Diagnostic Performance of Abnormal Nulling on Cardiac Magnetic Resonance Imaging Look Locker Inversion Time Sequence in Differentiating Cardiac Amyloidosis Types
Bibliographic record
Abstract
PURPOSE: To evaluate the diagnostic utility of the Look Locker inversion time (TI) sequence on cardiac magnetic resonance imaging in patients with suspected cardiac amyloidosis and to evaluate whether there are differences in the nulling pattern between amyloid types. MATERIALS AND METHODS: A total of 144 patients with suspected cardiac amyloidosis who had undergone cardiac magnetic resonance imaging were included in this retrospective study. Sixty-four had cardiac amyloidosis (62.1±9.2 y, 70.3% male, 68.8% had light chain amyloid [AL], 18.8% had familial transthyretin amyloid caused by mutant genes [ATTRm], and 12.5% had wild-type transthyretin amyloid [ATTRwt]) and 80 did not have cardiac amyloidosis (61.3±13.3 y, 58.8% male). Time to myocardial and blood pool nulling on the Look Locker TI sequence was classified as normal if blood pool nulled before myocardium or abnormal if blood pool nulling was coincident with or after myocardial nulling. RESULTS: The nulling pattern was abnormal in 26 patients with cardiac amyloidosis compared with none of the patients without cardiac amyloidosis (40.6% vs. 0.0%, P<0.0001). Abnormal nulling had 40.6% sensitivity and 100% specificity for cardiac amyloidosis (area under the receiver operating characteristic curve: 0.703, 95% confidence interval: 0.642-0.764). All patients with cardiac amyloidosis with an abnormal nulling pattern demonstrated late gadolinium enhancement. Among patients with cardiac amyloidosis, there was no significant difference in abnormal nulling between AL, ATTRm, and ATTRwt amyloid types (31.8%, 58.3%, 62.5%, respectively, P=0.10). CONCLUSIONS: An abnormal nulling pattern on the Look Locker TI sequence is highly specific for cardiac amyloidosis when present. However, abnormal nulling is a late finding with low sensitivity and does not differentiate between amyloid types.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".