Post‐therapeutic needle biopsy in patients with hepatocellular carcinoma is a useful tool to evaluate response to proton irradiation
Bibliographic record
Abstract
AIM: Proton beam therapy is safe and more effective than conventional radiation therapy for the local control of nodular hepatocellular carcinoma (HCC). However, evaluating therapeutic response by imaging is not accurate during the early post-irradiation period. Therefore, we examined whether the histopathological study of biopsy specimens obtained at 3 weeks after irradiation can be used to more accurately assess therapeutic response. METHODS: Fifteen HCC lesions from 13 patients were treated with proton beam irradiation. Tissue biopsy samples were obtained using abdominal ultrasound-guided percutaneous fine-needle aspiration from the center of the tumor before, 3 weeks after and 1 year post-proton therapy. The specimens were examined after staining with hematoxylin-eosin (HE) and a MIB-1 antibody. RESULTS: MIB-1 labeling indices (LI) before treatment were 13.0 ± 8.5% (mean ± SD; range, 0.6-27.0), whereas those 3 weeks after proton therapy were significantly reduced to 3.2 ± 2.4% (range, 0.6-8.9) (P < 0.05). Although the tumor size was reduced, we did not observe a reduction in tumor blood flow by dynamic computed tomography or degenerative changes by HE. All lesions that displayed reduced MIB-1 LI at 3 weeks post-proton treatment were ultimately diagnosed as complete response at 1 year after treatment. In contrast, one case with increased MIB-1 LI at 3 weeks had significant tumor size progression at 1 year post-treatment. CONCLUSION: The percutaneous fine-needle aspiration biopsy of HCC is a safe and useful tool that can be used to evaluate the response to proton irradiation. In particular, MIB-1 LI may provide additional information to assess the therapeutic response of HCC during the early post-irradiated period.
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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) | 0.001 | 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".