229560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82295602021-06-26 Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients Caruso, Damiano Zerunian, Marta Pucciarelli, Francesco Bracci, Benedetta Polici, Michela D’Arrigo, Benedetta Polidori, Tiziano Guido, Gisella Barbato, Luca Polverari, Daniele Benvenga, Antonella Iannicelli, Elsa Laghi, Andrea Diagnostics (Basel) Article Iterative reconstructions (IR) might alter radiomic features extraction. We aim to evaluate the influence of Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on CT radiomic features. Patients who underwent unenhanced abdominal CT (Revolution Evo, GE Healthcare, USA) were retrospectively enrolled. Raw data of filtered-back projection (FBP) were reconstructed with 10 levels of ASIR-V (10–100%). CT texture analysis (CTTA) of liver, kidney, spleen and paravertebral muscle for all datasets was performed. Six radiomic features (mean intensity, standard deviation (SD), entropy, mean of positive pixel (MPP), skewness, kurtosis) were extracted and compared between FBP and all ASIR-V levels, with and without altering the spatial scale filter (SSF). CTTA of all organs revealed significant differences between FBP and all ASIR-V reconstructions for mean intensity, SD, entropy and MPP (all p < 0.0001), while no significant differences were observed for skewness and kurtosis between FBP and all ASIR-V reconstructions (all p > 0.05). A per-filter analysis was also performed comparing FBP with all ASIR-V reconstructions for all six SSF separately (SSF0-SSF6). Results showed significant differences between FBP and all ASIR-V reconstruction levels for mean intensity, SD, and MPP (all filters p < 0.0315). Skewness and kurtosis showed no differences for all comparisons performed (all p > 0.05). The application of incremental ASIR-V levels affects CTTA across various filters. Skewness and kurtosis are not affected by IR and may be reliable quantitative parameters for radiomic analysis. MDPI 2021-05-31 /pmc/articles/PMC8229560/ /pubmed/34072633 http://dx.doi.org/10.3390/diagnostics11061000 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Caruso, Damiano Zerunian, Marta Pucciarelli, Francesco Bracci, Benedetta Polici, Michela D’Arrigo, Benedetta Polidori, Tiziano Guido, Gisella Barbato, Luca Polverari, Daniele Benvenga, Antonella Iannicelli, Elsa Laghi, Andrea Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title | Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title_full | Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title_fullStr | Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title_full_unstemmed | Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title_short | Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients |
title_sort | influence of adaptive statistical iterative reconstructions on ct radiomic features in oncologic patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8229560/ https://www.ncbi.nlm.nih.gov/pubmed/34072633 http://dx.doi.org/10.3390/diagnostics11061000 |
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