Journal articles

2026

  • Colombo A; Carbonaro D; Zhang M; Shen C; Gharleghi R; Kapoor A; Chiastra C; Jepson N; Webster M; Beier S, 2026, 'Are Ultrathin Stents Optimal for Bifurcation Lesions? Insights From Computational Modeling of Provisional and DK-Crush Techniques', Catheterization and Cardiovascular Interventions, 107, pp. 258-272, DOI: https://doi.org/10.1002/ccd.70329

    Finding: Ultrathin stents do not always provide superior outcomes; performance depends on lesion anatomy and stenting strategy.

  • Colombo A; Carbonaro D; Zhang M; Chiastra C; Webster M; Jepson N; Beier S, 2026, 'Mechanistic Insights Into How Rewiring and Bifurcation Angle Affect DK-Crush Stent Deployment', Catheterization and Cardiovascular Interventions, 107, pp. 1314-1323, DOI: https://doi.org/10.1002/ccd.70475

    Finding: The optimal rewiring strategy depends on bifurcation angle, demonstrating that patient-specific procedural planning can improve bifurcation stenting outcomes.

  • Shen C; Zhang M; Keramati H; Zhang S; Gharleghi R; Wentzel JJ; Khan MO; Morbiducci U; Qayyum A; Niederer SA; Samant S; Chatzizisis YS; Almeida D; Tsai TY; Serruys P; Beier S, 2026, 'The Anatomy of Coronary Risk: How Arterial Geometry Shapes Coronary Artery Disease Through Blood Flow Haemodynamics – Latest Methods, Insights and Clinical Implications', Archives of Computational Methods in Engineering, DOI: https://doi.org/10.1007/s11831-026-10530-w

    Finding: Coronary artery geometry strongly influences local blood flow patterns and contributes to the development and progression of coronary artery disease.

  • Sanhueza Ortega J; Shanmuganathan K; Poole-Warren L; Beier S; Aregueta Robles U, 2026, 'Physicochemical Reinforcement Unlocks Sterilization-Stable Anisotropic Hydrogels for Cell-Compatible Mock Arteries', Advanced Healthcare Materials, 15, DOI: https://doi.org/10.1002/adhm.202600010

    Finding: Developed sterilisation-stable anisotropic hydrogel mock arteries with physiological mechanical properties suitable for vascular research and device testing.

  • Zhang M; McGrath-Cadell L; Hesselson S; Shen C; Gharleghi R; Collins N; Muller D; Kovacic J; McLachlan C; Graham R; Beier S, 2026, 'Anatomical and Haemodynamic Determinants of Spontaneous Coronary Artery Dissection Identified by Computed Tomography Coronary Angiography', Heart, Lung and Circulation, 35, pp. S116-S117, DOI: https://doi.org/10.1016/j.hlc.2026.07.081

    Finding: Identified anatomical and haemodynamic characteristics associated with spontaneous coronary artery dissection, providing new insights into its underlying mechanisms.

  • Zhang M; Shen C; McGrath-Cadell L; Otton J; Graham R; McLachlan C; Beier S, 2026, 'Enhancing Risk Prediction in Moderate Coronary Stenosis: Added Value of Inflammation, Blood Flow and Vessel Geometry', Heart, Lung and Circulation, 35, pp. S143-S144, DOI: https://doi.org/10.1016/j.hlc.2026.07.129

    Finding: Combining inflammation, coronary blood flow metrics and vessel geometry improves risk prediction in patients with moderate coronary stenosis.

  • Leong CN; Dokos S; Al Abed A; Beier S; Alharbi Y; Farid M; Yoon J; Chatfield AG; Leipsic JA; Sellers SL; Slavich E; Yon HR; Muller D; Otton J, 2026, 'Simplified Patient-Specific In Silico Rigid Model for Simulating Left Ventricular Outflow Tract Pressure Gradient After Transcatheter Mitral Valve Implantation', In Silico Research in Biomedicine, 2.

    Finding: Developed a rapid patient-specific computational framework for predicting left ventricular outflow tract obstruction following transcatheter mitral valve implantation.

