TY  - JOUR
AU  - Heise, Daniel
AU  - Schulze-Hagen, Maximilian
AU  - Bednarsch, Jan
AU  - Eickhoff, Roman
AU  - Kroh, Andreas
AU  - Bruners, Philipp
AU  - Eickhoff, Simon B.
AU  - Brecheisen, Ralph
AU  - Ulmer, Florian
AU  - Neumann, Ulf Peter
TI  - CT-Based Prediction of Liver Function and Post-PVE Hypertrophy Using an Artificial Neural Network
JO  - Journal of Clinical Medicine
VL  - 10
IS  - 14
SN  - 2077-0383
CY  - Basel
PB  - MDPI
M1  - FZJ-2021-03081
SP  - 3079 -
PY  - 2021
AB  - Background: This study aimed to evaluate whether hypertrophy after portal vein embolization (PVE) and maximum liver function capacity (LiMAx) are predictable by an artificial neural network (ANN) model based on computed tomography (CT) texture features.Methods: We report a retrospective analysis on 118 patients undergoing preoperative assessment by CT before and after PVE for subsequent extended liver resection due to a malignant tumor at RWTH Aachen University Hospital. The LiMAx test was carried out in a subgroup of 55 patients prior to PVE. Associations between CT texture features and hypertrophy as well as liver function were assessed by a multilayer perceptron ANN model.Results: Liver volumetry showed a median hypertrophy degree of 33.9% (16.5-60.4%) after PVE. Non-response, defined as a hypertrophy grade lower than 25%, was found in 36.5% (43/118) of the cases. The ANN prediction of the hypertrophy response showed a sensitivity of 95.8%, specificity of 44.4% and overall prediction accuracy of 74.6% (p < 0.001). The observed median LiMAx was 327 (248-433) μg/kg/h and was strongly correlated with the predicted LiMAx (R2 = 0.89).Conclusion: Our study shows that an ANN model based on CT texture features is able to predict the maximum liver function capacity and may be useful to assess potential hypertrophy after performing PVE.Keywords: artificial neural network; computed tomography; liver function; liver volume; portal vein embolization.
LB  - PUB:(DE-HGF)16
C6  - 34300246
UR  - <Go to ISI:>//WOS:000676306200001
DO  - DOI:10.3390/jcm10143079
UR  - https://juser.fz-juelich.de/record/894190
ER  -