Fetal Lung-to-Liver Signal Intensity Ratio at MR Imaging: Development of a Normal Scale and Possible Role in Predicting Pulmonary Hypoplasia in Utero
Bibliographic record
Abstract
PURPOSE: To define retrospectively a normal range for lung-to-liver signal intensity ratio (LLSIR) in fetuses of 16-40 weeks gestation by using half-Fourier single-shot turbo spin-echo magnetic resonance (MR) imaging. MATERIALS AND METHODS: Approval from the regional ethics review board for retrospective evaluation was obtained, and informed consent was waived. Retrospective analysis and follow-up of 157 pregnant women who underwent MR imaging over the past 4 years were performed. Seventy-four fetuses were subsequently identified as having clinically normal lung function or normal lung morphologic features at autopsy. A total of 141 normal lungs were analyzed, and the LLSIR was calculated from images on an MR workstation. A mixed-effects statistical model was applied, and 95% prediction intervals were calculated. Ten fetuses with hypoplastic lungs at autopsy were also evaluated. RESULTS: Plotting LLSIR against gestational age demonstrated that, according to the fitted mean curve, the signal intensity ratio was higher with more advanced gestational age. Statistical modeling suggests a quadratic relationship between gestational age and LLSIR. For fetuses in the normal population, the LLSIR ranged from 1.52 at 21 weeks gestation to 4.31 at 34 weeks gestation. For all hypoplastic lungs in fetuses at or beyond 25 weeks gestation, the LLSIR was outside the lower bound of the 95% prediction interval for the normal population. The distinction between hypoplastic lungs and normal lungs at less than 25 weeks gestation is less definitive. CONCLUSION: This study provides a normal scale with a 95% prediction interval for LLSIR.
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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 | 0.000 |
| 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".