Cyber-physical twins of human organs

Dr. Tian Qiu led the project in collaboration with three medical departments at the University Hospitals in Tübingen and Freiburg. The project team successfully created and studied six highly realistic organ models, including the kidney, bladder, prostate, liver, vagina, and brain. These models combine the advantages of physical and cyber models to improve the collection of hard-to-get biomedical data under realistic conditions for analysis and modeling.

For the physical models, the project team optimized 3D printing and soft material molding techniques to replicate the anatomy and texture of human organs. Additionally, they engineered new hydrogel materials that behave like real soft tissue in surgical procedures. The team also created a brain model comprising composite hydrogel that exhibits life-like mechanical properties and high optical transparency, enabling high-resolution imaging. 

The project’s cyber models incorporated sensing technologies such as optical imaging, ultrasound imaging, and electrical sensing. These integrated systems can generate large amounts of data, making possible real-time feedback and quantitative evaluation of surgical outcomes. The project also leveraged Augmented Reality (AR) to enhance medical training. Medics participated in initial trials by applying the new cyber-physical organ models to optimize surgical instruments and digital surgical training.  

The Cyber Valley Research Fund has allocated five million euros to promote innovation and scientific excellence. Research groups were encouraged to submit project proposals that were evaluated according to ethical and societal considerations.  
 

This project yielded the following peer-reviewed publications:

1. Choi et al. (2021): Soft urinary bladder phantom for endoscopic training, Ann. Biomed. Eng., 49, 2412-2420, DOI: 10.1007/s10439-021-02793-0 

2. Hackner et al. (2021): Panoramic imaging assessment of different bladder phantoms – an evaluation study, Urology, 156, e103-e110, DOI: 10.1016/j.urology.2021.05.036

3. Kim et al. (2022): A high-fidelity artificial urological system for the quantitative assessment of endoscopic skills, J. Funct. Biomater., 13(4)301, DOI: 10.3390/jfb13040301 

4. Tan et al. (2021): Soft liver phantom with a hollow biliary system, Ann. Biomed. Eng., 49, 2139-2149, DOI: 10.1007/s10439-021-02726-x 

5. Tonyali S., Mueller A.-S. et al. (2024): Automated and quantitative surgical technique evaluation for TURP. In preparation

6. Mueller A.-S., et al. (2024): Surgical training of bladder tumor resection on hydrogel models with quantitative assessment based on 3D ultrasound scanning. In preparation

7. Li et al. (2020): Realistic full urinary tract phantom for endoscopic training, The European Association of Endoscopic Surgery (EAES), Poster 

8. Kim et al. (2021): Organ Phantom for the Assessment of Robotic Surgeries, Hamlyn Symposium on Medical Robotics (HSMR), Poster 

9. Kim et al. (2021): Computer-assisted quantitative assessment of endo. skills based on a urological phantom, 55th DGBMT Ann. Conf. on Biomed. Eng., Talk, 66, S212-217, Link to abstract

10. Kim et al. (2022): A hybrid surgical simulator for interactive endoscopic training, IEEE Inter. Conf. of the Engineering in Medicine and Biology Society (EMBC), Poster, DOI: 10.1109/EMBC48229.2022.9871697 

11. Tan et al. (2021): A realistic liver phantom for the training and quantitative evaluation of endoscopic skills, 17th World Congress of Endo. Surgery (WCES), Poster, 344272, P201 

12. Mueller A.-S., et al. (2023): Surgical training of tumor resection on hydrogel models with quantitative assessment based on 3D ultrasound scanning. DKFK German Cancer Research Congress (GCRC). Poster 

13. Fischer, F.; et al. (2023): Wireless force sensing of a micro-robot penetrating a viscoelastic solid, International Nonlinear Dynamics Conference (NODYCON), Talk 

14. Fischer, F. et al. (2022): 3D fabrication of microvascular networks on artificial organ models for endoscopic surgical simulation. Poster. Future 3D Additive Manufacturing – The 3DMM2O Conference

Public events and public media reports: 

1. Presentation of German Chancellor Dr. Merkel during virtual visit of Cyber Valley, 2020; Link to article

2. University of Stuttgart representing at Hannover Messe 2023; Link to article

3. Stuttgarter Zeitung; Link to article

4. Spotify, Cyber Valley Podcast, AI in Medicine; Link to spotify episode