Assessment of the Therapeutic Response of Hepatocellular Carcinoma Treated With Transcatheter Arterial Chemoembolization
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare contrast-enhanced sonography with 3-phase computed tomography (CT) in assessing the therapeutic response of hepatocellular carcinomas (HCCs) treated with transcatheter arterial chemoembolization (TACE). METHODS: Twenty-nine nodular HCCs treated with TACE were examined with contrast-enhanced sonography, 3-phase helical CT, and conventional angiography. Contrast-enhanced sonographic and CT findings were interpreted separately and prospectively for the presence or absence of contrast enhancement in the treated HCCs. Conventional angiography served as the reference standard. RESULTS: Intratumoral enhancement was seen in 19 HCCs (61%) on contrast-enhanced sonography and 12 HCCs (39%) on CT. Enhancement patterns on sonography were blush in 8 (42%), branching in 2 (11%), nodular in 4 (21%), and stippled in 5 (26%). Of the 19 HCCs with intratumoral enhancement on contrast-enhanced sonography, 13 (68%) showed tumor staining on angiography. Of the 12 HCCs without intratumoral enhancement on sonography, 1 (8%) showed tumor staining on angiography. The sensitivity and specificity of contrast-enhanced sonography in depicting flow in HCCs treated with TACE were 93% and 65%, respectively. The sensitivity and specificity of 3-phase CT were 64% and 100%. CONCLUSIONS: Contrast-enhanced sonography is a more sensitive imaging method than 3-phase CT in depicting vascularity in HCCs treated with TACE.
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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 | 0.001 | 0.004 |
| 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 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".