Upright Open MRI (MRO) Evaluation of the Anatomic Effects of Yoga Postures on the Bladder Neck and Urethra
Bibliographic record
Abstract
Background/Objectives: Upright open magnetic resonance imaging allows the impact of posture and gravity to be evaluated. Randomized controlled trials of yoga for treating urinary incontinence (UI) in women show significant clinical benefit, yet the anatomic impact of this therapy on the lower urinary tract remains unelucidated. This study tested the hypothesis that open MRI scans can be obtained with sufficient detail to visualize the bladder neck and urethra. Methods: We scanned a volunteer subject using a 0.5 Tesla MRO Open Evo scanner to obtain axial and sagittal T2-weighted pelvic scans during poses used in yoga therapy. To obtain images with the necessary detail, we employed variations in sequencing during scanning of each individual pose. The changes observed in the bladder neck and urethral outline in each pose were then compared to baseline supine images. Results: Images with sufficient anatomic detail were obtained in each of the four poses studied. These scans identified that the urethral outline changes anatomically based on the posture adopted and is dynamic with regional alternations evident in caliber during specific yoga poses. Conclusions: Open MRI can identify anatomical changes involving the bladder neck and urethra that occur during yoga poses used in the treatment of UI in women; these likely relate to effects of posture and gravity. Open MRI offers a way to elucidate the anatomic effects that specific yoga poses generate and to identify those with the potential to be most beneficial clinically to women as a form of therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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) | 0.000 | 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".