A nomogram based on bi-regional radiomics features from multimodal magnetic resonance imaging for preoperative prediction of microvascular invasion in hepatocellular carcinoma | Zendy

Rui Zhang | Zendy; Lei Xu | Zendy; Xue Wen | Zendy; Jiahui Zhang | Zendy; Pengfei Yang | Zendy; Lixia Zhang | Zendy; Xing Xue | Zendy; Xiaoli Wang | Zendy; Qiang Huang | Zendy; Chuangen Guo | Zendy; Yanjun Shi | Zendy; Tianye Niu | Zendy; Feng Chen | Zendy

Open Access

A nomogram based on bi-regional radiomics features from multimodal magnetic resonance imaging for preoperative prediction of microvascular invasion in hepatocellular carcinoma

Author(s) -

Rui Zhang,

Lei Xu,

Xue Wen,

Jiahui Zhang,

Pengfei Yang,

Lixia Zhang,

Xing Xue,

Xiaoli Wang,

Qiang Huang,

Chuangen Guo,

Yanjun Shi,

Tianye Niu,

Feng Chen

Publication year - 2019

Publication title -

quantitative imaging in medicine and surgery

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.766

H-Index - 21

eISSN - 2223-4292

pISSN - 2223-4306

DOI - 10.21037/qims.2019.09.07

Subject(s) - nomogram , medicine , magnetic resonance imaging , radiomics , hepatocellular carcinoma , radiology , cohort , oncology

We aimed to develop and validate a nomogram combining bi-regional radiomics features from multimodal magnetic resonance imaging (MRI) and clinicoradiological characteristics to preoperatively predict microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

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