A dynamic approach to identifying desired physiological phases for cardiac imaging using multislice spiral CT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this investigation, we describe a quantitative technique to measure coronary motion, which can be correlated with cardiac image quality using multislice computed tomography (MSCT) scanners. MSCT scanners, with subsecond scanning, thin-slice imaging (sub-millimeter) and volume scanning capabilities have paved the way for new clinical applications like noninvasive cardiac imaging. ECG-gated spiral CT using MSCT scanners has made it possible to scan the entire heart in a single breath-hold. The continuous data acquisition makes it possible for multiple phases to be reconstructed from a cardiac cycle. We measure the position and three-dimensional velocities of well-known landmarks along the proximal, mid, and distal regions of the major coronary arteries [left main (LM), left anterior descending (LAD), right coronary artery (RCA), and left circumflex (LCX)] during the cardiac cycle. A dynamic model (called the "delay algorithm") is described which enables us to capture the same physiological phase or "state" of the anatomy during the cardiac cycle as the instantaneous heart rate varies during the spiral scan. The coronary arteries are reconstructed from data obtained during different physiological cardiac phases and we correlate image quality of different parts of the coronary anatomy with phases at which minimum velocities occur. The motion characteristics varied depending on the artery, with the highest motion being observed for RCA. The phases with the lowest mean velocities provided the best visualization. Though more than one phase of relative minimum velocity was observed for each artery, the most consistent image quality was observed during mid-diastole ("diastasis") of the cardiac cycle and was judged to be superior to other reconstructed phases in 92% of the cases. In the process, we also investigated correlation between cardiac arterial states and other measures of motion, such as the left ventricular volume during a cardiac cycle, which earlier has been demonstrated as an example of how anatomic-specific information can be used in a knowledge-based cardiac CT algorithm. Using these estimates in characterizing cardiac motion also provides realistic simulation models for higher heart rates and also in optimizing volume reconstructions for individual segments of the cardiac anatomy.
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.
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 | 0.000 | 0.003 |
| 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 | 0.000 |
| 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 it