Purpose: Radiomics entails the extraction of quantitative imaging biomarkers (or radiomics features) hypothesized to provide additional pathophysiological and/or clinical information compared to qualitative visual observation and interpretation. This retrospective study explores the variability of radiomics features extracted from images acquired with the 0.35 T scanner of an integrated MRI-Linac. We hypothesized we would be able to identify features with high repeatability and reproducibility over various imaging conditions using phantom and patient imaging studies. We also compared findings from the literature relevant to our results. Methods: Eleven scans of a Magphan(®) RT phantom over 13 months and 11 scans of a ViewRay Daily QA phantom over 11 days constituted the phantom data. Patient datasets included 50 images from ten anonymized stereotactic body radiation therapy (SBRT) pancreatic cancer patients (50â Gy in 5 fractions). A True Fast Imaging with Steady-State Free Precession (TRUFI) pulse sequence was selected, using a voxel resolution of 1.5â mmâÃâ1.5â mmâÃâ1.5â mm and 1.5â mmâÃâ1.5â mmâÃâ3.0â mm for phantom and patient data, respectively. A total of 1087 shape-based, first, second, and higher order features were extracted followed by robustness analysis. Robustness was assessed with the Coefficient of Variation (CoVâ<â5%). Results: We identified 130 robust features across the datasets. Robust features were found within each category, except for 2 second-order sub-groups, namely, Gray Level Size Zone Matrix (GLSZM) and Neighborhood Gray Tone Difference Matrix (NGTDM). Additionally, several robust features agreed with findings from other stability assessments or predictive performance studies in the literature. Conclusion: We verified the stability of the 0.35 T scanner of an integrated MRI-Linac for longitudinal radiomics phantom studies and identified robust features over various imaging conditions. We conclude that phantom measurements can be used to identify robust radiomics features. More stability assessment research is warranted.
Robustness Assessment of Images From a 0.35T Scanner of an Integrated MRI-Linac: Characterization of Radiomics Features in Phantom and Patient Data.
阅读:5
作者:Ericsson-Szecsenyi Rebecka, Zhang Geoffrey, Redler Gage, Feygelman Vladimir, Rosenberg Stephen, Latifi Kujtim, Ceberg Crister, Moros Eduardo G
| 期刊: | Technology in Cancer Research & Treatment | 影响因子: | 2.800 |
| 时间: | 2022 | 起止号: | 2022 Jan-Dec;21:15330338221099113 |
| doi: | 10.1177/15330338221099113 | ||
特别声明
1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。
2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。
3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。
4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。
