An Accurate Model for Microvascular Invasion Prediction in Solitary Hepatocellular Carcinoma ≤5 cm Based on CEUS and EOB-MRI: A Retrospective Study with External Validation.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
493 patients, of which 134 were MVI positive, were evaluated.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Both the NRI and IDI values >0 indicated that the combined model had significantly positive improvement (p<0.05). [CONCLUSION] The CEUS+EOB model was developed to assist clinicians in evaluating MVI in solitary HCC ≤5 cm.
[RATIONALE AND OBJECTIVES] To develop a model combining contrast-enhanced ultrasound (CEUS) and ethoxybenzyl-enhanced magnetic resonance imaging (EOB-MRI) for predicting microvascular invasion (MVI) i
- p-value p<0.05
APA
Sun Y, Yang H, et al. (2025). An Accurate Model for Microvascular Invasion Prediction in Solitary Hepatocellular Carcinoma ≤5 cm Based on CEUS and EOB-MRI: A Retrospective Study with External Validation.. Academic radiology, 32(9), 5173-5186. https://doi.org/10.1016/j.acra.2025.04.021
MLA
Sun Y, et al.. "An Accurate Model for Microvascular Invasion Prediction in Solitary Hepatocellular Carcinoma ≤5 cm Based on CEUS and EOB-MRI: A Retrospective Study with External Validation.." Academic radiology, vol. 32, no. 9, 2025, pp. 5173-5186.
PMID
40335335 ↗
Abstract 한글 요약
[RATIONALE AND OBJECTIVES] To develop a model combining contrast-enhanced ultrasound (CEUS) and ethoxybenzyl-enhanced magnetic resonance imaging (EOB-MRI) for predicting microvascular invasion (MVI) in solitary hepatocellular carcinoma (HCC) ≤5 cm.
[MATERIALS AND METHODS] Patients between December 2019 and May 2024 in one center were retrospectively enrolled and randomly divided into the training cohort and internal validation cohort in a ratio of 7:3. Patients in a separate center were enrolled between January 2022 and December 2023 to be included as the external validation cohort. CEUS and EOB-MRI image features were extracted and used to develop models in the training cohort, and verified in the two validation cohorts. The predictive accuracy and clinical utility of models were evaluated using area under receiver operating characteristic curve (AUROC), Brier score, calibration plot and decision curve analysis (DCA). Net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compare different models.
[RESULTS] From the two centers a total of 493 patients, of which 134 were MVI positive, were evaluated. The CEUS+EOB model included seven image features and showed better discrimination ability than the individual CEUS/EOB-MRI model, with AUROCs of 0.92, 0.94, and 0.90 in the training cohort and two validation cohorts, respectively (p<0.05). The lowest Brier score of the combined model indicated the highest predictive precision. DCA also showed that the combined model added more net benefits. Both the NRI and IDI values >0 indicated that the combined model had significantly positive improvement (p<0.05).
[CONCLUSION] The CEUS+EOB model was developed to assist clinicians in evaluating MVI in solitary HCC ≤5 cm.
[MATERIALS AND METHODS] Patients between December 2019 and May 2024 in one center were retrospectively enrolled and randomly divided into the training cohort and internal validation cohort in a ratio of 7:3. Patients in a separate center were enrolled between January 2022 and December 2023 to be included as the external validation cohort. CEUS and EOB-MRI image features were extracted and used to develop models in the training cohort, and verified in the two validation cohorts. The predictive accuracy and clinical utility of models were evaluated using area under receiver operating characteristic curve (AUROC), Brier score, calibration plot and decision curve analysis (DCA). Net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compare different models.
[RESULTS] From the two centers a total of 493 patients, of which 134 were MVI positive, were evaluated. The CEUS+EOB model included seven image features and showed better discrimination ability than the individual CEUS/EOB-MRI model, with AUROCs of 0.92, 0.94, and 0.90 in the training cohort and two validation cohorts, respectively (p<0.05). The lowest Brier score of the combined model indicated the highest predictive precision. DCA also showed that the combined model added more net benefits. Both the NRI and IDI values >0 indicated that the combined model had significantly positive improvement (p<0.05).
[CONCLUSION] The CEUS+EOB model was developed to assist clinicians in evaluating MVI in solitary HCC ≤5 cm.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Neoplasm Invasiveness
- Microvessels
- Carcinoma
- Hepatocellular
- Liver Neoplasms
- Retrospective Studies
- Contrast Media
- Ultrasonography
- Magnetic Resonance Imaging
- Liver
- Risk Assessment
- ROC Curve
- Hepatectomy
- Humans
- Male
- Female
- Middle Aged
- Aged
- Contrast-enhanced ultrasound
- Ethoxybenzyl-enhanced magnetic resonance imaging
- Hepatocellular carcinoma
- Microvascular invasion
- Prediction
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