Quantification of 1.5 T <scp>T<sub>1</sub></scp> and <scp>T<sub>2</sub></scp><sup>*</sup> Relaxation Times of Fetal Tissues in Uncomplicated Pregnancies
Bibliographic record
Abstract
Background Despite its many advantages, experience with fetal magnetic resonance imaging (MRI) is limited, as is knowledge of how fetal tissue relaxation times change with gestational age (GA). Quantification of fetal tissue relaxation times as a function of GA provides insight into tissue changes during fetal development and facilitates comparison of images across time and subjects. This, therefore, can allow the determination of biophysical tissue parameters that may have clinical utility. Purpose To demonstrate the feasibility of quantifying previously unknown T1 and T2* relaxation times of fetal tissues in uncomplicated pregnancies as a function of GA at 1.5 T. Study Type Pilot. Population Nine women with singleton, uncomplicated pregnancies (28–38 weeks GA). Field Strength/Sequence All participants underwent two iterative decomposition of water and fat with echo asymmetry and least‐squares estimation (IDEAL‐IQ) acquisitions at different flip angles (6° and 20°) at 1.5 T. Assessment Segmentations of the lungs, liver, spleen, kidneys, muscle, and adipose tissue (AT) were conducted using water‐only images and proton density fat fraction maps. Driven equilibrium single pulse observation of T1 (DESPOT1) was used to quantify the mean water T1 of the lungs, intraabdominal organs, and muscle, and the mean water and lipid T1 of AT. IDEAL T2* maps were used to quantify the T2* values of the lungs, intraabdominal organs, and muscle. Statistical Tests F‐tests were performed to assess the T1 and T2* changes of each analyzed tissue as a function of GA. Results No tissue demonstrated a significant change in T1 as a function of GA (lungs [P = 0.89]; liver [P = 0.14]; spleen [P = 0.59]; kidneys [P = 0.97]; muscle [P = 0.22]; AT: water [P = 0.36] and lipid [P = 0.14]). Only the spleen and muscle T2* showed a significant decrease as a function of GA (lungs [P = 0.67); liver [P = 0.05]; spleen [P < 0.05]; kidneys [P = 0.70]; muscle [P < 0.05]). Data Conclusion These preliminary data suggest that the T1 of the investigated tissues is relatively stable over 28–38 weeks GA, while the T2* change in spleen and muscle decreases significantly in that period. Level of Evidence 3 Technical Efficacy Stage 2
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".