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HomeAcademic staffDr Jiaqiu Wang
Dr Jiaqiu Wang

Dr Jiaqiu Wang

e410296@lsbu.ac.uk

Computer Science and Informatics

https://orcid.org/0000-0001-7710-3508

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My research focuses on biomechanics and biomedical engineering. I've gained extensive experience in several cross-disciplinary fields, including computational modelling and simulation, medical imaging and processing, as well as mechanical and fluidic experiments.

My research area lies within biomedical engineering, with a primary focus on the computational biomechanical analysis of the cardiovascular system. I've made notable contributions, including the development of an innovative algorithm that automatically reconstructs 3D patient-specific coronary atherosclerotic models using optical coherence tomography (OCT) data. This algorithm significantly improves the accuracy and efficiency of generating personalized models for further analysis.

I've also successfully integrated the fluid-structural interaction (FSI) analytical model into patient-specific cardiovascular models, providing a more comprehensive understanding of the complex interactions between blood flow and the vessel wall. One significant application is the development of a protocol for assessing plaque vulnerability based on biomechanical risk factors using FSI computational models. This protocol has had a substantial impact on clinical decision-making and treatment strategies in patient-specific clinical cases involving carotid and coronary arteries.

In addition to these contributions, I've conducted novel investigations using the FSI model to explore the hemodynamic environment in a cyclic bending coronary artery under different heart rates, as highlighted in my most recent published research.

Beyond mechanical and fluidic computational models, I have extensive experience in working in medical imaging analysis. I currently lead a collaborative team working on an innovative imaging-based method for analysing displacement and strain. Our approach combines optical coherence tomography (OCT) imaging with the digital volume correlation (DVC) algorithm. Furthermore, we actively implement digital imaging/volume correlation (DIC/DVC) and optical flow (OF) algorithms on 4D-CT/MR imaging data of heart chambers or aneurysms, allowing us to track the displacement of these structures over time and calculate biomechanical parameters such as strain.

In the field of MR imaging processing, I've conducted research on fitting the intravoxel incoherent motion (IVIM) sequence using a quasi-diffusion equation, offering potential applications in differentiating glioblastoma by analysing diffusion and perfusion parameters. Additionally, I bring valuable experience in analysing CT imaging of bone structures.

Postgraduate Research Supervision
Current
Mr Chenrui QiuIntelligent solutions for scalable, mission-critical 6G networksPhD
Doctor of Philosophy (PhD)

Queensland University of Technology

2016
2020
Master of Science (MSc) by Research

University of Dundee

2014
2016
Bachelor of Engineering (BEng)

Chongqing University

2010
2014
Postdoctoral Researcher
Queensland University of Technology

2020
2023
Education
Facility Scientist
The University of Queensland

2021
2022
Education
ProposalProjectRoleFunderStatusStatus last updated
Advanced Modelling of Dynamic Coronary ArteriesAdvanced Modelling of Dynamic Coronary ArteriesPrincipal InvestigatorEngineering and Physical Sciences Research Council (EPSRC)OPEN In preparationDec 2023
Frontiers in Bioengineering and Biotechnology
BMC Cardiovascular Disorders
Cogent Engineering
Computer Methods in Biomechanics and Biomedical Engineering
Clinical Neurology and Neurosurgery
BioMedical Engineering OnLine
Queensland University of Technology
Other

Visiting Fellow

Analysis of the hemodynamic with dynamic fluidic domain.

Optical coherence tomography (OCT) imaging and processing.

Development of imaging-based displacement/strain analytical method.

Development of optical coherence elastography (OCE).

Clinical translation of computational biomechanical analysis of the cardiovascular system.

