TH-E-110-08: Free Breathing Hepatic CT Perfusion with Automatic a Posteriori Motion Correction
Bibliographic record
Abstract
Purpose: Current hepatic dynamic contrast enhanced CT (DCE-CT) protocols rely on patients holding their breath either once or multiple times. We propose that hepatic CT perfusion imaging is feasible using a free breathing DCE-CT scanning protocol without prior coaching on breathing and automatic post acquisition image registration to eliminate motion induced artifacts. Methods: 26 patients (21 males, 5 females, average age 71 years) with primary or metastatic hepatomas were scanned with a free- breathing axial shuttle DCE-CT. One-dimensional respiratory motion correction in the axial direction was performed automatically by registering high contrast liver features in every image to that of a chosen reference image. CT Perfusion (GE Healthcare) was extended to calculate root mean squared deviation (RMSD) maps to quantify the amount of respiratory motion before and after motion correction. Functional parameters were generated for both corrected and uncorrected scans to determine the effect of motion induced artifacts. Results: Within the liver, background levels of RMSD due to tissue inhomogeneity, imaging noise and reconstruction artifacts was found to be less than 20 HU. A threshold of 200 HU was chosen to indicate organ motion. The mean fraction of voxels in the liver with RMSD above 200 HU (VF) decreased from 8.0% to 4.0% after correction (p=0.01). A strong correlation was found between initial VF (VFI) and reduction in VF (DVF) due to motion correction (DVF = 0.94*VFI − 3.66, R=0.97). Total blood flow was 30 ml/min/kg (p=0.08) higher in tumour than normal tissue prior to correction and 40 ml/min/kg (p=0.008) after correction. Conclusion: Free breathing DCE-CT in liver is feasible and using a posteriori motion correction reduces potential motion artifacts in functional maps. Motion correction is beneficial in cases where initial VF is greater than 5% or an ROI can not be drawn that includes the portal vein in all volumes. “This research is funded by the Canadian Cancer Society (grant #700386)”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".