Quantification of Doppler Indices, Contrast Ultrasound Enhancement Phases and Perfusion Parameters of Hepatic Parenchyma in Healthy Dogs
Bibliographic record
Abstract
Background: The Liver is a well vascularized organ. Any pathology can impede its blood flow and this makes liver the most suitable organ for studying the Doppler indices and contrast enhanced perfusion parameters. Methods: This clinical study enrolled 9 healthy dogs including 2 breeds each of beagle, German shepherd, Labrador Retriever, and one breed each of Crossbred, Pug and Pit bull. Spectral Doppler sonography and contrast enhanced ultrasonography (CEUS) of liver vasculature using a second generation contrast agent (Sonovue) was performed to standardize their normal pulsed-wave Doppler indices and contrast enhanced perfusion parameters. Result: The mean ± SE values of Doppler indices of portal vein were PSV (27.68 ± 2.08 cm/s), EDV (15.32 ± 1.74 cm/s), MV (14.05 ± 1.94 cm/s), RI (0.44 ± 0.05) and PI (0.93 ± 0.11). Mean ± SE value of Doppler indices of hepatic artery were 53.78 ± 3.45 cm/s (PSV), 13.90 ± 1.82 cm/s (EDV), 21.63 ± 1.21 cm/s (MV), 0.73 ± 0.04 (RI), 1.93 ± 0.28 (PI) and for hepatic vein were 38.62 ± 4.62 cm/s (PSV), 11.92 ± 2.79 cm/s (EDV), 17.72 ± 2.95 cm/s (MV), 0.69 ± 0.06 (RI), 1.69 ± 0.23 (PI). CEUS of hepatic parenchyma showed three phases viz arterial, portal and late portal phase. Mean ± SE values of contrast enhanced hepatic perfusion parameters (in seconds) were 7.22 ±0.40 (Arrival time), 16.33 ±1.38 (Time to initial peak), 30.22 ±1.29 (Time to final peak), 54.55 ±2.93 (Decline time) and 160.78±8.60 (Washout time).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".