Radiological response in Saudi patients undergoing transarterial chemoembolization for hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is the second commonest cancer affecting males and the eighth most common one affecting females in Saudi Arabia. Transarterial chemoembolization (TACE) is currently considered the first line therapy for multifocal HCC in selected patients. OBJECTIVE: To evaluate HCC response to TACE based on triphasic computerized tomography (CT) of the liver obtained 6 weeks after the procedure. MATERIALS AND METHODS: A retrospective chart review of 15 patients who underwent TACE in King Khalid University Hospital for unresectable HCC. Patients were staged according to the Child-Pugh, Okuda, and CLIP scoring systems. The first triphasic CT of the liver after TACE was evaluated for Lipiodol uptake and interval change in tumor burden. RESULTS: The mean age was 63 years (40-82), 10 were males (66.7%), and five were females. About 11 patients had cirrhosis (73.3%). Eight patients (53.3%) were Child-Pugh class A while seven (46.7%) were Child-Pugh class B. One patient died and two were lost to follow up. Four patients had a complete response to TACE (26.7%), two had a partial response (13.3%), five showed no change (33.3%) and none showed progression of disease. Tumoral Lipiodol uptake in five patients was> 75% (33.3%), in two 75-50% (13.3%) while in four patients it was < 50% (26.7%). CONCLUSION: Our results show that TACE is an effective method of reducing the tumor burden in selected patients with unresectable HCC.
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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 | 0.002 |
| 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) | 0.001 | 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".