  • Zhang S; Gharleghi R; Singh S; Shen C; Adikari D; Zhang M; Moses D; Vickers D; Sowmya A; Beier S, 2026, 'Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation', Journal of Imaging Informatics in Medicine, 39, pp. 2680-2694, DOI: https://doi.org/10.1007/s10278-025-01677-2

    Finding: Demonstrated methods to improve the robustness and generalisability of deep learning models for automated coronary CT segmentation across diverse imaging datasets.

    2025

  • Kapoor A; Ray T; Jepson N; Beier S, 2025, 'A Surrogate-Assisted Multiconcept Optimization Framework for Real-World Engineering Design', Journal of Mechanical Design, 147(12), DOI: https://doi.org/10.1115/1.4068993

    Finding: Developed an efficient optimisation framework that enables complex engineering systems to be designed using multiple competing objectives while substantially reducing computational cost.

  • Saeed D; Gharleghi R; Beier S; Singh S, 2025, 'Machine-Learning Based Detection of Coronary Artery Calcification Using Synthetic Chest X-Rays', arXiv Preprint.

    Finding: Demonstrated the feasibility of detecting coronary artery calcification from synthetic chest radiographs using machine learning, potentially expanding opportunities for opportunistic cardiovascular screening.

  • Zhang S; Gharleghi R; Singh S; Shen C; Adikari D; Zhang M; Moses D; Vickers D; Sowmya A; Beier S, 2025, 'Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation', Journal of Imaging Informatics in Medicine, 39, pp. 2680-2694, DOI: 10.1007/s10278-025-01677-2

    Finding: Identified strategies that significantly improve the robustness and generalisability of deep learning models for automated coronary artery segmentation across diverse imaging datasets.

  • Beier S; Colombo A; Carbonaro D; Jepson N, 2025, 'Biomechanical and Haemodynamic Performance of Thin-Strut and Ultrathin-Strut Stents in Provisional Side Branch and Double-Kissing Crush Techniques: A Computational Study', Heart, Lung and Circulation, 34, pp. S612-S613.

    Finding: Showed that stent design influences arterial mechanics and blood flow patterns, with effects varying according to implantation strategy.

  • Shen C; Zhang M; Beier S, 2025, 'Low Endothelial Shear Stress and Low-Intensity Helical Flow are Surrogate Markers of Stenosis Formation in Females: A Longitudinal Study', Heart, Lung and Circulation, 34, pp. S189-S190.

    Finding: Identified low endothelial shear stress and reduced helical flow as early haemodynamic markers associated with future coronary stenosis development in women.

  • Shen C; Zhang M; Keramati H; Ferreira de Almeida D; Beier S, 2025, 'High-Intensity Helical Flow: A Double-Edged Sword in Coronary Artery Haemodynamics', Royal Society Open Science, 12(8).

    Finding: Demonstrated that while helical flow may improve coronary transport, excessively high levels can also generate adverse haemodynamic conditions.

  • Shen C; Zhang M; Keramati H; Zhang S; Gharleghi R; Wentzel JJ; Khan MO; Morbiducci U; Qayyum A; Niederer SA; Samant S; Chatzizisis YS; Almeida D; Tsai TY; Serruys P; Beier S, 2025, 'The Anatomy of Coronary Risk: How Artery Geometry Shapes Coronary Artery Disease Through Blood Flow Haemodynamics – Latest Methods, Insights and Clinical Implications', arXiv Preprint.

    Finding: Provided a comprehensive synthesis of evidence linking coronary geometry, disturbed blood flow patterns and coronary artery disease progression.

  • Wu H; Singh S; Gharleghi R; Sowmya A; Beier S, 2025, 'Enhanced Coronary Artery Segmentation in CTCA Using Bridging Centreline Integration', Medical Image Understanding and Analysis, pp. 266-278.

    Finding: Introduced a centreline-guided segmentation framework that improves coronary artery extraction accuracy from CT coronary angiography images.

  • Zhang S; Gharleghi R; Singh S; Moses D; Adikari D; Sowmya A; Beier S, 2025, 'LWT-ARTERY-LABEL: A Lightweight Framework for Automated Coronary Artery Identification', 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

    Finding: Developed a lightweight and computationally efficient framework for automated coronary artery identification suitable for large-scale clinical deployment.

