摘要
AIM: To establish a prognostic formula that distinguishes non-hypervascular hepatic nodules(NHNs) with higher aggressiveness from less hazardous one. METHODS: Seventy-three NHNs were detected in gadolinium ethoxybenzyl diethylene-triamine-pentaaceticacid magnetic resonance imaging(Gd-EOB-DTPA-MRI) study and confirmed to change 2 mm or more in size and/or to gain hypervascularity. All images were interpreted independently by an experienced, board-certified abdominal radiologist and hepatologist; both knew thatthe patients were at risk for hepatocellular carcinoma development but were blinded to the clinical information. A formula predicting NHN destiny was developed using a generalized estimating equation model with thirteen explanatory variables: age, gender, background liver diseases, Child-Pugh class, NHN diameter, T1-weighted imaging/T2-weighted imaging detectability, fat deposition, lower signal intensity in arterial phase, lower signal intensity in equilibrium phase, α-fetoprotein, des-γ-carboxy prothrombin, α-fetoprotein-L3, and coexistence of classical hepatocellular carcinoma. The accuracy of the formula was validated in bootstrap samples that were created by resampling of 1000 iterations. RESULTS: During a median follow-up period of 504 d, 73 NHNs with a median diameter of 9 mm(interquartile range: 8-12 mm) grew or shrank by 68.5%(fifty nodules) or 20.5%(fifteen nodules), respectively, whereas hypervascularity developed in 38.4%(twenty eight nodules). In the fifteen shrank nodules, twelve nodules disappeared, while 11.0%(eight nodules) were stable in size but acquired vascularity. A generalized estimating equation analysis selected five explanatories from the thirteen variables as significant factors to predict NHN progression. The estimated regression coefficients were 0.36 for age, 6.51 for lower signal intensity in arterial phase, 8.70 or 6.03 for positivity of hepatitis B virus or hepatitis C virus, 9.37 for des-γ-carboxy prothrombin, and-4.05 for fat deposition. A formula incorporating the five coefficients revealed sensitivity, specificity, and accuracy of 88.0%, 86.7%, and 87.7% in the formulating cohort, whereas these of 87.2% ± 5.7%, 83.8% ± 13.6%, and 87.3% ± 4.5% in the bootstrap samples. CONCLUSION: These data suggest that the formula helps Gd-EOB-DTPA-MRI detect a trend toward hepatocyte transformation by predicting NHN destiny.
AIM: To establish a prognostic formula that distinguishes non-hypervascular hepatic nodules(NHNs) with higher aggressiveness from less hazardous one. METHODS: Seventy-three NHNs were detected in gadolinium ethoxybenzyl diethylene-triamine-pentaaceticacid magnetic resonance imaging(Gd-EOB-DTPA-MRI) study and confirmed to change 2 mm or more in size and/or to gain hypervascularity. All images were interpreted independently by an experienced, board-certified abdominal radiologist and hepatologist; both knew thatthe patients were at risk for hepatocellular carcinoma development but were blinded to the clinical information. A formula predicting NHN destiny was developed using a generalized estimating equation model with thirteen explanatory variables: age, gender, background liver diseases, Child-Pugh class, NHN diameter, T1-weighted imaging/T2-weighted imaging detectability, fat deposition, lower signal intensity in arterial phase, lower signal intensity in equilibrium phase, α-fetoprotein, des-γ-carboxy prothrombin, α-fetoprotein-L3, and coexistence of classical hepatocellular carcinoma. The accuracy of the formula was validated in bootstrap samples that were created by resampling of 1000 iterations. RESULTS: During a median follow-up period of 504 d, 73 NHNs with a median diameter of 9 mm(interquartile range: 8-12 mm) grew or shrank by 68.5%(fifty nodules) or 20.5%(fifteen nodules), respectively, whereas hypervascularity developed in 38.4%(twenty eight nodules). In the fifteen shrank nodules, twelve nodules disappeared, while 11.0%(eight nodules) were stable in size but acquired vascularity. A generalized estimating equation analysis selected five explanatories from the thirteen variables as significant factors to predict NHN progression. The estimated regression coefficients were 0.36 for age, 6.51 for lower signal intensity in arterial phase, 8.70 or 6.03 for positivity of hepatitis B virus or hepatitis C virus, 9.37 for des-γ-carboxy prothrombin, and-4.05 for fat deposition. A formula incorporating the five coefficients revealed sensitivity, specificity, and accuracy of 88.0%, 86.7%, and 87.7% in the formulating cohort, whereas these of 87.2% ± 5.7%, 83.8% ± 13.6%, and 87.3% ± 4.5% in the bootstrap samples. CONCLUSION: These data suggest that the formula helps Gd-EOB-DTPA-MRI detect a trend toward hepatocyte transformation by predicting NHN destiny.
