Quantifying the effect of biopsy lateral decubitus patient positioning compared to supine prostate MRI scanning on prostate translocation and distortion
Bibliographic record
Abstract
INTRODUCTION: More than a quarter of tumors are missed by magnetic resonance imaging/ultrasound (MRI/US) fusion-guided biopsy, the majority due to software-based misregistration. Transrectal approaches to biopsy are typically performed in the lateral decubitus position; conversely, diagnostic MRI is performed with the patient lying supine. Any position-related difference in prostate location or gland deformation could potentially exacerbate misregistration at subsequent biopsy. METHODS: Fifteen healthy male volunteers (mean age 35.9 years, range 27-53) were included in this prospective, institutional review board-approved study. Each volunteer had an MRI performed in the supine position, followed by the second in the lateral decubitus position (mimicking a typical biopsy position). MRI images were co-registered and analyzed in order to assess prostate translocation and distortion. RESULTS: Whole prostate translocation of ≥5 mm was observed in 20% of patients and of ≥3 mm in 60% of patients. When dividing the prostate into prostatic sectors, the prostatic base demonstrated the largest positional difference. When plotting the translocation directions with relative volume difference, there was a moderate negative correlation trend in the latero-lateral direction. Only minimal distortion was observed, with similar distortion among all prostatic sectors. CONCLUSIONS: Positional change affects the prostate translocation, however, the effect on prostate distortion appears to be negligible. Prostate translocation in latero-lateral direction can be minimized with larger bladder volumes. Prostate translocation needs to be considered alongside software misregistration error; however, positional change should not affect software registration of MRI/US fusion-guided prostate biopsy.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 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 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".