Advances in Medical Devices 3

Micro-Computed Tomography and Structured Light Scanning of Human Hearts Presenting with Ischemic Cardiomyopathy or Atrial Fibrillation: Generating “A Heart To Learn” Mobile Application

Abstract: Access to high-resolution cardiac imaging is essential for medical professionals, students, and device developers. This study presents the development of "A Heart to Learn," a mobile application integrating micro-computed tomography (μ-CT) and structured light scanning to generate interactive 3D models of human hearts with ischemic cardiomyopathy (ICM) and atrial fibrillation (AF). Utilizing an Artec Space Spider structured light scanner and high-resolution μ-CT imaging, we reconstructed detailed cardiac models incorporating patient histories, echocardiography, ECG, and endoscopic videos from reanimated hearts. These models, now freely available via mobile platforms, provide an innovative tool for education and research, enhancing the understanding of cardiac pathology and advancing digital medical learning.

Presenting Authors

Bio: Madeline Wethington, MS, is a researcher in the Visible Heart Laboratories at the University of Minnesota. She earned her Bachelor of Science in Cellular and Organismal Physiology in May 2023 and her Master of Biological Sciences in May 2024, both from the University of Minnesota, where she was also a Division I hockey player. Her research focuses on heart scanning using micro-CT and structured light scanners, as well as developing virtual reality and 3D printing tools for medical education and outreach. As part of this work, she has contributed to the creation of several free applications, including A Heart to Learn, Coronary Quest, and CHD 360 which are all available on the Apple App Store and Google Play Store and have been downloaded in over 40 countries. Passionate about expanding medical education and accessibility, she strives to leverage emerging technologies to enhance learning, improve patient care, and empower patients to make informed decisions about their health. She has been accepted to multiple medical schools and is currently deciding where she will be attending this fall, with aspirations to pursue a career in cardiothoracic or orthopedic surgery.  

Bio: David Buyck, MS, is a researcher at the University of Minnesota’s Medical School, specializing in the development of medical simulators for patient and student education. He is currently pursuing a Ph.D. in Bioinformatics and Computational Biology and is affiliated with the Visible Heart® Laboratories. Buyck holds a Master’s degree in Computer Science from the University of Minnesota, earned in 2024. His research focuses on integrating virtual and augmented reality technologies into cardiac education and device training. He has contributed to publications such as “Virtual and Augmented Realities for Cardiac Education and Device Training,” highlighting his role in advancing medical training through innovative technologies.

Co-authors: John Brigham, Enrique Vergara Escudero and Paul Iaizzo

Quantitative Analysis of Periprocedural Thrombus Fragmentation using an Automated Optical Detection System in a Comprehensive Stroke Intervention Training Platform 

Presenting Author: Jonte Schmiech, PhD Student
Institute of Product Development and Mechanical Engineering Design
Hamburg University of Technology

Bio: Jonte Schmiech studied Medical Engineering at Hamburg University of Technology (TUHH). Since 2022, he has been working as a research associate at the Institute of Product Development and Mechanical Engineering Design (PKT) at TUHH. His research focuses on the analysis of objective evaluation metrics for assessing neurointerventionalists' training performance during treatment simulations.

Co-authors: Helena Guerreiro, Nadine MacMillan, Eve Sobirey, Nora Ramdani, Matthias Bechstein, Maximilian Wagner, Anna Kyselyova, Jens Fiehler and Dieter Krause

Total Hip Arthroplasty (THA) is a widely performed surgical procedure, with increasing frequency worldwide. Despite its high success rate, many patients require revision surgeries due to complications such as aseptic loosening, primarily resulting from stress shielding, cortical hypertrophy, and micromotion. These issues often stem from a mechanical mismatch between the bone and the solid dense implant, particularly a mismatch in stiffness. A potential solution lies in the use of porous or lattice structures in implant design, which offer lower stiffness and improved biocompatibility by facilitating bone ingrowth, cell seeding, and vascularization. Among these designs, Triply Periodic Minimal Surfaces (TPMS), especially gyroid structures, closely resemble bone morphology and present a viable alternative to solid implants. However, optimizing parameters such as pore size, porosity, and wall thickness is critical for both biological integration and manufacturability. Given the non-uniform stress distribution experienced by implants under physiological loading, a gradient porosity design is necessary. This study develops a bio-inspired gyroid hip implant with gradient porosity, guided by stress mapping, and evaluates its impact on stress shielding in the femur through bone remodeling theory using finite element modeling (FEM). Results indicate that the gradient porous implant reduces stress shielding by 36.5% and can withstand mechanical loads with an acceptable safety factor.

