Usefulness of Segmented TrueFISP Cardiac Pulse Sequence in Evaluation of Congenital and Acquired Adult Cardiac Abnormalities
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to compare ultrashort TR, segmented trueFISP (fast imaging with steady-state precession) cine MR imaging with segmented FLASH (fast low-angle shot) cine MR imaging for the detection and characterization of congenital and acquired adult cardiac abnormalities. SUBJECTS AND METHODS: Twenty-five patients with known or clinically suspected cardiac abnormalities were imaged on a 1.5-T scanner. Valve plane movies were obtained in patients with suspected valve morphology or function abnormalities or whose horizontal long-axis images showed jets. For each patient, three radiologists independently compared corresponding matched cine FLASH and trueFISP movies for image quality in evaluating anatomy and function of the great vessels and heart. Image quality was rated on a five-point scale, and data were analyzed using both a Wilcoxon's signed rank test and a repeated-measures analysis of variance. RESULTS: Image quality ratings of trueFISP and FLASH showed a statistically significant difference (F = 58.67; df = 1, 72; p < 0.0001), with the average rating for the trueFISP images being significantly higher (mean rating, 4.1 +/- 0.92) than that for the FLASH images (mean, 3.0 +/- 1.0). However, valve architecture in the aortic valves appeared to be better visualized and was more easily measured in valve plane images with FLASH. No statistically significant differences among the ratings of the interpreters (F = 0.018; df = 2, 72; p = 0.9821) were evident, and, therefore, no suggestion of bias was indicated (F = 0.775; df = 1, 2; p = 0.4645). TrueFISP yielded the correct diagnosis prospectively in 13 (100%) of 13 patients, whereas FLASH yielded the correct diagnosis in 12 (92%) of 13 patients. CONCLUSION: TrueFISP images depict morphologic and functional abnormalities with greater clarity and provide greater diagnostic confidence than FLASH images-and in a fraction of the time. A specific exception is in the assessment of valve leaflet architecture and cross-sectional area calculation (i.e., bicuspid aortic valves); in these evaluations, FLASH maintains a complementary diagnostic imaging role.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".