التفاصيل البيبلوغرافية
| العنوان: |
Additional file 1 of Reproducibility of radiomic features in CT images of NSCLC patients: an integrative analysis on the impact of acquisition and reconstruction parameters |
| المؤلفون: |
Lisa Rinaldi (11995914), Simone P. De Angelis (11995917), Sara Raimondi (11995920), Stefania Rizzo (68079), Cristiana Fanciullo (11995923), Cristiano Rampinelli (11995926), Manuel Mariani (1750339), Alessandro Lascialfari (640759), Marta Cremonesi (7109249), Roberto Orecchia (34228), Daniela Origgi (68081), Francesca Botta (11995929) |
| سنة النشر: |
2022 |
| المجموعة: |
Smithsonian Institution: Digital Repository |
| مصطلحات موضوعية: |
Artificial Intelligence and Image Processing, Carcinoma (non-small-cell lung), Image processing (computer-assisted), Machine learning, Reproducibility of results, Tomography (x-ray computed) |
| الوصف: |
Additional file 1: Supplementary Methods. Details on the extracted radiomic features. Table S1. List of radiomic features included in the study: the name of the feature and the corresponding category, sub-category and cluster is reported. Table S2. False Discovery Rate (FDR) adjusted p values for univariate and multivariable analysis for the effect of scanner and tube voltage on selected radiomic fetaures^. Table S3. OCCC values and False Discovery Rate (FDR) adjusted p values from the multivariable mixed model for the reconstruction algorithm impact for all the original features (shape features are not included because their value was always 1 since the same VOI was used for all the reconstructions). Table S4. OCCC values and False Discovery Rate (FDR) adjusted p value from the multivariable mixed model for the reconstruction algorithm impact for all the wavelet features. Table S5. OCCC values and False Discovery Rate (FDR) adjusted p value from the multivariable mixed model for the reconstruction algorithm impact (FDR corrected) for all the LoG features. Table S6. Percentage of features falling in each of the 4 groups, for the IR50 and the IR80 reconstructions. The results reported in this table refer to the sub-analysis performed on IR40, IR50, IR60 and IR80 (taking IR40 for comparison), similarly to Table 4 for the complete analysis. The percentage for the original images is evaluated excluding the features of the shape category. Figure S1. Study flowchart with exclusion criteria. Figure S2. Overall Concordance Correlation Coefficient (OCCC) for concordance between different algorithms for the sub-analysis of the blending levels mostly used in our clinical setting (IR40, IR50, IR60 and IR80). The OCCC is plotted within each subtype of feature and for feature extracted from the original images (a), and the Wavelet (b) and LoG-filtered (c) images. Figure S3. Heatmap representing the number of features significantly different for paired comparisons of reconstruction algorithm strength (Wilcoxon signed ... |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| Relation: |
https://figshare.com/articles/journal_contribution/Additional_file_1_of_Reproducibility_of_radiomic_features_in_CT_images_of_NSCLC_patients_an_integrative_analysis_on_the_impact_of_acquisition_and_reconstruction_parameters/19028904 |
| DOI: |
10.6084/m9.figshare.19028904.v1 |
| الاتاحة: |
https://doi.org/10.6084/m9.figshare.19028904.v1 |
| Rights: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.8E40438C |
| قاعدة البيانات: |
BASE |