Texture analysis of preoperative CT images for prediction of postoperative hepatic insufficiency: a preliminary study.

BACKGROUND: Texture analysis is a promising method of analyzing imaging data to potentially enhance diagnostic capability. This approach involves automated measurement of pixel intensity variation that may offer further insight into disease progression than do standard imaging techniques alone. We postulated that postoperative liver insufficiency, a major source of morbidity and mortality, correlates with preoperative heterogeneous parenchymal enhancement that can be quantified with texture analysis of cross-sectional imaging. STUDY DESIGN: A retrospective case-matched study (waiver of informed consent and HIPAA authorization, approved by the Institutional Review Board) was performed comparing patients who underwent major hepatic resection and developed liver insufficiency (n = 12) with a matched group of patients with no postoperative liver insufficiency (n = 24) by procedure, remnant volume, and year of procedure. Texture analysis (with gray-level co-occurrence matrices) was used to quantify the heterogeneity of liver parenchyma on preoperative CT scans. Statistical significance was evaluated using Wilcoxon's signed rank and Pearson's chi-square tests. RESULTS: No statistically significant differences were found between study groups for preoperative patient demographics and clinical characteristics, with the exception of sex (p < 0.05). Two texture features differed significantly between the groups: correlation (linear dependency of gray levels on neighboring pixels) and entropy (randomness of brightness variation) (p < 0.05). CONCLUSIONS: In this preliminary study, the texture of liver parenchyma on preoperative CT was significantly more varied, less symmetric, and less homogeneous in patients with postoperative liver insufficiency. Therefore, texture analysis has the potential to provide an additional means of preoperative risk stratification.

Remnant growth rate after portal vein embolization is a good early predictor of post-hepatectomy liver failure.

BACKGROUND: After portal vein embolization (PVE), the future liver remnant (FLR) hypertrophies for several weeks. An early marker that predicts a low risk of post-hepatectomy liver failure can reduce the delay to surgery. STUDY DESIGN: Liver volumes of 153 patients who underwent a major hepatectomy (>3 segments) after PVE for primary or secondary liver malignancy between September 1999 and November 2012 were retrospectively evaluated with computerized volumetry. Pre- and post-PVE FLR volume and functional liver volume were measured. Degree of hypertrophy (DH = post-FLR/post-functional liver volume - pre-FLR/pre-functional liver volume) and growth rate (GR = DH/weeks since PVE) were calculated. Postoperative complications and liver failure were correlated with DH, measured GR, and estimated GR derived from a formula based on body surface area. RESULTS: Eligible patients underwent 93 right hepatectomies, 51 extended right hepatectomies, 4 left hepatectomies, and 5 extended left hepatectomies. Major complications occurred in 44 patients (28.7%) and liver failure in 6 patients (3.9%). Nonparametric regression showed that post-embolization FLR percent correlated poorly with liver failure. Receiver operating characteristic curves showed that DH and GR were good predictors of liver failure (area under the curve [AUC] = 0.80; p = 0.011 and AUC = 0.79; p = 0.015) and modest predictors of major complications (AUC = 0.66; p = 0.002 and AUC = 0.61; p = 0.032). No patient with GR >2.66% per week had liver failure develop. The predictive value of measured GR was superior to estimated GR for liver failure (AUC = 0.79 vs 0.58; p = 0.046). CONCLUSIONS: Both DH and GR after PVE are strong predictors of post-hepatectomy liver failure. Growth rate might be a better guide for the optimum timing of liver resection than static volumetric measurements. Measured volumetrics correlated with outcomes better than estimated volumetrics.