Externally placed vs intravaginally positioned radio frequency coils for quantitative spin-spin relaxometry of ovarian follicular fluid.
Bibliographic record
Abstract
OBJECTIVE: To evaluate different imaging protocols, especially with respect to radio frequency (RF) receiver coil location, for their suitability in providing least squares derived quantitative T2 values of ovarian follicular fluid for investigations of basic ovarian physiology. METHODS: The ovaries of 10 women were imaged via magnetic resonance imaging (MRI) using externally positioned and intravaginally placed RF receiver coils. Half-Fourier acquisition with single-shot turbo spin-echo (HASTE), multiple-echo T2, Dixon, turbo spin-echo, and 3-dimensional (3D) fast imaging with steady-state precession (FISP) and time-reversed FISP (PSIF) sequences were used. Quantitative T2 nuclear spin relaxation rate information from the ovarian follicles between data acquired with the external and intravaginal coils were compared. Additionally, the amount of ovarian follicle and corpora lutea structural detail visible was qualitatively assessed. RESULTS: The T2 computations indicated that there was no difference in the follicular fluid T2 values or in the heterogeneity (spatial variance) of the T2 values between data acquired with the external RF coil and data acquired with the intravaginal RF coil. The best sequences for the visualization of ovarian internal structure were the 3D PSIF sequences and the multiple-echo T2-weighted images, confirming our earlier imaging work on excised cow ovaries. CONCLUSION: It is best to use an externally placed RF coil for quantitative MRI study of ovarian physiology given the lack of difference in quantitative T2 information and the difficulty associated with imaging the ovaries using an intravaginal RF probe.
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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 | 0.004 |
| 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 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".