Presenting Author: Babak Ziaie, PhD
Atlantic Technological University (Ireland)

Bio: Babak Ziaie is a final-year PhD researcher in the Mechanical and Manufacturing Engineering Department at Atlantic Technological University (Ireland) and a member of the Centre for Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). His research focuses on the design and development of porous biomedical devices using topology optimization and additive manufacturing, supported by advanced numerical modeling and Finite Element Method (FEM) analysis. He has authored several journal publications and presented his research on porous biomedical devices at national and international conferences. He has also served as a keynote speaker at computational and health engineering events and participated in the Erasmus+ BIP program on sustainability-focused computational modeling. Alongside his academic research, Babak brings nearly a decade of professional experience in mechanical and manufacturing engineering, with a strong background in design, reverse engineering, numerical analysis, manufacturing, and process optimization. He collaborates with industry partners such as Croom Medical and the PEM Technology Gateway to apply and validate his research in real-world biomedical applications.

Co-authors: Xavier Velay and Waqas Saleem

The design philosophy of leading interventional devices and software typically employs point- or line-like fiducial markers that are detected via multiple external optical cameras and/or the primary medical imaging system employed in the procedure (MRI, CT, fluoroscopy, etc.). Fiducial markers with characteristic geometric signals encoded into their physical design can provide more robust information on device location and orientation than point or line signals at lower imaging resolutions while leveraging the volumetric imaging capabilities of MRI and CT to circumvent the need for additional external camera hardware in the operating room.

This work describes efforts to develop unique geometric fiducial designs and software methods to detect and determine their orientation based on volumetric MR-imaging. Using these methods, a single MR scan can be used to localize and orient specific medical devices autonomously, rather than relying on multimodal imaging or semi-manual detection methods.

These results have been validated in a series of MRI scans using human cadaver heads and fruit-based phantoms, successfully detecting and isolating the device fiducial in 8/8 T2w MRI scans, and coregistering the signal to an orthonormal template with a Dice-based evaluation metric of 0.819.

These methods have the potential to accelerate image-guided surgeries by improving automated detection and registration methods to reduce the number and/or duration of required scans while minimizing the amount of supplemental hardware (external optical cameras).

Presenting Author: Thomas Lilieholm
UW Madison Medical Physics Dept. and ImgGyd LLC

Bio: Thomas Lilieholm, PhD, is UW Madison’s 2024 Postdoctoral Entrepreneurial Fellow in Medical Physics and a co-founder of a medical device startup, ImgGyd, LLC. His research is primarily concerned with image-guided surgery, which he has applied in over 40 minimally invasive prostate interventions as a member of the Interventional MRI Team at the UW Madison Hospital. Thomas previously worked at another medtech startup, Oncospace Inc., where he developed AI models to rapidly and autonomously generate CT segmentations of 70 different organs-at-risk across multiple body sites to accelerate cloud-based external beam radiotherapy treatment planning. During his doctoral studies, Thomas worked intermittently as a consultant for local businesses in Madison as a member of UW's WiSolve consulting group.

Thomas earned his Bachelor’s degree in Physics with a minor in Business at the University of Texas at Austin in 2019. He received his Master’s and PhD in Medical Physics at the University of Wisconsin - Madison, graduating in 2024. His doctoral studies in medical image analysis and image-guided surgery were funded by the UW Biotechnology Training Program fellowship via the National Institute for General Medical Sciences (NIGMS) to support interdisciplinary science in the biotech industry.

Thomas's research interests include developing AI methods for analyzing pathologies and local organs at risk in preoperative planning for image-guided interventions and/or external beam radiotherapy, quantitative neuroimaging, and developing specialized hardware to guide devices in transformative surgical interventions.

Co-authors: Jose Guerrero Gonzalez, Andrew Alexander, Terrence Oakes and Walter Block