Critical assessment of intramodality 3D ultrasound imaging for prostate IGRT compared to fiducial markers
Bibliographic record
Abstract
PURPOSE: A quantitative 3D intramodality ultrasound (US) imaging system was verified for daily in-room prostate localization, and compared to prostate localization based on implanted fiducial markers (FMs). METHODS: Thirteen prostate patients underwent multiple US scans during treatment. A total of 376 US-scans and 817 matches were used to determine the intra- and interoperator variability. Additionally, eight other patients underwent daily prostate localization using both US and electronic portal imaging (EPI) with FMs resulting in 244 combined US-EPI scans. Scanning was performed with minimal probe pressure and a correction for the speed of sound aberration was performed. Uncertainties of both US and FM methods were assessed. User variability of the US method was assessed. RESULTS: The overall US user variability is 2.6 mm. The mean differences between US and FM are: 2.5 ± 4.0 mm (LR), 0.6 ± 4.9 mm (SI), and -2.3 ± 3.6 mm (AP). The intramodality character of this US system mitigates potential errors due to transducer pressure and speed of sound aberrations. CONCLUSIONS: The overall accuracy of US (3.0 mm) is comparable to our FM workflow (2.2 mm). Since neither US nor FM can be considered a gold standard no conclusions can be drawn on the superiority of either method. Because US imaging captures the prostate itself instead of surrogates no invasive procedure is required. It requires more effort to standardize US imaging than FM detection. Since US imaging does not involve a radiation burden, US prostate imaging offers an alternative for FM EPI positioning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".