An evaluation of the Clarity 3D ultrasound system for prostate localization
Bibliographic record
Abstract
The purpose of this study is to evaluate the accuracy and precision of the Clarity 3D ultrasound system to track prostate gland positional variations due to setup error and organ motion. Seventeen patients (n = 17) undergoing radical external beam radiation therapy for localized prostate cancer were studied. Subsequent to initial reference ultrasound and planning CT scans, each patient underwent seven repeat weekly tracking CT and ultrasound (US) scans during the course of treatment. Variations in the location of the prostate between reference and tracking scans were measured. Differences reported by CT and ultrasound scans are compared. Ultrasound tracking was initially performed clinically by a group of trained general users. Retrospective prostate localization was then performed by a trained dedicated user upon the original raw data set and also a reduced data set derived from the original by an expert user from Resonant Medical. Correlation accuracy between ultrasound and CT shifts acquired and delineated by a pool of trained general users was deemed unacceptable for radiotherapy purposes. A mean discrepancy between CT and US localizations of greater than 10 mm, with a 5 mm or greater discrepancy rate of nearly 90%, was observed. Retrospective analysis by a dedicated user of both the original and Resonant Medical reduced data sets yielded mean CT-Us discrepancies of 8.7 mm and 7.4 mm, respectively. Unfortunately, the 5 mm or greater CT-US discord rate for these retrospective analyses failed to drop below 80%. The greatest disparity between CT and ultrasound was consistently observed in the superior-inferior direction, while greatest agreement was achieved in the lateral dimension. Despite an expert reanalysis of the original data, the Clarity ultrasound system failed to deliver an acceptable level of geometric accuracy required for modern radiotherapy purposes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".