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Functional liver imaging and dosimetry for risk stratification in patients with hepatocellular carcinoma undergoing radiotherapy: validation study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 2025 Vol.209() p. 110963

Tsai J, Grassberger C, Nyflot MJ, Thonglert K, Zaki P, Nguyen MH, Schaub SK, Apisarnthanarax S, Bowen SR

📝 환자 설명용 한 줄

[BACKGROUND] Functional liver imaging has potential to personalize management of Hepatocellular Carcinoma (HCC) by mitigating hepatotoxicity risk.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • p-value P<0.001
  • 95% CI 0.67-0.73
  • HR 1.56

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BibTeX ↓ RIS ↓
APA Tsai J, Grassberger C, et al. (2025). Functional liver imaging and dosimetry for risk stratification in patients with hepatocellular carcinoma undergoing radiotherapy: validation study.. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 209, 110963. https://doi.org/10.1016/j.radonc.2025.110963
MLA Tsai J, et al.. "Functional liver imaging and dosimetry for risk stratification in patients with hepatocellular carcinoma undergoing radiotherapy: validation study.." Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, vol. 209, 2025, pp. 110963.
PMID 40456294

Abstract

[BACKGROUND] Functional liver imaging has potential to personalize management of Hepatocellular Carcinoma (HCC) by mitigating hepatotoxicity risk. We validated functional liver imaging and dosimetric parameters for risk-stratification in an expanded cohort of patients with HCC.

[METHODS] We reviewed 109 consecutive patients who underwent Sulfur Colloid (SC)-SPECT/CT scans for radiation therapy (RT) planning and extracted previously reported functional liver imaging metrics. We generated elastic net multivariable Cox models with event-stratified and nested cross-validation folds to predict Overall Survival (OS) and increase in Child-Pugh score ≥ 2 (CP+2). Test-fold patients were risk-stratified, and time-dependent model performance was characterized. ROC analysis generated prognostic cutoffs with confidence intervals to guide functional liver avoidance treatment planning.

[RESULTS] Cross-validated model concordance was 0.70 (95% CI: 0.67-0.73) for OS and 0.67 (95% CI: 0.63-0.71) for CP+2. Top-ranked OS predictors included tumor volume (HR=1.56, 1.54-1.58), CP-score (HR=1.36, 1.34-1.38), Liver-GTV V20 (HR=1.310, 1.306-1.314), prior liver-directed therapy (HR=0.83, 0.82-0.85), functional liver volume dosimetry (FLV V20) (HR=1.19, 1.14-1.23), and RT-year (HR=0.89, 0.88-0.91). Top-ranked CP+2 predictors were total liver function (TLF) (HR=0.64, 0.63-0.66), Liver-GTV mean dose (HR=1.40, 1.36-1.49), and CP-score (HR=1.19, 1.16-1.23). Test-fold risk groups were defined for each endpoint (log-rank P<0.001). OS model performance stabilized beyond 2 years; CP+2 model stability peaked within 1 year. Optimal strata for 2-yr OS were FLV V20 < 25.8% and Liver-GTV V20 < 25.4%; 1-yr CP+2 strata were TLF < 0.91 and Liver-GTV mean dose < 18.9 Gy.

[CONCLUSION] Functional liver metrics on SC-SPECT/CT were validated alongside clinical and dosimetric factors within robust outcome models. Testing of personalized RT planning for patients with HCC to preserve liver function is warranted in clinical trials.

MeSH Terms

Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Female; Male; Middle Aged; Aged; Risk Assessment; Radiotherapy Dosage; Single Photon Emission Computed Tomography Computed Tomography; Radiotherapy Planning, Computer-Assisted; Retrospective Studies; Liver