Automated liver lesion detection in ⁶⁸Ga DOTATATE PET/CT using a deep fully convolutional neural network.

ABSTRACT:

Background

Gastroenteropancreatic neuroendocrine tumors most commonly metastasize to the liver; however, high normal background ⁶⁸Ga-DOTATATE activity and high image noise make metastatic lesions difficult to detect. The purpose of this study is to develop a rapid, automated and highly specific method to identify ⁶⁸Ga-DOTATATE PET/CT hepatic lesions using a 2D U-Net convolutional neural network.

Methods

A retrospective study of ⁶⁸Ga-DOTATATE PET/CT patient studies (n = 125; 57 with ⁶⁸Ga-DOTATATE hepatic lesions and 68 without) was evaluated. The dataset was randomly divided into 75 studies for the training set (36 abnormal, 39 normal), 25 for the validation set (11 abnormal, 14 normal) and 25 for the testing set (11 abnormal, 14 no

SUBMITTER: Wehrend J 

PROVIDER: S-EPMC8487415 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature