Cargando…
MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study
PURPOSE: To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. MATERIALS AND METHODS: Separate water and tissue phantoms were imaged twice with the same protocol in a test-retest experiment using a 1.5-T scanner....
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813908/ https://www.ncbi.nlm.nih.gov/pubmed/33462642 http://dx.doi.org/10.1186/s41747-020-00199-6 |
_version_ | 1783637953578270720 |
---|---|
author | Shur, Joshua Blackledge, Matthew D’Arcy, James Collins, David J. Bali, Maria O’Leach, Martin Koh, Dow-Mu |
author_facet | Shur, Joshua Blackledge, Matthew D’Arcy, James Collins, David J. Bali, Maria O’Leach, Martin Koh, Dow-Mu |
author_sort | Shur, Joshua |
collection | PubMed |
description | PURPOSE: To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. MATERIALS AND METHODS: Separate water and tissue phantoms were imaged twice with the same protocol in a test-retest experiment using a 1.5-T scanner. Protocols were acquired to favour signal-to-noise ratio and resolution. Forty-six features including first order statistics and second-order texture features were extracted, and repeatability was assessed by calculating the concordance correlation coefficient. Separately, base image noise and resolution were manipulated in an in silico experiment, and robustness of features was calculated by assessing percentage coefficient of variation and linear correlation of features with noise and resolution. These simulation data were compared with the acquired data. Features were classified by their degree (high, intermediate, or low) of robustness and repeatability. RESULTS: Eighty percent of the MRI features were repeatable (concordance correlation coefficient > 0.9) in the phantom test-retest experiment. The majority (approximately 90%) demonstrated a strong or intermediate correlation with image acquisition parameter, and 19/46 (41%) and 13/46 (28%) of features were highly robust to noise and resolution, respectively (coefficient of variation < 5%). Agreement between the acquired and simulation data varied, with the range of agreement within feature classes between 11 and 92%. CONCLUSION: Most MRI features were repeatable in a phantom test-retest study. This phantom data may serve as a lower limit of feature MRI repeatability. Robustness of features varies with acquisition parameter, and appropriate features can be selected for clinical validation studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41747-020-00199-6. |
format | Online Article Text |
id | pubmed-7813908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78139082021-01-25 MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study Shur, Joshua Blackledge, Matthew D’Arcy, James Collins, David J. Bali, Maria O’Leach, Martin Koh, Dow-Mu Eur Radiol Exp Original Article PURPOSE: To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. MATERIALS AND METHODS: Separate water and tissue phantoms were imaged twice with the same protocol in a test-retest experiment using a 1.5-T scanner. Protocols were acquired to favour signal-to-noise ratio and resolution. Forty-six features including first order statistics and second-order texture features were extracted, and repeatability was assessed by calculating the concordance correlation coefficient. Separately, base image noise and resolution were manipulated in an in silico experiment, and robustness of features was calculated by assessing percentage coefficient of variation and linear correlation of features with noise and resolution. These simulation data were compared with the acquired data. Features were classified by their degree (high, intermediate, or low) of robustness and repeatability. RESULTS: Eighty percent of the MRI features were repeatable (concordance correlation coefficient > 0.9) in the phantom test-retest experiment. The majority (approximately 90%) demonstrated a strong or intermediate correlation with image acquisition parameter, and 19/46 (41%) and 13/46 (28%) of features were highly robust to noise and resolution, respectively (coefficient of variation < 5%). Agreement between the acquired and simulation data varied, with the range of agreement within feature classes between 11 and 92%. CONCLUSION: Most MRI features were repeatable in a phantom test-retest study. This phantom data may serve as a lower limit of feature MRI repeatability. Robustness of features varies with acquisition parameter, and appropriate features can be selected for clinical validation studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41747-020-00199-6. Springer International Publishing 2021-01-19 /pmc/articles/PMC7813908/ /pubmed/33462642 http://dx.doi.org/10.1186/s41747-020-00199-6 Text en © The Author(s) 2021 Open AccessThis 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/. |
spellingShingle | Original Article Shur, Joshua Blackledge, Matthew D’Arcy, James Collins, David J. Bali, Maria O’Leach, Martin Koh, Dow-Mu MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title | MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title_full | MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title_fullStr | MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title_full_unstemmed | MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title_short | MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
title_sort | mri texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813908/ https://www.ncbi.nlm.nih.gov/pubmed/33462642 http://dx.doi.org/10.1186/s41747-020-00199-6 |
work_keys_str_mv | AT shurjoshua mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT blackledgematthew mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT darcyjames mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT collinsdavidj mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT balimaria mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT oleachmartin mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy AT kohdowmu mritexturefeaturerepeatabilityandimageacquisitionfactorrobustnessaphantomstudyandinsilicostudy |