June 2023

Filter publications

Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA
Xie, H., Wu, H., Wang, J., Mendieta, J.B., Yu, H., Xiang, Y., Anbananthan, H., Zhang, J., Zhao, H., Zhu, Z., Huang, Q., Fang, R., Zhu, C. and Li, Z. (2024). Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA. Computer Methods and Programs in Biomedicine. 244, p. 107975. https://doi.org/10.1016/j.cmpb.2023.107975

Computer-assisted pre-operative automatic segmentation and registration tool for malunited radius osteotomy: A proof-of-concept study
Wang, J., Zietal, R., Arase, A., Couzens, G., Pivonka, P. and Fontanarosa, D. (2023). Computer-assisted pre-operative automatic segmentation and registration tool for malunited radius osteotomy: A proof-of-concept study. Results in Engineering. 19, p. 101295. https://doi.org/10.1016/j.rineng.2023.101295

Shape dependent protein‐induced stabilization of gold nanoparticles: From a protein corona perspective
Tukova, A., Nie, Y., Tavakkoli Yaraki, M., Tran, N.T., Wang, J., Rodger, A., Gu, Y. and Wang, Y. (2023). Shape dependent protein‐induced stabilization of gold nanoparticles: From a protein corona perspective. Aggregate. 4 (4), p. e323. https://doi.org/10.1002/agt2.323

MRI-based mechanical analysis of carotid atherosclerotic plaque using a material-property-mapping approach: A material-property-mapping method for plaque stress analysis
Mendieta, J.B., Fontanarosa, D., Wang, J., Paritala. P.K., Muller, J., Lloyd, T. and Li, Z. (2023). MRI-based mechanical analysis of carotid atherosclerotic plaque using a material-property-mapping approach: A material-property-mapping method for plaque stress analysis. Computer Methods and Programs in Biomedicine. 231, p. 107417. https://doi.org/10.1016/j.cmpb.2023.107417

Reproducibility of the computational fluid dynamic analysis of a cerebral aneurysm monitored over a decade
Paritala, P.K., Anbananthan, H., Hautaniemi, J., Smith, M., George, A., Allenby, M., Mendieta, J.B., Wang, J., Maclachlan, L., Liang, E., Prior, M., Yarlagadda, P.K.D.V., Winter, C. and Li, Z. (2023). Reproducibility of the computational fluid dynamic analysis of a cerebral aneurysm monitored over a decade. Scientific Reports. 13, p. 219. https://doi.org/10.1038/s41598-022-27354-w

The Need to Shift from Morphological to Structural Assessment for Carotid Plaque Vulnerability
Xiang, Y., Huang, X., Mendieta, J.B., Wang, J., Paritala, P.K., Lloyd, T. and Li, Z. (2022). The Need to Shift from Morphological to Structural Assessment for Carotid Plaque Vulnerability. Biomedicines. 10 (12), p. 3038. https://doi.org/10.3390/biomedicines10123038

Atomistic Investigation of Titanium Carbide Ti8C5 under Impact Loading
Xia, K., Zhan, H., Shao, J., Wang, J., Zheng, Z., Zhang, X. and Li, Z. (2022). Atomistic Investigation of Titanium Carbide Ti8C5 under Impact Loading. Metals. 12 (11), p. 1989. https://doi.org/10.3390/met12111989

Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function
Wu, H., Wang, J., Catano, J.A.A., Sun, C. and Li, Z. (2022). Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function. Optics Express. 30 (23), pp. 41954-41968. https://doi.org/10.1364/OE.473898

Computational Fluid Dynamics Simulations at Micro-Scale Stenosis for Microfluidic Thrombosis Model Characterization
Zhao, Y.C., Vatankhah, P., Goh, T., Wang, J., Chen, X.V., Kashani, M.N., Zheng, K., Li, Z. and Ju, L.A. (2021). Computational Fluid Dynamics Simulations at Micro-Scale Stenosis for Microfluidic Thrombosis Model Characterization. Molecular & Cellular Biomechanics. 18 (1), pp. 1-10. https://doi.org/10.32604/mcb.2021.012598

Automated classification of coronary plaque calcification in OCT pullbacks with 3D deep neural networks
He, C., Wang, J., Yin, Y. and Li, Z. (2020). Automated classification of coronary plaque calcification in OCT pullbacks with 3D deep neural networks. Journal of Biomedical Optics. 26 (9), p. 095003. https://doi.org/10.1117/1.JBO.25.9.095003

Atherosclerotic Plaque Tissue Characterization: An OCT-Based Machine Learning Algorithm With ex vivo Validation
He, C., Li, Z., Wang, J., Huang, Y., Yin, Y. and Li, Z. (2020). Atherosclerotic Plaque Tissue Characterization: An OCT-Based Machine Learning Algorithm With ex vivo Validation. Frontiers in Bioengineering and Biotechnology. 8. https://doi.org/10.3389/fbioe.2020.00749

