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A new formula to calculate the resection limit in hepatectomy based on Gd-EOB-DTPA-enhanced magnetic resonance imaging.

ABSTRACT: BACKGROUND AND AIM:Dynamic magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) can be used not only to detect liver tumors but also to estimate liver function. The aim of this study was to establish a new EOB-MRI-based formula to determine the resection limit in patients undergoing hepatectomy. METHODS:Twenty-eight patients with a normal liver (NL group) and five with an unresectable cirrhotic liver (UL group) who underwent EOB-MRI were included. Standardized liver function (SLF) was calculated based on the signal intensity (SI), the volume of each subsegment (S1-S8), and body surface area. A formula defining the resection limit was devised based on the difference in the SLF values of patients in the NL and UL groups. The formula was validated in 50 patients who underwent EOB-MRI and hepatectomy. RESULTS:The average SLF value in the NL and UL groups was 2038 and 962 FV/m2, respectively. The difference (1076 FV/m2) was consistent with a 70% in resection volume. Thus, the resection limit for hepatectomy was calculated as a proportion of 70%: 70×(SLF-962)/1076 (%). The one patient who underwent hepatectomy over the resection limit died due to liver failure. In other 49 patients, in whom the resection volume was less than the resection limit, procedures were safely performed. CONCLUSIONS:Our formula for resection limit based on EOB-MRI can improve the safety of hepatectomy.

SUBMITTER: Yamada S

PROVIDER: S-EPMC6347147 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A new formula to calculate the resection limit in hepatectomy based on Gd-EOB-DTPA-enhanced magnetic resonance imaging.

Yamada Shinichiro S Shimada Mitsuo M Morine Yuji Y Imura Satoru S Ikemoto Tetsuya T Saito Yu Y Takasu Chie C Yoshikawa Masato M Teraoku Hiroki H Yoshimoto Toshiaki T

PloS one 20190125 1

<h4>Background and aim</h4>Dynamic magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) can be used not only to detect liver tumors but also to estimate liver function. The aim of this study was to establish a new EOB-MRI-based formula to determine the resection limit in patients undergoing hepatectomy.<h4>Methods</h4>Twenty-eight patients with a normal liver (NL group) and five with an unresectable cirrhotic liver (UL group) who underwent EOB-MRI ...[more]

PMID: 30682046

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Project description:BackgroundNuclear protein Ki-67 indicates the status of cell proliferation and has been regarded as an attractive biomarker for the prognosis of HCC. The aim of this study is to investigate which radiomics model derived from different sequences and phases of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI was superior to predict Ki-67 expression in hepatocellular carcinoma (HCC), then further to validate the optimal model for preoperative prediction of Ki-67 expression in HCC.MethodsThis retrospective study included 151 (training cohort: n = 103; validation cohort: n = 48) pathologically confirmed HCC patients. Radiomics features were extracted from the artery phase (AP), portal venous phase (PVP), hepatobiliary phase (HBP), and T2-weighted (T2W) images. A logistic regression with the least absolute shrinkage and selection operator (LASSO) regularization was used to select features to build a radiomics score (Rad-score). A final combined model including the optimal Rad-score and clinical risk factors was established. Receiver operating characteristic (ROC) curve analysis, Delong test and calibration curve were used to assess the predictive performance of the combined model. Decision cure analysis (DCA) was used to evaluate the clinical utility.ResultsThe AP radiomics model with higher decision curve indicating added more net benefit, gave a better predictive performance than the HBP and T2W radiomic models. The combined model (AUC = 0.922 vs. 0.863) including AP Rad-score and serum AFP levels improved the predictive performance more than the AP radiomics model (AUC = 0.873 vs. 0.813) in the training and validation cohort. Calibration curve of the combined model showed a good agreement between the predicted and the actual probability. DCA of the validation cohort revealed that at a range threshold probability of 30-60%, the combined model added more net benefit compared with the AP radiomics model.ConclusionsA combined model including AP Rad-score and serum AFP levels based on enhanced MRI can preoperatively predict Ki-67 expression in HCC.

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Dataset Information

A new formula to calculate the resection limit in hepatectomy based on Gd-EOB-DTPA-enhanced magnetic resonance imaging.

Publications

A new formula to calculate the resection limit in hepatectomy based on Gd-EOB-DTPA-enhanced magnetic resonance imaging.

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