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Gao, Mingyuan

https://orcid.org/0000-0002-7360-3684

Mayo Clinic

Soochow University

Citations 2

A preliminary study of the local biomechanical environment of liver tumors in vivo
Ma, Shengyuan , Zhu, Mo, Xia, Xiaolong, Guo, Liang , Genin, Guy M. , Sacks, Michael S. , Gao, Mingyuan , Mutic, Sasa , Hu, Yanle , Hu, Chunhong , Feng, Yuan

Medical Physics | February 7, 2019 | Volume: 46 | Issue: 4 | Pages: 1728-1739

10.1002/mp.13434 Get It

PurposeBiomechanical properties can be used as biomarkers to diagnose tumors, monitor tumor development, and evaluate treatment efficacy. The purpose of this preliminary study is to characterize the biomechanical environment of two typical liver tumors, hemangiomas (HEMs) and hepatocellular carcinomas (HCCs), and to investigate the potential of using strain metrics as biomarkers for tumor diagnosis, based on a limited clinical dataset.MethodsMagnetic resonance (MR) tagging was used to quantify the motion and deformation of the two types of liver tumors. Displacements of the tumors arising from a heartbeat were measured over one cardiac cycle. Local biomechanical conditions of the tumors were characterized by estimating two principal strains (ε1 and ε2) and an octahedral shear strain (εsoct) of the tumor and its peripheral region. Biomechanical conditions of the tumors were compared with those of the arbitrarily selected regions from healthy volunteers.ResultsWe observed that the HCCs had significantly smaller strain values compared to their peripheral tissues. However, the HEMs did not have significantly different strains from those of the peripheral tissues, and were similar to healthy liver regions. The sensitivity of using ε1, ε2, and εsoct to diagnose HCC were all 1, while the sensitivity of using ε1, ε2, and εsoct to diagnose HEM were 0.67, 0.17, and 0.67, respectively.ConclusionsLagrangian strain metrics provide insight into the biomechanical conditions of certain liver tumors in the human body and may provide another perspective for tumor characterization and diagnosis.
An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images
Dong, Fenglin, Xia, Xiaolong, Hu, Chun-Hong, Fan, Qianmin, Hu, Yanle , Gao, Mingyuan , Mutic, Sasa , Feng, Yuan

Medical Physics | May 17, 2017 | Volume: 44 | Issue: 7 | Pages: 3752-3760

10.1002/mp.12350 Get It