Evaluation of the routine use of pelvic MRI in women presenting with symptomatic uterine fibroids: When is pelvic MRI useful?
Bibliographic record
Abstract
BACKGROUND: Pelvic ultrasound (US) diagnosis of uterine fibroids may overlook coexisting gynecological conditions that contribute to women's symptoms. PURPOSE: To determine the added value of pelvic MRI for women diagnosed with symptomatic fibroids by US, and to identify clinical factors associated with additional MRI findings. STUDY TYPE: Retrospective observational study. POPULATION: In all, 367 consecutive women with fibroids diagnosed by US and referred to our multidisciplinary fibroid center between 2013-2017. FIELD STRENGTH/SEQUENCE: -weighted imaging. ASSESSMENT: Demographics, symptoms, uterine fibroid symptom severity scores, and health-related quality of life scores, as well as imaging findings were evaluated. STATISTICAL TESTS: Patients were separated into two subgroups according to whether MRI provided additional findings to the initial US. Univariate and multivariate regression analyses were performed. RESULTS: Pelvic MRI provided additional information in 162 patients (44%; 95% confidence interval [CI] 39-49%). The most common significant findings were adenomyosis (22%), endometriosis (17%), and partially endocavitary fibroids (15%). Women with pelvic pain, health-related quality of life scores less than 30 out of 100, or multiple fibroids visualized on US had greater odds of additional MRI findings (odds ratio [OR] 1.68, 2.26, 1.63; P = 0.02, 0.004, 0.03, respectively), while nulliparous women had reduced odds (OR 0.55, P = 0.01). Patients with additional MRI findings were treated less often with uterine fibroid embolization (14% vs. 36%, P < 0.001) or MR-guided focused US (1% vs. 5%, P = 0.04), and more often with medical management (17% vs. 8%, P = 0.01). DATA CONCLUSION: Pelvic MRI revealed additional findings in more than 40% of women presenting with symptoms initially ascribed to fibroids by US. Further evaluation using MRI is particularly useful for parous women with pelvic pain, poor quality of life scores, and/or multiple fibroids. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019.
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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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".