  • Zhang M; Keramati H; Gharleghi R; Beier S, 2025, 'Reliability of Characterising Coronary Artery Flow with the Flow-Split Outflow Strategy: Comparison Against the Multiscale Approach', Computer Methods and Programs in Biomedicine, 263, DOI: https://doi.org/10.1016/j.cmpb.2025.108669

    Finding: Simplified flow-split boundary conditions can provide reliable coronary haemodynamic predictions while substantially reducing computational complexity.

2024

  • Li DD; Yu TJ; Renaud-Assemat I; Beier S, 2024, 'Enhancing Academic Integrity: Development of an Innovative Plagiarism Detection Tool for CAD-Modelling Courses', 2024 World Engineering Education Forum - Global Engineering Deans Council Conference.

    Finding: Developed an automated approach for detecting plagiarism in CAD modelling assignments, supporting academic integrity in engineering education.

  • Li DD; Chin ZY; Zhao L; Burr PA; Beier S, 2024, 'A Case Study on the Implementation of Retrieval and Spaced Practice in a Third-Year Mechanics of Solids Course to Promote Active Learning', Proceedings of the 35th Annual Conference of the Australasian Association for Engineering Education.
    Finding: Demonstrated that retrieval practice and spaced learning techniques can improve student engagement and knowledge retention in engineering education.

  • Liu T; Wang J; Wong S; Razjigaev A; Beier S; Peng S; Do TN; Song S, et al., 2024, 'A Review on the Form and Complexity of Human–Robot Interaction in the Evolution of Autonomous Surgery', Advanced Intelligent Systems, 6(11), DOI: https://doi.org/10.1002/aisy.202400197
    Finding: Reviewed the evolution of surgeon-robot interaction and identified challenges and opportunities for increasing autonomy in surgical robotics.

  • Keramati H; Lu X; Cabanag M; Wu L; Kushwaha V; Beier S, 2024, 'Applications and Advances of Immersive Technology in Cardiology', Current Problems in Cardiology, 49(10), DOI: https://doi.org/10.1016/j.cpcardiol.2024.102762
    Finding: Summarised emerging applications of virtual, augmented and mixed reality technologies across cardiovascular diagnosis, intervention and education.

  • Zhang M; Gharleghi R; Shen C; Beier S, 2024, 'A New Understanding of Coronary Curvature and Haemodynamic Impact on the Course of Plaque Onset and Progression', Royal Society Open Science, 11(9), DOI: https://doi.org/10.1098/rsos.241267
    Finding: Demonstrated that coronary artery curvature plays a significant role in shaping haemodynamic conditions associated with plaque development and progression.

  • Beier S; Gharleghi R; Shen C; Zhang M, 2024, 'Atherosclerotic Plaque Onset Driven by Vessel Curvature and Oscillatory Shear Index (OSI)', Heart, Lung and Circulation, 33, p. S164.
    Finding: Identified vessel curvature and oscillatory shear index as important biomechanical drivers of early plaque formation.

  • Mazher M; Razzak I; Qayyum A; Tanveer M; Beier S; Khan T; Niederer SA, 2024, 'Self-Supervised Spatial–Temporal Transformer Fusion Based Federated Framework for 4D Cardiovascular Image Segmentation', Information Fusion, 106, DOI: https://doi.org/10.1016/j.inffus.2024.102256
    Finding: Developed a federated deep-learning framework that improves 4D cardiovascular image segmentation while preserving data privacy.

  • Kapoor A; Jepson N; Bressloff NW; Loh PH; Ray T; Beier S, 2024, 'The Road to the Ideal Stent: A Review of Stent Design Optimisation Methods, Findings, and Opportunities', Materials & Design, 237, DOI: https://doi.org/10.1016/j.matdes.2023.112556
    Finding: Provided a comprehensive review of computational and experimental stent optimisation approaches, highlighting pathways toward next-generation coronary stent designs.

To see the full list, see Susann Beier’s Google Scholar page.