Quantitative Susceptibility Mapping for Following Intracranial Hemorrhage
Bibliographic record
Abstract
Purpose To follow the evolution of intracranial hemorrhage (ICH) by using quantitative susceptibility mapping (QSM). Materials and Methods Thirty-six patients with ICH confirmed at CT were enrolled to follow ICH evolution on day 2, 7, and 30 after symptom onset between August 2013 and April 2017. QSM was reconstructed from MRI gradient-echo phase images acquired at 1.5 T or 3.0 T. ICH regions were manually drawn on two-dimensional sections of co-registered CT and MR images independently by two raters. The ICH areas and mean values were compared between CT and MRI by using Bland-Altman plots and Pearson correlation. QSM time evolution of ICH was assessed by using paired t tests and was compared with conventional T2-weighted fluid-attenuated inversion recovery, or T1-weighted or T2*-weighted magnitude intensities. Results Significant reductions in ICH susceptibility were found between day 2 and day 7 (P < .001) and between day 7 and day 30 (P = .003), corresponding to different disease stages. The ICH areas measured at CT and QSM were linearly correlated (r2 = 0.98). The mean CT attenuation and mean susceptibility of ICH were linearly correlated (r2 = 0.29). Excellent intra- and interobserver reproducibility were found for QSM (intraclass correlation coefficient, 0.987 and 0.966, respectively). Conclusion Longitudinal evolution of intracranial hemorrhage (ICH) by using quantitative susceptibility mapping (QSM) demonstrated susceptibility differences in different disease stages, which was not found at conventional MRI; therefore, QSM may assist in quantitatively following ICH iron content. © RSNA, 2018 Online supplemental material is available for this article.
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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 | 0.001 |
| 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".