Characterization of the Atherosclerotic Plaque Tissue
Paritala, P.K., Yarlagadda, T., Mendieta, J.B., Wang, J., Gu, Y., Li, Z. and Yarlagadda, P.K.D.V. (2020). Characterization of the Atherosclerotic Plaque Tissue. Advanced Materials Letters. 11 (5). https://doi.org/10.5185/amlett.2020.051507

Stress-Relaxation and Cyclic Behavior of Human Carotid Plaque Tissue
Wang, J. (2020). Stress-Relaxation and Cyclic Behavior of Human Carotid Plaque Tissue. Frontiers in Bioengineering and Biotechnology. 8. https://doi.org/10.3389/fbioe.2020.00060

The importance of blood rheology in patient-specific computational fluid dynamics simulation of stenotic carotid arteries
Mendieta, J.B., Fontarosa, D., Wang, J., Paritala, P.K., McGahan, T., Lloyd, T. and Li, Z. (2020). The importance of blood rheology in patient-specific computational fluid dynamics simulation of stenotic carotid arteries. Biomechanics and Modeling in Mechanobiology. 19, pp. 1477-1490. https://doi.org/10.1007/s10237-019-01282-7

Carotid Bifurcation With Tandem Stenosis—A Patient-Specific Case Study Combined in vivo Imaging, in vitro Histology and in silico Simulation
Wang, J., Paritala, P.K., Mendieta, J.B., Gu, Y., Raffel, O.C., McGahan, T., Lloyd, T. and Li, Z. (2019). Carotid Bifurcation With Tandem Stenosis—A Patient-Specific Case Study Combined in vivo Imaging, in vitro Histology and in silico Simulation. Frontiers in Bioengineering and Biotechnology. 7. https://doi.org/10.3389/fbioe.2019.00349

Prediction of atherosclerotic plaque life – Perceptions from fatigue analysis
Paritala, P.K., Yarlagadda, T., Wang, J., Gu, Y.T. and Li, Z. (2019). Prediction of atherosclerotic plaque life – Perceptions from fatigue analysis. Procedia Manufacturing. 30, pp. 522-529. https://doi.org/10.1016/j.promfg.2019.02.073

3D-printing based Transducer Holder for Robotic Assisted Ultrasound Guided HIFU
Wang, J., Xu, X., Huang, Z. and Melzer, A. (2019). 3D-printing based Transducer Holder for Robotic Assisted Ultrasound Guided HIFU. Procedia Manufacturing. 30, pp. 3-10. https://doi.org/10.1016/j.promfg.2019.02.002

Numerical investigation of atherosclerotic plaque rupture using optical coherence tomography imaging and XFEM
Paritala, P.K., Yarlagadda, P.K.D.V., Wang, J., Gu, Y. and Li, Z. (2018). Numerical investigation of atherosclerotic plaque rupture using optical coherence tomography imaging and XFEM. Engineering Fracture Mechanics. 204, pp. 531-541. https://doi.org/10.1016/j.engfracmech.2018.11.002

Intravascular Optical Coherence Tomography Image Segmentation Based on Support Vector Machine Algorithm
Huang, Y., He, C., Wang, J., Miao, Y., Zhu, T., Zhou, P. and Li, Z. (2018). Intravascular Optical Coherence Tomography Image Segmentation Based on Support Vector Machine Algorithm. Molecular & Cellular Biomechanics. 15 (2), pp. 117-125. https://doi.org/10.3970/mcb.2018.02478

The Correlation Between Texture Features and Fibrous Cap Thickness of Lipid-Rich Atheroma Based on Optical Coherence Tomography Imaging
He, C., Wang, J., Huang, Y., Zhu, T., Miao. Y. and Li, Z. (2016). The Correlation Between Texture Features and Fibrous Cap Thickness of Lipid-Rich Atheroma Based on Optical Coherence Tomography Imaging. Molecular & Cellular Biomechanics. 13 (1), pp. 23-36. https://doi.org/10.3970/mcb.2016.013.027