Han Wang

Prof. Dr. Han Wang

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 December 2021 in ACS Nano
Verified
Journal Article
Closed access
TXTingting Xiao
Tingting Xiao
MHMeijuan He
Meijuan He
FXFang Xu
Fang Xu
YFYu Fan
Yu Fan
BJBingyang Jia
Bingyang Jia
Xiangyang ShiXiangyang Shi
Xiangyang Shi

25 November 2023 in ACS Nano
Verified
Journal Article
Closed access
YGYue Gao
Yue Gao
ZOZhijun Ouyang
Zhijun Ouyang
SSSiyan Shen
Siyan Shen
HYHongwei Yu
Hongwei Yu
BJBingyang Jia
Bingyang Jia
Xiangyang ShiXiangyang Shi
Xiangyang Shi

26 October 2018 in Journal of Magnetic Resonance Imaging
Verified
Journal Article
Open access
PDF file
ZLZhicong Li
Zhicong Li
HLHailin Li
Hailin Li
SWShiyu Wang
Shiyu Wang
DDDi Dong
Di Dong
FYFangfang Yin
Fangfang Yin
HWHan Wang
Han Wang
Background: Lymph‐vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI.Purpose: To develop and validate an axial T1 contrast‐enhanced (CE) MR‐based radiomics nomogram that incorporated a radiomics signature and some clinical parameters for predicting LVSI of cervical cancer preoperatively.Study Type: Retrospective.Population: In all, 105 patients were randomly divided into two cohorts at a 2:1 ratio.Field Strength/Sequence: T1 CE MRI sequences at 1.5T.Assessment: Univariate analysis was performed on the radiomics features and clinical parameters. Multivariate analysis was performed to determine the optimal feature subset. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of prediction model and radiomics nomogram.Statistical Tests: The Mann–Whitney U‐test and the chi‐square test were used to evaluate the performance of clinical characteristics and LVSI status by pathology. The minimum‐redundancy/maximum‐relevance and recursive feature elimination methods were applied to select the features. The radiomics model was constructed using logistic regression.Results: Three radiomics features and one clinical characteristic were selected. The radiomics nomogram showed favorable discrimination between LVSI and non‐LVSI groups. The AUC was 0.754 (95% confidence interval [CI], 0.6326–0.8745) in the training cohort and 0.727 (95% CI, 0.5449–0.9097) in the validation cohort. The specificity and sensitivity were 0.756 and 0.828 in the training cohort and 0.773 and 0.692 in the validation cohort.Data Conclusion: T1 CE MR‐based radiomics nomogram serves as a noninvasive biomarker in the prediction of LVSI in patients with cervical cancer preoperatively.Level of Evidence: 4Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2019;49:1420–1426.

31 January 2020 in Small
Verified
Journal Article
Closed access
PDF file
KLKaicheng Liang
Kaicheng Liang
ZLZhicong Li
Zhicong Li
Yu LuoYu Luo
Yu Luo
QZQiuhong Zhang
Qiuhong Zhang
FYFangfang Yin
Fangfang Yin
HWHan Wang
Han Wang

30 November 2016 in Advanced Healthcare Materials
Verified
Journal Article
Closed access
PDF file
PWPing Wei
Ping Wei
JCJingwen Chen
Jingwen Chen
Yong HuYong Hu
Yong Hu
Xin LiXin Li
Xin Li
HWHan Wang
Han Wang
Xiangyang ShiXiangyang Shi
Xiangyang Shi

10 August 2017 in Journal of Materials Chemistry B
Verified
Journal Article
Closed access
PDF file
DMDan Ma
Dan Ma
JCJingwen Chen
Jingwen Chen
YLYu Luo
Yu Luo
HWHan Wang
Han Wang
Xiangyang ShiXiangyang Shi
Xiangyang Shi
We report a convenient strategy to prepare ultrasmall Fe3O4 nanoparticles (NPs) coated with zwitterion L-cysteine (Cys) for enhanced T1-weighted magnetic resonance (MR) imaging applications. The formed Fe3O4–PEG–Cys NPs possess antifouling properties, good r1 relaxivity, excellent cytocompatibility and hemocompatibility, and can be used as a contrast agent for enhanced blood pool and tumor MR imaging.