Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics

ConclusionsMachine learning –based ultrasound radiomics features are able to non-invasively distinguish primary liver tumors from metastatic liver tumors.Key Points•Ultrasound-based radiomics was initially used for preoperative classification of primary versus metastatic liver cancer.•Multiple machine learning –based algorithms with cross-validation strategy were applied to extract machine learning–based ultrasound radiomics features.•Distinction between primary and metastatic tumors was obtained with a sensitivity of 0.768 and a specificity of 0.880.
Source: European Radiology - Category: Radiology Source Type: research