Table 1.
Description of RQS parameters
| Parameters | Marks | |
|---|---|---|
| 1 | Image protocol: recorded image protocols in detail (+1) and/or general utilization for reproducibility (+1). | 0 _ 2 |
| 2 | Multiple segmentation: Multiple segmentation is done by different fellows or made by different applications (+1). To study feature validity at different segmentation modules. | 0, 1 |
| 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
Phantom study:
To study features validity, a phantom study is an origin of
diversity on the scanners (+1). Multiple time points: Images at different time points - multiple images for treatment and/or pre-treatment follow-up (+1). To study features validity at different time points. Feature reduction: To study features validity by feature selection, feature reduction accommodates features for multiple trials. It prevents the selection of corresponding features for a set of samples. Non-Radiomics: Non-Radiomics features represent an integrated Radiomic study to find the potential correlations between Non-Radiomics and Radiomics features (+1). Biological correlates: identifying biological correlation provides insight into the biological correspondence with Radiomics (+1). Cut-off: cut-off investigations identify risk factors or at-risk populations using statistical analyses (+1). Discrimination and resampling: based on the results of statistical analyses, discrimination is determined by the ROC curve, AUC, concordance statistic. Statistical significance is determined by P-value, confidence interval (+1). The resampling method can be utilized by cross-validation and bootstrap techniques in statistics (+1). Calibration: calibration statistics are used in predictive analytics by calibration slope, calibration plot, calibration in the large, and determining the statistical significance by P-value, confidence interval (+1). The resampling method can be utilized by cross-validation and bootstrap techniques in statistics (+1). Prospective: prospective models are used in the trial studies for validation of clinical prediction models to determine the application of specific radiomic biomarkers (+7). Validation: validation is an established set of data from the same institute (+2), from another institute (+3), two separate institutes (+4), a published study in the past (+4), and three or more separate institutes (+5), or lack of validation (−5). Gold standard: it determines which model in the Radiomic study is in concordance with the gold standard model (+2). Clinical utility: it determines whether the Radiomic study is potentially useful (+1) or currently active (+1) in clinical applications. Cost-effectiveness: it determines whether the Radiomic study is valuable and cost-effective in clinical applications (+1). Open science: making encoded data available for public and open encrypted data, promotes consistency and the ability to reproduce the study. Open source of scans (+1), open-source of ROI segmentation (+1), open-source of code (+1), calculation radiomic features based on a typical set of ROIs and ROIs are open source (+1). |
0,
1 0, 1 −3, + 3 0, 1 0, 1 0, 1 0 _ 2 0 _ 2 0, + 7 −5, 2 _ 5 0, + 2 0 _ 2 0, 1 0 _ 4 |